Environmental responsibility and economic benefits have promoted the development of closed-loop supply chain (CLSC), and shortages and channels are considered to be two important issues in CLSC. This paper explores ordering and channel decisions in CLSC with new and differentiated remanufactured products, and considers the price and sales effort-dependent demands, as well as the proportion of emergency orders determined by emergency order costs and backorder losses, and establishes an integrated and decentralized CLSC game models. We introduce a stochastic sales effort, which affects two types of products. Numerical results show that sales effort and the order quantity of new and remanufactured products exhibit concave and convex functions, respectively. Wherein, the upper limit of sales effort has a greater impact on supply chain decisions. High sales efforts can serve as a means of coordinating dispersed supply chains. Moreover, in different cases, decisions of integrated channel are better than those of decentralized channel. Finally, whether the supply chain adopts an emergency order strategy depends on the relative cost of emergency orders and out of stock costs. According to the research in this article, some management insights are also provided.

Doping can alter the electronic and thermoelectric attributes of an organic semiconductor system. These alterations can enable viable tunable devices that have applications in temperature sensing for environmental controls. Here we demonstrate a dual-modulation organic field-effect transistor (OFET) where temperature effectively modulates the current-voltage characteristics of the OFET and gate voltage modulates the thermoelectric properties of the active layer. Poly(3-hexylthiophene-2,5-diyl) (P3HT) was utilized as the host donor polymer, iodine was utilized as the dopant acceptor molecule Finished devices were characterized by a semiconductor analyzer system with temperature controlled by two thermoelectric cooling plates. The doping of iodine in the range of 0.25% to 0.5% mole ratio with respect to the P3HT exhibited the greatest on-off ratio of the investigated dopant concentrations. Iodine doping concentrations of 0.5% mole ratio or less can greatly improve the thermoelectric properties of a binary P3HT-based system and the current-voltage performance of the dual-modulation device.

Prime numbers are the atoms of mathematics and mathematics is needed to make sense of the real world. Finding the Prime number structure and eventually being able to crack their code is the ultimate goal in what is called Number Theory. From the evolution of species to cryptography, Nature finds help in Prime numbers. One of the most important advances in the study of Prime numbers was the paper by Bernhard Riemann in November 1859 called “Ueber die Anzahl der Primzahlen unter einer gegebenen Grösse” (On the number of primes less than a given quantity). In that paper, Riemann gave a formula for the number of primes less than x in terms the integral of 1/log(x) and the roots (zeros) of the zeta function defined by: Where ζ(z) is a function of a complex variable z that analytically continues the Dirichlet series. Riemann also formulated a conjecture about the location of the zeros of RZF, which fall into two classes: the "trivial zeros" -2, -4, -6, etc., and those whose real part lies between 0 and 1. Riemann's conjecture Riemann hypothesis [RH] was formulated as this: [RH] The real part of every nontrivial zero z* of the RZF is 1/2. Proving the RH is, as of today, one of the most important problems in mathematics. In this paper we will provide a proof of the RH. The proof of the RH will be built following these five parts: PART 1: Description of the RZF PART 2: The C-transformation PART 3: Application of the C-transformation to in Re(z) 0 to obtain ζ(z)=X(z)-Y(z) PART 4: Analysis of the values of z such that X(z)=Y(z), and |X(z)|=|Y(z)|, that equates to ζ(z)=0 Proof that |X(z)|=|Y(z)| only if Re(z)=1/2 Conclude that ζ(z)=0 only if Re(z)=1/2 for Re(z) 0 PART 5: We will also prove that all non-trivial zeros of ζ(z) in the critical line of the form are not distributed randomly. There is a relationship between the values of those zeros and the Harmonic function that leads to an algebraic relationship between any two zeros.

The maritime sector, grapples with environmental challenges, but the adoption of "cold ironing" emerges as a promising solution, signifying a shift toward sustainability by providing energy to ships at port, reducing reliance on fossil fuels, and significantly lowering emissions, contributing to global climate change efforts. This transition towards renewable energy is especially crucial for islands like Lesvos, addressing challenges of high energy costs and environmental degradation resulting from reliance on imported fossil fuels, highlighting the potential for positive economic and environmental impacts. The existing literature highlights a research gap in the development of Renewable Energy Sources (RES) to support cold ironing operations, specifically due to the absence of specific data for the power demand needed in such operations and the lack of monitoring data for accurate calculations. This study's primary objective is to utilize real monitoring data from the port of Lesvos to evaluate the power demand for a potential cold ironing application. Additionally, the study aims to analyze the implementation of a wind power park to meet the energy needs of an electric port and evaluate the potential reduction in CO2 emissions. The database of Marine Traffic S.A. was utilized, while the determination of the energy used in-port per ship depended on factors such as the number of arrivals, the duration of hoteling, and the type of engine used by the ships. In addition, the software RETSCREEN was used for the energy analysis of a simulated 20 MW wind park that can support the in-port operations. The combined monthly energy demand for both main and auxiliary engines of shipping vessels at Mytilini port was assessed to be 6118 MWh and averaging a power demand equaled to 8.2 MW. The simulation analysis indicates that the annual electricity delivered to the port can be72080 MWh, with a significant portion remaining unused and exported to the grid, amounting to 14956 MWh annually. Due to demand fluctuations, in-port activities require an additional 924 MWh from the main electrical grid, which highlights the importance of additional measures like energy storage and demand-response practices for the gradual transition to 100% Renewable Energy Sources (RES) operations.

The main aim of this work is to present a step-by-step procedure to model and analyze the power loss distribution of three-level Gallium Nitride (GaN) inverters. It has been applied to three distinct three-phase three-levels voltage source inverters utilized in electric traction drives: Active Neutral Point Clamped, Neutral Point Clamped and T-Type Neutral Point Clamped. The proposed analytical power loss modelling, combined to an equivalent representation of the electrical machine demonstrated to be a viable solution to achieve a time-saving and low computational burden simulation platform, leading to satisfying accuracy results. This has been confirmed by comparing the results carried out from the simulations of a 110kW permanent magnet synchronous motor drive and those determined by considering a simplified circuital representation based on the proposed analytical power loss modelling.

This study delves into the complex dynamics of Underwater Wireless Optical Communication (UWOC) in varied Harbor water conditions. Focusing on four distinct types of Harbor water, the research employs the Monte Carlo method to simulate photon transmission and analyze critical UWOC characteristics. Key parameters such as the transmitted full divergence angle, received aperture, and Field of View (FOV) are meticulously evaluated for their impact on communication efficacy. The study first explores the relationship between laser power variation, attenuation length, and divergence angle, revealing how different water qualities influence received power and time delay spread. Notably, the received normalized power loss and time delay spread are found to be more significantly affected by communication distance than water quality. In addition, under the condition of small received aperture and FOV, the influence on normalized power loss and time spread is more obvious in Harbor water. The findings offer novel insights into the challenges of UWOC in Harbor waters, particularly in terms of light scattering and absorption properties, and contribute to the optimization of communication systems in such complex underwater environments. Furthermore, the analysis of time pulse spread in turbid water quality is of great significance for the analysis and improvement of underwater wireless optical timing, ranging and positioning.

This research review paper comprehensively assesses the environmental impacts of diverse energy sources and proposes sustainable solutions. Fossil fuels contribute to pollution, habitat destruction, and greenhouse gas emissions. Renewable energy offers cleaner alternatives but faces challenges in manufacturing and disposal. Nuclear power has low emissions but poses risks in waste management and radiation. Biomass can be sustainable if responsibly sourced, but unsustainable practices lead to deforestation and emissions. Solutions include renewable technologies, energy efficiency, carbon capture, and sustainable transportation. Effective policies, incentives, and individual actions are crucial for a greener future. This review highlights the urgency of addressing energy-related environmental impacts and offers valuable insights for policymakers and individuals to take decisive actions for a sustainable energy future that protects the environment and promotes well- being.

The current globally dominant SARS-CoV-2 variants are showing immune escape and reduced susceptibility to antiviral drugs. Therefore, agencies responsible for drug evaluation and regula-tion such as the FDA and EMA are revising their emergency authorization use of several COVID-19 neutralizing antibodies. These NAbs proved to be unlikely effective against new variants espe-cially Omicron descendants and several pharmaceutical companies are pursuing the development of more potent neutralizing antibodies. To address the issue of using in silico prediction for the rapid assessment of anti-SARS-CoV-2 MAbs neutralization power, we used a computational method we developed previously, to evaluate 10 SARS-CoV-2 antibodies propensity to neutralize the new Omicron’s subvariants Eris (EG.5) and Pirola (BA.2.86) based on comparative binding affinity and previous experimental and clinical observations. Nine of these MAbs were once granted emergency use authorization, and one is currently under clinical investigation. The rapid, cost-effective in silico evaluation provided reliable predictions consistent with published clinical and experimental data. Furthermore, our data showed new potential therapeutic MAbs combi-nation that could be effective for the treatment countermeasure of the new Omicron’s subvariants Eris (EG.5) and Pirola (BA.2.86).

As the international community attaches importance to environmental and climate issues, carbon dioxide emissions in various countries have been subject to constraints and limits. Carbon trading market, as a market tool to reduce greenhouse gas emissions, has gone through a development process from a pilot carbon market to a national carbon market in China. At present, the industries included in the national carbon market are mainly the electric power industry, and the carbon emissions of the electric power industry account for about 40% of the national carbon emissions. According to the construction history of foreign carbon markets, China's future carbon quota allocation will gradually transition from free allocation to auction allocation,the auction mechanism will bring a heavy economic burden to the electric power industry, especially the thermal power generation industry. Therefore, this study takes Guangdong Province as an example to optimize the power generation mix with the objective of minimizing the total economic cost after the innovative introduction of the carbon quota auction mechanism and constructs an optimization model of the power generation mix based on the auction ratio by comprehensively applying the system dynamics model and the multi-objective linear programming model and systematically researches the power generation structure under different auction ratios with the time scale of months and quantitatively evaluates the economic inputs needed to reduce the greenhouse gas emissions.The results of the study show that after comprehensively comparing the total economic cost, renewable energy development and carbon emissions, it is the most scientific and reasonable to set the auction ratio of carbon allowances at 20%, which achieves the best level of economic and environmental benefits.

The temporo-spatial theory of consciousness postulates that the brain implements its own inner time and space for conscious processing of outside world. In line with this hypothesis, I present a mechanistic model of mutually connected processes that encode the inner space and time. The model is used to elaborate the binding mechanism between two sets of processes representing the inner space and time, respectively. Further, a stochastic version of the model is developed to investigate the interplay between the binding strength and noise. The spectral entropy is used to characterize the noise effects on the systems of processes when the binding strength is varied. The stochastic modeling results reveal that the spectral entropy values for strongly bound systems have similar entropy values for weakly bound or even decoupled systems. Thus, the analysis performed in this study allows to conclude that the binding mechanism is noise-resilient.

Smart farm is a technology that greatly helps improve the productivity and quality of crops and is being actively introduced into indoor environments such as green houses. However, it has not yet been distributed to field-grown crops. The main reason is that, unlike indoor environments, it is very difficult to collect sensor data for monitoring the growth environment of crops in open fields where weather conditions change significantly and power supply is difficult. Additionally, because various sensors are used, the data formats of the devices are different, making it difficult to process. This paper presents a field crop growth environment monitoring and big data analysis system. The proposed system first solves power supply and data communication problems using solar power generation and LPWA technology. Additionally, based on the oneM2M architecture, data from various sensors is transmitted to the server using standardized technology. The transmitted data is stored and managed on the server as big data, and can be used to predict the production and quality of field-grown crops and take appropriate measures. The proposed system is expected to create an environment optimized for the growth of field crops and help prevent and manage diseases.

This paper presents the design and measurement of an IEEE 802.11ad standard compatible RF transceiver for 60GHz wireless communication system. In addition to the traditional half-duplex (HD) mode, this work supports full-duplex (FD) operation to deliver better channel utilization and faster response time for the system. The isolation between the transmitter and receiver from the architecture design to system integration for FD operation has been fully considered. A digital self-interference cancellation (DSIC) is implemented in MATLAB to verify the FD performance. The super-heterodyne architecture with an intermediate frequency (IF) of 12GHz is designed to suppress the image frequencies without using extra filters. A flexible phase-locked loop (PLL) synthesizer provides a local oscillator (LO) frequency with a 2kHz resolution. Other than the time division duplex (TDD) mode used in the conventional 60GHz system, a wide bandwidth baseband digital variable gain amplifier (DVGA) with a 3dB bandwidth of more than 4GHz also supports frequency division duplex (FDD) operation. The transceiver chip is fabricated in Tower Jazz 0.18µm SiGe BiCMOS process. With on-board antenna, the transceiver covers all four channels in 802.11ad standard with MCS-12 (7.04Gbps under 1.76GSym/s and 16-QAM) under 1.5m. In the proposed system design, the RF frontend based self-interference (SI) suppression from the local transmitter to receiver LNA is around 54dB. To achieve a practical FD application, the SI is further suppressed with the help of digital SI compensation. The measured power consumption for transmitter and receiver configuration is 194mW and 231mW, respectively, in HD mode and 398mW for FDD or FD operation mode.

