This work utilizes the particle swarm optimization (PSO) for the optimal sizing of a solar – wind – battery hybrid renewable energy system (HRES) for a rural community in Rivers State, Nigeria (Okorobo-Ile Town). The objective is to minimize the total economic cost (TEC), the total annual system cost (TAC) and the levelized cost of energy (LCOE). A two – step approach is used. The algorithm first determines the optimal number of solar panels and wind turbines. Based on the results obtained in the first step, the optimal number of batteries and inverters is computed. The overall results obtained is then compared with results from the NGSA-II and hybrid GA – PSO optimization algorithm. An energy management system monitors the energy balance and ensures the load management is adequate using the battery state of charge as a control strategy. Results obtained showed that the optimal configuration consist of solar panels (154), wind turbine (3), inverter (136) and batteries (29). This results in a minimized TEC, TAC and LCOE of 476, 731USD, 301, 947USD and 0.011USD/kWh respectively. The optimal configuration when simulated under various climatic scenarios was able to meet the energy needs of the community irrespective of ambient condition.

This study provides a detailed numerical assessment of the productivity of single-slope solar stills across key cities in the Caspian region, including Aktau, Atyrau, Astrakhan, Makhachkala, Baku, Tehran, and Turkmenbashi. Employing a mathematical model based on heat balance equations and the 4th-order Runge-Kutta method, we simulated the distillation process under various climatic conditions. The results reveal that productivity is significantly influenced by geographic location and local meteorological conditions. Tehran demonstrated the highest productivity across all seasons, with values of 1.75 × 10³ kg/(m²·year) and an efficiency of 0.53, due to its optimal solar irradiation and ambient temperature. In contrast, Atyrau and Makhachkala exhibited lower productivity, particularly in colder months, highlighting the effect of ambient temperature on solar still efficiency. The analysis identified optimal water depth at 2 cm and insulation thickness between 4 and 9 cm for enhancing productivity in continental climates like Aktau. Additionally, the lowest cost of distilled water was $0.024 per kilogram in Baku. These findings align with existing literature, validating the numerical model's accuracy. Future research will explore integrating solar stills with other renewable and fossil fuel-based technologies.

Excess associated gas from unconventional wells is typically flared while excess produced water is injected underground. In this work, flare gas recovery is integrated with produced water desalination and a solar pre-heater. The solar module with a beam splitter preheats the produced water. Aspen Plus was used to perform process modeling as well as to estimate capital and operating costs. The Solar-Flare Gas RDcovery- desalination (Solar-FGRD) process can conserve water resources and reduce the brine injection by 77%. The accompanying solar farm results in excess solar electricity for exporting to the grid. The process burner combustion efficiency (CE) is 99.8% with the destruction and removal efficiency (DRE) of 99.99% for methane as opposed to the flare CE of 80-98% (and a methane DRE of 91-98%). The greenhouse gas (GHG) emissions for CO2 and methane in terms of CO2 equivalent (CO2e) can be reduced by 45 % for US North Dakota & Texas flaring and 13% for North Sea flaring by employing the Solar- FGRD process. The comprehensive financial analysis demonstrates the financial-economic feasibility of the investment project with or without tax credits. Best-case and worst-case scenarios provide a realistic range that investors can consider before making investment decisions.

In order to enhance the efficiency of direct absorption solar collectors, this study carried out an experimental analysis about the optical and photothermal conversion performance of Fe3O4, ATO and Fe3O4/ATO nanofluids with total concentration of 0.1wt%. According to the results of experiments, Fe3O4 nanofluid outperform ATO nanofluid in terms of optical absorption; nevertheless, at wavelengths shorter than 600 nm, it also shows significant scattering reflection. The solar-weighted absorption coefficient of Fe3O4/ATO nanofluid rose from 0.863 (mFe3O4mTotal= 0.2) to 0.932 (mFe3O4mTotal= 0.8) when the optical path length increased from 0.01 m to 0.06 m. Additionally, the photothermal conversion efficiency of Fe3O4/ATO hybrid nanofluid was attained 0.932 at (mFe3O4mTotal= 0.2), above the 0.892 and 0.898 photothermal conversion efficiencies recorded for 0.1 wt% ATO and Fe3O4 nanofluids, respectively. When present together, the opposing optical characteristics of Fe3O4 and ATO boost photothermal conversion performance, which is anticipated to raise the efficiency of direct absorption solar collectors.

