The pore-throat radius of shale oil reservoir is extremely small, and it is difficult to accurately obtain the absolute permeability and oil-water two-phase relative permeability of actual oil reservoir through conventional core experiments. However, these parameters are very important for reservoir numerical simulation. In this paper, a method for characterizing flow parameters based on pore network model that considers differential pressure flow and diffusion flow is proposed. Firstly, a digital core was reconstructed using focused ion beam scanning electron microscopy (FIB-SEM) from the Gulong shale reservoir in the Songliao Basin, China, and a pore network model was extracted. Secondly, quasi-static single-phase flow and two-phase flow equations considering diffusion were established in the pore network model. Finally, pore throat parameters, absolute permeability, and oil-water two-phase permeability curves were calculated, respectively. The results show that the pore throat distribution of Gulong shale reservoir is mainly concentrated in the nanometer scale, the mean pore radius is 87 nm, the mean throat radius is 41 nm, and the mean coordination number is 3.97; The calculated permeability considering diffusion is 0.000124mD, which is approximately twice the permeability calculated without considering diffusion; The irreducible water saturation of the Gulong shale reservoir is approximately 0.26, and the residual oil saturation is approximately 0.73. The method proposed in this paper can provide an important approach for characterizing the flow parameters of similar shale oil reservoirs.

The western Sulige gas field is a new and key reserve area for the rolling development of the Sulige gas field in China. However, due to the complex gas–water relationship and the difficulty in identifying gas and water formation, the scale and benefit deployment of the gas field are seriously restricted. In particular, almost all of the wells in the area produce water and no water measurement has been carried out for any single well, which leads to an unclear understanding of the dynamic characteristics of the production wells, thus affecting the productivity calculations of the gas wells and the overall regional productivity evaluation. Based on the testing data for a gas well, the impacts of the reservoir property parameters on the gas and water production were analyzed by combining the production performance and static geological characteristics. It was determined that the physical parameters K, Kh, and φSg had good positive correlations with gas production but not with water production; thus, effective prediction cannot be obtained for water production in gas well testing. After the analysis of the liquid loading law, the gas wells were classified into three types: continuous liquid carrying production, slight liquid loading, and liquid loading wells. In general, up to 96% of the gas wells were liquid loaded. According to the different production performances exhibited in the different stages of the gas wells, five types of methods for diagnosing water production wells were proposed (gas testing, pilot production, gas–liquid two-phase measurement testing, liquid level detection, and production performance analysis), as well as the diagnostic criteria and corresponding solutions. To obtain real-time water production data for each well and investigate the change of water-gas ratio (WGR) during the whole production process, a water production splitting method for gas wells based on three-dimensional geological modeling and numerical simulation combined with the constraints of the total water production of gas gathering stations was explored and established. The splitting results can be used to evaluate the water and gas productivity of gas wells and determine the best deliquification period. The gas well productivity when water production was considered was about 10% lower than that when water production was not considered. The best deliquification period was determined to be 125 days for wells with small water production, 20 days for wells with moderate water production, and 3 days for wells with serious water production. The results of this study could provide technical support for the scientific evaluation of gas well production indicators, reduction of development costs, and improvement of oil recovery.

In this paper, the linear nonequilibrium thermodynamic approach is used to analyze energy processes in the wind energy conversion system (WECS), with a directly connected vertical axis wind turbine (VAWT) and vector controlled permanent magnet synchronous generator (PMSG). Both elements are considered as linear universal energy converters (EC) linearized at the points of the given range of common to VAWT and PMSG angular velocity. The dependences on the angular velocity of the coupling coefficients between the ECs input and output and the dimensionless parameters of their operating modes were received. This allows for choosing the optimal points of ECs operation according to the specified criteria and obtaining indicators of their maximum efficiency. To assess the quality of the cascade connection of two ECs, the appropriate coefficient was introduced, the dimensionless parameters and characteristics of the equivalent EC were obtained, and the conditions of its maximum efficiency were determined. Analysis of the VAWT-PMSG connection quality showed reserves for improving WECS efficiency. The impact of VAWT and PMSG variable parameters on the quality of this connection is studied, and further research directions are shown. The proposed thermodynamic approach allows an effective search for solutions for the efficiency improvement of various systems with energy transfer and transformation.

Enhanced oil recovery using nanoparticles is a promising method. However, when injected into a reservoir, nanoparticles can block pores and cause permeability damage. Therefore, enhancing their performance to lower the permeability damage effect is crucial. This study investigated the effect of pH alteration through carbon dioxide (CO2) injection on the permeability damage of limestone caused by the aluminum oxide (α-Al2O3) nanofluid. The methodology involved nanofluid alternating CO2 core flooding experiments by using nanofluids with pH of 4.5 and 2.8. After core flooding, permeability damage was calculated as a percentage of the reduction of the original permeability. The results revealed that the permeability damage in the case of nanofluid alternating CO2 injection was 23.23%. In only nanofluid with a pH of 4.5 injection case, permeability damage was 47.53%. In the 2.8 pH nanofluid injection case, permeability damage was 31.01%. The retention of nanoparticles was confirmed through scanning electron microscopy and energy dispersive X-ray analysis. Permeability damage could be attributed to a large nanoparticles’ agglomeration size, roughness of pore surfaces, and nanoparticle sedimentation. The results of the study revealed that altering pH through the α-Al2O3 nanofluid alternating CO2 injection can effectively reduce the permeability damage of limestone.

This paper focuses on the impact of defects density and carrier capture cross-section area in the electron transport material (ETM), hole transport material (HTM), and absorber layers on the performance of perovskite solar cells and quantum efficiency (QE). Furthermore, the impact of defects density at the interface between ETM/absorber and absorber/HTM is also studied. SCAPS-1D software is used in the current study in determining solar cell performance. The proposed perovskite solar cell structure is a planar FTO/TiO2/ CH3NH3PbI3/ Cu2O. The results indicated that increasing the defect density in the absorber layer significantly affects cell performance, while in ETM and HTM layers, the cell parameters remain unaffected. It is also found that the defect capture cross-section has a similar behavior to the defect density in the main layers (ETM, absorber, and HTM). In addition, it is observed that by increasing the defects density in the ETM/absorber and absorber/HTM interfaces layer, the cell parameters FF, Jsc, and PCE have been slightly decreased, with no effect on Voc. Moreover, it is also noted that the quantum efficiency QE is sharply reduced. Finally, this paper introduced the correlation between the defect density and the capture cross-section, which is the first attempt to find such a relationship in perovskite solar cells to the knowledge of the authors.

We investigated the influence of the fuel change, from pure hydrogen to hydrogen-ammonia mixture at different percentage, on the electrochemical behaviour of 50 mm in diameter Solid Oxide Fuel Cells (SOFC) with sputtered thin buffer layers of Gd doped Ceria, varying the working temperatures from 800°C to 650°C. The results show that the performances of the cells are not affected by the fuel change for the high working temperatures (800°C and 750°C). As an example, a power density value of 802 mW∙cm-2 at 1 A∙cm-2 is found when directly feeding the cell with 8 Nml∙min-1cm-2 of ammonia and with an equivalent flowrate of 12 Nml∙min-1cm-2 of H2. These power density output values are comparable to those obtained in industrial State of Art (SoA) SOFC cells with screen printed buffer layers fed with higher hydrogen flowrates, thanks to the improved electrochemical performances obtained in the case of cells with sputtered thin buffer layers of Gd doped Ceria. At lower working temperatures (700°C and 650°C), slight changes in the electrochemical behaviour of the cells are observed. Nevertheless, also in this temperature range, we obtain an output current density value of 0.54 A∙cm-2 in pure ammonia flowrate of 12 Nml min-1cm-2, at 800 mV and 700°C, equal to the value observed in SoA button cells with industrial screen printed GDC barrier layer fuelled with 16 Nml∙min-1cm-2 of H2. These results pave the way towards the use of innovative SOFC structures with sputtered thin buffer layers fuelled by ammonia.

The evolution of transportation has been inextricably tied to the progress of civilization. Through innovation, the automobile business has been working to improve safety, quality, and compliance with environmental regulations. Electric vehicles have made significant strides in this area, but optimizing their efficiency requires a special focus because they expend energy that can be recovered in a variety of ways. Energy harvesting, a cutting-edge technology that captures wasted energy from vehicles, has recently received a lot of attention as it constitutes a means to improve the efficiency of electric vehicles. Dissipated energy can be converted into electricity using regenerative energy recovery systems and put to various uses. This study tenders a thorough examination into energy recovery technologies which could be applied to the various types of energy dissipated in electric vehicles. Firstly, the paper investigates the possible sources of energy recoverable from an electric vehicle, as well as the various types of energy dissipated. Secondly, the article examines the energy recovery technologies most frequently used in vehicles, categorizing them according to the type of energy and application. Finally, it determines that with further research and development, energy harvesting holds considerable potential for improving the energy efficiency of electric vehicles. New and innovative methods for capturing and utilizing wasted energy in electric vehicles can be established. The potential benefits of applying energy recovery systems in electric vehicles is a vital issue for the automobile industry to focus on due to the potential benefits involved. The ongoing progress currently being made in this field is expected to play a significant role in shaping the future of transportation.

Perovskite solar cells are an evolving technology owing to self-assembling and highly tunable bandgap properties of materials. In this context, thin films of perovskites have attracted immense attention and witnessed great advancement because of their low manufacturing cost. The key development in these devices is the conversion efficiency, which rose from 3.8% to 28%. The formulation of innovative materials with the proper replacement of lead in perovskites is imperative to mitigate lead toxicity. Here, we analyzed the challenges like material and structural stability, device stability under high temperature and humidity conditions, lifetime, manufacturing cost, etc. faced in the commercialization of perovskite devices. This review shows that challenges such as device engineering, performance stability against the harsh environment, cost-effectiveness, and environmental concern should be taken into consideration for the widespread acceptance of perovskite-based solar devices. In conclusion, we suggested that an enormous scope exists for exploring high-performance and long-lasting perovskites for energy applications.

The broad acceptance of electromobility depends heavily on the performance and service life of the battery technology used. Lithium-ion battery technology is currently the most promising energy storage technology for mobile applications, but the performance and capacity of the cells is extremely temperature sensitive. Especially in these new complex and powerful applications there is a significant need for thermal management. Depending on the ambient conditions, part of the effective battery energy must therefore be used to temper the system. So far, mainly active components have been used for this task. This not only reduces the overall efficiency, but also increases the weight, volume and maintenance requirements of the system. In the present work, an alternative battery temperature management system (BTMS) was developed. A concept based on latent heat storage materials was created, which uses the advantages of thermal energy storage and the design freedom of additive manufacturing technology, and its suitability for use in battery applications was checked. On the one hand, the use of systems for storing thermal energy was researched and, on the other hand, an innovative cooling concept was created considering new production possibilities.

The global demand for energy has been steadily increasing due to population growth, urbanization, and industrialization. Numerous researchers worldwide are striving to create precise forecasting models for predicting energy consumption to manage supply and demand effectively. In this research, a time-series forecasting model based on multivariate multilayered long short-term memory (LSTM) is proposed for forecasting energy consumption and tested using data obtained from commercial buildings in Melbourne, Australia: the Advanced Technologies Center, Advanced Manufacturing and Design Center, and Knox Innovation, Opportunity, and Sustainability Center buildings. This research specifically identifies the best forecasting method for subtropical conditions and evaluates its performance by comparing it with the most used methods at present, including LSTM, bidirectional LSTM, and linear regression. The proposed multivariate multilayered LSTM model was assessed by comparing mean average error (MAE), root-mean-square error (RMSE), and mean absolute percentage error (MAPE) values with and without labeled time. Results indicate that the proposed model exhibits optimal performance with improved precision and accuracy. Specifically, the proposed LSTM model achieved a decrease in MAE by 30%, RMSE by 25%, and MAPE by 20% compared to the LSTM method. Moreover, it outperformed the bidirectional LSTM method with a reduction in MAE by 10%, RMSE by 20%, and MAPE by 18%. Furthermore, the proposed model surpassed linear regression with a decrease in MAE by 2%, RMSE by 7%, and MAPE by 10%. These findings highlight the significant performance increase achieved by the proposed multivariate multilayered LSTM model in energy consumption forecasting.

For the agricultural sector to develop sustainably in the future, progress toward more environmentally friendly technologies and methods is crucial. It is necessary to increase output while reducing the demand for energy, agrochemicals, and water resources. Although greenhouses can be utilized successfully for this purpose, significant technical advancements are required, especially when it comes to heating, to lower the use of fossil fuels and boost energy efficiency. Infrared waves and microwaves, for instance, can warm plants without having to heat the entire greenhouse volume, which takes a significant amount of energy to compensate for heat loss to the outdoor environment. In this paper, through a thorough examination of the state of the art, a general overview of novel greenhouse heating systems based on radiation is reported. First, infrared heating of greenhouses is analyzed, then the strengths and weaknesses of microwave and dielectric heating are discussed, and finally the use of microwaves for soil sterilization is examined. All outcomes suggest these irradiation-based technologies can contribute significantly to an agriculture that is energetically sustainable.

Recently, there is a growing need for sensors that can operate autonomously, without the need for an external power source. This is especially important in applications where conventional power sources, such as batteries, are impractical or difficult to replace. Self-powered sensors have emerged as a promising solution to this challenge, offering a range of benefits such as low cost, high stability, and environmental friendliness. One of the most promising self-powered sensor technologies is L-S TENG, which stands for the liquid-solid triboelectric nanogenerator. This technology works by harnessing the mechanical energy generated by external stimuli such as pressure, touch, or vibration, and converting it into electrical energy that can be used to power sensors and other electronic devices. Therefore, self-powered based on L-S TENG, which provides numerous benefits such as rapidly responding, portability, cost-effectiveness, and miniaturization, is critical for increasing living standards and optimizing industrial processes. In this review paper, the working principle with three basic modes has been briefly introduced firstly. After that, affecting parameters to L-S TENG are reviewed based on the properties of the liquid and solid phases. With different working principles, L-S TENG has designed a lot of structure that works as a self-powered sensor for pressure/force change, liquid flow motion, concentration, and chemical detection or biochemical sensing. Moreover, the continuous output signal of TENG plays an important role in a real-time sensor that is vital to the growth of the Internet of Things.