Natural gas plays a significant role in Tunisia's energy mix. Tunisia imports 66% of natural gas (NG) from Algeria (ANG), and the rest is provided by local gas fields mainly Miskar gas (MNG). To counteract this deficit, the Power-to-Gas approach emerges as a promising solution, given Tunisia's abundant renewable energy resources. By blending green hydrogen into the NG network, it is possible to (i) address the current energy crisis, (ii) lower the carbon intensity of the gas grid, and (iii) encourage sector coupling through the use of various renewable energy sources. This study presents an overview of various interchangeability indicators and investigates accordingly the allowable ratios for hydrogen blending with two types of natural gas distributed in Tunisia (ANG and MNG). It also explores the impact of hydrogen injection on the energy content variation and various combustion parameters. The results confirm that both ANG and MNG can withstand a maximum hydrogen blend of up to 20%. The article concludes with recommendations for further experimental testing of the findings and emphasizes the need to look into infrastructure and safety requirements with regards to the Natural gas network in Tunisia. This research serves as a critical step towards harnessing the potential of green hydrogen in Tunisia.

Over the last ten years, the integrated pond aquaculture (IPA) has been developing rapidly as a new aquaculture mode, and mechanical power oxygenator is a common oxygenation device in this aquaculture mode. However, with the gradual expansion of the application range of this aquaculture mode, the problems of low efficiency, poor oxygenation uniformity, and low applicability of mechanical power oxygenators, which can produce water reflux and suction pollution accumulation, have gradually emerged. Therefore, we designed a new type of push-water aerator device (NPWAD) applicable to the integrated recirculating water aquaculture mode of ponds. Mainly, the specific parameters of the key components were clarified through the selection calculation and structural design, and the experiments were carried out in the self-constructed pond integrated aquaculture system at the experimental base. The experiments were carried out on the water in the tank for grass carp culture, and the oxygenation and water pushing effects of the type of push-water aerator device under 15 groups of different operating parameters were carried out by using multiple types of high-precision water quality monitoring sensors, with the rotational speed of the device, the operating time (0-30 min) and the height of the water (0.5-1.5 m) as the independent variables, and the oxygenation amount R, the oxygenation power efficiency E_s and the surface layer of the water as the evaluation indexes, average flow velocity V_f were used as its evaluation indexes of oxygenation and water pushing. The results show that the optimal parameters of the NPWAD are impeller water lifting component speed n_1=1000r/min, small-hole aeration component speed n_2=2280r/min. At this time, the average oxygen increase of this device is R=1.96mg/L, the average oxygenation power efficiency is E_s=3.8 kg·(h·kW)-1, the DO uniformity of the water M_1=95.3%, and the average flow velocity V_f=190.8mm/s, which can effectively promote the water directional flow and achieve the water circulation and layer exchange, and it is in line with the preferred swimming speed of grass carp at various growth stages. The new type of push-water aerator device is able to enhance the DO concentration of the water faster, but also to achieve the purpose of promoting the directional flow of the water and renewing the water in the tank, as well as in a short period of time to improve the uniformity of the DO of the water faster, for the improvement of the pond aquaculture production efficiency has practical significance.

The fluctuation of the conditions on Lake Limboto affects people's activities around the lake. They try to survive by facing the problem of the lake, which is shallowing and narrowing. Yet the lake is predicted will be disappeared in 2030. This means that the productivity of the lake also diminishes. This article aims to analyze how the communities around the lake respond to the evolution and shocking prediction toward the lake into their daily activities. This study uses an interdisciplinary approach by integrating some fields of study to understand and solve the problems. One of the approaches involves interviewing people around the lake. Nevertheless, the base of the study is socio-cultural studies, which uses also old texts and oral literature as the support of the study. The research needs the theory of cultural studies to look at the survival and resilience of the people of lake so that they form their special daily activity. The results of the study show that some people know that there is a prediction of disappearing of the lake, but they have not anticipated it, as if this problem is only a government affair. They still live at the lake bank, try to survive and to be resilience even in poor conditions.

In the field of delta-sigma modulators, reducing system power consumption without sacrificing accuracy has become a challenge. The summing circuit, as the main part of the cascade-of-integrator-in-feedforward delta-sigma modulator, consumes a significant amount of power in active summing. On the other hand, passive summing circuits have low power consumption but can cause attenuation in the summing results. This article proposes a low-power multi-bit delta-sigma modulator based on passive and attenuationless summation scheme. The summation circuit achieves multiplication of the voltage signal carried on the summation capacitor through bidirectional sampling technique, compensating for the inherent attenuation caused by passive summation, thus eliminating the need for active OTA to achieve perfect summation. A 2-order delta-sigma modulator based on 4-bit 1-order passive noise-shaping (NS) SAR quantizer is designed to verify the scheme. By combining a passive NS SAR as the 4-bit quantizer and the third-stage integrator of the system, and incorporating an energy-efficient cascode floating inverter amplifier (FIA) structure as the core active OTA, these elements have significantly enhanced the energy-efficiency of the modulator. Simulation results show that at a supply voltage of 1.2 V and a bandwidth of 20 kHz, the SNDR reaches 102.62 dB, power consumption is only 148.32 μW, and Schreier figure-of-merit (FoM) of SNDR is 183.92 dB.

Gas turbine engines are widely used in various industries such as aviation, power generation, and marine propulsion due to their high efficiency and reliability. The combustion chamber of a gas turbine engine design contains a number of elements, including as the chamber's size and form, the fuel injection system, the ignition system, and the cooling system and it plays a critical role in the performance and efficiency of the engine. This research discusses the fabrication of a combustion chamber model for a gas turbine engine. The aim of this research is to develop a combustion chamber that is cost-effective, easily available, and can be fabricated in less time. The research covers the different types of combustion chambers used in gas turbine engines and compares their advantages and disadvantages. It then selects the best type of combustion chamber for the gas turbine engine based on its cost, availability, and fabrication time, Efficiency and high power to fuel ratio. The report also describes the fabrication process involved, including the techniques and materials used, along with safety precautions and environmental protection measures. Lastly, the research suggests future improvements and potential applications for the fabricated combustion chamber model.

The Power Theory of Exchange and Money (PTEM) refines the economic neoclassical two-equation model of exchange. PTEM replaces the statistical average condition of exchange, which represents the equality of supply and demand for all transactions in the market, with a more specific equation of the equality of the generalized power of the parties in relation to their objects of exchange. The purpose of the article is to show the application of PTEM for the study of various social phenomena. Along with a brief summary of the main statements of this theory, its integration into the existing corpus of theories and ideas in economics and sociology is considered. The conclusions of power theory are then applied to consider the following topics: the objective motivation of exchange by the desire to increase power, the power nature of market equilibrium, the power nature of money, the accumulation of power through profit, the creation of money as a power act, the role of the state in the creation of money, the measure of power as a possible tool for social and political research.

Ultralight power generation equipment has high requirements for the power density, continuous operation, and transient stability of the whole machine, and there is a direct conflict between high power density design and substantial stability control in the power unit design. In order to meet the power density requirements of ultra-light power stations, three main problems need to be solved, namely engine speed oscillation and flameout in the process of load power mutation, matching of the generator and engine torque, and stabilizing the voltage waveform of the AC output end. In this paper, we proposed an exquisite control strategy for ultralight power generation systems in engines, generators, and inverters. The effectiveness and practicability of the proposed strategy are verified by both simulation and experiment. The results show that the proposed control strategy can effectively solve the instability problem of the ultralights generator set and improve the stability of the system, where the response recovery can be achieved within 0.9 seconds under the condition of total load increase or decrease, and the mismatching degree of the generator following the engine is reduced by 90%. The strategy could also guarantee long-term stable operation with high-quality electrical energy output.

Improving performance and promoting sustainability in women's handball are key objectives to maximize the potential of female players and ensure the long-term viability of the sport. In this context, training with Olympic movements and their derivatives improves the development of strength, power, and speed, which are determinants of performance in team sports. The aim of this study was to determine if training with Olympic movements produces significant improvements in jumping, throwing, sprinting, and change of direction performance in women handball players. Twenty-one female handball players participated in the study (10 for the control group and 11 for the intervention group). Age ranged from 15 to 17 years. All participants performed four assessment tests (Abalakov Test, throw test, 20-meter Sprint and V-Cut Test) to determine jump height, throwing speed, running speed, and change of direction ability. Measurements were carried out before and after the intervention. For six weeks, the control group performed the strength work established by the club twice a week while the intervention group additionally performed training with Olympic movements. Significant differences (p <0.05) were found between the pre and post measurement of the control group and the intervention group in jump height, throwing speed and running speed, being higher in the intervention group. For the change of direction, no significant differences were found. Between groups, significant differences were observed at the end of the intervention for jump height and running speed. The conclusion of this study was that, by training with Olympic movements, in addition to regular training, could produce greater improvements in jumping performance, throwing speed and running speed in female handball players.

A key component for the proper functioning, availability, and reliability of power grids is the power trans- former. Although these are very reliable assets, the early detection of incipient degradation mechanisms are very important to prevent failures that may shorten their lifetime. In this work a review and comparative analysis, of classical Machine Learning algorithms (such as single and ensemble classification algorithms) and two automatic machine learning classifiers, are presented for the fault diagnosis of power transformers. The goal is to determine whether fully automated ML approaches are worse or better than traditional ML frameworks that require a human in the loop (such as a data scientist) to identify transformer faults from oil-dissolved gases data. The methodology uses a DB compiled from published and proprietary transformer fault samples. Faults data is obtained from the literature, the Duval pentagon method, and user-expert knowledge. The parameters from, either single or ensemble classifiers, were optimized through standard machine learning procedures. The results showed that the best performing algorithm is a robust automatic machine learning classifiers model followed by classical algorithms such as neural networks and stacking ensembles. These results highlight the ability of a robust automatic machine learning model for, handling imbalanced power transformers faults datasets with high accuracy, using the minimum tuning effort by the electrical experts. By providing the most probable transformer fault condition will reduce the time required to find and solve the fault.

So far, scientific studies on high frequency welding (HF) have observed the three main parameters: anode current, welding time and pressure of upper electrode. Some authors have also observed and studied the welding frequency, the power, and the values of the dielectric constants of the materials or the angle of dielectric losses. Due to the complex effects that the parameters have on the quality of the welded joint, it is necessary to extend the research and study the mutual relationships between a large numbers of process parameters on the welded joint in order to achieve satisfactory strength of the welded joint. In this research, the number of considered parameters is increased to 17, each of which is relevant to the processes of HF welding, and their mathematical equations are presented. The research is carried out on a HF welding machine improved with a linear pneumatic actuator for lowering the upper electrode and regulating the compressive force, and a measuring machine with the appropriate measuring method for determining the breaking forces with a tension gage and performing the „T“ test is made. Numerous researches were carried out on the functional changes of the process parameters of the percentage share of the values of the coupling capacitor, the anode current and the welding time on the values of the breaking forces of the welded joints. Based on the conducted research, it was concluded that the optimization of the process parameters of HF machine must be performed before the welding process, which is determined by a certain amount of energy that must be introduced into the material. These parameters are the capacity of the output capacitor, i.e., the value of the electric current flowing through the material and the time for the development of the operating power to produce welded joints with a certain strength and quality of welded joints for a specific material used in the process.

We introduce the Transformation Flower Approach (TFA), a Theory of Change that attends to multiple value creation and institutional change as a dual design challenge. We highlight how the TFA integrates social scientific theories and models relevant for transformative change (in particular focusing on pathways, leverage points, governance, power, and values) and demonstrate its practical value by an application to the ongoing transformation of the Dutch food system. By providing a holistic, transdisciplinary and practically relevant approach that aims to support new social contract formation, the TFA goes beyond other transformative change approaches. Based on the notion of pathways, it offers a toolbox that aids in working towards desired futures, involving both incumbents and challengers in an effort to harness untapped yet proximal potentials in a forward-looking way. By embracing an innovation approach, it not only promises to circumvent resistance to change, but also serves as a step-by-step approach to identify options for multiple value creation and effective cooperation. We demonstrate the analytical and practical value of the TFA by discussing action perspectives at various levels and scales in the context of the Dutch food system transition, including (1) area-oriented approaches, (2) acceleration agendas for specific transformation pathways, and (3) actor-specific transformation flowers. In developing these, we emphasize the importance of interdependencies between leverage points. Our approach helps to identify opportunities to link transformative options (the what), actors (the who) and levers (the how) in dynamic interaction to embark on transformative pathways.