The growing demand for clean energy transitions has become increasingly significant, with solar energy emerging as one of the most prominent clean energy resources contributing to this effort. However, there remains limited knowledge regarding the economic feasibility of solar project development across different geographic locations and scales. This study introduces a comprehensive economic analysis framework to assess the economic viability of residential and utility-scale solar projects, using California, Tennessee, and Texas as case studies. The economic assessment is conducted through a cost-benefit analysis that adopts a full life-cycle approach, encompassing phases from permitting to demolition for both scales of solar projects. We found that utility-scale solar projects generally offer more favorable investment return ratios compared to residential projects, despite the absence of land acquisition costs and lower initial capital expenditures for the latter. Furthermore, the incorporation of energy storage solutions, such as Battery Energy Storage Systems (BESS), is shown to be essential for improving the efficiency of residential solar energy usage, with efficiency gains of up to 50%. Finally, region-specific strategies, including net metering policies, electricity retail market structures, and the promotion of solar adoption, play a crucial role in enhancing the financial viability of solar projects for both residential and utility scales.

The month of May 2024 was characterized by solar energetic particles events directed towards the Earth, especially the big event causing a strong terrestrial geomagnetic storm during the night from 10 to 11 May 2024, with auroras observed everywhere in Europe. This was the strongest storm for the last 20 years with a Dst < -400 nT. In the present work, we show with observations of GOES, PROBA-V/EPT and MetOP/MEPED that this exceptional event was associated with the injection of energetic protons in the proton radiation belt, with important consequences for the South part of the South Atlantic Anomaly (SAA). In addition, the geomagnetic storm caused by the solar eruption has had tremendous impacts on the electron radiation belts. Indeed, we show that for 0.3 to 1 MeV electrons, the storm led to a long lasting four belts configuration which was not observed before with EPT launched in 2013, until a smaller geomagnetic storm on June 15 took place. Moreover, for the first time since its launch, observations of the EPT show that ultra-relativistic electrons with E>2 MeV have been injected into the inner belt until L=2.4, violating the impenetrable barrier previously estimated to be located at L=2.8.

The study addresses the fabrication of indium aluminum nitride (InAlN) layers by DC co-sputtering at room temperature, highlighting their potential in optoelectronic and solar cell applications. Experiments were carried out with different powers for the aluminum target, observing changes in the stoichiometry and material properties. XPS and AES analysis confirmed the variation in indium and aluminum concentration, directly affecting bandgap and electrical properties such as mobility and free carrier concentration. The layers showed smooth surfaces with low roughness, suitable for high efficiency interfaces. This method promises to reduce costs and improve the accessibility of efficient solar technologies based on InAlN semiconductor alloy.

Dye-sensitized solar cells (DSSCs) belong to the group of thin-film solar cells which have been extensively researched for over two decades due to their low cost of fabrication, flexibility and ability to function under low-light conditions. Some issues have to be addressed in terms of energy losses, material integration, weak photocurrent generation and stability to improve the performance of DSSCs. One of the approaches to enhance the performance of DSSCs is through luminescent materials. These are materials which can absorb light and re-emit at different wavelengths which can be used to convert ultraviolet (UV) and near infra-red (NIR) light that are not efficiently utilized by the DSSCs, into visible light that can be absorbed. The main objective of this article is to provide a comprehensive review on the impact of luminescent materials in DSSCs. Research interest in luminescent materials particularly, down conversion, up conversion and quantum dots were analyzed from the “Web of Science”. It reflected a remarkable number of over 200, 000 publications in the past decade. Therefore, the state of the art of luminescent materials for enhancing the performance of the solar cells were reviewed, which showed significant potential in enhancing the performance of DSSCs.