The global trade and transportation sectors heavily rely on the maritime industry. Still, its dependence on fossil energy sources poses significant environmental challenges and leads to unstable fuel prices that affect the cost of goods transported by sea. This paper aims to evaluate the viability of seaports as energy-intensive entities and explore the feasibility of implementing a Nuclear-Renewable Hybrid Energy System (NRHES). The study presents a case study of the Tanjung Priok Port in Indonesia, focusing on estimating energy consumption, emissions, and the potential impact of carbon taxation on seaport operations. By quantifying these factors, the research provides insights into the energy requirements, environmental effects, and potential costs associated with seaport carbon taxation. A comprehensive analysis of the technical and economic feasibility of implementing an NRHES in the seaport case study is conducted, determining the optimal sizing and composition of components, considering the proportion of nuclear and renewable energy sources. Additionally, the economic analysis considers energy costs, net present cost, cash flow, return on investment, and internal rate of return. The findings aim to inform decision-makers about the benefits and challenges of adopting an NRHES, contributing to a cleaner and more sustainable future for the maritime industry.

In this paper, the performance and emission characteristics of the engine were investigated with varying ratios of tung oil-based biodiesel blends (B10, B20, and B50) and 0# diesel under different operating conditions. The experimental results indicated that both the power and torque of B10 increased compared with 0# diesel, which increased by 1.9% and 6.6%. But the power and torque of B20 and B50 decreased slightly. The fuel consumption rate increased slightly with an increasing percentage of biodiesel added. In general, the overall emissions of tung oil-based biodiesel blends were lower compared to 0# diesel. Compared to 0# diesel, the CO-specific emissions of B10 decreased by 42.86% at medium and large load, and NOX-specific emissions of tung oil-based biodiesel blends were reduced at all load conditions, except for B50. In addition, HC-specific emissions were all reduced, especially for B20 decreased by 27.54% at 50% load. With the increase of the biodiesel blend ratio, the smoke decreased significantly. Among the blends tested, B50 showed the greatest reduction of 38.05% at 2000 rpm. Overall, it can be asserted that using biodiesel presents a favorable alternative fuel option that can lead to a more environmentally friendly exhaust output.

This study explores the impact of temperature and molarity in the pyrolysis of Açaí seeds (Euterpe Oleraceae, Mart.) activated with KOH on the yield of bio-oil, hydrocarbon content of bio-oil, and chemical composition of aqueous phase. The experiments were carried out at 350, 400, and 450 °C and 1.0 atmosphere, with 2.0 M KOH, and at 450 °C and 1.0 atmosphere, with 0.5 M, 1.0 M and 2.0 M KOH, in laboratory scale. The composition of bio-oils and aqueous phase determined by GC-MS, while the acid value, a physico-chemical property of fundamental importance in bio-fuels, of bio-oils and aqueous phases by AOCS methods. The solid phase (biochar) characterized by X-ray diffraction (XRD). The diffractograms identified the presence of Kalicinite (KHCO3) in biochar, and those higher temperatures favor the formation peaks of Kalicinite (KHCO3). The pyrolysis of Açaí seeds activated with KOH show bio-oil yields from 3.19 to 6.79 (wt.%), aqueous phase yields between 20.34 and 25.57 (wt.%), solid phase yields (coke) between 33.40 and 43.37 (wt.%), and gas yields from 31.85 to 34.45 (wt.%). The yield of bio-oil shows a smooth exponential increase with temperature. The acidity of bio-oil varied between 12.3 and 257.6 mgKOH/g, decreasing exponentially with temperature, while that of aqueous phase between 17.9 and 118.9 mgKOH/g, showing and exponential decay behavior with temperature, demonstrating that higher temperatures favor not only the yield of bio-oil but also bio-oils with lower acidity. For the experiments with KOH activation, the GC-MS of bio-oil identified the presence of hydrocarbons (alkanes, alkenes, cycloalkanes, cycloalkenes, and aromatics) and oxygenates (carboxylic acids, phenols, ketones, and esters). The concentration of hydrocarbons varied between 10.19 to 25.71 (area.%), increasing with temperature, while that of oxygenates from 52.69 to 72.15 (area.%), decreasing with temperature. For the experiments with constant temperature, the concentrations of hydrocarbons in bio-oil increase exponentially with molarity, while those of oxygenates decrease exponentially, showing that higher molarities favor the formation of hydrocarbons in bio-oil. Finally, it can be concluded that chemical activation of Açaí seeds with KOH favors the not only the yield of bio-oil but also the content of hydrocarbons. The study of process variables is of utmost importance in order to clearly assess reaction mechanisms, economic viability and design goals that could be derived from chemically activated biomass pyrolysis processes.

The EU has set the ambitious target of raising the share of EU energy consumption produced from renewable resources to 32% by 2030 with a target of climate neutrality by 2050. The aim of this paper is to assess the role of biomass usage in the context of these targets. The paper identifies progress made between 2013–2022 by focusing on a selection of EU countries. The largest bio-energy increments of 130PJ, 77PJ and 60PJ were reported for Poland, Sweden, and the Nether-lands. This study valuates the crucial role in co-generation and heat in EU regions, with biomass usage between 55-80% of the combined heat and power (CHP) energy in Nordic countries. The future perspectives for bioenergy based on EU policies, biomass resources and technical issues were addressed. The EU possess around 9% of the global biomass supply, ensuring a certain level of biomass resource dependence. Thus, the biomass usage demand in energy production, non-energy sectors and transport is expected to rise leading to increments of 13%-76% on biomass imports. It appears that bioenergy development is mostly limited by economic issues and uneven support for bioenergy in different EU countries as well as environmental issues. The study shows a promising and sustainable potential of bioenergy in the EU as a renewable energy source while minimizing negative impacts on the environment and the economy. By 2050, liquid biofuels are likely to be increasingly used in the transport sector. Non-energy sector usage of biomass is still in an early stage of development, except for the pulp and paper industry, and significant use of biomass in non-energy sectors seems unlikely in the near future.

In today's human society, diesel generators (DGs) are highly applied into the human energy and electricity supply system due to its technical, operational and economic advantages. This paper proposes an intelligent nonlinear $H_2/H_{\infty}$ robust controller based on the chaos particle swarm gravity search optimization algorithm (CPSOGSA), which controls the speed and excitation of a DG. In this method, firstly, establish the nonlinear mathematical model of the DG and then design the nonlinear $H_2/H_{\infty}$ robust controller based on this. The direct feedback linearization and the $H_2/H_{\infty}$ robust control theory are combined and applied. Based on the design of the integrated controller for DG speed and excitation, the system's performance requirements are transformed into a standard robust $H_2/H_{\infty}$ control problem. The parameters of the proposed solution controller are optimized by using the proposed CPSOGSA. The introduction of CPSOGSA completes the design of an intelligent nonlinear $H_2/H_{\infty}$ robust controller for DG. The simulation is implemented in MATLAB/Simulink, and the results are compared with the PID control method. The obtained results prove that the proposed method can effectively improve the dynamic accuracy of the system and the ability to suppress disturbances and improve the stability of the system.

Liability to prevent consequences of an unhealthy situation due to accumulating toxic and hazardous emissions caused by open dumping of municipal solid waste with increasing urbanization has necessitated a renewed thinking on waste disposal. Grate fired incineration systems were adopted by urban managements in past and present but with criticisms due to formation of air borne emissions. Improved combustion methods like fluidized bed are now propagated because of current requirements like efficient energy recovery potential, stricter emission norms, adaptability with urban growth, adaptability to co-firing with other waste like biomass, edible oil wastes or industrial effluent and integration with conventional energy generation. Such a comprehensive and futuristic approach is more sustainable for the community. Multi-criteria decision-making tool is used to identify the best technology option among grate combustion and fluidized bed combustion for disposing and energy recovery from waste. Ten different collection and disposal options involving two combustion methods, namely, grate combustion and fluidized bed method are considered. Utilization of the energy is done for three end uses, namely, power generation, water distillation and district cooling. Two different regions in Saudi Arabia are considered for this study under two types of scenario, namely with recycling and without recycling. The different options are prioritized based on their overall ranking using five major performance factors.

In order to harmonize supply and demand of green energy, new future-proof technologies are needed. Here, hydrogen plays a key role. Within the current framework conditions, the production of green hydrogen is not yet economically viable. The use of the oxygen produced and the possible increase in efficiency associated with it mostly remains unconsidered. The aim is to demonstrate that the economic efficiency of a power-to-gas (PtG) project can be increased by using the by-product oxygen. In this research project, a water electrolyser connected to grid is powered to supply hydrogen to a hydrogen refuelling station. By utilising the by-product oxygen from water electrolysis for a wastewater treatment plant (WWTP), it is shown that the net present value (NPV) of the project can be improved by up to 13 % compared to the initial scenario. If a photovoltaic (PV) system is used in addition to grid electricity for higher green hydrogen production, the NPV can be further improved by up to 58 %. The levelized cost of hydrogen (LCOH) is calculated for different scenarios with and without oxygen configuration. A sensitivity analysis is then performed to find important parameters.

Many advanced reactor concept designs rely on high-assay low-enriched uranium (HALEU) fuel, enriched up to approximately 19.75% 235U by weight. Efforts are underway by the US government to increase HALEU production in the United States to meet anticipated needs. However, very little data exists for validation of computational models that include HALEU, beyond a few fresh fuel benchmark specifications in the International Reactor Physics Experiment Evaluation Project. Nevertheless, there is other data with potential value available for developing into quality benchmarks for use in data and software validation efforts. This paper reviews the available evaluated HALEU fuel benchmarks and some of the potentially relevant benchmarks for fresh highly enriched uranium. It then introduces experimental data for HALEU fuel irradiated at Idaho National Laboratory, from relatively recent irradiation programs at the Advanced Test Reactor. Such data should be evaluated and, if valuable, collected into detailed benchmark specifications to meet the needs of HALEU-based reactor designers.

Currently, the district heating (DH) in Poland is facing many challenges. The business model used hitherto was very simple—in most cities, heating plants produced heat, and centralized heating systems supplied the "product" at a price approved annually by the president of the Energy Regulatory Office (URE). However, recent years have brought significant changes on the market. EU regulations force the elimination of old coal-fired plants that were still built in the Polish People's Republic (PRL), moreover, high prices of CO2 emission allowances aggravate the financial situation of companies. In addition, in the heating sector, the trend observed in the power sector is becoming increasingly visible—limiting the role of large sources in favor of energy generated locally, closer to the customer. One of the biggest challenges is achieving the targets set by the EU for the share of renewable energy sources (RES) in the heating sector. The war in Ukraine and problems with the supply of coal and gas are an additional impulse to turn to RES. Thus, the development of sustainable and innovative solutions for energy production and supply at the level of urban networks is currently one of the main technical challenges. The purpose of the paper is to present the current situation and perspectives of development of district heating systems in Poland with a view to the status of district heating in the world, and some deeper insight into European conditions. The review presents energy sources with particular emphasis on renewable energy sources (RES) and their cogeneration for heat production. The examples of existing heating network solutions using renewable energy sources, based on the selected published case studies, are also discussed.

Electric energy is one of the driving forces in every country. The supply of electrical energy continues to present various challenges, such as high costs associated with procuring raw materials for generation, sparsely populated areas that are not connected to the main grid, and the need for infrastructure to support generation and network delivery. These challenges have contributed to the growing adoption of renewable energy sources, particularly solar photovoltaics (PV).In this study, we have developed a practical method to assess the spatial PV potential in a selected urban area. The methodology combines data collected from an unmanned aerial vehicle (UAV) photogrammetry, Geographic Information System (GIS), and the energy output from three remote photovoltaic systems installed at different locations. The results obtained from this approach not only provide the energy generated per square meter, per year (kWh m-2 yr-1), but also provides a base to calculate the potential distance that electric cars could travel based on the energy generated. To illustrate the application of this method, two practical cases were selected: Senglea, Malta, and Munxar, Gozo. These examples highlight the versatility and effectiveness of our approach for evaluating and harnessing solar energy through photovoltaic panels in different contexts.

In offshore drilling, accidents such as gas invasion, overflow, and kicks are inevitable, and they can escalate into blowouts and other catastrophic events that result in casualties and substantial economic losses. Therefore, maintaining drilling safety requires accurate monitoring of gas invasion and overflow. The majority of overflow monitoring methods currently utilized at drilling sites are threshold-based. However, monitoring parameters acquired during actual drilling operations frequently contain noise signals, making it difficult for threshold-based methods to strike a balance between improving accuracy and minimizing false positives. In this paper, Pattern Recognition-based Kick Detection (PRKD) is proposed as a novel method for diagnosing overflow in offshore drilling. This method utilizes the overflow evolution process by integrating multi-phase flow calculations, data filtering theory, pattern recognition theory, the Bayesian framework, and other theoretical models. The PRKD effectively detects and monitors gas intrusion and overflow based on single parameters by analyzing the shape and wave characteristics of the curves. The case analysis demonstrates that the proposed method for monitoring drilling overflow achieves high precision while maintaining a low false positive rate. By combining advanced computational techniques with pattern recognition algorithms, the PRKD improves the accuracy and reliability of kick detection, enabling proactive responses to potential risks, protecting the environment and human lives, and optimizing drilling operations.

Energy efficiency is, in principle, a simple idea: an output of human value, for example, vehicle-km traveled, divided by the needed input energy. Efficiency improvements are regarded by many as an important means of mitigating not only climate change, but also other environmental problems. Accordingly, many countries have efficiency ratings for appliances and efficiency standards for road vehicles. Despite the vast number of articles published on energy efficiency, few question whether it is a useful or accurate measure in its present form. This review addresses this lack, by a critical review of the literature, not only in energy efficiency, but in other areas of research, such as ‘energy services’, that can help broaden the scope of this idea, both geographically and conceptually. These shortcomings are illustrated in case studies of road passenger transport and buildings. The main findings are that energy efficiency inevitably has an ethical dimension, that feedbacks are more widespread than generally considered, and that conventional efficiency measures omit important energy input items, particularly those concerned with mining of the materials needed for renewable energy plants. Finally, the key results of this review are summarized, and its limitations are discussed, as is the future research needed to overcome these shortcomings.

Accurately predicting the power of solar power generation can greatly reduce the impact of the randomness and volatility of power generation on the stability of the power grid system, which is beneficial for the balanced operation and optimized dispatch of the power grid system, and reduces operating costs. Solar PV power generation depends on weather conditions, which are prone to large fluctuations under different weather conditions. Its power generation is characterized by randomness, volatility and intermittency. Recently, the demand for further investigation and effective use on the uncertainty of short-term solar PV power generation prediction has been getting increasing attention in many application of renewable energy sources. In order to improve the predictive accuracy of output power of solar PV power generation and develop a precise predictive model, the authors worked predictive algorithms for the output power of a solar PV power generation system. Moreover, since short-term solar PV power forecasting is one of the important aspects for optimizing the operation and control of renewable energy systems and electricity markets, this review focuses on the predictive models of solar PV power generation, which can be verified in the daily planning and operation of a smart grid system. In addition, the predictive methods in the reviewed literature are classified according to the input data source used for accurate predictive models, and the case studies and examples proposed are analyzed in detail. The contributions, advantages and disadvantages of the predictive probabilistic methods are compared. Finally, the future studies of short-term solar PV power forecasting is proposed.