Permeability is an important transport property of porous materials, and its accurate evaluation is relevant in studying applied tasks such as CO2 injection into reservoirs and investigating groundwater quality issues. This study examines the dependence of permeability on total and connected porosity, hydraulic tortuosity, specific surface area, and mean pore radius based on the data of 408 cubic sub-volumes extracted from heterogeneous and naturally fractured cylindrical carbonate samples before and after injection of HCl solutions into them. These parameters were computed using pore-scale modeling of fluid flow. It has been shown that permeability correlates well with porosity and mean pore radius with correlation coefficients of R2≈0.65-0.79 for heterogeneous samples. It was found that the presence of natural fractures significantly influenced the relationship between permeability and other parameters. The relationship between permeability k, tortuosity τ, and specific surface area S is described by power laws k~τ-α and k~S-β, with coefficients α and β substantially exceeding those in the Kozeny-Carman equation. It was also found that there is a parabolic relationship between connected and total porosities both before and after rock dissolution with R2≈0.96-0.99. This allowed for estimation of percolation threshold porosity that are in good agreement with the literature data.

Accurate short-term solar irradiance forecasting is crucial for the efficient operation of solar energy driven photovoltaic (PV) power plants. In this research, we introduce a novel hybrid ensemble forecasting model that amalgamates the strengths of machine learning tree-based models and deep learning neuron-based models. The hybrid ensemble model integrates the interpretability of tree-based models with the capacity of neuron-based models to capture complex temporal dependencies within solar irradiance data. Furthermore, stacking and voting ensemble strategies are employed to harness the collective strengths of these models, significantly enhancing prediction accuracy. This integrated methodology is enhanced by incorporating pixels from satellite images provided by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT). These pixels are converted into structured data arrays and employed as exogenous inputs in the algorithm. The primary objective of this study is to improve the accuracy of short-term solar irradiance predictions, spanning a forecast horizon up to 6 hours ahead. The incorporation of EUMETSAT satellite image pixels data enables the model to extract valuable spatial and temporal information, thus enhancing the overall forecasting precision. This research also includes detailed analysis of the derivation of GHI using satellite images. The study was carried out and the models tested across three distinct locations in Austria. A detailed comparative analysis was carried out for traditional Satellite (SAT) and Numerical Weather Prediction (NWP) models with hybrid models. Our findings demonstrate a higher skill score for all of the approaches compared to smart persistent model and consistently highlight the superiority of the hybrid ensemble model for short-term prediction window of 1 to 6 hours. This research underscores the potential for enhanced accuracy of the hybrid approach to advance short-term solar irradiance forecasting, emphasizing its effectiveness at understanding the intricate interplay of the meteorological variables affecting solar energy generation worldwide. The results of this investigation carry noteworthy implications for advancing solar energy systems, thereby supporting the sustainable integration of renewable energy sources into the electrical grid.

Finnish government's carbon neutrality goal by 2035 requires integration of renewable energy sources into the power grid. Considering the stochasticity of these resources, additional sources of flexibility are necessary to balance supply and demand in the power grid. District heating network (DHN) operators in Finland plan to shut down fossil-fuel-based combined heat and power plants and electrify heating systems by deploying heat pumps (HPs) and electric boilers. Techno-economic analysis and optimal operation of DHN-connected HPs and electric boilers in providing ancillary balancing services considering the 15-minute granularity in the balancing markets in Finland were investigated. The objective was to maximize the potential revenue for DHN operators gained from the day-ahead electricity market and frequency containment reserve (FCR) balancing markets. Three inter-connected DHNs in the Helsinki metropolitan area were optimized considering the reference year 2019 and each operator's decarbonization strategies for 2025. HPs could gain the highest profit from FCR-D up-regulation market, while the electric boiler may gain considerable profits from FCR-D down-regulation market. Compared to other balancing markets studied, the FCR-N market had a limited profit margin. Sensitivity analysis indicated that spot electricity prices and CO2 emission allowance prices have a significant impact on the profit from balancing markets.

Availability and continuous operation under critical conditions are very important in electric machine drive systems. However, such systems, are suffering from several type of failures that affect the electric machine or the associated voltage source inverter. Therefore, fault diagnosis and fault tolerance are highly required. This paper presents a new robust deep learning-based approach to diagnosis multiple open-circuit fault in three phase two level voltage source inverter for induction motor drive applications. The proposed approach uses fault diagnosis variables obtained from sigmoid transformation of the motor stator currents. The open-circuit fault diagnosis variables are then introduced to a Bidirectional Long Short-Term Memory algorithm to detect the faulty switch(es). Several simulation and experimental results are presented to show the proposed fault diagnosis algorithm effectiveness and robustness.

This paper presents a Modified Gate Diffusion Input (MGDI) design with four inputs for Quantum-dot Cellular Automata (QCA) technology. QCA is a promising nanotechnology that offers benefits such as low power consumption, and high density, making it a potential alternative to CMOS technology. The proposed planar cell design has advantages over previous designs, including a 19% reduction in the number of cells, a 29% reduction in total energy consumption, and a 44% reduction in average energy loss at the same occupancy level. The proposed block is capable of implementing 21 basic combinational functions and various sequential functions. The simulation of functions in 18nm technology and energy consumption calculation indicates that the resulting circuits have improvements of 41%, 27%, 27%, and 20% compared to multiplexers, comparators, four-bit parity circuits, and single-bit memory, respectively. Additionally, the number of cells in the proposed circuits has improved by 10%, 7%, 22%, and 19%, respectively.

This paper proposes a circuit model of Cross-Coupled CMOS AC – DC Charge Pump (XC – CP) operating in subthreshold region. The aim is improving the efficiency to design XC – CPs with variety of specifications, e.g., input and output voltages and AC input frequency. First, it is shown that the output resistance (Ro) of XC – CP is much higher than those of CPs with single diodes (SD – CP) and ultra-low-power diodes (ULPD – CP) as charge transfer switches (CTSs). Second, the reason behind the above feature of XC – CP is identified by a simple model that the gate-to-source voltages of CTS MOSFETs are independent of the output voltage of the CP. Third, high but finite Ro of XC – CP is explainable with a more accurate model that includes the dependence of the saturation current of MOSFETs operating in subthreshold region on the drain-to-source voltage which is a function of the output voltage of CP. The model was in good agreement with measured and simulated results of XC – , SD – and ULPD – CPs fabricated in 250 nm CMOS.

This article presents a proposed system that enables energy transfer from the dc grid to a single-phase onboard grid, operating at an hi frequency. In addition to the energy transfer function, it additionally enables compensation of reactive power in the ac grid when the converter operates at less than rated power. To operate in compensator mode, it is necessary to decouple the current from the grid into active and reactive components and control them independently. To achieve good dynamics, synchronizers that operate in the dq system are used. In the case of a single-phase grid, it requires such a synchronizer to generate virtual quadrature signals. The used systems based on second-order generalized integrator are good, but to improve dynamics in the work a quadrature generator based on trigonometric calculations was proposed. The developed system was implemented in a proportional resonant current control system. Tests performed in steady state and in dynamic states related to typical grid disturbances showed better dynamic properties than the standard integrator-based system.Keywords: power transfer; compensator; P+R controller

Automatic generation control (AGC) plays a vital role in creating an equilibrium between generated output power and load demand, in order to maintain frequency at desired value. This study focuses on performance analysis of simple-multi attribute rating technique (SMART) assisted proportional-integral-derivative (PID) controller design for AGC of two interconnected power systems. PID controller is designed by minimizing frequency variations, area control errors for area-1 and area-2, and tie-line power deviation. An objective function is framed considering error minimization of aforementioned factors as sub-objectives. The construction of objective function involves using the integral of time-multiplied absolute error (ITAE) for frequency deviations for area-1 and area-2, ITAE for deviation in tie-line power, and ITAEs for area control errors for area-1 and area-2 as sub-objective functions. By assigning appropriate weights to these sub-objective functions, an overall objective function is formed. This study determines these weights in an organized manner using SMART method, rather than randomly/equally assigning them. Overall objective function is minimized using Jaya algorithm. To demonstrate effectiveness of the proposed Jaya-based PID controller, its performance is analysed and compared with controllers tuned using other optimization algorithms, including sine cosine, Luus-Jaakola, teacher-learner based optimization, Nelder-Mead simplex, and elephant herding optimization. Considering six different case studies that consider a range of load variations, responses for fluctuations in frequency and tie-line exchange are plotted. Statistical and non-parametric analysis performed further provide additional insights into the performance of Jaya-based PID controller.

Since the energy sector is the main source of greenhouse gases, it has the highest potential for improvement. Improvements can be achieved by generating energy from renewable sources. Combined with thermal energy storage, concentrating solar power plants represent a promising technology for dispatchable renewable energy, ensuring a stable energy supply even in remote areas without contributing to greenhouse gas emissions during operation. However, it is important to note that greenhouse gases and other polluting emissions may occur during the manufacturing process of concentrating solar power plant components. This work analyses the design of the receiver to produce thermal energy for the existing solar dish CSP plant at the Energy Center of the Politecnico di Torino. The objective of this plant is to produce hot water for a small case study. Considering the average solar irradiance for Turin equal to 800 W/m2, the surface heat flux was obtained from the first part of the analysis, which was used to obtain the maximum internal temperature in the receiver equal to 873.7 °C. The maximum temperature obtained was a constraint for the selection of the material for the solar receiver. Of the various possibilities, copper was chosen. In the second part of the work, a Life Cycle Assessment was carried out to compare the emissions generated during the production of the main components of the CSP plant with the emissions generated by the methane-fuelled water heater that produces the same amount of water as the CSP plant. It can be concluded that the manufacture of the main components of the CSP plant results in lower greenhouse gas emissions than the operational phase of a conventional natural gas-fired water heater (1.6 kg CO2/day).

To ensure sustainability of the future power grid, the rate of expansion of distributed renewable energy resources (DRER) has introduced operational challenges. These includes managing transmission constraints with DRER power injection, dispatching DRER efficiently, managing system frequency and ensuring sufficient reactive power for voltage support. Coupled with the intensification of wildfires, power infrastructure across the United States faces challenges to minimize the impact to maintain system reliability and resiliency. This research embarks on a comprehensive evaluation, beginning with an in-depth historical analysis to delineate regions most susceptible to wildfires. Utilizing a multidimensional approach, the study assesses wildfire-induced risks to power grids, by integrating historical wildfire occurrences, real-time wildfire proximities, Moderate Resolution Imaging Spectroradiometer (MODIS) derived vegetation metrics, and system parameters, by employing Principal Component Analysis (PCA) based optimal weights, leading to the formulation of a novel risk factor model. This risk factor has the potential to be the key to ensuring the resilience of a renewable-rich smart grid when faced with a severe weather event. Our model’s applicability was further verified through an empirical assessment, selecting representative networks from diverse regions, providing insights into the geographical variability of risk factors. Ultimately, this study offers stakeholders and policymakers a comprehensive tool-set, empowering decisions regarding infrastructure investments, grid reinforcements, and strategic power rerouting to ensure consistent energy delivery using risk assessment against wildfire.

The temperature-dependent intensities of the exciton (X) and biexciton (XX) peaks from single GaAs cone-shell quantum dots (QDs) are studied with micro photoluminescence (PL) at varied excitation power and QD size. The QDs are fabricated by filling of self-assembled nanoholes, which are drilled in an AlGaAs barrier by local droplet etching (LDE) during molecular beam epitaxy (MBE). This method allows the fabrication of strain-free QDs with sizes precisely controlled by the amount of material deposited for hole filling. Starting from the base temperature T = 3.2 K of the cryostat, single-dot PL measurements demonstrate a strong enhancement of the exciton emission up to a factor of five with increasing T. Both, the maximum exciton intensity and the temperature Tx,max of the maximum intensity depend on excitation power and dot size. At an elevated excitation power, Tx,max becomes larger than 30 K. This allows an operation using an inexpensive and compact Stirling cryocooler. Above Tx,max, the exciton intensity decreases strongly up to its disappearance. The experimental data are quantitatively reproduced by a model which considers the competing processes of exciton generation, annihilation, and recombination. Exciton generation in the QDs is given by the sum of direct excitation in the dot plus additional bulk excitons diffusing from the barrier layers into the dot. The thermally-driven bulk-exciton diffusion from the barriers causes the temperature enhancement of the exciton emission. Above Tx,max, the intensity decreases due to exciton annihilation processes. In comparison to the exciton, the biexciton intensity shows an only very weak enhancement, which is attributed to more efficient annihilation processes.

The power system has rapidly grown and expanded over the past decades and has been experiencing major changes and challenges. The increase in energy demand and the modern advancements in the smart grid, such as solar and wind energies and electric vehicles, have led to complexity and complications for utilities. A further layer of complexity and difficulty was added by the rapid expansion of behind-the-meter (BTM) photovoltaic (PV) systems with various designs and characteristic features. The rapid increase and the invisible solar power (BTM) have led to fluctuations in power grid stability and reliability and to inefficiency. Accurate forecasting of load generation will help to assure optimal planning, minimize the negative effects of the PV systems, and minimize the operational and maintenance costs. The authors propose a solution that uses combinations of K-means clustering with neural network machine learning models, AMI real-world PV load generation, and weather data to forecast the generation load at customer locations to achieve a 2.49% error between actual and predicted generation load.