Energy demand has exponentially increased with the increase in the world population and ur-banization. Renewable energy is clean, renewable, and environmentally friendly. Hydrogen production through Proton Exchange Membrane (PEM) electrolyzer is an efficient way to produce renewable energy. The efficiency and energy consumption of the PEM electrolyzer depends on the feed water quality. In this report, we study the effect of pH, TDS, and conductivity on hydrogen production as well as energy consumption during the process. pH values (3, 7, 9), TDS values (300ppm, 600ppm, 900ppm), and conductivity values (30mS/cm, 70mS/cm, 100mS/cm) were studied to understand and optimize the hydrogen production using PEM electrolyzer. The in-vestigations showed that hydrogen production is significantly affected by pH, total dissolved solids, and conductivity, and the best levels of each variable were identified by extensive testing. The findings show both the scientific significance of proton exchange electrolysis in meeting the growing energy demands of society as well as the importance of knowing the influence that di-verse conditions have on the creation of hydrogen. Our research, in general, contributes to the expanding body of scientific knowledge on the topic of the effective production of hydrogen and offers useful insights for the continuation of investigation in this field.

The pace of implementation of renewable electricity storage in Europe is disappointingly slow. Several factors influence it, but there is a need to speed up the rate and increase the volumes in order to promote a 100% transition to renewable energy resources, expand the practice of using renewable energy, and contribute to the improvement of the user's quality of life. Also, an important factor is significantly reducing the global impact on the environment and climate change. Electricity from renewable energy sources such as solar and wind has a seasonal nature that cannot provide the necessary electricity consumption and cover peak loads. Also, the so-called "energy resource crisis" is a very topical problem at the moment, which reinforces the global need to increase the share of renewable energy resources in the overall balance of primary energy resources. It is precisely the wider integration of renewable electricity storage in practice that can help stimulate this. The availability of renewable electricity is constantly increasing and the level of technological innovation is rapidly developing, therefore it is valuable to analyze, look for connections and at the same time the main differences in the ways of accumulation in order to promote its availability from a private house to the national and European scale as a whole. Therefore, this article analyses and compares the different options for renewable electricity storage, from small batteries to large storage systems, arriving at the best solution according to needs, using analysis methods such as multicriteria decision analysis (MCDA) and TOPSIS. After comparing nine criteria, such as the amount of investment required, existing power density, efficiency, duration of operation and others, in both groups, it was concluded that lithium-ion batteries are currently the best solution among batteries, while in the group of large accumulation systems – pumped hydro storage.

This study explores the feasibility of using an oscillating plate downstream of a cylindrical body to produce mechanical energy from a Von Kármán vortex street. The study aims to quantify the impact of the plate length, its separation from the cylinder, and a machine damping factor on the power coefficient and the blade’s displacement to identify the optimal configuration. This preliminary assessment assumes that the plate oscillation is small enough to avoid changes in the vortex dynamics. This assumption allows the construction of a surrogate model using CFD to evaluate the effect of plate length and separation from the cylinder on the fluctuating lift forces over the plate. Later, the surrogate model, combined with varying machine damping factors, facilitates the description of the device’s dynamics through the numerical integration of an angular momentum equation. The results showed that a plate with 0.52D length, 5.548D separation from the cylinder, and a damping factor of 0.013 achieved a power coefficient of 0.147 and a perpendicular displacement of 0.266D. These results demonstrate a substantial improvement in the performance of bladeless generators.

Climate change is one of the main issues that humanity is currently facing due to carbon dioxide emissions caused by the use of fossil fuels. Organic Rankine cycles may play an important role in reducing these emissions since they can be operated by using industrial waste heat of renewable energies. The present study presents a comprehensive bibliographic review of organic Rankine cycles. The study not only actualizes previous reviews that mainly focused on basic cycles operating on subcritical or supercritical conditions but also includes the analysis of novel cycles such as two-stage and hybrid cycles and the used fluids. Recuperative and regenerative cycles are more efficient than reheated and basic single-stage cycles. The use of two-stage cycles makes it possible to achieve higher thermal efficiencies and net power outputs of up to 20% and 44%, respectively, compared with those obtained with single-stage cycles. Theoretical studies show that hybrid systems, including Brayton and organic Rankine cycles, are the most efficient; however, they require very high temperatures to operate. Most organic Rankine cycle plants produce net power outputs from 1 kW up to several tens of kW, mainly using microturbines and plate heat exchangers.

The thermal insulation properties of building walls are critical to the overall energy efficiency and comfort of a building. One important factor that can affect these properties is the type of bricks used in construction. Bricks can vary in their geometry and thermal coefficient, which can impact their ability to transfer heat through the wall. The geometry of a brick can affect its thermal properties by altering the amount of air trapped within it and the surface area available for heat transfer. Hollow bricks or those with complex geometries may have lower thermal conductivity than regular solid bricks due to the air pockets trapped within them. Conversely, larger surface areas on the exterior of the brick can increase heat transfer. The thermal coefficient of clay, a common material used in brick production, is another important factor. Clay has a relatively low thermal conductivity, meaning it is a poor conductor of heat. However, the quality of the clay, as well as the firing temperature and duration used in brick production, can impact its thermal coefficient. Higher firing temperatures and longer firing times can result in a more compact and dense clay brick, which can improve its thermal properties. In summary, the thermal insulation properties of building walls can be significantly affected by the type of bricks used in their construction. It is important to consider the geometry and thermal coefficient of the bricks when designing a building to achieve the desired level of thermal insulation. By selecting bricks with appropriate properties, designers can help to improve the energy efficiency and comfort of the building while reducing its environmental impact.

Recently, in a previous study, we have experimentally shown the existence of an optimal injected steam mass flow rate, per unit length, ϕopt, which produces the maximal recovery of con- densate in a preformed steam chamber with an elliptical cross section of horizontal semi-major axis. Mutatis mutandis, in this work we present experimental studies in preformed steam chambers, one elliptical and the other circular. In both cases, we also have found the existence of unique optimal values. These configurations try to recreate the steam condensation, at a given time lapse, as it would occur during the growth stage of the steam-assisted gravity drainage (SAGD) process, a method used in the recovery of heavy and extra-heavy oil from homogeneous reservoirs. Finding the optimal mass flow rates in actual recovery process could become useful in the design of optimized SAGD processes.

This study aims to focus on using the Volterra series and machine learning for forecasting random and chaotic wind speed regimes, since the calm weather is mostly noticed at the local site, making the dataset selection difficult. A novel method is proposed to predict Volterra kernels up to the third order, using a forward-back propagation neural network with 12-month measurements at Fujairah site (UAE). Both daily and monthly wind speed data sets are investigated for forecasting. The three dominant hourly and daily kernels are extracted for each day and each month. Predicted future Volterra kernels are estimated from past values using both statistical analysis and individual neuro networks for each of the Volterra kernel coefficients. Due to the random nature of wind speed at the local site, a two-layer with 4 neurons per layer neuro network is used to locate the most variable and intense speed during 8-hours in the day. Forecasted wind speed is determined with errors arising from different sources such as the utilization of only 3rd-order Volterra kernels and the difficulty of machine training of the employed shallow network. Nevertheless, this work depicts a useful algorithm to forecast chaotic and random wind speed regimes. Computational time is a trade of the complexity of Volterra mathematical analysis.

The state estimation for lithium-ion battery cells has been the topic of many publications concerning the different states of a battery cell. They often focus on a battery cell’s state of charge (SOC) or state of health (SOH). Therefore this paper introduces a, on one hand, a new lithium-ion battery data set with dynamic validation data over degradation and on the other hand a model-based SOC and SOH estimation based on this dataset as a reference. An unscented Kalman filter-based approach was used for SOC estimation and extended with a holistic ageing model to handle the SOH estimation. The paper describes the dataset, the models, the parameterisation, the implementation of the state estimations, and their validation using parts of the dataset resulting in a SOC and SOH estimation over battery life. The results show that the dataset can be used to extract parameters, design models based on it and validate with dynamically degraded battery cells.

In terms of obtaining fuels as well as chemicals with or without catalysts at different conditions, the plum seed stands out as an alternative biomass source. Under varying heating rates (10, 50, and 100ºC min-1) and pyrolysis temperatures (400, 450, 500, 550 and 600 °C), the plum seed was pyrolysed at constant sweep gas flow at a constant rate (100 cm3min-1) in a tubular fixed bed reactor. According to the results, an oil yield reaching to a maximum of %45 was procured at the heating rate of 100 ºCmin-1 and the pyrolysis temperature of 550ºC in non-catalytic procedure. The catalytic pyrolysis was carried out in optimum conditions with two selected commercial catalysts, namely ZSM-5 and PURMOL-CTX and clinoptilolite (natural zeolite, NZ) with catalyst ratio of 10 % of raw material. Along with the catalyst addition, the quantity and the quality of bio-oil increased including the calorific value, removal of oxygenated groups, and hydrocarbon distribution. An increase related to the desirable products like phenols, alkene, and alkane and a decrease in undesirable products like acids were observed in the presence of catalysts. When all the results are considered and evaluated, using zeolite materials in the pyrolysis as catalysts is a recommendable option to achieve enhanced chemicals and fuels.

The photocatalytic biohydrogen generation using ZnO with the aid of simultaneous deposition of copper from an aqueous biomass-derivative glycerol solution was investigated. The effects of concentration of glycerol solution, Cu ion concentration and reaction temperature on biohydrogen generation were investigated. The photocatalytic biohydrogen production rate increased with increasing the concentration of aqueous glycerol solution, and the observed data could be fitted to the Langmuire-Hinshelwood kinetic models. The photocatalytic H2 production efficiency with ZnO could be significantly improved by simultaneous Cu deposition. The photocatalytic biohydrogen production rate was dependent on temperature, and increased with the increasing temperature. The possible mechanisms for oxidation of glycerol solution and photocatalytic hydrogen generation were proposed.

Integrating numerous renewable resources has been extensively researched and studied to create a dependable energy system. This study investigated the best techno-economical hybrid energy system configuration while using hydrogen energy to keep the system's energy balanced. Additionally, this study aims to determine the best hybrid system configuration for the location under investigation. A novel technique of DBM (Deterministic Balanced Method) was introduced to determine the total annual energy output for the project's lifetime. This approach is used to contrast the outcomes of other HOMER software tools. Then, using HOMER, it is possible to confirm the sizing optimization results for the suggested method by comparing the power ratings and yearly energy output. A detailed comparison between our proposed method and HOMER Pro has been conducted for validation and verification. Our method has been rigorously tested in various hybrid off-grid energy systems, ensuring its applicability and reliability across different scenarios and configurations. The results of our study indicate a high degree of similarity between the proposed approach and HOMER pro for computing annual energy power for the studied energy systems. Specifically, our analysis revealed that the difference between the approaches was within a range of 5%, indicating a high level of consistency and reliability in our method. These findings suggest that our approach can be confidently applied to determine the appropriate size of hybrid energy systems accurately. Overall, our study provides valuable insights into the development of effective sizing methodologies for hybrid energy systems. After considering the amount of solar radiation and wind speed gathered by global weather data platforms like NASA and METEONORM, this paper has also included a real case study of the Cairo International Airport's hybrid renewable energy production systems. To guarantee the viability of this study, the system design was founded on an actual load that was researched and simulated. A cluster of distributed networks was finally proposed to use the excess energy and enable energy conversion processes to be used in industry and transportation applications.

The Gulong shale oil reservoir is formed in freshwater to slightly saline lacustrine basins, mainly consisting of pure shale geological structure, which is quite different from other shale reservoirs around the world. Currently, the development of Gulong shale oil mainly relies on hydraulic fracturing, while the subsequent shut-in period for imbibition has been proven to be an effective method for enhancing shale oil recovery. To clarify the characteristics of fluid occurrence space and the variation of fluid occurrence during saltwater imbibition in Gulong shale, this paper carried out porosity and permeability tests on Gulong shale cores, and analyzed the fluid occurrence space characteristics and imbibition oil recovery based on nuclear magnetic resonance (NMR). In the porosity and permeability tests, the porosity measured by saturation method was calibrated using NMR T2 spectra. Combined with the identification of fractures in shale cores using micro-CT and the analysis of porosity and permeability parameters, it was found that the permeability of shale cores was related to the development of fractures in shale cores. Through the testing and analysis of NMR T1-T2 two-dimensional spectra of the shale cores before and after saturation with oil, it was found that the shale mainly contains heavy oil, light oil, and clay-bound water, and they were distributed in different positions in the T1-T2 spectrum. Finally, the T1-T2 two-dimensional spectra of the shale core at different imbibition stages were analyzed, and it was found that the saltwater mainly entered the minuscule inorganic pores of clay minerals during the imbibition process, and squeezed the larger-sized inorganic pores containing light oil through the hydration expansion effect, thus expelling the light oil from the shale core and achieving the purpose of enhanced oil recovery.

The global context of research for new sustainable energy storage technologies makes it a very active sector with significant scientific and economic challenges. Indeed, due to the irregular development of renewable energies and the shutdown of traditional power facilities, it is difficult to maintain a stable balance in terms of supply and demand: energy storage can help in particular for substantial changes in the latter. Metal air batteries have a higher energy density and are safer than other available energy storage devices. Based on the existing and proven lead-acid battery technology, this paper proposed an open cell foam manufactured by the Excess Salt Replication process for use as an anode for lead-air battery cellsies with sulphuric acid as the electrolyte. This will save lead and reduce the battery weight. A 25% antimonial lead alloy was used to produce open cell foams with a cell diameter between 2 mm and 5 mm for the antimonial lead-air battery. Preliminary results of the effective electrical conductivity of self-discharged primary battery cells, measured experimentally, showed that all antimonial lead foam-air battery cellsies performed better than that made from the same dense non porous antimonial lead alloy. This is generally due to their important specific surface area where oxidation-reduction reactions took place. A correlation between the effective electrical conductivity and the cell diameter has been established and the highest conductivity was obtained with a cell diameter of 5mm. The feasibility of such an electrical system has been demonstrated.

A new three-dimensional numerical model of a polymer electrolyte fuel cell (PEFC) with a single straight channel has been developed to primarily investigate the important impact of the double-sided microporous layer (MPL) coating on the overall performance of the fuel cell and the distribution of the current and the oxygen concentration within the cathode gas diffusion layers (GDLs). Realistic experimentally estimated interfacial contact resistance values between the gas diffusion layer and each of the bipolar plates and the catalyst layer values were incorporated into the model, and parametric studies were performed. The results showed that the double-sided MPL coating could significantly improve the fuel cell performance by up to 30%. Also, it was shown that the neglect of the contact resistance between the MPL and the catalyst layer could overestimate the fuel cell performance by up to 6%. In addition, the results showed that the fuel cell performance and the distribution of the current and oxygen are more sensitive to the porosity of the MPL facing the bipolar plate than the porosity of the MPL facing the catalyst layer. All the above results are presented and critically discussed in detail.

Photovoltaic(PV) power generation is highly nonlinear and stochastic. Accurate prediction of PV power generation plays a crucial role in grid connection as well as the operation and scheduling of power plants. To predict the PV power combination model, this paper suggests a method based on Empirical Mode Decomposition (EMD), Ensemble Empirical Mode Decomposition (EEMD), Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Nonlinear Auto-Regressive Neural Networks with Exogenous Input (NARXNN), Long Short Term Memory (LSTM) Neural Network, and Light Gradient Boosting Machine (LightGBM) algorithms. To attempt to reduce the non-smoothness of PV power, the weather variable features with the greatest effect on PV power are first identified by correlation analysis. Following this, the PV power modal decomposition is split and reorganized into a new feature matrix. Finally， a NARX is used to obtain preliminary PV power components and residual vector features， and the PV power is predicted by combining three models of LightGBM， LSTM, and NARX and then the final prediction results are obtained by combining the PV power prediction results using error inverse method weighted optimization. The prediction results demonstrate that the model put forth in this paper outperforms those of other models and validate the model's validity by utilizing real measurement data from Andre Agassi College in the United States.

This paper develops a chemical model for a closed constant volume combustion of gaseous mixtures of methane and hydrogen. Since the combustion is strongly depending on temperature, pressure and fuel composition, they were chosen the actual corresponding thermodynamic systems using this kind of combustion, respectively the spark ignition reciprocating engines in order to evaluate the combustion parameters and exhaust flue gases composition. The actual cycles impose extra restrictive operational conditions through the engine volumetric compression ratio, the geometry of combustion volume, the mode to prepare the mixture of methane and hydrogen, the cooling system and the delivered power. The chemical model avoided the unknown influences in order to explain accurately the influence of hydrogen upon the constant volume combustion and flue gases composition. The model adopted simplifying hypotheses, respectively isentropic compression and expansion processes, closed constant volume combustion developed by two successive steps obeying to the energy and mass conservation laws and, flue gases exhaust described also by two steps, i.e. an isentropic expansion through the flow section of exhaust valves followed by a constant pressure stagnation (this succession is corresponding in fact to a throttling direct process). The chemical model supposed the homogeneous mixtures of gases with variable heat capacities function of temperatures, the Mendeleev - Clapeyron ideal gas state equation and, the variable chemical equilibrium constants for chosen chemical reactions. It was assumed that the flue gases chemistry is prevailing during the isentropic expansion and flue gases exhaust and has mainly a thermal ground. The chemical model allowed evaluation of flue gasses composition and of noxious emissions.

In this paper, dual-rotor counter-rotating (CR) configurations of vertical axis wind turbines (VAWT) are briefly inspected and divided into three types. This investigation was focused on one of these types – the CR-VAWT with co-axial rotors, in which two equal rotors are placed on the same shaft, displaced from each other along it and rotate in opposite directions. For this CR-VAWT with three-blade H-Darrieus rotors, the properties of the design in terms of aerodynamics, mechanical transmission and electric generator, as well as control system are analyzed. A new direct-driven dual-rotor (DR) permanent magnet synchronous generator (PMSG) was proposed, in which two built-in low-power PM electric machines have been added. They perform two functions – start-up and overclocking of the rotors to the angular velocity at which the lifting force of the blades is generated and stabilizing the CR-VAWT work as wind gusts act on the two rotors. Detailed in this paper is the evaluation of aerodynamic performance of the CR-VAWT via 3D computational fluid dynamics (CFD) simulations. The evaluation was conducted using the CONVERGE CFD software with the inclusion of the actuator line model for the rotor aerodynamics, which significantly reduces the computational effort. Obtained results show that both rotors, while they rotate in opposite directions, had a positive impact on each other: the power coefficients of the upper and lower rotors in the CR-VAWT increased by 5.5% and 13.3% respectively compared to the single-rotor VAWT at the optimal distance between the rotors of 0.3 from a rotor height.

Due to pollution and environmental deterioration, man needed to find other alternatives as energy sources, including biomass. (1) Background: The present research was conducted to evaluate the sugarcane cutting residue; this type of biomass has no use and can be burned to obtain energy. (2) Methods: Through the elaboration of pellets and, in turn, reduce the environmental impact of flora and fauna in crops, for the characterization, the raw material was subjected for the first time to physical treatment such as cleaning, drying, grinding, and sieving so that have the optimal characteristics to be used in the pelleting stage. Then a proximal analysis was conducted based on the ASTM -3172-89 Standard and the determination of the calorific value using the ASTM D-240 Standard. Likewise, the pellets were analyzed in their final stage. This method analyzes the parameters of moisture content, volatile material, ashes, and fixed carbon. (3) Results: It was obtained as a result that for the raw material, the % H=3.543, %MV=86.53, %Cz=6.939, %Cf= 2.987 and Pc= 15.702 KJ/Kg; and for the elaboration of the pellets it was carried out using the mixing proportion, 53% SAR with 47% binder, this was determined using the proximal analysis and the determination of the calorific value, from which the results of % H=5,768 were obtained., %MV=82.313, %Cz=6.376, %Cf= 5.543 and Pc= 15.635 KJ/Kg. (4) Conclusions: In other words, sugarcane cutting residues meet the physicochemical properties to be used as raw material in producing solid biofuel.

The increased interest in space activities, structural health monitoring, and terrestrial monitoring in hostile and inaccessible zones places a high demand for energy sources for autonomous systems. Conventional electrochemical batteries that could be used are plagued by low energy storage density, short life, disposal of unwanted batteries, and related undesired recharging or replacement maintenance requirements, which endangers the environment. Fuel cells and solar energy sources being exploited to mitigate the adverse effect of environmental threats posed by batteries and fossil fuels are costly to acquire and maintain. The availability of energy sources derived from waste heat from radioactive decay for domestic appliances and industrial equipment will also help alleviate the effects of climate change, which continues to threaten the environment due to fossil fuel energy-based sources that emit harmful carbon monoxide into the atmosphere. A combination of energy from waste heat, harvested via thermoelectricity and existing battery technology to produce a hybrid energy source, can guarantee secured energy for an extended period. Based on the Seebeck effect, thermoelectric energy generation may considerably contribute to sustainable energy development and meet the power demand for spacecraft applications. Modeling of the energy from waste heat, the Li-ion battery, and a hybrid energy source are considered, and their performances are established using the MATLAB/Simulink environment. Results confirmed the comparative advantage of the hybrid energy source over and above the respective electrochemical batteries and waste heat energy sources regarding effectiveness and performance efficiency. Since batteries are required to operate in a constantly changing environment, the effects of temperatures on batteries were investigated. The results show that the performances of batteries decrease with a decrease in ambient temperature and that the higher the maximum operating capacity, the higher the battery's internal temperature.

To overcome the temperature effect of NaI(Tl) detectors for energy spectrometry without additional hardware, a new correction method was put forward based on pulse deconvolution, trapezoidal shaping and amplitude correction, named DTSAC. To verify this method, actual pulses from a NaI(Tl)-PMT detector were measured at different temperatures from -20℃ to 50℃. Pulse processing and spectrum synthesis showed that the position drift of the 662 keV peak was less than 3 keV, and the corresponding resolution at 662 keV of the sum spectra ranges from 6.9% to 10.60% with trapezoidal width set as 1000 ns to 100 ns. The DTSAC method corrects temperature effect by pulse processing, and need no reference peak, reference spectrum and additional circuits. The method solves the problem of correction of pulse shape and pulse amplitude at the same time, and can be used even at high counting rate.

Green hydrogen is likely to play an important role in meeting the net zero targets of countries around the globe. Hence, producing green hydrogen cheaply and effectively is an important area of research. One potential option for green hydrogen production is to run electrolysers directly from offshore wind turbines, with no grid connection and hence no expensive cabling to shore. The removal of the grid presents an unusual integration challenge. The variable nature of wind turbines and farms results in a power output that can fluctuate more quickly than the electrolyser’s ability to respond without significantly stressing the electrolyser. Thus, the use of a battery, with the wind farm, becomes essential to even out some of the power variations that the electrolyser cannot deal with. In this work, a proof of concept of a wind farm control methodology designed to reduce variability in wind farm active power output is presented. Smoothing the power supplied by the wind farm to the battery reduces the size and number of battery charge cycles and helps to increase battery lifetime. Considering off-grid wind farms which exclusively power an electrolyser, this work quantifies the impact of the wind farm control method on battery lifetime for wind farms of 1, 4, 9 and 16 wind turbines. This is achieved using suitable wind farm, battery and electrolyser models. As an example, for the largest wind farm studied, consisting of 16 x 5 MW wind turbines, batteries with a lifetime of 15 years have approximately a 30 % reduction in required capacity (reduced from 14 MWh to 10 MWh) compared to operating without wind farm control. It is found that reducing the variability of the active power output of wind farms through the wind farm control methodology presented can have a significant impact on battery degradation and hence on battery lifetime. Hence, wind farm control can reduce the required battery capacity for a given lifetime or it can increase the lifetime of a given battery capacity. The work presented shows that wind farm control could play a critical role in reducing the levelised cost of green hydrogen produced from wind farms with no grid connection and paves the way for the design and testing of a full implementation of the wind farm control.

Intense thermoacoustic oscillations may lead to severe deterioration due to the induced intolerable damage to combustors. A better understanding of unstable behaviors is important to prevent or suppress these oscillations. Active thermoacoustic coupling in practical combustors is caused primarily by two approaches: inherent turbulent fluctuations and the flame response to acoustic waves. Turbulent fluctuations are generally characterized by random noise. This paper experimentally expands on previous analytic studies regarding the influence of colored disturbances on the thermoacoustic response near the supercritical bifurcation point. Therein, a laboratory-scale Rijke-type thermoacoustic system is established, and both supercritical and subcritical bifurcations are observed. Then, Ornstein–Uhlenbeck (OU)-type external colored noise is introduced near the supercritical bifurcation point, and the effects of the corresponding correlation time τc and noise intensity D are studied. The experimental results show that these variables of the colored noise significantly influence the dynamics of thermoacoustic oscillations in terms of the most probable amplitude, autocorrelation, and correlation time. A resonance-like behavior is observed as the noise intensity or the autocorrelation time of the colored noise is continuously varied, which means that the coherent resonance occurs in the thermoacoustic system. Finally, when the system is configured closer to the stability boundary, the extent of the coherence motion is intensified in the stochastic system response. Meanwhile, the Signal to Noise Ratios (SNRs) of the colored-noise-induced response are found to become more distinguished, the optimal colored noise intensity decreases, and the optimal autocorrelation time increases. This provides valuable guidance to predict the onset of thermoacoustic instabilities.

The heat release response of the flame to acoustic excitation is a critical factor for understanding combustion instability. In the present work, the nonlinear heat release response of a methane-air non-premixed flame to the low frequency acoustic excitations is experimentally investigated. The flame describing function (FDF) was measured based on the overall CH* chemiluminescence intensity and the velocity fluctuations obtained by two-microphone method. The CH* chemiluminescence images and the schlieren images were analyzed to reveal the mechanism of nonlinear response. The excitation frequency ranges from 10Hz to 120Hz. The forced relative velocity fluctuation amplitude ranges from 0.10 to 0.50. The corresponding flame Strouhal number (Stf) ranges from 0.43 to 4.67. The study has shown that the flame length responds more sensitively to changes in excitation amplitude when subjected to relatively high frequency excitations. The normalized flame length (Lf/D) decreases from 3.79 to 2.37 with the increase of excitation amplitude at excitation frequency of 100Hz. The number of oscillation zones along the flame increases with increasing excitation frequency, which is consistent with the increase of the Stf. The low-pass filtering characteristic of FDF is caused by the dispersion of multiple oscillation zones, as well as the cancellation effect of the adjacent oscillation zones under relatively high frequency excitation. The cancellation effect of the positive and negative oscillation zones with various Stf is main mechanism for the local gain peak and valley. When two adjacent oscillation regions have approximate amplitudes, the overall phase-lag becomes more sensitive to changes in excitation frequency and amplitude. This sensitivity leads to nonlinear anomalous changes in the phase-lag near the frequency corresponding to the gain valley. The calculated disturbance convection time is consistent with the measured time delay in the short flame scenario. Future research is necessary to establish whether the observed agreement occurs due to the oscillation zone consistently occurring proximate to the flame's center of mass, coupled with a precise determination of the average convective velocity.

Indirect fracturing from roof rock to coal using a horizontal well is a new and promising technology for coalbed methane surface exploitation in soft and low-permeability coal seams. In order to study the propagation law of hydraulic fracture across the coal-rock interface, a pore pressure cohesive element is used to establish a numerical model for indirect fracturing. Combined with practical engineering in 3# coal seam in Xinjing mine in China, the propagation behavior of hydraulic fracture across the coal-rock interface was researched, and the range of horizontal well position for indirect fracturing was determined. The results show that: (1) the pore pressure cohesive element can be used to simulate accurately the interaction between hydraulic fracture and natural fracture, and the propagation of hydraulic fracture across the coal-rock interface. (2) As the vertical distance between the horizontal well and coal-rock interface decreases, the breakdown pressure of perforation decreases; while the injection pressure increases when the hydraulic fracture crosses the coal-rock interface. (3) For the indirect fracturing engineering in 3# coal seam in Xinjing mine, the vertical distance between the horizontal well and coal-rock interface should not be larger than 2.0m to make the hydraulic fracture propagate into the coal seams.

Nowadays, hydropower is the principal renewable; however, climate change increases extreme events such as floods, droughts, erosion, and sedimentation of rivers that produce uncertainty in hydroelectric generation. Thus, this document aims to analyze the climate change projections in the hydropower systems of Ecuador based on data from 14 projects studying the scenarios ac-cording to the Shared Socioeconomic Pathways from the Intergovernmental Panel on Climate Change. The study period starts from 2010 to 2020 with historical data, collects the tendency, defines a database year, and then projects the scenarios to 2050. The quantitative methodology uses a statistic on Ecuador's hydropower obtained inflow time series to calculate the deviation over the last years and develop a model to simulate future generation. The results show that the hydropower in Ecuador is expected to decrease considerably through 2050 due to meteorological changes. In this calculation of the Shared Socioeconomic Pathways, the selected scenarios show a reduction in SSP5 of 11.5%, SP2 of 16.2%, and SSP4 of 18.2% to 2050, concluding that the oppor-tunities for hydroelectric production facing climate change are variable, but the challenges are broad. In Ecuador, the projections of hydropower plants represent a sensitive issue of their re-ductions, especially knowing that the country had an energy grid in 2020 that depended on 87% of hydroelectric production.