To address the problems of wind abandonment in the regional integrated energy system (RIES), which occurs when cogeneration unit operates in a heat-determined electricity operation mode, and the low efficiency of the energy storage system in a low-temperature environment, we propose an optimal scheduling method for RIES based on fine energy storage and wind power dissipation. First, a fine energy storage model is established on the source side and the conditional value at risk(CvaR) theory is used to quantify the uncertainty of wind power; then a combined heat and power demand response mechanism is introduced on the load side to reduce the peak-to-valley difference between heat and power loads, and to promote the consumption of wind power. Finally, with the objective of minimizing the total cost of RIES optimal dispatch, the example is solved on the MATLAB platform. The simulation results show that compared with the traditional model, the proposed model is not only more adaptable to the low-temperature environment, but also can effectively improve the system economy and wind power consumption.

Abstract: High power semiconductor laser is a kind of photoelectric device with high efficiency and high stability, the performance of its drive system directly affects its output characteristics and service life. In order to solve the problems of stability and robustness of the output power of semiconductor laser, a semiconductor laser driving power supply with high efficiency, low ripple and strong anti-interference ability was developed. The power supply adopts full-bridge LCC resonant power topology. Firstly, a mathematical model is established to analyze the relationship between LCC resonator parameters and output current gain. Secondly, a LCC resonator parameter design method is proposed to reduce the current stress of components, and the variable frequency phase shift (PFM-PWM) composite control strategy and linear active disturbance rejection control (LADRC) algorithm are proposed, which not only ensures the zero voltage (ZVS) conduction of MOS tube, but also reduces the on-off loss of MOS tube. Improved power efficiency and suppressed output current ripple; At the same time, the instability of the output current is ensured due to the input voltage, load and parasitic parameter change of the circuit. Finally, the simulation and experimental results show that the power supply can be continuously adjustable in the output current range of 0-40A, the current ripple is less than 0.8%, and the working efficiency is up to 92%. It has the characteristics of high stability, small ripple, high efficiency, low cost and good robustness.

In this study, a new empirical equation was established to predict the sedimentation volume resulting from the construction of a multipurpose weir or low-head dam. The study employed a one-dimensional numerical model (STAFF) to investigate the key parameters affecting sedimentation volume. Short-term predictions were conducted through laboratory experiments with movable bed, and the results indicated that dimensionless unit stream power and the Shields parameter exhibited the most significant correlation with dimensionless deposition volume. Using a multiple regression approach, an empirical equation was formulated and validated for predicting sedimentation in the upstream reservoir of the weir.

This review focuses on the Just Energy Transition (JET) policies of the BRICS member countries, with the aim of finding lessons and possible adoption of some of the key energy policy aspects utilized in other countries for benchmarking for the South African context. Considerations of the present stage of JET in South Africa and the energy-source mix supporting the electricity sector, cognisant of the lifespan and condition of power plants. Analysis of the energy mix revealed that all nations were energy dependent on electricity which was produced by predominantly fossil fuelled power plants with high GHG (concentrating on high CO2 emissions). It was concluded that some of the learnings and lessons learnt from the BRICS countries might be incorporated into a South African energy plan for the transition with options and guidance for formulation of policies. This study will attract responsible environmentally conscious audience that has a commitment and drive to combat global warming and curbing climate change.

When describing the tribological behaviour of technical surfaces, the need for full length scale microtopographic characterization often arises. The self-affine of surfaces and the characterization of self-affine by a fractal dimension and its implantation into tribological models are commonly used. The goal of our present work was to determine the frequency range of fractal behaviour of surfaces by analysing the microtopographic measurements of a brake plunger. We also wanted to know if the bifractal and multifractal behaviour can be detected in real machine parts. As a result, we developed a new methodology for determining the fractal range boundaries to separate the nano- and micro-roughness. In order to reach our goals, we used atomic force microscope (AFM) and stylus instrument to provide measurements in wide frequency range (19 nm - 3 mm). As a result of the power spectral density (PSD) based fractal evaluation, it was found that the examined surface could not be characterized by a single fractal dimension and that we developed a methodology for stopping the margin of validity of each fractal dimension, and we also developed a methodology for determining the limits of validity of certain fractal dimensions.

The study aims to analyze the characteristic parameters of rooftop photovoltaic (PV) power generation on industrial plant buildings in the Ningxia region of China, in order to evaluate the impact of passive design characteristic parameters on the benefits of PV power generation and determine the degree of impact of different passive design characteristic parameters. The methodology involves analyzing the characteristics of existing industrial plant buildings in Ningxia, China, and conducting a series of regional studies on the parameters of plant PV power generation influencing factors. The simulation results revealed that five features, including roof form, PV panel laying pattern, PV panel laying area, azimuth angle, and PV module material, have a significant impact on PV power generation benefits of industrial plant buildings.The study further uses MATLAB 2022b to build a backpropagation neural network model with 5 neurons in the implicit layer to predict the PV power generation benefits. The model calculates the whole-life cycle power generation benefits and the whole-life cycle reduction of carbon emissions as output data. Finally, the Mean Impact Value (MIV) method is employed to select the feature parameter values one by one within their range, and the passive design feature parameters that have the greatest influence on the prediction results are identified as the PV panel laying method, the PV panel tilt angle, and the PV material parameters, respectively.

This paper studies a multihop amplify-and-forward (AF) simultaneous wireless information and power transfer (SWIPT) relaying system. Each relaying node harvests energy using power splitting (PS) scheme from a part of its received signal to amplify and forward the rest the received signal to the next relay. Based on this system model and signal flow, we derived and solved the convex energy minimization problem with optimal PS ratio. The influence of processing cost was then investigated for the AF-SWIPT system with the decode-and-forward SWIPT as benchmark, where AF-SWIPT was found to be superior.

Synchronization is a prerequisite for the stability of electrical energy, which is the cornerstone of a functioning society. Identifying whether generators are synchronized or not has been attracting immense research interest. Utilizing synchronized stability boundaries can strongly simplify stability discrimination. However, fundamental issues such as determining accurate stability boundaries remain challenging. In this study, an accurate synchronized stability boundary equation that is independent of the system and disturbances is presented, and it is applicable to an arbitrarily coupled grid. The special structure induced by spontaneous synchronization appears to be only near the stability boundary. The results of this study show that: the synchronous stability boundary is an intrinsic property of the system, independent of its structure and parameters. Synchronization on the network may be independent of the network. These conclusions will challenge the traditional perception of synchronization on networks, and the synchronization stability of the grid can be analyzed in a uniform way.

The complexity of modern power grids, exacerbated by integrating diverse energy sources, espe-cially inverter-based resources (IBRs), presents a significant challenge to grid operation and plan-ning since linear models fail to capture the intricate IBR dynamics. This study employs the Sparse Identification of Nonlinear Dynamics (SINDy) method to bridge the gap between theoretical un-derstanding and practical implementation in power system analysis. It introduces the novel Volterra-based Nonlinearity Index (VNI) to examine system-level nonlinearity comprehensively. The distinction of dynamics into first-order linearizable terms, second-order nonlinear dynamics, and third-order noise elucidates the intricacy of power systems. The findings demonstrate a fundamental shift in system dynamics as power sources transit to IBRs, revealing system-level nonlinearity compared to module-level nonlinearity in conventional syn-chronous generators. The VNI quantifies nonlinear-to-linear relationships, enriching our comprehension of power system behavior and offering a versatile tool for distinguishing between different nonlinearities and visualizing their distinct patterns through the proposed VIN profile.

Under the "dual carbon" target in China, virtual power plants (VPPs) play an important role in improving grid security and promoting clean and low-carbon energy transformation. VPPs can integrate and control distributed resources to participate in the energy market and make full use of distributed resources. However, the intermittency and volatility of renewable energy and the "heat-driven" working mode of CHP units create contradictions that seriously affect the peak-shaving ability of VPPs and lead to high carbon emissions. To solve these problems, this paper aggregates CHP units, wind power, photovoltaics, carbon capture, hydrogen energy storage, and electric boilers into a new type of virtual power plant. The "hydrogen energy storage-electric boiler" joint decoupling CHP working mode is used to strengthen the coupling relationship between electric-thermal-hydrogen load. At the same time, a tiered carbon trading mechanism is considered, with the net profit of the VPP as the optimization objective, balancing economic and environmental considerations. A low-carbon economic dispatch model for VPPs is established, and a genetic algorithm is used for optimization. Three different scheduling strategies are set, and simulations are conducted in three different seasonal scenarios. The results show that the net profit in the cooling season increased by 50.4%, and carbon emissions decreased by 42.3%. In the transitional season, the net profit increased by 39.2%, and carbon emissions decreased by 44.9%. In the heating season, the net profit increased by 19.4%, and carbon emissions decreased by 43.4%. Overall, the proposed dispatch strategy can improve the new energy consumption capacity and total revenue of VPPs while achieving the goal of reducing carbon emissions.

Road-embedded inductive power transfer (IPT) systems have the potential to accelerate the electrification of the transportation sector. For these systems to be economically viable however, they need to have a similar durability and lifespan compared to that of asphalt roads. One area that has lacked investigation is thermally induced stresses in a primary IPT pad, which is caused by the increase in temperature of the pad when it is energized and the differing thermal expansion of the materials within. This paper presents an experimental and a finite-element based methodology for investigating the thermal-mechanical behaviour of a ¼-scale double-D pad, which was energized while suspended in air, as well as energized when embedded in pavement. A focus was placed on the measurement and prediction of strains in the magnetic ferrite cores because of their brittleness. Ferrite strains were measured using a combination of resistive strain gauges and non-metallic Fibre Bragg Grating (FBG) sensors. Coupled electromagnetic-thermal-structural simulations were conducted to predict temperature and strains in the system, with temperature-dependent properties obtained through physical testing. At an ambient temperature of 50°C, the temperature in the middle of the copper litz wire coil was predicted to be 100°C in both the suspended and embedded case. There was excellent correlation to experimental results, with a difference of less than 10% for most temperature measurements. When energized, the pad was predicted to experience an upward bow due to its temperature rise, resulting bending strains in the ferrite cores. At an ambient temperature of 50°C, maximum tensile strain in the ferrites of the embedded pad was measured to be 62 microstrain (με), with a root-mean square error that was 18 με across three sensors. The experimental and validated numerical methodology can be applied to full-scale operational IPT pads to analyse and improve their thermal-mechanical performance.

We examine a linear q-difference differential equation which is singular in complex time t at the origin. Its coefficients are polynomial in time and bounded holomorphic on horizontal strips in one complex space variable. The equation under study represents a q-analog of a singular partial differential equation, recently investigated by the author, which comprises Fuchsian operators and entails a forcing term that combines polynomial and logarithmic type functions in time. A sectorial holomorphic solution to the equation is constructed as a double complete Laplace transform in both time t and its complex logarithm log t and Fourier inverse integral in space. For a particular choice of the forcing term, this solution turns out to solve some specific nonlinear q-difference differential equation with polynomial coefficients in some positive rational power of t. Asymptotic expansions of the solution relatively to time t are investigated. A Gevrey type expansion is exhibited in a logarithmic scale. Furthermore, a formal asymptotic expansion in power scale is displayed, revealing a new fine structure involving remainders with both Gevrey and q-Gevrey type growth.

This article presents the development of an innovative Maximum Power Point Tracking (MPPT) strategy, utilizing a Particle Swarm Optimization (PSO) algorithm to improve the effectiveness of PV systems and expedite convergence. The new MPPT method incorporated a unique Swarm Self-Reinforcement Mechanism (SSRM) within the PSO algorithm, targeting quick convergence and excellent tracking accuracy. This approach enables the PSO to eliminate the fitness function that has the lowest value and subsequently reinforce it in the next iteration, revolving around the global maximum power point (GMPP). By applying this novel PSO-based method, the MPPT performance of PV systems was significantly improved, facilitating the algorithm to proficiently navigate through the solution space and quickly locate the GMPP, even in rapidly changing environmental conditions. The outcomes derived from this novel approach were contrasted with other algorithmic optimization methods, validating its superior convergence speed and tracking accuracy. Different swarm sizes were examined using SSRM, and the optimal swarm size for the system employing MPPT was identified to achieve the lowest convergence time (CT). The results showcased the impressive performance capabilities of this novel strategy, resulting in a time con-traction of up to 28% compared to the conventional PSO technique, where the optimal swarm size was found to be 5. This achievement marks a significant milestone in the evolution of PSO-based MPPT techniques, and paves the way for future advancements in this exciting field.