Rooftop solar (RTS) projects have the potential to contribute to climate change mitigation and sustainable development objectives. In India, grid-connected RTS capacity has been targeted at 40 GW by the end of the year 2022 however, the installed capacity is limited to 8.2 GW only. As a result, the country missed its 2022 target of installing 100 GW of solar power capacity, largely due to inadequate uptake of RTS. The prevailing practices of RTS implementation is observed to be complex, repetitive, tedious, and time-consuming for potential consumers and there is a lack of coordination among implementing agencies. Therefore, even with vast potential, supportive measures, dedicated policies, and regulations the penetration of RTS systems is far below their respective potential. The introduction of information technology (IT) intervention in the RTS sector would integrate key stakeholders at a single platform so as to reduce the administrative burden of implementing agencies, optimization of processing time, handle multiple consumers simultaneously, and connect consumers with authentic vendors, etc. This would help them to understand and perform their shared roles and responsibilities and enhance the RTS implementation across the state. In this study, the scope for IT interventions in the existing RTS implementation process of the Odisha Renewable Energy Development Agency (OREDA) has been assessed and a simplistic approach has been developed for the execution of the RTS projects in relatively lesser time with the least human interface as well as resources. This approach has been successfully demonstrated with OREDA and a cumulative capacity of around 5 MWp (individual project of 1-2 kWp) residential grid-connected RTS projects implemented through the web platform. Currently, other state nodal agencies are also adopting the model for RTS execution and consumer proliferation through IT interventions.

The transportation sector is a significant source of greenhouse gas emissions. Electric vehicles (EVs) have gained popularity as a solution to reduce emissions, but the high load of charging stations poses a challenge to the power grid. Nuclear-Renewable Hybrid Energy Systems (N-RHES) present a promising alternative to support fast charging stations, reduce grid dependency, and decrease emissions. However, the intermittent problem of renewable energy sources (RESs) limits their application, and the synergies among different technologies have not been fully exploited. This paper proposes a predictive and adaptive control strategy to optimize the energy management of N-RHES for fast charging stations, considering the integration of nuclear, photovoltaics, and wind turbine energy with a hydrogen storage fuel cell system. The proposed dynamic model of a fast-charging station predicts electricity consumption behavior during charging processes, generating probabilistic forecasting of electricity consumption time-series profiling. Key performance indicators and sensitivity analyses illustrate the practicability of the suggested system, which offers a comprehensive solution to provide reliable, sustainable, and low-emission energy to fast-charging stations while reducing emissions and dependency on the power grid.

The prediction of wind power output is part of the basic work of power grid dispatching and energy distribution. At present, the output power prediction is mainly obtained by fitting and regressing the historical data. The medium- and long-term power prediction results exhibit large deviations due to the uncertainty of wind power generation. In order to meet the demand for accessing large-scale wind power into the electricity grid and to further improve the accuracy of short-term wind power prediction, it is necessary to develop models for accurate and precise short-term wind power prediction based on advanced algorithms for studying the output power of a wind power generation system. This paper summarizes the contribution of the current advanced wind power forecasting technology and delineates the key advantages and disadvantages of various wind power forecasting models. These models have different forecasting capabilities, update the weights of each model in real time, improve the comprehensive forecasting capability of the model, and have good application prospects in wind power generation forecasting. Furthermore, the case studies and examples in the literature for accurately predicting ultra-short-term and short-term wind power generation with uncertainty and randomness are reviewed and analyzed. Finally, we present prospects for future studies that can serve as useful directions for other researchers planning to conduct similar experiments and investigations.

Small hydro-power systems seem to be the best solution for energy generation through the use of pump as turbine (PAT) due to its low cost and lesser environmental hazards associated with it. Recently, PAT applications are gaining global attention in energy generation but its operation is not fully understood. The performance and flow behavior is affected by several operational conditions. This study seeks to investigate the effects of rotational speed on flow behavior and performance of a PAT. Rotational speed is an important physical parameter that affects the operation of a PAT. A selected centrifugal pump model of four blades and splitters was used for the study. Numerical simulations were carried out using k-ε turbulence model to solve the three-dimensional (3D) equations in both pump and PAT modes. The outcomes were then validated using experimental results in the pump mode to obtain overview flow physiognomies. The results predicted that the efficiency increases as the rotational speed increases in the pump mode whereas in turbine mode, higher rotational speed cannot convert hydraulic energy into mechanical energy. Thus, a rotational speed of 1500 rpm performed the highest efficiency of 69.8% at QBEP among the other rotational speeds selected. Moreover, the head performance in the turbine mode increases as the flow rate increases. This research provides useful information which will help improve PAT performance as well as selecting PAT for small hydro-power site.

The population growth, economic development and urbanization of the city of Douala in Cameroon are facing great challenges, particularly environmental and economic problems. However, there is an evolution of the road transport sector that has led to an excessive increase in the consumption of fossil fuels and over the last decades to an increase in greenhouse gases in the road transport sector. From this observation, no real policy has yet been put in place with a view to improving the energy efficiency of the transport sector. This work aim at analyzing the driving force factors of energy consumption in road transport in the city of Douala. In this study, a decomposition analysis through the Logarithmic Mean Divisa Index (LMDI) method is used during the period 2010-2019 to quantify their respective contributions in energy consumption. We have broken down road transport energy consumption into four main factors as main determinants such as: vehicle energy intensity, vehicle intensity, Gross Domestic Product (GDP) per capita and population. The results show that vehicle energy intensity, vehicle intensity, GDP per capita and population effect all have a positive impact on energy consumption and therefore main responsible for the increase in fuel consumption energy contributing respectively to 13.06%, 31.30%, 12.85% and 42.76% of the total variation of energy consumption. It is therefore necessary to implement several energy saving strategies in order to achieve a rationalization of energy consumption for a reduction of road transport energy. Political decision-makers must take such a study into account to better integrate the notion of sustainable transport.

For thermoelectric materials study and development, it is very important to measure the electrical power and efficiency of a thermoelectric generator (TEG). In this study, thermoelectric properties such as electrical conductivity, Seebeck coefficient, and thermal conductivity of cement composites with graphene nanoplatelets and metallic oxides (Fe2O3, ZnO, MnO2) are measured and subsequently used to figure out the output electrical power and efficiency. A maximum of 1.5 W power per square meter for a temperature difference of about 50 °C can be estimated using GnP-ZnO added cement composites. This paper also talks about how to make a cement composite-based structural TEG module to enhance the total output voltage, power, and efficiency of the system.

The spiral tube heat exchange is widely used in large-scale liquefaction process. However, the research on the friction pressure drop of the two-phase flow in the spiral tube is limited, especially for the offshore sloshing condition. In this paper, an experimental system is designed and built, and the effects of sloshing form (roll, pitch, heave), sloshing period (5-15s), mass flux (200-800 kg/(m2·s)), vapor quality (0.3-0.9) and operating pressure (2-4 MPa) on friction pressure drop of methane/ethane (C1/C2) mixture in spiral tube are studied. The result shows that the growth rate of time-averaged friction pressure drop during condensation under sloshing condition is less than 0, which indicates that sloshing will lead to drag reduction. And under the three sloshing parameters, the growth rate of time-averaged friction pressure drop of C1/C2 is reduced by-5.99%%, 5.97% and -6.70% respectively.

: Efficient or at least rational use of energy resources is a problem that occupies an overwhelming number of people in modern society – from major scientists and politicians to journalists and schoolchildren who have a poor understanding of the basic laws of physics.(the knowledge of politicians in this area is also sometimes doubtful). At the same time, the main focus of the discussions is on the resource base, possible waste and consequences. According to these features, they want to see the future of energy. However, the division of "energetik" follows different principles. On the one hand, these are thermal, nuclear and hydropower sources. On the other – wind and solar energy. Obviously, this separation is not only related to the renewable resources or the absence of consequences for the environment and humans. If we do not touch on geopolitical problems. which are not the subject of this article, it is obvious that the main dividing feature of these types of energy production will be their controllability. The theory of automatic control (TAU) is one of the most complex modern sciences that has been developing for many years to solve precisely the problems of energy Now, when considering energy problems, this science is most often not remembered. Maybe because the most active participants in the discussions don't know much about it? Or is this situation beneficial to someone? How efficiency and controllability are related to some problems with controllability in the "household" energy sector, which concerns almost every inhabitant of the planet and in the global energy sector, this article is devoted to

The production of SOX by ship engines is a serious environmental problem and has been addressed by international standards. The restrictions limit the sulphur content of the fuel to 0.5% by mass to reduce SOX emissions; however, using low sulphur fuels such as LNG causes logistical and operational problems, as well as having a higher price. For these reasons, there has been renewed interest in developing devices such as the Seawater Scrubber (SWS). This paper describes a simplified numerical model to simulate the absorption of SO2 in a drop of water during a dynamic "wet scrubbing" process. The dependence on the initial conditions is demonstrated by running multiple simulations as the initial droplet diameter, temperature and SO2 concentration in the flue gas vary. The work shows how the amount of sulphur dioxide absorbed is strongly related to the concentration in the exhaust gases and the initial diameter of the droplet, and highlights how distributions of smaller droplets than an upper limit value optimize the absorption process.

Activated Corrosion Products (ACPs) formation and deposition pose a critical safety issue for nuclear fusion reactors. The working fluid transports the ACPs towards regions accessible to worker personnel. Predicting ACPs formation deposition and transport is fundamental for source term identification, reduction of radiation exposure assessment, maintenance plan definition, design optimization, and waste management. The code OSCAR-Fusion has been developed by the CEA (France) to evaluate the ACPs generation and transport in closed water-cooled loops for fusion application. This work aims at assessing the impact of water chemistry on the transport, precipitation, and deposition of corrosion products for the EU-DEMO divertor Plasma Facing Unit Primary Heat Transfer System. Sensitivity analyses and uncertainty quantification are needed due to the multi-physics phenomena involved in ACPs formation and transport. The OSCAR-Fusion/RAVEN code coupling developed by the Sapienza University of Rome and ENEA has been used. This work presents the perturbation results of different parameters chosen for a closed water-cooled loop considering a continuous scenario of 1888 days. The aim of this work is to assess the variation of build-up of ACPs, perturbing the alkalizing agent concentration into the coolant and the corrosion and release rates of different materials.

In Lubumbashi, the capital of Haut Katanga in the Democratic Republic of the Congo (DR Congo), diesel power plants are a common source of electricity. The need to utilise local renewable energy sources in DR Congo has increased due to the unreliability of the state grid and the rising cost of running Diesel generators. Solar photovoltaic (PV) panels and batteries, in particular, have recently seen significant price drops. Therefore, it is important for operators and suppliers to choose optimal generators together with a renewable energy system to lessen the energy deficit. Diesel generators are still widely used in DRC, but their efficiency pales in contrast to that of more recent power facilities. Consuming fossil fuels results in high expenses for upkeep and operation, in addition to severe environmental damage. This study assessed the feasibility of using local weather and technical data to evaluate the efficiency of a diesel power plant hybridized with a PV system. Hybrid Optimization Model for Electric Renewable (HOMER) simulations suggest that the hybrid system schedule is preferable due to its many economic and environmental advantages for the local community and its inhabitants. The promotion of such a hybrid system, then, may encourage the sustainable economic development of a stable source of electricity for the Congo Region.

To promote low-carbon and green travel, this study proposes a tripartite evolutionary game model among new energy vehicle manufacturers, consumers, and government agencies. The game strategy combinations of each party and the stability conditions of the equilibrium point in the evolutionary game system are analyzed, and the validity of the conclusions is verified through simulation results. The study shows a strong correlation between the three parties in the evolutionary game system. From the perspective of car manufacturers, the probability of producing new energy vehicles is positively proportional to the subsidy received from new energy policy, the additional revenue gained from the management of the carbon trading scheme, and the fine received for producing conventional fuel vehicles. However, from the consumer perspective, the likelihood that consumers purchase new energy vehicles is positively related to the utility value to consumers and the coverage of public charging points in the city, and inversely related to the sales price of new energy vehicles. From the government perspective, a combination of direct subsidy policies and indirect support strategies should be considered to stimulate the rapid development of the new energy vehicle industry.

Nowadays, in low voltage (LV) electric distribution networks (EDNs), the Distribution Network Operators (DNOs) are encountering a high number of connected small-scale distributed generation units, mainly photovoltaic (PV) prosumers. The irregular behavior of the prosumers, together with the uncertainty degree of the requested and injected powers associated with all end-users from the LV EDN, can cause voltage variations with violations of the allowable limits. In this context, the paper developed an efficient and resilient expert system integrating the rule-based reasoning applied to the On-load Tap Changer (OLTC)-fitted transformer to improve the efficiency of the voltage control in the PV-rich LV EDNs. An in-depth analysis based on 75 scenarios, resulting from the combinations of three indicators: the penetration degree of the PV prosumers, consumption evolution associated with the consumers, and energy production of the PV systems, has been performed to demonstrate the efficiency of the proposed expert system in an LV EDN from a rural area belonging to a Romanian DNO. The success rate of the expert system has been 86.7% (65 out of 75 scenarios didn't have voltage issues, all values being between the allowable limits in 100% of the time slots associated with the analyzed period). For the other scenarios (representing 13.3%), the values have been inside the range [-10%, +10%] at least 95% of the time slots, according to the European Power Quality Standard, and for the rest of the time slots up to 100% being very close to the upper and lower limits of the range, with highly mitigating of the voltage variations.

Our planet faces several serious and urgent challenges to sustainability, not just climate change. Most researchers argue that technological solutions can solve these problems. This review paper first examines the prospects for decoupling environmental damages in general from economic growth, considered at the global level, then looks at whether the recent advances in Information and Communication Technology (ICT) can help. It is argued that although absolute decoupling might have occurred in some countries, even after accounting for energy-intensive imports, it has not occurred at the global level, which is the relevant level for global sustainability problems. This conclusion is strengthened by the very high correlation over the past three decades found between GDP and several parameters relevant for sustainability, particularly for atmospheric CO2 ppm and ecological footprint as a function of Gross Domestic Product (GDP). ICT innovations relevant to energy use include smart grids and smart cities, especially smart urban transport. A review of recently published papers shows no definite findings of energy or carbon reduction, although some innovations show energy/carbon reduction potential, if given strong policy support. However, the needed policies could well give marked reductions even without ICT approaches. Overall, it is concluded that Earth’s sustainability challenges will necessitate deep energy reductions, which in turn require profound sociopolitical changes.

Nonequilibrium work switching simulations and Jarzynski’s equation are a reliable method to compute free energy differences, ΔAlow→high, between two levels of theory, such as a pure molecular mechanical (MM) and a quantum mechanical/molecular mechanical (QM/MM) description of a system of interest. Despite the inherent parallelism, the computational cost of this approach can quickly get very high. This is particularly true for systems where the core region, the part of the system to be described at different levels of theory, is embedded in an environment, such as explicit solvent water. We find that even for relatively simple solute–water systems, switching lengths of at least 5 ps are necessary to compute ΔAlow→high reliably. In this study, we investigate two approaches towards an affordable protocol, with emphasis on keeping the switching length well below 5 ps. Inserting a hybrid charge intermediate state with modified partial charges which resembles the charge distribution of the desired high level makes it possible to obtain reliable calculations with 2 ps switches. Attempts using step-wise linear switching paths, on the other hand, did not lead to improvement, i.e., faster convergence for all systems. To understand these findings, we analyzed the solutes’ properties as a function of partial charges used, the number of waters in direct contact with the solute, and studied the time needed for water molecules to reorient themselves upon a change in the solute’s charge distribution.

Agrivoltaics (Agri-PV, AV) – the joint use of land for the production of agricultural products and energy – has recently been rapidly gaining popularity, as it can significantly increase income per unit of land area. In a broad sense, AV systems can include converters of not only solar, but also energy from any other local renewable source, including bioenergy. Current approach to AV represents an evolutionary development of agroecology and integrated PV power supply to the grid. That results in nearly doubled income per unit area. While AV could provide a basis for revolution in large-scale unmanned precision agriculture and smart farming which is impossible without on-site power supply, chemical fertilisation and pesticides reduction, and yield processing on-site. These approaches could change the logistics and the added value production chain in agriculture dramatically, and so, reduce its carbon footprint. Utilisation of decommissioned solar panels in AV could make the technology twice cheaper and postpone the need for bulk PV recycling. Unlike the mainstream discourse on the topic, this review feature is in focusing on the possibilities for AV to be stronger integrated into agriculture that could also help in relevant legal collisions (considered as neither rather than both components) resolution.

Raman-based Distributed Temperature Sensing (DTS) is a valuable tool for field testing and validating heat transfer models in Borehole Heat Exchanger (BHE) and Ground Source Heat Pump (GSHP) applications. However, temperature uncertainty is rarely reported in the literature. In this paper, a new calibration method is proposed for single-ended DTS configurations, along with a method to remove fictitious temperature drifts due to ambient air variations. The methods are implemented for a Distributed Thermal Response Test case study in an 800 m deep coaxial BHE. The results show that the calibration method and temperature drift correction are robust and give adequate results, with a temperature uncertainty of ± 0.58, 0.74, 1.1 and 1.7 K found at depths of 200, 300, 500 and 800 m, respectively. The temperature uncertainty increases non-linearly with depth and is dominated by the uncertainty in the calibrated parameters for depths larger than 200 m. The paper also offers insights into thermal features observed during the DTRT, including a heat flux inversion along the borehole depth and the slow temperature homogenization under circulation. Distributed temperature measurements and their uncertainties are useful tools in determining the strengths and drawbacks of ground heat transfer models.

This work investigates how to balance the electricity supply and demand in a carbon-neutral northern Europe. Applying a cost-minimizing electricity system model including options to invest in eleven different flexibility measures, cost-efficient combinations of strategies to manage varia-tions are identified. The results of the model are post-processed using a novel method to map the net load before and after flexibility measures are applied to reveal the contribution of each flexi-bility measure. The net load is mapped in the space spanned by the amplitude, duration, and number of occur-rences. The mapping shows that, depending on cost structure, flexibility measures contribute to reduce the net load in three different ways; 1) by reducing variations of long duration but low amplitude, 2) by reducing variations of high amplitude but short duration and low occurrence or 3) by reducing variations of high amplitude, short duration and high occurrence. It is found that cost-efficient variation management is achieved by combining wind and solar power and by combining strategies (1-3) to manage variations. The cost-efficient combination of strategies de-pends on electricity system context where electricity trade, flexible hydrogen and heat production (1) manage the majority of variations in regions with good conditions for wind power while sta-tionary batteries (3) are the main contributors in regions with good conditions for solar power.

The digital era offers many opportunities to the wind energy industry and research community. Digitalisation is one of the key drivers for reducing costs and risks over the whole wind energy project life cycle. One of the largest challenges in successfully implementing digitalisation is the lack of data sharing and collaboration between organisations in the sector. In order to overcome this challenge, a new collaboration method called WeDoWind was developed in recent work. The main innovation of this method is the way it creates tangible incentives to motivate and empower different types of people from all over the world to actually share data and knowledge in practice. In this present paper, the challenges related to comparing and evaluating different SCADA data based wind turbine fault detection models are investigated by carrying out a new case study, the "WinJi Gearbox Fault Detection Challenge", based on the WeDoWind Method. Six new solutions were submitted to the challenge, and a comparison and evaluation of the results show that, in general, some of the approaches (Particle Swarm Optimisation algorithm for constructing health indicators, performance monitoring using Deep Neural Networks, Combined Ward Hierarchical Clustering and Novelty Detection with Local Outlier Factor and Time-to-failure prediction using Random Forest Regression) appear to have a high potential to reach the goals of the Challenge. However, there are a number of concrete things that would have to have been done by the Challenge providers and the Challenge moderators in order to ensure success. This includes enabling access to more details of the different failure types, access to multiple data sets from more wind turbines experiencing gearbox failure, provision of a model or rule relating fault detection times or a remaining useful lifetime to the estimated costs for repairs, replacements and inspections, provision of a clear strategy for training and test periods in advance, as well as provision of a pre-defined template or requirements for the results. These learning outcomes are used directly to define a set of best practice data sharing guidelines for wind turbine fault detection model evaluation. They can be used by the sector in order to improve model evaluation and data sharing in the future.

The most potential renewable energy source for global emissions reductions is green hydrogen production. Iraq is looking into several sources of alternative energy to lessen its dependency on fossil fuels and to considerably cut its carbon dioxide emissions. This research examined the conceptual framework for the production and consumption of green hydrogen in Iraq. On the basis of accessible official and public data from government agencies, the potential capabilities of renewable energy resources are assessed, and certain fair assumptions are also established for a full study and evaluation of a possible hydrogen production in the country. The data presented here demonstrate conclusively that the contributions of renewable energy to the production of green hydrogen are substantial, giving the country prominence in the area of green hydrogen production. A pathway for a green hydrogen economy in the country by 2050 is proposed by this research based on its analysis. It is distributed in three stages: green hydrogen as a fuel for industry; using green hydrogen for fuel cells; and hydrogen commercialization. On the other hand, the research found a number of challenges to the implementation of a green hydrogen production that can be used in Iraq and other developing countries, including technological, economic, and social problems in addition to the related policy consequences.

Significant amount of oil remains in the reservoir after primary and secondary operations and to recover the remaining oil, enhanced oil recovery (EOR) can be applied as one of the feasible options remaining nowadays. In this study new nano polymeric materials have been prepared from purple yam and cassava starches. The yield of purple yam nanoparticles (PYNPs) was 85% and that of cassava nanoparticles (CSNPs) is 90.53%. Synthesized materials were characterized through particle size distribution (PSA), zeta potential distribution, Fourier transform infrared spectroscopy (FTIR), differential scanning calorimetry (DSC) and transmission electron microscopy (TEM). The performance of PYNPs in recovering oil was better than CSNPs as found from recovery experiments. Zeta potential distribution results confirmed the stability of PYNPs over CSNPs (-36.3 mV for PYNPs and -10.7 mV for CSNPs). The optimum concentration for these nanoparticles has been found from interfacial tension measurements and rheological properties and it was 0.60 wt.% for PYNPs and 0.80 wt.% for CSNPs. More incremental recovery (33.46%) has achieved for the polymer that contained PYNPs in comparison to the other nano-polymer (31.3%). This opens the inception for a new technology for polymer flooding that may replace the conventional method that depends on partially hydrolyzed polyacrylamide (HPAM).

This work investigated the effect of temperature and acid or alkalis chemical activation by pyrolysis of Açaí seeds (Euterpe Oleraceae, Mart.) on the yield of bio-oil, hydrocarbon content of bio-oil, and chemical composition of aqueous phase. The experiments were carried out at 350, 400, and 450 °C and 1.0 atmosphere, KOH and HCl activation, in laboratory scale. The acidity of bio-oils and aqueous phases determined by AOCS methods, while the chemical composition of bio-oils and aqueous phase by GC-MS and FT-IR. The bio-char characterized by XRD. For the activation with KOH, the XRD analysis identified the presence of Kalicinite (KHCO3), the dominant crystalline phase in bio-char, while an amorphous phase was identified in bio-chars for the activation with HCl. The yield of bio-oil, for the pyrolysis of Açaí seeds activated with KOH, varied between 3.19 and 6.79 (wt.%), showing a smooth exponential increase with temperature. The acidity of bio-oil varied between 12.3 and 257.6 mgKOH/g, decreasing exponentially with temperature, while the acidity of aqueous phase lies between 17.9 and 118.9 mgKOH/g, showing and exponential decay behavior with temperature, demonstrating that higher temperatures favor not only the yield of bio-oil but also bio-oils with lower acidity. For the pyrolysis experiments activated with HCl, the yield of bio-oil varied between 2.13 and 3.37 (wt.%), decreasing linearly with temperature, while that of gas phase varied between 17.91 and 37.94 (wt.%), increasing linearly with temperature. The acidity of bio-oil varied between 127.1 and 218.5 mgKOH/g, increasing with temperature, showing that higher temperatures did not favor the yield of bio-oil and bio-oils acidity. For the chemical activation with KOH, the FT-IR analysis of bio-oils identified the presence of chemical groups characteristics of hydrocarbons and oxygenates, while that of aqueous phase only groups characteristics of oxygenates. For the chemical activation with HCl, the FT-IR analysis of bio-oil and aqueous phases identified only the presence of groups characteristics of oxygenates. For the experiments with KOH activation, the GC-MS of bio-oil identified the presence of hydrocarbons (alkanes, alkenes, cycloalkanes, cycloalkenes, and aromatics) and oxygenates (carboxylic acids, phenols, ketones, and esters). The concentration of hydrocarbons varied between 10.19 to 25.71 (area.%), increasing with temperature, while that of oxygenates from 52.69 to 72.15 (area.%), decreasing with temperature. For the experiments with HCl activation, the GC-MS of bio-oil identified only the presence of oxygenates. Finally, it can be concluded that chemical activation of Açaí seeds with KOH favors the not only the yield of bio-oil but also the content of hydrocarbons while activation with HCl produced bio-oils with only oxygen compounds.

Human and animal waste, including waste products originating from human or animal digestive systems such as urine, feces, and animal manure, have constituted a nuisance to the environment. Inappropriate disposal and poor sanitation of human and animal waste often cause negative impacts on human health through contamination of the terrestrial environment, soil, and water bodies. Therefore, it is necessary to convert these wastes into useful resources to mitigate their adverse environmental effect. The present study provides an overview and research progress of different thermochemical and biological conversion pathways for the transformation of human- and animal-derived waste into valuable resources. The physicochemical properties of human and animal waste are meticulously discussed as well as nutrient recovery strategies. In addition, a bibliometric analysis is provided to identify the trends in research and knowledge gaps. The results reveal that the U.S.A, China and England are the dominant countries in the research areas related to resource recovery from human or animal waste. In addition, researchers from the University of Illinois, the University of California Davis, the Chinese Academy of Science and Zhejiang University are front runners in research related to these areas. Future research should be centred on developing technologies for the on-site recovery of resources, exploring integrated resource recovery pathways, and exploring different safe waste processing methods.

Nuclear technologies have the potential to play a major role in the transition to a global net-zero society. Their primary advantage is the capability to deliver controllable 24/7 energy on demand. However, as a prerequisite for successful worldwide application, significant innovation will be required to create the nuclear systems of the 21st century, the need of the hour. The pros and cons of nuclear are discussed and analysed at different levels – the societal and public recognition as well as the scientific/engineering and economic level – to assure a demand driven development. Based on the analysis of the different challenges a vision for the nuclear system of the 21st century is synthesised consisting of three pillars – unlimited nuclear energy, zero waste nuclear, and accident free nuclear. These three combined visions are then transformed into dedicated and verifiable missions which are discussed in detail regarding challenges and opportunities. In the following a stepwise approach for the development of such a highly innovative nuclear system is described. Essential steps to assure active risk reduction and the delivery of quick progress are derived as answer to the critique on the currently observed extensive construction time and cost overruns on new nuclear plants. The 4-step process consisting of basic studies, experimental zero power reactor, small scale demonstrator, and industrial demonstrator is described. The 4 steps including sub-steps deliver the pathway to a successful implementation of such a ground breaking new nuclear system. The potential sub-steps are discussed with the view not only onto the scientific development challenges, but also as an approach to reduce the regulatory challenges of a novel nuclear technology.

The second-order factor effect of burner optical ports and edge inter-matrices (EIM) and the first-order factor of pressure on the soot formation process and behavior of premixed sooting flames in a high-pressure burner are numerically investigated here. Three-dimensional computational fluid dynamics (CFD) simulations of a premixed flame C₂H₄/air at p = 1.01 and 10 bar using a one-step chemistry approach are first performed to justify the satisfied predictability of the prospective axisymmetric two-dimensional (2D) and one-dimensional (1D) simulations. The justified 2D simulation approach shows the generation of an axial vorticity around the EIM and axial multi-vorticities due to the high expansion rate of burnt gases at the high pressure of 10 bar. This leads to the development of axial multi-sooting zones, which are manifested experimentally by visible luminous soot streaks, and to the boosting of soot formation conditions of a relatively low-temperature field, < 1800 K, and a high mixing rate of gases in combustion around and above the EIM location. Nevertheless, a tolerable effect on the centerline soot volume fraction (f_V) profile, f_V < 3%, is manifested only at high heights above the burner of the atmospheric sooting flame C₂H₄/air ϕ = 2.1, and early at the high pressure of 10 bar of this flame, f_V < 10%. Enhancing the combustion process reactivity by decreasing the rich equivalence ratio of the fuel/air mixture and/or rising the pressure results in the prior formation of soot precursors, which shifts the sooting zone upstream.