Geothermal energy is likely to be a significant contributor in achieving sustainable energy goals and net-zero emissions targets. Within geothermal power plants, heat exchangers play a critical role in harnessing this renewable energy source. However, these heat exchangers encounter significant challenges when exposed to geothermal fluids, including erosion, corrosion, and scaling, which adversely affects their performance and longevity. The current review focuses on surface engineering techniques, particularly coatings, as a highly effective and economically viable solution to address these challenges in geothermal heat exchangers. The review begins by providing an overview of geothermal energy, its significance in the context of sustainability and the important role played by heat exchangers in geothermal power generation, followed by the challenges and their impact on heat exchangers. The subsequent section focuses on surface engineering by coatings and its types employed to enhance the performance of heat exchangers. In the final part, the reader is presented with an overview of the challenges associated with the application of coatings in geothermal heat exchangers and potential future directions in this field. This review offers a detailed understanding of the critical role coatings play in improving the efficiency and service life of heat exchangers in geothermal power plants.

The article concerns problems related to the assessment of reactive power in power networks with non-linear, fast-varying loads, such as electric arc furnaces, rolling mill drives, etc. The operation of this type of loads is characterized by the introduction of interharmonic currents (including higher harmonics) into the power supply network and a relatively low power factor. Rapid changes in the RMS value of the current also cause voltage fluctuations and the related phenomenon - flicker. Therefore, there is a need to evaluate the selection of power of compensating devices taking into account the random nature of load changes and the distortion of current and voltage waveforms, in particular interharmonic components, the impact of which has not been fully investigated so far. To analyze the random nature of load changes, autocorrelation functions were used, which allowed for the estimation of the expected values of the arc furnace current distortion coefficient (based on the recorded waveforms). In order to determine the parameters of reactive power compensating devices, and in particular capacitor banks, an autocorrelation function in the exponential-cosine-sine form was used, which meets the conditions of differentiation. The article contains comparative results of calculations of the reactive power of capacitor banks determined using different methods.

The power generation structure and load characteristics in different provinces are quite different in China, and the distribution of peak regulating resources and demands is extremely unbalanced. Due to many factors such as low power marketization degree, shortage of peak regulating resources and block of transmission channels, the consumption of new energy is facing greater pressure. In order to improve the mutual aids in regional power grid, this paper proposes a two-layer optimization dispatching model considering the mutual aids of peak regulation resources between each province, and determines the optimal units startup mode and power output in each provinces, thus obtaining all the power supply output arrangements and the technical and economic indicators. Finally, take the actual regional power grid in China as an example, the simulation results show that the proposed model can significantly improve the new energy utilization rate, which verified the effectiveness and feasibility of the proposed model and methods in this paper.

Energy supply interruptions or blackouts caused by faults in power distribution feeders entail several damages to power utilities and consumer units: financial losses, damage to power distribution reliability, power quality deterioration, etc. Most studies in the specialized literature concerning faults in power distribution systems present methodologies for detecting, classifying, and locating faults after their occurrence. In contrast, this study aims to prevent faults by estimating the city regions whose power grid is most vulnerable to them. This work incorporates the geographic space study to prevent faults in the distribution power grid through a spatial data analysis using local variables that increase the fault risk in feeders in some city regions. Geographically weighted spatial analysis is applied to data aggregated by regions to produce thematic maps with the city regions whose feeders are more vulnerable to failures. Spatial data analysis is developed in QGIS and R programming environments. It is applied in real data of electrical discharges in a medium-sized city with approximately 200,000 inhabitants. In this study, we highlight a moderate positive correlation between electrical discharge density and the percentage of faults in transformers by regions in the central and western areas of the city under study.

A new power receiving unit (PRU) is proposed in this paper for the resonant wireless power transfer (WPT), which is characterized by the capability of attracting high power from the power transmitting unit (PTU). The resonant WPT is designed for delivering the electrical power to the PRU attached on an electrical vehicle (EV) chassis 50cm away from a PTU installed on the ground. The proposed PRU uses only the passive elements such as inductors, diodes and the capacitors, which needs no initial power from the EV. It is then applicable for charging a battery to several hundred volts for even a first-time charging battery. At a switching frequency of the resonant WPT in the experiment being 4MHz, the proposed PRU behaves itself as a negative impedance converter (NIC) in the subharmonics of 4MHz. The NIC effect plus the subharmonic oscillation causes an instability current charging the battery connected to the PRU. In this paper, we simulated the PRU and performed the experiment. The experiment demonstrates a battery charging of 150W from 50cm away using three D-mode GaN HEMT transistors via the instability current ramp. The power transfer efficiency (PTE) improved as the power delivered to load (PDL) goes higher. The best power transfer efficiency (PTE) is 65% in the present findings. The simulation analysis shows that the circuit allows itself be used to much higher power transfer when it is implemented with more GaN HEMT transistors connected in parallel. The theoretical derivation of the PRU circuit is also used to support both the experimental and simulation results.

Soiling accumulated on a photovoltaic (PV) module can significantly reduce the transmittance of the cover glass, resulting in power losses and consequent economic losses. Natural atmospheric parameters influence the accumulation of soiling at the various geographic locations. In this paper, the approaches and outcomes of the research studies on either indoor (simulator-based) or outdoor (field-based) PV soiling have been thoroughly reviewed. Different parameters depicted for the power loss of PV modules are analyzed individually and presented. Moreover, this study delves into a detailed examination of the key factors influencing dust depositions on PV modules in various geographical regions, with a particular focus on their relationship with climatic conditions. This way, probable future research directions to quantify soiling losses are identified. In addition, different loss prevention and mitigation techniques are also reviewed. This makes it possible to highlight effective strategies and pinpoint potential future research lines in these areas.

Optical power splitters play a crucial role as the fundamental building blocks for many integrated optical devices. They should have low losses, broad bandwidth, and a high tolerance to fabrication errors. Adiabatic optical power splitters inherently possess these qualities while being compatible with foundry processes well-suited for mass-production. The long device lengths of adiabatic power splitters, however, are a limiting factor to achieve compact device sizes, which must be reduced. Here, we use a polynomial taper profile optimization algorithm to design 1×2 and 2×2 adiabatic power splitters with significantly shorter lengths than their adiabatic counterparts. The best performing 1×2 and 2×2 power splitters have 20 μm and 16 μm coupling lengths, respectively. Our designs have minimum feature sizes ranging from 140 nm to 200 nm, and our measurements averaged across 9 different chips show excellent consistency in performance for devices with 180 nm and 200 nm minimum features. Both the 1×2 and 2×2 adiabatic optical power splitters have excess losses less than 0.7 dB over a 100 nm bandwidth, with a standard deviation lower than 0.3 dB. Furthermore, our measurements show greater than 20 dB extinction ratios over 130 nm bandwidth. We also demonstrate the design of 1×2 power splitters with arbitrary splitting ratios, where splitting ratios ranging from 50:50 to 94:6 were achieved with standard deviations between 2% and 6%.

This study examines the wind shear coefficient (WSC) values at three coastal wind sites located in the southern region of Balochistan, Pakistan: Pasni, Ormara, and Jiwani. These WSC values were obtained using 10-minute measured wind speed data at heights of 20, 40, and 60 meters above ground level (AGL). Since wind measurements are typically recorded at lower heights due to cost and resource constraints, extrapolation techniques were employed to estimate wind speeds at higher altitudes. However, using a constant WSC value for extrapolation may lead to significant errors between extrapolated and actual wind speed measurements, impacting the energy output of wind turbines. To evaluate the effect of WSC on energy yield, the study employed power curves and frequency distributions for 2MW and 1.5MW wind turbines. Additionally, wind power density was calculated using air density derived from measured air temperature and surface pressure data, covering two years period from November 2016 to August 2018. The overall mean WSC values were found to be 0.076 at Pasni, 0.094 at Jiwani, and 0.053 at Ormara. The study further investigated the seasonal, monthly, and diurnal variations of WSC. For assessing wind resources at a height of 60m, the study utilized Wind Roses, wind power density, and Weibull parameters. Comparing the actual WSC values presented in this paper with those obtained using the 1/7 power law and measured data at 60m AGL, the energy yield from the wind turbines showed reduced output and capacity factor.

In this paper, we study the effect of parasitic channel on electrical characteristics and power consumptions of vertically stacked gate-all-around (GAA) silicon nanosheet (NS) MOSFETs of the bulk and silicon-on-insulator (SOI) substrates. Through deliberate control of the bottom parasitic channel coverage, we systematically assess its influence on DC, AC, and RF characteristics including power consumption. The observed findings highlight a significant differentiation among the bottom parasitic channels: GAA (i.e., control sample with 100% coverage), omega-shaped gate NS (70% and 80% coverages), and FinFET (60% coverage). Compared with the device with a 60% coverage channel, the device with a 100% coverage channel possesses 3520% and 8030% normalized leakage current improvement for both NFET and PFET under the bulk substrate, respectively. Compared with bulk-substrate devices, the SOI-substrate devices further significantly improve the leakage current. Due to enhanced off-state current leakages in the 100% covered bulk-substrate device, the static power demonstrates a notable improvement (about 98.1%), compared to 60% covered devices. Hence, the utilization of a 60% covered channel will result in a degradation of both device and circuit performance. The observation of GAA NS MOSFET indicates that an increase in the bottom parasitic channel coverage ratio leads to a positive impact on power consumption and leakage currents. The examination presented here is useful in the fabrication of stacked GAA NS MOSFETs.

The electrical motor design requires a lot of work and resources. In the field, motor designers need to decide on competitive motor sizing quickly to compete with other motor suppliers. Generally, it requires expensive FEM S/W to get accurate motor sizing results, but buying and maintaining many licenses is costly. Moreover, it needs some patience to get the result from FEM analysis. In this paper, the motor sizing technique using an existing production motor is presented to respond to urgent requests from customers without using FEM analysis. In order to enhance the fidelity of the result, magnetic flux loss by magnet coating and non-linear characteristics are considered during the motor sizing process. The proposed sizing method was verified by comparison to the FEM analysis and test result and showed reasonable confidence in them. Also, this method has the substantial advantage of outputting accurate results instantly without taking any time. It helps with the modification design of electrical motors without using expensive FEM S/W and a certain level of skill or experience.

Obesity in adolescents combined with the increased exposure time to electronic devices, enhances a sedentary lifestyle and is linked to the risk of developing musculoskeletal injuries. The aim of this study was to identify possible correlations between anthropometric characteristics, body composition, exposure time to electronic devices or screen time (ST) and physical activity (PA) level along with muscle power and dynamic knee valgus (DKV) in young athletes to avoid future injuries. A total of 125 adolescent basketball athletes (66.4% boys), 12 to 17 years old (13.94±1.58 years) participated. Anthropometric and demographic characteristics were recorded. PA level was assessed through IPAQ and ST through a single question from the HELENA study. The Counter Movement Jump test was used for the evaluation of the lower limb muscle power, while the Single Leg Drop Jump test was used for the evaluation of the dynamic knee valgus via two-dimensional (2D) kinematic analysis. The Pearson index showed a statistically significant positive correlation between muscle power and height (r=0.788, p<0.001), while the Spearman index showed a smaller but equally statistically significant positive correlation with BMI (rs =0.651, p<0.001) and age (rs=0.579, p<0.001). The ST (rs= -0.194, p=0.03) showed a weak negative correlation with DKV, while PA (r=0.85, p<0.001) showed a high, statistically significant, positive correlation. The anthropometric characteristics of adolescent athletes can determine their ability to produce muscle power. A high level of physical activity could play a key role in compensating and thus reducing the negative effects of high exposure to screen time on the dynamic knee valgus

This article introduces the design and analysis of a slope detection circuit tailored for on-chip sensing of the load current in DC-DC converters. The novel indirect sensing approach is grounded in measuring the output voltage slope across the filtering capacitor during discharge phases. Consequently, this slope data can be effectively harnessed to control the converter switches. The slope detector circuit was designed in standard 65 nm CMOS technology using the nominal supply voltage of 1.2 V and can be used for current sensing within the range from one to hundreds of mA. Since the proposed circuit has mainly digital character, the robustness to process, temperature and supply voltage variations can be ensured rather conveniently.

Smart grids are seeing an increase in renewable energy and an enormous introduction of advanced power electronics, increasing the number of disturbance sources. This requires improving the accuracy of measurement systems capable of acquiring data for use in power system monitoring applications. Rogowski Coils (RCs) and Merging Units (MUs) are being widely deployed in controlling, metering, and monitoring of digital power systems. Because the performance of digital measurement devices has a direct influence on power measurement accuracy, it is critical to perform a laboratory calibration of these measurement instruments before they are installed in any project. To determine the magnitude and phase displacement errors of the RC+MU under normal and abnormal operating conditions, this article presents a comprehensive laboratory digital calibration system constructed from precise, readily available commercial products such as a fluxgate current transducer and a National Instrument. In addition, the analysis of measurement chain is affected by sources of uncertainty is discussed. The tests yield findings that are consistent with the relevant standards.