SStatistical characteristics of the wind speed in Samaria region of Israel have been analyzed by processing 11 years of wind data provided by the Israeli Meteorological Service, recorded at 10 m height above the ground. The cumulative mean wind speed at measurement height was shown to be 4.53 m/s with standard deviation of 2.32 m/s. Prevailing wind direction is shown to be char-acterized by cumulative mean azimuth of 226° with standard deviation of 79.76°. The results were extrapolated to 70-meter height in order to estimate wind characteristics at hub height of a me-dium-scale wind turbine. Moreover, Weibull distribution parameters were calculated annually, monthly and seasonally, demonstrating a good match with histogram-based statistical repre-sentations. Shape parameter of the Weibull distribution was shown to reside within a narrow range of 1.93 to 2.15, allowing us to assume a Rayleigh distribution, thus simplifying wind tur-bines energy yield calculations. The novelty of the current paper is related to gathering wind statistics for a certain area (Samaria) we are not aware of any published statistics regarding wind velocity and direction in this area. The data may be interesting for potential regional wind energy development in which the obtained Weibull distribution can be used in calculations of expected power generation of particular turbines with known power dependence on velocity. We also point out that the fact that realistic wind velocity statistics is well described by an analytic formula (Weibull distribution) is not trivial, and in fact the fit may have been poor.

This study investigates the power production and blade fatigue of a three-turbine array subjected to active yaw control (AYC) in full-wake and partial-wake configurations. A framework of two-way coupled large-eddy simulation (LES) and aeroelastic blade simulation is applied to simulate the atmospheric boundary-layer (ABL) flow through the turbine array and the structural responses of the turbine blades. Mean power outputs and blade fatigue loads are extracted from the simulation results. By exploring the feasible AYC decision space, we find that (a) in the full-wake configuration, the local power-optimal AYC strategy with positive yaw angles endures less flapwise blade fatigue and more edgewise blade fatigue than the global power-optimal strategy; (b) in the partial-wake configuration, applying positive AYC in certain inflow wind directions achieves higher optimal power gains than that in the full-wake scenario and reduces the blade fatigue from the non-yawed benchmark. Through a theoretical analysis based on the blade element momentum theory, we reveal that the aforementioned differences in flapwise blade fatigue between the positively and negatively yawed turbine are due to the differences in the azimuthal distributions of the local relative velocity on blade sections, resulting from the combined effects of vertical wind shear and blade rotation. Furthermore, the difference in the blade force between the positively and negatively yawed front-row turbine induces different wake velocity and turbulence distributions, causing different fatigue loads on the downwind turbine exposed to the wake.

Canada has committed to reducing greenhouse gas (GHG) emissions by increasing the non-emitting share of electricity generation to 90% by 2030. As solar energy costs have plummeted, agrivoltaics (co-development of solar photovoltaic (PV) systems and agriculture) provide an economic path to these goals. This study quantifies agrivoltaic potential in Canada by province using geographical information system analysis of agricultural areas and numerical simulations. Systems modeled would enable conventional farming of field crops to continue (and potentially increase yield) by using bifacial PV for single-axis tracking and vertical system configurations. Between a quarter (vertical) to more than one third (single axis tracking) of Canada’s electrical energy needs can be provided solely by agrivoltaics using only 1% of current agricultural lands. These results show that agrivoltaics could be a major contributor to sustainable electricity generation and provide the ability for Canada to render the power generation sector net zero/GHG emission free. It is clear that the potential of agrivoltaic-based solar energy production in Canada far outstrips current electric demand and can thus be used to electrify and decarbonize transportation, heating, expand economic opportunities by powering the burgeoning computing sector, and export green electricity to the U.S. to help eliminate their dependence on fossil fuels.

Fusion device and its structure may be designed by various means. Two of most popular are; weight basis (described in previous study by author) and energy basis. In present research, later method is explored and described. Energy basis is based on amount of energy released from device upon detonation followed by explosion. Its beneficial in a sense that device size can be kept as independent variable as compared to dependent in former case. Further, it shortens the design procedure. For example, heat transfer pattern in such approach directly helps in quantifying wall thickness which dictates material, fabrication, and manufacturing route. It may also eliminate anisotropy as wall thickness is direct function of amount of heat at which it will rupture and can be much thinner. Device geometry can also be flexibility controlled as it is no longer dependent on pay load bay capacity. This allows more freedom in designing subsystems (compartments, their locations, focusing, switches, and mixers). Such devices can be more compact and simpler. Few such design configurations are proposed.

The global transport sector of the world economy contributes about 15% of the Greenhouse Gas (GHGs) emissions in the world today. The University of Saskatchewan has pursued the green energy transition over the years. They have spearheaded diverse sustainability projects and agendas, due to the importance of curbing climate change and advancing sustainability. The transport system in the university campus is one area of focus where the Sustainability Office plans to introduce some innovations, as a way of curbing GHG emissions while also advancing sustainability practice in the university campus. The study carried out an economic benefit analysis on the campus fleet (consisting of 91 ICE vehicles) to determine if it is economically or financially feasible to transition from Internal Combustion Engine (ICE) or PVs (Petrol Vehicles) to Electric Vehicles (EVs). The analysis used RETScreen Expert software for analyzing renewable energy technology projects. The variables of Payback Period (PBP), cash flow projections, savings made from transitioning (fuel cost savings and energy cost savings), Benefit-Cost-ratio, GHG emission reduction potential, etc. were analyzed. The findings revealed that the GHG emission from the campus fleet will be reduced by 100% (this will result in the removal of about 298.1 tCO₂ from the environment). Also, the fleet manager will save approximately $129,049 (88.9%) in fuel costs. Apart from these, the return on investment will be achieved in year 5 (all things being equal), but can be reduced to year 2 if the vehicles are put into constant and active use (eliminating most idle times. Also, the Sustainability Office will be making a GHG reduction revenue of $14,906.

The current manuscript presents a review on existing kiln burner technologies for the cement production process, in the context of the current climate of energy transition and environmental remediation. Environmental legislation has become ever stricter in response to global climate change, and cement plants need to adapt to this new reality in order to remain competitive in the market and ensure their longevity. The cement production process is a well-established technology with more than a century of existence. There are several plants in operation whose process is outdated by modern standards, particularly considering the current industry decarbonization needs. The cement process requires tremendous amounts of energy, mainly recovered from the combustion of solid, liquid or gaseous fuels, which yields massive emissions of greenhouse gases. Thus, an important onus is placed upon the minimization of pollutant emission in the combustion system, as well as a substitution of fossil fuels with more sustainable alternatives. One of the sus-tainable alternative fuels comes in the form of refuse derived fuels (RDF). These high caloric frac-tions of municipal solid waste present a double advantage by reducing the amount of fossil fuels used and reducing the landfilling fraction of waste. However, their use in rotary kiln burners comes with important limitations for burner operation, namely that a high degree of control over primary air supply is needed to ensure complete combustion with minimal pollutant emission.

As the structure of horizontal gas wells is more complicated than that of vertical wells, the form of the liquid-carrying in different sections does not well agree. This makes it problematic to apply the widely used liquid-carrying theory of vertical gas wells in horizontal gas wells. Since the theory focused on the critical gas flow rate, it cannot quantify how much liquid it can remove. Simultaneously, it ignores the fact that the liquid-carrying ability of gas flow is limited and the producing liquid has a certain amount of flowing energy. In this study, the gas-liquid flow law of horizontal gas wells and wellhead drainage stability in different tubing depths were firstly studied. Then, the stability of gas drainage for different tubing depths was analyzed and confirmed. Given the disadvantages of the typical theory of critical gas flow, the mathematical model of different tubing depths for gas drainage is established for horizontal gas wells. The innovative model could take the energy of gas flow and liquid flow into account, and quantify the liquid volume which was removed. By verifying the model with the experiments, the result showed that the relative error of the model is generally less than 10%. It shows the research could provide a scientific basis for the analysis and liquid-carrying capacity for horizontal gas wells.

Hydrogen plays a key role in the transition to a carbon-free economy. One of the areas of hydrogen use is the substitution of hydrocarbon fuel in gas turbine engines and power plants. This review article discusses the features of hydrogen combustion and their influence on the characteristics of combustion chambers in comparison with methane. The paper presents both the results of a study of pure hydrogen or methane and methane-hydrogen mixtures with different hydrogen content. Among the main features, it is worth noting a smaller ignition delay time and higher laminar flame speed with a shift in its maximum value to a rich mixture, which significantly affects on flashback inside burners premixer, especially at elevated air temperatures. Another feature is the increased temperature of the flame, which can lead to an increase in the rate of nitrogen oxides formation. However, wider combustion concentration ranges contribute to the stable combustion of hydrogen at temperatures lower than those of methane. Along with this, it was shown that even at the same adiabatic temperature, more nitrogen oxides are formed in a hydrogen flame than in a methane flame, which indicates an additional mechanism for NOx formation in addition to the Zeldovich mechanism. The article also summarizes some of the results of a study on the effect of hydrogen on the occurrence of thermoacoustic instability, which depends on the initial nature of pulsations during methane combustion. The presented data will be useful both to engineers who are engaged in solving the problems of designing hydrogen combustion devices, and to scientists in this field of study.

Coffee is regarded as the highly consumed beverage throughout the world and has established a key spot in the world economy as an important commodity for trading. In general, they are produced by brewing their roasted and ground beans, which release aromatic coffee; as well as produce an equivalent amount of spent coffee grounds (SCG). Previously, they were discarded as wastes or used as natural pest repellent or garden fertilizer; however, in recent times, are valorized into biofuels owing to their high calorific value. In fact, SCG briquettes have gained wide attention for supplying energy renewably, especially to the rising energy demand; and also have been identified as an effective measure to reduce their pollution. With this in mind, this present chapter focuses on reviewing the availability and chemistry involved in these SCG wastes, pre-treatments and preparations required for their briquetting, compacting techniques followed, and fuel characteristics of their briquettes, from various available works of literature. Here, their availability showcases the amount of SCG wastes generated with respect to time and consumption, wherein understanding their chemistry helps in deciding the pre-treatments necessary for their briquetting. Meanwhile, preparation techniques briefs about the necessary pre-treatments undertaken before compaction by different researchers; and the fuel characteristics define the physicochemical and mechanical properties of their briquettes, developed using various compaction methods. Besides, combustion behaviors of these briquettes are explained in terms of their burning characteristics and emission levels, as reported in literatures; which help in deciding their suitability as a replacement for existing fossil coal. Eventually, all the reported data were in accordance with their permissible standards and suggested these SCG as a highly renewable solid biofuel.

The solar water heater must be integrated into future residential buildings as the main energy source, which will subsequently reduce the energy cost of water heating. An original configuration for efficient Domestic Hot Water "DHW" storage tank is developed and experimentally evaluated under Saharan climate. This novel DHW configuration includes a hybrid (solar and electric) energy system with a flat plate solar collector coupled with an electric heater. Additionally, phase change material "PCM" mixture that is composed of paraffin wax and animal fat with a melting temperature between 35.58°C and 62.58°C and latent heat between 180 and 210 kJ/kg is integrated into this novel tank configuration. The experimental results indicated that hot water production by using latent heat storage could be economically attractive. In this proposed configuration, one liter of hot water may cost around 0.1362 DZD/liter (i.e., 0.00096 US$/liter) compared to 0.4431 DZD/liter for the conventional water heater, an average energy cost savings of 69.26%. On a yearly basis, the average energy cost savings may reach up to 80.25% if optimal tilt for the solar collector is adopted on a monthly basis. The flat plate collector may be vulnerable to convective heat transfer, and therefore, other solar collectors such as vacuum tube collectors may provide enhanced energy performance.

Cashew nut shells (CNS) are the primary waste produced during the processing of cashew nuts; and needs constant attention to handle or valorize these wastes effectively. As a result, these CNS wastes are processed into solid briquettes citing their significant calorific content, thus making them as a promising renewable biofuel for combustion based applications. In most cases, these wastes are pre-treated either through de-oiling or carbonizing prior to compaction, thus removing the harmful hydrocarbons present in them in form of CNS liquids. Presently, this chapter focus on summarising various data related to these CNS wastes and their briquettes in terms of their availability, chemical characteristics, pre-treatment and processing technique, fuel and combustion properties as reported in various literatures. Here, availability depicts the current trend in global consumption of these snack nuts and the proportionate amount of waste shells produced; while, chemical characteristics focused on discussing their anatomy, proximate, lignocellulosic and elemental compositions. Following this, pre-treatment and processing techniques list out the various practises followed to remove CNSL, process de-oiled CNS cakes into bio-char through carbonization, and briquetting of pre-treated CNS wastes along with their compacting techniques prescribed by various researchers. Lastly, fuel and combustion properties brief out about the fuel traits of developed CNS briquettes along with their burning characteristics; and include parameters like proximate and elemental compositions, density and compressive strength, and results related to their combustion and water boiling tests. Moreover, all the reported results and data in this study were in accordance with the international testing standards; and ranged in between their permissible range.

This work aims to investigate systematically the tecno-economic feasibility of ther-mos-catalytic cracking process for two solid waste materials, a lipid-base material (re-sidual fat/scum from retention box of the University Restaurant of UFPA) and a lig-nin-cellulosic material Açaí seed (Euterpe oleracea. Mart). The thermo-catalytic process-es were carried out in pilot scale (THERMTEK/LEQ/UFPA/IME/RJ), and their economic feasibility analyzed. The yields of biofuels produced by fractional distillation were al-so studied. The physicochemical characteristics of the raw materials, the organic liquid product (bio-oil) and the chemical composition of kerosene, light-diesel and heavy-diesel from the lipid-base material, as well as those of kerosene and light-diesel from the Açaí seed were also determined. The economic indicators for the evaluation of the most viable cracking (pyrolysis) and distillation process of bio-oils were: a) the sim-ple payback criterion, b) discounted payback, c) net present value (NPV), d) internal rate of return (IRR), and e) index of profitability (IP). The analysis of the indicators showed the economic viability of crude palm oil (Elaeis guineensis, Jacq) and unfeasibil-ity for the palm oil neutralization. The minimum fuel selling price (MFSP) obtained is this work for the biofuels was of 1.34 US$/L) and the breakeven point obtained was of 1.28 US$/L. The sensibility analysis demonstrated that the pyrolysis and distillation yields are the most important variables to affect the minimum fuel selling price (MFSP).