Frontotemporal dementia (FTD) is the second most common form of presenile dementia; however, its diagnosis has been poorly investigated. Previous attempts to diagnose FTD using quantitative electroencephalography (qEEG) have yielded inconsistent results in both spectral and functional connectivity analyses. This study aimed to introduce an accurate qEEG marker that could be used to diagnose FTD and other neurological abnormalities. We used open-access electroencephalography data from OpenNeuro to investigate the power ratio between the frontal and temporal lobes in the resting state of 23 patients with FTD and 29 healthy controls. Spectral data were extracted using a Fast Fourier Transform in the delta (1–4 Hz), theta (4–8 Hz), alpha (8–13 Hz), beta (13–32 Hz), and gamma (32–45 Hz) bands. We found that the spectral power ratio between the frontal and temporal lobes is a promising qEEG marker of FTD. Frontal/temporal (F/T) theta/alpha, alpha/theta, al-pha/gamma, and gamma/alpha showed a consistently high discrimination score for the diagnosis of FTD for different parameters and referencing methods. The study findings can serve as reference for future research focused on diagnosing FTD and other neurological anomalies.

A layout of urban waste fired zero emission power plant is described in this paper. The principle of layout, which comes from similar coal-fired plants retrieved from the literature, integrates gasification with a power generation section, and implements two parallel conversion processes, one supplied by the heat of the gasifier consisting of a thermoacousticmagnetohydrodynamic (TAMHD) generator, while in the second one the syngas is treated in order to obtain almost pure hydrogen, which is fed to fuel cells. The CO2 deriving from the oxidation of Carbon base is stocked in liquid form. The novelty of the proposed layout lies in the fact that the entire conversion is performed without solid moving parts. The resulting plant avoids any type of emissions in the atmosphere, increases mechanical efficiency as compared to traditional plants, thanks to the absence of moving parts, nonetheless, resolving at its root the ever-increasing waste-related pollution problems.

This research, which focuses on wave energy generating technology, suggests a brand-new oscillating float-type wave energy conversion system that is appropriate for the offshore wave environment. To accurately model the device, a three-dimensional viscous numerical pool is created based on STAR-CCM+. The array-type power generation device is numerically simulated using theoretical analysis and numerical simulation, and the wave energy power generation device is arranged as double floats in the front and rear rows, representing triangular array type and rectangular array type, respectively. The triangular array type is a superior layout and can make greater use of marine resources, according to this paper's analysis of the hydrodynamic and power generation impacts of the three array types. The findings are meant to serve as a guide for engineering practice.

Thailand has formulated her climate change policy and updated relevant plans and policies to align with the goal of achieving carbon neutrality and net zero GHG emissions. This study investigates the optimal level of GHG mitigation in Thailand, taking into account the marginal abatement cost (MAC) and social cost of carbon (SCC). It evaluates how energy efficiency and renewable energy technologies influence GHG reduction in the power and industrial sector and illustrates policy recommendations that align with the 2020 to 2050 policy and plan period. The findings indicate that there may be instances where GHG mitigation potential is insufficient to reach the national mile-stone. In such cases, it becomes imperative to leverage all technologies within the marginal abatement cost curve (MACC) and also utilization of the social cost of carbon for policy decision making and meeting the desired goals. In certain scenarios, the adoption of additional technologies or measures may be necessary, such as flexible power generation and deploying carbon capture and storage or hydrogen which are high-cost technologies. Furthermore, preparations should be made for multiple levels of climate change policies and plans beyond 2030.

Continuous greenhouse gas emissions are causing global warming and impacting the habitats of many animals. Researchers in the field of electric power are making efforts to mitigate this situation. Operating and maintaining the power grid in an economic, low-carbon, and stable is challenging. To address the issue, we propose a grid dispatching technique that combines prediction technology, reinforcement learning, and optimization technology. Prediction technology can forecast future power demand and solar power generation, while reinforcement learning and optimization technology can make charging and discharging decisions for energy storage devices based on current and future grid conditions. In the power system, the aggregation of distributed energy resources increases uncertainty, particularly due to the fluctuating generation of renewable energy. This requires the use of advanced predictive control techniques to ensure long-term economic and decarbonization goals. In this paper, we present a real-time dispatching framework that integrates deep learning-based prediction, reinforcement learning-based decision-making, and stochastic optimization techniques. The framework can rapidly adapt to target uncertainty caused by various factors in real-time data distribution and control processes. The proposed framework achieved global Champion in the NeurIPS Challenge 2022 competition and demonstrated its effectiveness in practical scenarios of intelligent building energy management.

The main objective of the paper is to provide a thorough analysis of currently used modulation control schemes for single phase bidirectional dual active bridge DC/DC converter. In this article, it will be shown that single phase shift, extended phase shift and Dual phase shift modulation schemes are special cases of triple phase shift (TPS) modulation scheme. The article aims to highlight six TPS switching modes and their complements with the operational constraints. Unlike previous studies that regarded TPS as a complex scheme, this paper simplifies the analysis of each mode and aims to standardize the understanding of TPS modulation in DAB converters. Power equations, range of power transferred and zero voltage switching (ZVS) are derived for all the modes under TPS without assuming fundamental component analysis. Additionally, a generic optimization algorithm is developed to show the advantages of TPS modulation and thus, detailed analysis presented in this paper provides valuable insights for single phase DAB converter designers in identifying a wide range of optimization algorithms to achieve higher efficiency under TPS modulation. This analysis contributes to the advancement of bidirectional DAB converter technology and facilitates its application in various power electronic systems.

The paper proposes an innovative solution for managing and ensuring high energy efficiency of power supply systems at high non-linear loads. This is realized by maintaining optimal value of reliability indicators and high quality of power supply. The validation is carried out using analyzes and tests of quality of electromagnetic compatibility (EMC) for increased number of powered frequency converters. It has been proven that the effective use and reduction of energy consumption can be achieved thanks to the unique technological features of the employed electrical devices. This enables a normal operation of the system with decreased power and adequate control of energy processes. The problem of predicting power losses under changing conditions in a decentralized electrical network has been solved based on the theory of electromagnetic compatibility. The influence of the mains mode parameters and the indices of instantaneous distortion of current and voltage waveforms caused by the operation of converters on the resonance phenomena in power supply systems were investigated. Recommendations were developed for the selection of proper parameters of compensators for 6-10 kV and 0.4-0.66 kV circuits based on the analysis of the optimization problem when minimizing active power losses. Results of our findings may aid parties involved in designing and maintaining power networks in various applications, such as mines, etc.

Hypoglossal nerve stimulator (HGNS) is a minimally invasive device used for treating obstructive sleep apnea (OSA). The conventional implantable HGNS is a device that consists of a stimuli generator, a breathing sensor, and electrodes connected to the hypoglossal nerve via leads. However, this implant is bulky and causes significant trauma. In this paper, we propose a minimally invasive HGNS based on an electrocardiogram (ECG) sensor and a wireless power transfer (WPT), consisting of a wearable breathing monitor and an implantable stimulator. The breathing external monitor utilizes an ECG sensor to identify abnormal breathing patterns associated with OSA with 88.68$\%$ accuracy, achieved through the utilization of a Convolutional Neural Network (CNN) algorithm. With a skin thickness of 5mm and a receiving coil diameter of 9mm, the power conversion efficiency was measured at 31.8$\%$. The implantable device, on the other hand, is composed of a front-end CMOS Power Management Module (PMM), a Binary Phase Shift Keying (BPSK)-based data demodulator, and a bipolar biphasic current stimuli generator. The PMM, with a silicon area of 0.06 $mm^2$ (excluding pads), demonstrates a power conversion efficiency of 77.5$\%$ when operating at a receiving frequency of 2 MHz. Furthermore, it offers three-voltage options (1.2V, 1.8V, and 3.1V). Within the data receiver component, a low-power BPSK demodulator has been ingeniously incorporated, consuming only 42 $\mu$W when supplied with a voltage of 0.7V. The performance is achieved through the implementation of the self-biased phase-locked loop (PLL) technique. The stimuli generator delivers biphasic constant currents, providing a 5-bit programmable range spanning from 0 to 2.4 mA. The functionality of proposed ECG and WPT-based HGNS was validated, representing a highly promising solution for the effective management of OSA, all while minimizing trauma and space requirements.

The aim of this article is to review hydrogen combustion applications within the energy transition framework. Hydrogen blends are also included, from the well known hydrogen enriched natural gas (HENG) to the hydrogen and ammonia blends whose chemical kinetics is still not clearly defined. Hydrogen and hydrogen blends combustion characteristics will be firstly summarized, in terms of standard properties like the laminar flame speed and the adiabatic flame temperature, but also evidencing the critical role of hydrogen preferential diffusion in burning rate enhancement and the drastic reduction in radiative emission with respect to natural gas flames. Then, combustion applications in both thermo-electric power generation (based on internal combustion engines, i.e., gas turbines and piston engines) and hard-to-abate industry (requiring high temperature kilns and furnaces) sectors will be considered, highlighting the main issues due to hydrogen addition related to safety, pollutant emissions, and potentially negative effects on industrial products (e.g., glass, cement and ceramic).

Maritime ports represent an important ecosystem for pollutant emissions and, taking into account the ongoing energy transition, need to adopt new solutions to mitigate current emission levels. These emissions are partially avoidable if ships and vessels docked at the port use electric energy to feed their internal power needs instead of using their internal combustion engines. In Europe, there is an ongoing discussion on including such emissions in the European Emissions Trading System which will represent added costs for maritime operators. Onshore Power Supply systems can contribute to the ongoing energy transition by allowing the use of electric power to feed docked ships. As a first step to contribute to the development of Onshore Power Supply solutions, it is necessary to evaluate the added power needs that these systems would represent for the port. This paper presents a methodology that allows port operators to verify, straightforwardly and transparently, their power needs for Onshore Power Supply applications. The methodology is based on the historical data of docked ships at the port or quay level and provides an energy analysis of each type of vessel to determine the power to be installed at the port so that it is possible to supply energy to different types of ships and vessels simultaneously. Additionally, the implemented methodology provides economic and technical decision support factors by comparing the fuel costs with electric power costs, assessing the potential for this transition to Onshore Power Supply. The methodology is validated using a real case study for the port of Lisbon and obtained results demonstrate the potential for the installation of Onshore Power Supply in medium to large-dimension maritime ports.

The hybridization of conventional thermal power plants by incorporation of renewable energy systems has witnessed widespread adoption in recent years. This trend aims not only to mitigate carbon emissions but also to enhance the overall efficiency and performance of these power generation facilities. However, calculating the performance of such intricate systems using fundamental thermodynamic equations proves to be both laborious and time-intensive. Nevertheless, possessing accurate and real-time insights into their performance is of utmost significance to ensure optimal plant operation, facilitate decision-making, and streamline power production planning. In this paper, we delve into the application of machine learning techniques, particularly hybrid methodologies, to predict the performance of power plants. Specifically, we employ three approaches: the Adaptive Neuro-Fuzzy Inference System (ANFIS), the ANFIS optimized via Particle Swarm Optimization (ANFIS-PSO), and the ANFIS optimized through Genetic Algorithm (ANFIS-GA). These techniques are alternatively applied to a complex hybrid thermal power plant, namely an Integrated Solar Combined Cycle Power Plant (ISCCPP). This ISCCPP comprises a steam turbine section, a gas turbine section, and a concentrated solar power system utilizing troughs as collectors. The energy transfer fluid, in conjunction with exhaust from the gas turbine section, heats water within a vessel or steam generator, producing steam to propel the steam turbine's rotor. Electricity generation is facilitated by both gas and steam turbines, which are coupled to a generator. The findings of this study underscore the accuracy and appropriateness of ANFIS-based models in evaluating and predicting the performance of intricate hybrid power plants. The ANFIS model exhibited an impressive overall coefficient of correlation of 0.9991. Notably, the integration of evolutionary algorithms (PSO and GA) into the ANFIS framework elevated model performance, yielding correlation coefficients of 0.9994 for ANFIS-PSO and 0.9997 for ANFIS-GA. It is noteworthy that ANFIS-GA demonstrated superior predictive capability. The modeling framework developed in this research offers valuable support to designers, energy managers, and decision-makers. It provides a robust and dependable tool to assess the performance of hybrid thermal power plants, which are poised for a global surge in numbers amid the ongoing energy transition.

The tension cable-supported power transmission structure (TC-PTS) is a new type of power transmission structure suitable for mountainous terrain, which is sensitive to wind load. In this regard, a nonlinear finite element analysis model of wind-induced vibration is proposed for the TC-PTS, and the wind-induced vibration response of the structure is analyzed. Firstly, the tangent stiffness matrix of the three-dimensional truss element for the supporting suspension cable and transmission line, considering the geometric nonlinearity of structures, is derived through the relationship between the element elastic energy and its displacement. Subsequently, the element mass matrix and damping matrix of the supporting suspension cable and transmission line, as well as the element nodal load vector obtained from wind load equivalence are given. Then, based on the nonlinear finite element theory, the nonlinear dynamic equation of wind-induced vibration is established for the TC-PTS and solved by Newmark-β method combined with Newton-Raphson iterative method. Furthermore, the rain-flow counting method and Miner's linear fatigue cumulative damage theory were used for wind induced fatigue damage assessment. Finally, a two-span TC-PTS is selected as an example, and the wind-induced nonlinear vibration and fatigue damage assessment are analyzed through the proposed model. The results show that the proposed model has high computational accuracy and efficiency. With the increase of wind speed and wind direction angle, the maximum lateral displacement and tension of the supporting suspension cable and transmission line increase, and their degree of increase shows a nonlinear trend. In terms of the wind-induced fatigue analysis results of TC-PTS, the fatigue damage at the end of the supporting-conductor suspension cable is greater than the fatigue damage at its midpoint. Compared to the fatigue damage at the midpoint of the conductor, the fatigue damage at the end of the conductor is less affected by wind direction angle, and both are more significantly affected by the wind speed.