The objective of this study is to design an optimal model predictive control (MPC) strategy using manipulated variables to control the production of a sufficient amount of hydrogen through low temperature autothermal reforming of dimethyl ether (DME), a reforming reaction performed using PdO/ZnO/γ-Al2O3 catalysts coated on honeycomb cordierite ceramics. Experiments and simulation have verified that the optimal activity temperature of the catalyst is 400 °C, and the hydrogen volume fraction in syngas is over 43%. In the implementation of the hydrogen production system, the MPC controller can precisely determine the feed rates of DME, high-purity air, and water based on the space state equation of the reformer, to achieve the anti-disturbance of the reformer temperature. Thus, the reduction of hydrogen yield and sintering of the catalyst as a result of overheating are prevented. As the static and dynamic performance of hydrogen production exhibits excellent tracking of the setpoints, an autonomous, automated, and reliable continuous system was designed to meet the desired hydrogen demand situation. This study shows that an autonomous, automated, and reliable continuous hydrogen production reforming system can be designed to actively respond to the on-board hydrogen usage situation.

Following the international trend of using hydrogen as combustible in many industry branches, this paper investigates the impact of mixing methane gas with 23% hydrogen (G222) on condensing boilers’ operation. After modeling and testing several boilers with heat exchange surface different designs, the authors gathered enough information to introduce a new concept, namely High-Performance Condensing Boiler (HPCB). All the boilers that fit into this approach have the same operational parameters at nominal heat load, including the CO2 concentrations in flue gases. After testing a flattened pipes condensing boiler, a CO2 emission reduction coefficient of 1.1 was determined, when converting from methane gas to G222 as combustible. Thus, by inserting into the national grid a G222 mixture, an important reduction in greenhouse gases can be achieved. For a 28 kW condensing boiler the annual reduction in CO2 emissions averages 1.26 tons, value which was experimentally obtained and is consistent with the theoretical evaluation.

In this work, the effect of reaction time and biomass-to-H2O ratio on the structural evolution of hydro-char and kinetic of by hydrothermal processing of corn Stover with hot compressed H2O, have been systematically investigated. The experiments were carried out at 250 °C, heating rate of 2.0 °C/min, biomass-to-H2O ratio of 1:10, and reaction times of 60, 120, and 240 minutes, and at 250 °C, 240 minutes, heating rate of 2.0 °C/min, and biomass-to-H2O water ratio of 1:10, 1:15, and 1:20, using a pilot scale stirred tank reactor of 5 gallon. The characterization of solid phase products performed by thermo-gravimetric analysis, scanning electron microscope, energy dispersive X-ray spectroscopy, X-ray diffraction, and elemental analysis (C, N, H, S). The physical-chemistry properties of solid phase analyzed in terms of dry matter (DM), total organic content (TOC), and ash. The yields of solid and gas phases decrease linearly with decreasing biomass-to-H2O ratio, while that of liquid phases increases linearly. For constant biomass-to-H2O ratio, the yields of solid, liquid, and gaseous reaction products varied between 52.97 and 35.82% (wt.), 44.84 and 54.59% (wt.), and 2.19 and 9.58% (wt.), respectively. The yield of solids decreases exponentially by decreasing the reaction time, while the yields of liquid and gas phases increase exponentially. For constant biomass-to-H2O ratio, TG/DTG curves shows that reaction time of 60 minutes was not enough to carbonize corn Stover. For constant reaction time, TG/DTG curves shows that increasing the H2O-to-biomass ratio worse the carbonization of corn Stover. For constant biomass-to-H2O ratio, the SEM images show the main morphological structure of the corn Stover remains practically unchanged, while for constant reaction time, SEM images show that plant microstructure retains part of its original morphology, demonstrating that a decrease on biomass-to-H2O ratio worse the carbonization of corn Stover. For constant biomass-to-H2O ratio, the EDX analysis shows that the carbon content in hydro-char increases with reaction time, while for constant reaction time, the carbon content decreases with increasing biomass-to-H2O ratio. The kinetic of corn Stover degradation was correlated with a pseudo-first order exponential model, exhibiting a root-mean-square error (r2) of 1.000, demonstrating that degradation kinetics of corn Stover with hot compressed H2O, expressed as hydro-char formation, is well described by an exponential decay kinetics.

Transportation, environmental conditions, quality of human life within smart cities, and system infrastructure have all needed practical and dependable smart solutions as urbanization has accelerated in recent years. In addition, the emerging Internet of Things (IoT) provides access to a plethora of cutting-edge, all-encompassing apps for smart cities, all of which contribute significantly to lowering energy consumption and other negative environmental impacts. For smart cities to meet the challenge of using less energy, the authors of this research article suggest planning and implementing an integrated power and heat architecture that puts renewable energy infrastructure and energy-storage infrastructure at the top of the list. To address these issues, we describe a smart proposed NEOSRD architecture that uses a distributed smart area domain to optimize renewable demand energy in a smart city across a wide area network. The energy requirements of desalination procedures are negligible when compared to the total local energy consumption and transportation, a feat accomplished by the proposed NEOSRD system. Here, the computational model shows how the established system is a valuable response to our problems and a cost-effective strategy for creating smarter structural elements that cut down on overall smart cities' energy costs.

Nuclear technologies have a strong potential and a unique role to play in delivering reliable low carbon energy for a future net-zero society. However, to assure the sustainability required for the long-term success, nuclear will need to deliver innovative solutions as proposed in iMAGINE. One of the most attractive features, but also a key challenge for the envisaged highly integrated nuclear energy system is the need for a demand driven salt clean-up system. The work described provides an insight into the interplay between a potential salt clean-up system and the reactor operation in a plutonium started core in a dynamic approach. The results presented will help to optimize the parameters for the salt clean-up process as well as to understand the differences which appear between a core started with enriched Uranium and Plutonium as the fissile material. The integrated model is used to investigate the effects of the initial fissile material on core size, achievable burnup, and long term operation. Different approaches are tested to achieve a higher burnup in the significantly smaller Pu driven core. The effects of different clean-up system throughputs on the concentration of fission products in the reactor salt and its consequences are discussed for general molten salt reactor design. Finally, an investigation of how a plutonium loaded core could be used to provide fuel for future reactors through fuel salt splitting is presented with the outcome that one Pu started reactor of the same size as a uranium started core could deliver fuel for 1.5 new cores due to enhanced breeding. The results provide an essential understanding for the progress of iMAGINE as well as the basis for inter-disciplinary work required for optimizing iMAGINE.

Shale gas and coalbed methane are energy sources that partly or even mainly consist of methane stored in an adsorbed state in the pores of the organic-rich rock and coal seams. In this study, the graphene nanoslit model is employed to model the nanometer slit pores in shale and coal. The Grand Canonical Monte Carlo (GCMC) and Molecular Dynamics (MD) modelling methods are used to investigate the mechanisms of adsorption and displacement of methane in the slit pore. It was found that the CVFF forcefield resulted in the largest adsorption amount, while the PCFF forcefield resulted in the least. The COMPASS and COMPASS II force fields led to similar results. As the width of the slit pore increases, the adsorption amount of gas molecules increases, and the number density profile of adsorbed methane molecules alters from a single adsorption layer to multi-adsorption layers. The minimum slit pore width at which methane molecules can penetrate the slit pore was found to be 0.7 nm. Moreover, it is demonstrated that by lowering the temperature, the adsorption rate of the methane increases since the adsorption is an exothermic process. Enhancing methane recovery was investigated by the injection of gases such as CO2 and N2 to displace the adsorbed methane. The comparison of adsorption isotherms of gas molecules provided the following order in terms of the amount of adsorption: CO2&gt;CH4&gt;N2.

With increasing constraints on energy and resource markets and the non-decreasing trend in energy demand, the need for relevant clean energy generation and storage solutions is growing and is gradually reaching the individual home. But small-scale energy storage is still an expensive investment in 2022 and the risk/reward ratio is not yet attractive enough for individual homeowners. One solution is for homeowners not to store excess clean energy individually but to produce hydrogen for mutual use. In this paper a collective production of hydrogen for a daily filling of a bus is considered. Following our previous work on the subject, the investigation consists of finding an optimal buy/sell rule to the grid, and the use of the energy with an additional objective: mobility. The dominant technique in the energy community is reinforcement learning, which is however difficult to use when the learning data is limited as in our study. We chose a less data-intensive and yet technically well-documented approach. Our results show that rulebooks, different but more interesting than the usual robust rule, exist and can be cost-effective. But they require fine-tuning as to not deteriorate system performance. In some cases, it is worth missing the H2 production requirement in exchange for higher economic performance.

Renewable active sludge is a smart material for wastewater treatment and the protection of surface water bodies. The generated pellets (dried and pelletised dehydrated anaerobically stabilised excess sludge) are produced in a quantity of 31.4 g ± 5.6 g dry matter (DM) per one Population equivalent (PE) calculated to COD (PE_COD) in one day. As pellets are combustible material, their energy utilisation must reach sustainable development goals (SDGs) - a bridge must be created between »treated sewage sludge as the tool to remove pollutants and nutrients from wastewater« and »preparation of the valuable material as a solid recovered fuel (SRF) that meets customer-specific requirements«. Technical Report CEN/TR 15508 and Technical Standard EN ISO 21640 set up methods for specifying and classifying pellets as an SRF. In the last eleven years (2010 – 2021), pellets' net calorific value (NCV) is 13.0 ± 0.7 MJ kg^-1 as received (ar). In 2021, the 80^th percentile of the Hg/NCV ratio was 0.079 mg Hg MJ^-1. In 2010 – 2021, the annual amount of Hg transferred to stakeholders reduced by 64.3 % m/m - from 10.1 kg to 3.67 kg. The halogen contents of the pellets do not threaten corrosion to the incineration facility. Stable pellets' energy potential and perspective ash composition for critical raw materials recovery qualify pellets as a specific waste stream and a renewable material for SRF production.

As Alberta increases solar power generation, land use conflicts with agriculture increase. A solution that enables low-carbon electricity generation and continued (in some cases increased) agricultural output is the co-locating of solar photovoltaics and agriculture: agrivoltaics. This study reviews policies that impact the growth of agri-voltaics in Alberta. Solar PV-based electricity generation is governed by three regula-tions based on system capacity. In addition, agrivoltaics falls under various legisla-tions, frameworks, and guidelines for land utilization. These include Land Use Frame-work, Alberta Land Stewardship Act, Municipal Government Act, Special Areas Dis-position, Bill 22 and other laws/policies all of which are reviewed in the context of agrivoltaics. Several policies are recommended to support rapid diffusion of agrivolta-ics. First, open access research into agrivoltaics, which not only will help optimize agrivoltaic systems for the region, but also coupled with public education is expected to galvanize social acceptability of large-scale PV deployment. Clearly defining and categorizing agrivoltaic technology, developing agrivoltaic standards, making agri-voltaic technology-friendly regulations/frameworks and developing programs and pol-icies to incentivize agrivoltaic deployment over conventional PV will all accelerate dif-fusion. Through these measures, Alberta can achieve conservation and sustainability in food and energy sector while simultaneously addressing the renewable energy and climate-related goals.

Alternative fuels have the potential to reduce exhaust emissions in the transportation sector. In this study, the effects of oxygenated fuels on the performance and emissions of a gasoline single-cylinder spark-ignition engine have been investigated experimentally. Experiments were conducted using a DIDACTA-T85 testbed under full load conditions and variable engine speed. Performance tests were performed by measuring the brake torque, brake power, brake mean effective pressure (BMEP), brake specific fuel consumption (BSFC), and brake thermal efficiency (BTE). The tested fuel blends were G0, E10, A10, and M10. G0 represented the base fuel and pure gasoline. E10, A10, and M10 were represented by a 10% volume of ethanol, acetone, and methanol in gasoline respectively. Results showed that M10 produced better engine performance in terms of brake torque, brake power, and BMEP, while E10 performed better results in terms of BSFC and BTE. A10 gave the lowest value in NOx emission at all engine speeds. On the other hand, it increased the NOX emission for E10 and M10 blends. This study showed that oxygenated fuel blends significantly reduced carbon monoxide emission at all engine speeds whereas carbon dioxide emission was higher at the highest engine speed.

Renewable Energy Communities (RECs) are emerging as an effective concept and model to empower the active participation of citizens on the energy transition, not only as energy consumers, but also as promoters of environmentally friendly energy generation solutions. This paper aims to contribute to the management and optimization of individual and community Distributed Energy Resources (DER). The solution follows a price and source-based REC management program, in which consumers day-ahead flexible loads (Flex Offers) are shifted according to electricity generation availability, prices and personal preferences, to balance the grid and incentivize user participation. The heuristic approach used in the proposed algorithms allows the optimization of energy resources in a distributed edge and fog approach with a low computational overhead. The simulations performed using real world energy consumption and flexibility data of a REC with 50 dwellings show an average cost reduction of 10.6% and an average increase of 11.4% in individual self-consumption. Additionally, the case-study demonstrates promising results regarding grid load balancing and the introduction of intra-community energy trading.

Wind energy is one of the most attractive renewable energy sources because of its low operating, maintenance, and production costs as well as its low environmental impact. The goal of this study is to discover the best locations in Bangladesh where wind farms can be built and operated efficiently. This study applied the GIS and AHP methodologies to examine the eight important parameters upon which the suitability of locations is highly dependent. This analysis finds that Bangladesh has large regions appropriate for wind farm installation, with 3718.76 km² and 16631.14 km² classified as "very high" and "high" suitability, respectively. It was also observed that wind speed, land slope, and elevation each had a height-weighted criterion of 32 %, 27 %, and 12 %, respectively, when picking suitable locations. However, the viability of this study in identifying suitable sites has been evaluated based on ROC and AUC techniques and found satisfactory as per AUC value. The knowledge gained from this study will help the sustainable and renewable energy development authority (SREDA), Bangladesh to expedite the renewable energy investment process and will ensure the great certainty. The findings of this research can be considered as baseline information in the wind energy sector.

Ion Transport Membrane (ITM) is a well-developed technology for producing O₂ by separating air in its membrane. To decrease energy loss in air separation unit and to increase the overall efficiency of a power generation unit ITM is added with the gasification unit in this model. Ceramic materials are generally used to make ion transport membrane that produces oxygen by conducting oxygen ions at specified temperature. Potential advantages can be gained by integrating ITM technology with power generation units as 99% pure oxygen is produced from ITM. A salient comparison between ITM air separator combined with IGCC and cryogenic air separator combined with IGCC is done in this paper where the total power generation cycle remains same for both cases excluding the air separation units (ITM and cryogenic). Using ITM air separator is more beneficial compared to cryogenic air separation as ITM technology helps to improve IGCC overall efficiency and also reduces plant auxiliaries than that of power generation systems integrated with cryogenic.