Due to the intermittency and fluctuation of photovoltaic (PV) output power, a high proportion of grid-connected PV power generation systems has a significant impact on power systems. Accurate PV power forecasting can alleviate the uncertainty of the PV power and is of great significance for the stable operation and scheduling of the power systems. Therefore, in this study, a feature rise-dimensional (FRD) two-layer ensemble learning (TLEL) model for short-term PV power deterministic forecasting and probability forecasting is proposed. First， based on the eXtreme Gradient Boosting (XGBoost), Random Forest (RF), CatBoost, and Long-short-term memory (LSTM) models, a TLEL model is constructed utilizing the ensemble learning algorithm. Meanwhile, the FRD method is introduced to construct the FRD-XGBoost-LSTM (R-XGBL), FRD-RF-LSTM(R-RFL), and FRD- CatBoost - LSTM (R-CatBL) models. Subsequently, the above models are combined to construct the FRD-TLEL model for deterministic forecasting, and perform probability interval forecasting based on quantile regression(QR). Finally, the performance of the proposed model is demonstrated with a real-world dataset. By comparing with other models, the proposed model displays better forecasting accuracy for deterministic forecasting and reliable forecasting intervals for probability forecasting, and good generalization ability in the datasets of different seasons and weather types.

One of the rapidly developing research areas in the power system is the integration of distributed generation (DG) with the distribution system. The size and location of DG sources had a considerable impact on power system networks. Artificial intelligence (AI) techniques can be used to address multidimensional problems relating to DG size and location in distribution systems. Heuristic optimization offers a reliable and effective method for solving complicated real-world problems. This work focuses on a hybrid approach that combines the two heuristic optimization methods i.e., Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) for the optimal siting and sizing of DG in distribution systems. This hybrid approach combines ideas from GA and PSO and generates individuals in a new generation using both PSO mechanisms and the procedures found in GA. An extensive performance analysis of the IEEE 14 busbar standard test system is conducted to demonstrate the viability of the suggested methodologies. In the designated locations, DG is placed, and the outcomes have been verified. The results indicated that the right placement of DG injection enhances the voltage profile and lowers the distributed system’s power losses. These techniques offer unique methods for determining the location of the DG unit, demonstrating the potential of such a computational techniques to reduce computing time and complexity while simultaneously reducing human errors associated with hit-and-trail methods.

Besides the increase in global energy demand, access to clean energy, reduction in greenhouse gas emissions caused by conventional power generation sources, energy security, and availability of electricity in remote villages in emerging nations are some of the factors that foster the use of renewable energy sources (RESs) in generating electricity. One of the aims of initiating microgrids (MGs) is to maximize the benefits of RES and alleviate the associated grid integration issues. Microgrids are made up of RES connected to electrical loads within clearly delineated electrical limits that operate as individual controllable units on the electrical network. It can operate in-dependently as well as in connection with the grid. The paper presents an overview of microgrids and investigates the system's performance when connected to and disconnected from the grid. Furthermore, in both modes of operation, the functioning and behavior of system components such as the bidirectional DC-DC converter and energy storage system (ESS) were evaluated. The architecture of the proposed microgrid consists of a small hydropower plant, a wind farm, and a battery energy storage system (BESS). The microgrid under investigation is modeled and simu-lated using MATLAB and Simulink.

Growing population, industrialization, and power requirements are adversely affecting the environment by increased greenhouse gases, resulting from fossil fuel burning. Global greenhouse gas mitigation targets have led the nations to promote clean and self-renewable sources of energy to address the environmental issue. Offshore wind power resources are relatively more attractive due to high winds, less turbulence, minimal visualization effects, and no interaction of infrastructure. The present study aims at conducting offshore wind power resources assessment (OWPRA) at some locations in the Gulf of North Suez. For this purpose, the long-term hourly mean wind speed (WS) and wind direction above means sea level (AMSL) and temperature and pressure data near surface is used. The data is obtained from ERA5 (fifth generation reanalysis for the global climate weather) at chosen six (L1-L6) offshore locations. The data covers a period of 43 years, between 1979 and 2021. The WS and direction are provided at 100 m AMSL while temperature and pressure are available near water surface level. At L1 to L6 locations, the log-term mean WS and wind power density (WPD) values are found to be 7.55 m/s and 370 W/m2, 6.37 m/s and 225 W/m2, 6.91 m/s and 281 W/m2, 5.48 m/s and 142 W/m2, 4.30 m/s and 77 W/m2, and 5.03 and 115 W/m2 and at 100 m AMSL; respectively. The higher magnitudes of monthly and annual windy site identifier indices (MWSI and AWSI) of 18.68 and 57.41 and 12.70 and 42.94 at L1 and L3 sites and generally lower values of wind variability indices are indicative of favourable winds source, which is also supported by higher magnitudes of mean WS, WPD, annual energy yields, plant capacity factors, and wind duration at these sites. The cost of energy, for the worst and the best cases are estimated as 10.120 USD/kWh and 1.274 USD/kWh at L5 and L1 sites corresponding to wind turbines WT1 and WT4. Based on the analysis, sites L1, L3, and L2 are recommended for wind farm development in order of preference. The wind variability and windy site identifiers indices introduced, will help decision-makers in deciding the potential windy sites with more confidence.

The integration of the increasing share of Renewable Energy Sources (RES) requires the availability of suitable energy storage systems to improve the grid flexibility, and Compressed Air Energy Storage (CAES) systems could be a promising option. In this study, a CO2-free Diabatic CAES system is proposed and analysed. The plant configuration is derived from a down-scaled version of the McIntosh diabatic CAES plant, where the natural gas is replaced with green hydrogen, produced on site by a Proton Exchange Membrane electrolyser powered by a Photovoltaic power plant. In this study, the components of the hydrogen production system are sized to maximize the Self-Consumption share of PV energy generation and the effect of the design parameters on the H2-CAES plant performance are analysed on a yearly basis. Moreover, a comparison between the use of natural gas and hydrogen in terms of energy consumption and CO2 emissions is discussed. The results show that the proposed hydrogen fuelled CAES can effectively match the generation profile and the yearly production of the natural gas fuelled plant by using all the PV energy production, while producing zero CO2 emissions.

Combining wind and solar photovoltaic (PV) generation can provide complementary renewable power production, but depends on correlated resources. This study analyzed 10 years of wind data from Naama, Algeria to evaluate the potential for evening wind generation to offset the loss of solar at sunset. Average wind speeds showed a distinct increase during evening hours, coinciding with the decrease in solar irradiance. Wind turbine simulations using a 1.5 MW turbine and the wind data showed sufficient resources for profitable power production after sunset. Statistical analyses confirmed significantly higher wind speeds and simulated power output in evening vs daylight periods (p&lt;0.05). The Pearson correlation coefficient between evening wind speeds and decreasing solar irradiance was 0.63, supporting a strong positive relationship. These findings indicate Naama has adequate wind resources to deploy economically viable wind power capacity that can complement existing solar infrastructure and provide renewable electricity after dark , .

Considering that traditional energy sources such as fossil fuel are about to deplete during the following decades, governments try to turn to renewable energy. It is commonly known that Greece has a natural advantage of abundant solar energy and wind power due to its geographical location and characteristics.The main focus of this study is to examine how wind energy potential across the Aegean Sea and continental Greece can provide a promising field for investments in Greece, considering the economic crisis, current trends and future perspectives.We firstly focus on current legislation framework considering that laws associated with such types of investment in Greece are very complex and rapidly changing. Furthermore, a case study for a hypothetical investment plan concerning a wind park located in an Aegean island will be presented. RetScreen which is a software made by the Canadian government, will be used as a decision support tool for analyzing the potential investment scenario and a financial report will follow with estimation of the overall cost, depreciation, upcoming benefits, and payback period of the investment.Data analysis concludes that wind parks still prove to be an economically viable investment, although incentives considering the guaranteed price per kwh and faster investment times must be provided by the government.

Multi-board electronic cases with high density and high power modules are widely used in industrial power supply management. With the improvement of case performance and miniaturization requirements, heat dissipation becomes one of the important factors to be considered in the design process. First,The existing small electronic thermal design methods focus on heat dissipation structure or heat source layout optimization,and ignores on-load test for modeling analysis. Second,The selected power module has on-load power consumption, resulting in relatively low calorific value and the effectiveness of thermal design cannot be verified. Third, The thermal lacks Intelligent monitoring and feedback control mechanism. In order to solve these problems, this paper designs a kind of heat dissipation case with intelligent temperature control based on high-power and high-density power supply array. Based on the extremely miniaturization design principle, we adopt the composite heat dissipation mode based on conduction and supplemented by forced air cooling . The case is made of magnesium and aluminum alloy with a perforated design. Finally, we compare and analyze with the existing cooling design. The results show that the case is smaller in volume, and the cooling performance parameters are slightly better than the existing case. Under the condition of high-density and high-power design, The output power of the whole system is not less than 10kw and the lowest packing-level density is not less than 47w/cm2 with high reliability, portability and practicability. It also provides technical support and prototype support for the standardized design of similar power arrays.

Keywords: Electrical power systems, Support vector machines, Random Forest, Machine learning, Wavelet transform, Transmission lines fault, Electrical power quality, Short circuit, Classification of faults, Localization of faults, Decision trees, Ensemble learning, K-nearest neighbors.

In the Neighborhood Area Network (NAN), the Advanced Metering Infrastructure (AMI) enables a bidirectional connection between the Smart Meter (SM) and the Data Concentrator (DC). Sensors, such as smart meter node or Radio Frequency transceiver, play a crucial role in collecting and transmitting data from meters to central unit for advanced monitoring, management, and analysis of energy consumption. Wired and wireless communication technologies can be used to implement the AMI-NAN. This paper delves into a novel approach for optimizing the choice of communication medium, Radio Frequency (RF) or Power-Line Communication (PLC), between the SM and DC in the context of AMI-NAN. The authors methodically select the specific technologies, RF and NB-PLC (Narrow Band Power-Line Communication), and meticulously characterize their attributes. Then, a comparative analysis spanning rural, urban, and industrial settings is conducted to evaluate the proposed method. The overall reliability performance of the AMI-NAN system requires a Packet Error Rate (PER) lower than 10%. To this end, a comprehensive methodology is introduced to assess and enhance the reliability of NB-PLC and RF for AMI-NAN applications. Simulation results demonstrate that wireless communication is the optimal choice for the rural scenario, especially for Signal to Noise Ratio (SNR) lower than 25 dB. However, in urban environments characterized by higher SNR values and moderately dense networks, NB-PLC gains prominence. In denser networks, it outperforms wireless communication, exhibiting a remarkable 10 dB gain for a bit error rate (BER) of 10-3. Moreover, in industrial zones characterized by intricate network topologies and non-linear loads, the powerline channel emerges as the optimal choice for data transmission, affording a gain surpassing 20 dB.

This paper proposes a position recognition method for the receiver coil by the secondary coil current. Based on the practical value of the current of the receiver coil, the position recognition of the receiver coil in the WPT system is realized. This paper proposes a 3×3 array multi-transmitter coil grouping and control logic. The mathematical model of mutual inductance between the receiver and transmitter coil at different positions on the X-Y plane is established. A method for identifying the position of the receiver coil according to the current of the receiver coil is proposed. Compared with the traditional position recognition method of the receiver coil, this method does not need to add a detection coil and position sensor and can realize the position recognition of the receiver coil on the 2D plane.

To supply stable and high-quality power according to the advancement of industrial growth, electric power companies have performed maintenance of power facilities using various meth-ods. In the case of domestic power distribution facilities, there are limitations in performing di-agnostic management on all facilities owing to the large number of facilities; therefore, old fa-cilities are managed by the health index assessment method. The health index assessment com-prises only facility operation data and external environmental data and is managed only for four types of distribution facilities, including overhead/underground transformers and switchgear. In the case of extra high–voltage overhead wires, there is no standard for old replacement, despite the large number of wires, such as transformers and switchgear, and the large ripple effect of power failure in the event of a power outage. Therefore, in this paper, a health index assessment methodology for extra-high voltage overhead cables was developed. In this paper, we devel-oped an economic health index assessment methodology that additionally considers risk cost, which is different from the existing health index assessment method that uses only operational data and external environmental data to determine facility performance evaluation and aging replacement criteria. Using the health index assessment methodology developed in this paper, it is possible to expect a reduction in facility operating costs and investment costs from the per-spective of electric power companies through the replacement of old extra-high voltage over-head cables. In addition, from the perspective of consumers, it is expected to increase power re-liability and reduce the ripple effect of failure by preferentially replacing equipment with a high probability of failure.

This paper presents a parametric study of the multistorey hydro-powered pump, known as "Bunyip," which has demonstrated significant potential in contributing to rural regions. The study aims to understand the underlying physics of the system and enhance its hydraulic performance. A transient three-dimensional model using the commercial Computational Fluid Dynamics (CFD) tool Ansys-Fluent is utilized to gain insights into the fundamental flow mechanics, operational efficiency, standard capacity, and relative delivery. The investigation involves an initial assessment of performance for three Bunyip devices based on manufacturing data. Parametric analysis is conducted, and a parametric dataset is generated through meticulous application and numerical modelling. The CFD results are validated against experimental data. Three design configurations are considered, and 58 sets of varied input parameters are examined. The best design configuration is evaluated against five cases of conventional hydro-power pump systems. The results indicate that a smaller diameter of the pressure chamber and a higher supply head lead to higher pressure, achieving a target head of 3 m with 15% efficiency and a flowrate of 11.82 l/min.

Using graph theory, computer aided motion, static force and power flow analysis of planetary gear mechanism is realized. The motion, static force and efficiency calculations of 6HP26 automatic transmission are carried out. Based on kinematic and static force analysis model, related matrices are acquired. Hence, kinematic and static force analysis of planetary gear mechanism is achieved. The link power can be determined by the link speed and torque. Power flow diagrams of each gear are acquired. The efficiency is calculated by transmission ratio method.

This paper presents a comprehensive evaluation of metal foam employment within polymer electrolyte fuel cells (PEFCs) and compares it with conventional serpentine channels from both experiment viewpoints and computational fluid dynamics simulation. The experiments are designed to study the effects of material, area density, compression ratio, and final thickness of metal foam. Additionally, the influence of housing plate material and relative humidity (RH) is also tested for the first time. The results reveal that at RH=75-100%, the best distributor design is nickel foam with a compression ratio of 70%, a final thickness of 0.5mm, and SS-304 housing plate, which delivers 3110 mA cm^-2 as limiting current density that is scarce in the literature. The PEFC with this foam distributor shows a 10% improvement in maximum power density and 45% in limiting current density compared to the serpentine channel case. While at RH=30%, the same foam flow field with a final thickness of 1mm is a superior option. The experiments also indicate that maximum power density increases by 23% as the compression ratio rises from 0 to 70%, while reducing final thickness from 1 to 0.5 mm causes a 19% enhancement in cell performance. Simulation results reveal that metal foam is more successful in evenly reactant distribution so that the average oxygen mass fraction at the cathode catalyst layer is increased by 38% in the metal foam case compared to the serpentine channel.

A full potential all-electron density functional method within generalized gradient approximation is used to investigate the electronic, elastic and transport properties of cubic copper sulphide and copper selenide. The electronic structure suggests metallic behavior with a zero energy band gap for both materials. Elastic property calculations suggest a stiff material with the bulk to shear modulus ratio of 0.35 and 0.44 for Cu2S and Cu2Se respectively. The transport properties were estimated using the Boltzmann transport approach. Seebeck coefficient, electrical conductivity, thermal conductivity, and power factor all suggest a potential p-type conductivity for Cu2S and n-type conductivity for Cu2Se.

In this paper for every number field K generated by a root α of a trinomial x⁷ + ax + b ∈ Z[x] and for every prime integer p, we calculate ν_p(i(K)), the highest power of p dividing the index i(K) of the field K. In particular, we calculate the index i(K). As application, when the index of K is not trivial, then K is not monogenic.

Neutral beam injection (NBI) is used for thermonuclear plasma heating, non-inductive current drive, rotation, operation scenario control, and for plasma diagnostics in nuclear fusion devices. NBI is the main source of fast particles in plasma which transmit energy to thermal plasma during their slow-down. Steady-state tokamak operation is only possible when the sub-thermal particles energy is absorbed and effectively confined in plasma volume. While NBI purposes and applications vary through different fusion systems, the engineering tasks performed during research and development (R&D) stage of neutral beamline design have much in common. The NBI studies, especially addressing long pulse and high-power operation typically include a beam transmission analysis and power loads distribution at the structural components of the beamline. Thermo-structural analysis is applied next to heat removal circuits design. ‘Beam Transmission’ (BTR) code is a dedicated tool, developed by a physicist and used by NBI physicists and engineers. BTR was created and 1^st applied during R&D phase of the world’s largest tokamak ITER. BTR code is intended for public usage and routinely applied for detailed simulations of neutral beam propagation through complex beamlines. BTR is flexible and intuitive in input, user-friendly and fully interactive. Thanks to visualization and high performance BTR looks and feels like a real NB flight simulator. Despite BTR ‘mature’ age, the code is still in evolution. Support is available to all new BTR users.

The methanation of CO2 is of great interest in power-to-gas systems and contributes to the mitigation of climate change through carbon dioxide capture and the subsequent production of high value-added products. This study investigated CO2 methanation with three Ni catalysts supported on Al2O3 and ZrO2, which were simulated using a mathematical model of a packed bed reactor designed based on their chemical kinetics reported in the literature. The simulated reactive system was fed with syngas obtained from residual coffee pulp, obtained after solvent phytochemical extraction process, under several gasification conditions. The results reflect a high incidence of catalyst support, preparation method, and syngas composition on CO2 conversion and CH4 selectivity. For all the syngas compositions, Ni/ZrO2 catalysts show the best values for CO2 conversion and CH4 selectivity for Ni/Al2O3 catalyst.

This study presents a cost-effective IoT-based remote monitoring system for solar PV energy systems, along with a machine learning-based PV power estimator. Remote access is crucial for tracking PV systems installed in remote areas. In this system, an open-source and IoT-compatible data logger is employed. The data logger collects important performance data of the PV system and transfers it to a server. Real-time visualization of this data is displayed in the designed web and mobile monitoring interfaces. The measured data includes the current, voltage, and temperature information of the PV generator and battery, as well as environmental parameters such as temperature, radiation, humidity, and pressure. Subsequently, this data is used for PV power estimation using machine learning methods. This enables the identification of maintenance requirements and the prediction of potential issues in the PV system. When a problem occurs in the PV system, the user is alerted through the mobile application. Early detection and intervention prevent power loss and damage to system components. When comparing the results of linear regression, SVM, decision trees, random forests, and KNN machine learning methods for power estimation based on performance evaluation criteria, it was observed that the random forests algorithm provided the best results. In conclusion, the developed monitoring and estimation system, along with web and mobile interfaces, is suitable for large-scale PV energy systems.

Plasma generation by means of electrical discharge requires specialized power supply systems. The applicability of plasma for various plasma processes depends on its parameters, and these in turn depend on the parameters of the power supply systems. Arc plasma can be unstable, generating a lot of electromagnetic interference and overvoltage and overcurrent. The power system of a plasma reactor must guarantee good plasma control characteristics, be immune to disturbances and ensure good cooperation with the power grid. The article analyzes the cooperation of a three-phase plasma reactor, with gliding arc discharge, with a power supply system of a new type. This system integrates an AC/DC/AC converter with a five-column transformer of special design in a single device. Using the properties of magnetic circuits, it was possible to integrate the functions of ignition and sustaining the burning of the discharge in the reactor in a single transformer. Proper design of the transformer is crucial to achieve good cooperation of the AC/DC/AC converter with both the plasma reactor and the power supply network. The presented power supply design shows a number of positive features predisposing it to powering arc plasma reactors.

This article presents a comprehensive study on enhancing grid resilience through advanced forecasting and optimization techniques in the context of power outages. Power outages pose significant challenges to modern societies, affecting various sectors such as industries, households, and critical infrastructures. The research combines statistical analysis, machine learning algorithms, and optimization methods to address this issue to develop a holistic approach for predicting and mitigating power outage events. The proposed methodology involves the use of Monte Carlo simulations in MATLAB for future outage prediction, Long Short-Term Memory (LSTM) networks for forecasting solar irradiance and load profiles, and a hybrid LSTM-Particle Swarm Optimization (PSO) model to improve accuracy. Furthermore, the role of Battery State of Charge (SoC) in enhancing system resilience is explored. The study also assesses the techno-economic advantages of a grid-tied microgrid integrated with solar panels and batteries over conventional grid systems. The results highlight the potential of the proposed approach in strengthening grid resilience, reducing downtime, and fostering sustainable energy utilization.

Foundational and state-of-the-art anomaly detection methods through power system state estimation are reviewed. The traditional components for bad data detection such as chi-square testing, residual-based methods, and hypothesis testing are discussed to explain the motivations for recent anomaly detection methods given the increasing complexity of power grids, energy management systems, and cyber-threats. In particular, state estimation anomaly detection based on data-driven quickest change detection and artificial intelligence are discussed and directions for research are suggested with particular emphasis on considerations of the future smart grid.

A Savonius wind turbine is one of the simplest vertical-axis turbines. Several researchers have been attracted to it because of its simple structure, low noise, appropriate torque, and independence from wind direction. SR3345 and SR5050 blade profiles will be investigated for their effects on the performance of Savonius wind turbines. First, the fabricated wind turbine is placed in front of an open circuit wind tunnel with a velocity of 6 m/s. Furthermore, governing relationships are used to calculate power and torque coefficients as well as tip speed. In this study, the power and torque coefficients of the turbine are compared with the two profiles considered based on overlap ratios between 0 and 0.3. Despite its increased stability, the central shaft reduced the power coefficient of the turbine. For blade SR3345, the best performance occurs at tip speed ratios of less than 1, while for blade SR5050, the best performance occurs at higher tip speed ratios. Both blades SR3345 and SR5050 achieve the highest power coefficients at overlap ratios of 0 and 0.18 when a central shaft is present.

Cantilever beams are the most widely used form of strain-driven energy harvesting, which uses piezoelectric materials. Although researchers are constantly seeking improved power output from cantilever-beam-driven piezoelectric energy harvesters, a systematic and fundamental analysis of the effect of beam geometry on the power capacity of energy harvesters warrants further investigation. Most of the previous research accounts for beams that are fully coated with piezoelectric material. While a larger coating area increases energy output, it also escalates costs as piezoelectric materials are very expensive. Considering the high cost of piezoelectric materials when dealing with limited piezoelectric material, enhancing power output can be achieved by employing a larger base beam and coating a portion of it at the fixed end. As such, the aim of this work is to investigate a wide variety of cantilever beam shapes (e.g., trapezoidal, triangular, V-cut, concave, and convex) with partial piezoelectric material coating on the base beam to maximize the power output capacity of the harvester. To ascertain a comparable argument, the surface area, volume, and mass of all the considered beam shapes are kept consistent, as these parameters influence the power output of the harvester. The geometry of each shape is systematically varied to understand the effect of geometric configuration on the output power density. Finally, the power capacities of all types of beams are compared, and a design is proposed to obtain the maximum power output. It was found that when the surface area of both the beam and piezoelectric material is kept constant and piezoelectric material is located at the fixed end, a trapezoidal beam with a smaller base width and larger free end width is the most efficient in generating power as long as the structural integrity is maintained. The finding is completely opposite as was suggested by previous studies, which proposed that a trapezoidal beam with a smaller free end yields higher output. Instead, this study demonstrates that an inverted trapezoidal beam produced higher output, considering partial coating compared to the full beam coating used in previous studies. Additionally, a correlation is presented on how the beam resonance frequency shifts with variation in beam parameters.

This study aims to identify the model that best approximates the credit spread that should be fixed on debt instruments issued by both public and private companies, considering the particularities of the Mexican market. Five models were analyzed: Merton's [1], those proposed by Denzler et al., the one presented in this paper, which includes the conformable derivatives, taking as a reference the change of variable made by Morales-Bañuelos et al., and the Corporate Default Risk Model (DRSK) for Publics Firms of Bloomberg [4]. The required financial information was obtained from the Bloomberg platform, from which the probabilities of default, credit spreads, and credit ratings for each company in the sample under the model (DRSK) were extracted directly. Likewise, the program developed by Moody's K.M.V. was used to obtain the EDF (Expected Default Frequencies). It was concluded that the Modified Merton model approximates to a greater extent the credit spreads that fix on a prime rate on the loans granted to the Mexican non-financial companies.

The most important step for the installation of a wind farm is to know the wind regime in the region, since an error in estimating this wind speed causes an error proportional to the cube of power, resulting in financial losses for investors. Therefore, knowing the methods used for predicting wind speed becomes important and the knowledge of how research and studies in this area are going helps map the subject and outline strategies for developing research in strategic areas. For this purpose, the Scopus database was used considering some keywords, such as ("forecast" OR "prevision") AND "wind" AND ("turbine" OR "power" OR "energy" or "velocity" or "speed"), considering the period since 2019, and analyzing the data of the documents found using the Bibliometrix package. With the results found, it was possible to map researchers, institutions that are developing work in this area, in addition to the most cited articles, among other aspects analyzed.