Dry Fish is a rich source of proteins and nutrients and can be eaten in many forms. Oman is one of the important fish producers in the world and having high demand in neighboring countries for Oman’s fish. Fishery sector is considered as one of the important economic development sector in sultanate of Oman. In the fishery sector, use of technology is not up to the mark because of less awareness of technology application among Omani fishermen. Also, there is a demand for a greater number of cold storages in different regions to store fresh fishes which is not materialized yet. Similarly, there is a demand of perfect and cheap technology in Oman to dry fishes to improve the profit to the fishermen. Solar energy is abundantly available in Oman and there are high possibilities in Oman to use solar energy in domestic and industrial applications. Since the sunlight is available throughout the year, it is possible to convert in to thermal energy or electrical energy. Electricity can be produced from photovoltaic principle (PV) or indirectly with concentrated solar power. Similarly, we can use solar concentrators for many thermal applications. The solar dryer is a device which is used to dry fruits, vegetables, leaves, clothes etc. If any of the items are dried with the help of solar energy, then we can save lot of non-renewable source of energy and can help to improve economy of the country. The sun can, at least seasonally at Oman’s latitudes, provide a substantial part of the energy needed for various applications. In this work, we used solar dryer to make dry fish with high quality. Use of parabolic type concentrator to dry the fish is an effective solution which is an innovative idea to the fishermen. The temperature variation in dryer is directly proportional to the intensity of solar. The tracking mechanism is a combination of electronic and mechanical design which tracks the sun automatically. In this work, a parabolic concentrator with automatic tracking mechanism was designed and the performance analysis have been done. In the design, copper tubes are used for heat transfer and then the hot fluid is circulated in the box which is used to dry the fishes. As per the experiment, fish drying efficiency obtained from solar dryer is 77.9% and it took 3 days to dry king fish of 20kg. There are many advantages in parabolic type solar concentrators relate to the quality of dryness in the fishes and time taken to dry the fishes which are elaborately discussed in this paper. This solar dryer technology will improve green environment and also will save non-renewable sources of sultanate of Oman for longer period of time.

The amount of solar energy produced is directly proportional to the surface area of solar panels exposed to sun rays. To increase the productivity of solar panels, a number of techniques are proposed by curving the surface or protruding the panel surface to maximise the surface area, e.g. Protruding panel surfaces with shapes such as pyramidal, cone, spherical cap, sinusoidal wavy curve, etc. These techniques are analysed to determine whether the panel surface area increases. The geometrical design analysis showed that, depending on the chosen surface curving method, the panel can achieve a remarkable increase in surface area.The system advisor model was used to assess a sample of solar cells with standard measurements of 6 by 6 inches that were organised in a zigzag pattern with different angles of inclination (10°, 15°, 20°, 25°, 30°, and 35°). Overall, the maximum power pump and annual AC energy performance increase by 1.4%, 4.2%, 6.8%, 10.8%, 14.9%, and 21.6%, respectively, over a one-year period of productivity. However, by applying the concept of solar panel efficiency degradation due to tilting solar panels at an angle by Mamun et al. (2022), for each 5° increase in tilt angle beyond the ideal 10°, the efficiency decreases by approximately 0.76%. In conclusion, the overall efficiency is greater than that of standard flat solar panels, provided the tilt angle is within a reasonable range.

In 1944 the architect Antonio Gómez Davó designed and built a new house for Mr. Ferrer at Rocafort in the suburbs of Valencia (Spain). In this same year, Europe, America, Russia and even Japan were still at war and Spain was only recovering from its own intestine conflict. Therefore, architectural innovations and influences were scarce as was the circulation of specialized journals on the matter. But in many creations, like the ceramic vaults and the brise-soleil, Le Corbusier himself had declared his profound nostalgia from the Mediterranean, a Sea that he had come to appreciate in his travels to the “orient”. In the case of Gómez Davó, having been born and raised in a prominent family of Valencia he could not remain indifferent to the design features that appeared in the vernacular architecture of the area, specially the type of inclined louvers of Arabic descent, that covered bow-windows and balconies and which have come to be known in Spain as the Majorcan louvers; nowadays even employed by Rafael Moneo for instance at the extension of the Painter Miro Foundation. However, with so many difficult circumstances surrounding him, Gómez Davó could not get to the point of producing a ground breaking design based on solar assumptions for the whole façade of the building, instead when providing an entrance porch apt for spending life, meals and well deserved rest hours outdoors in the pure Mediterranean tradition, he ventured to construct a surprising perforated wall oriented to the South in order to control radiation in winter and provide shade in the summer while affording excellent light and superb conditions of ventilation. By means of our own devised simulation tools we have analyzed the conditions of the house and especially of such innovative brise-soleil at times reminiscent of Alvar Aalto solutions for day-lit roofs, which he was aware intuitively and by his own incipient study of solar geometry, that needed adaptation from so distant latitudes as Finland and Valencia. By outlining such unknown and bold precedent we contribute to revitalize the early and daring pioneers of solar architecture in peripheral Spain and Europe, at the birth of critic regionalism, a fact often disregarded in conventional history of Modern Architecture.

A medium scale household in South Africa consumes about 1000 kWh on average, and ae household spend about 3000 ZAR per month on energy supply using grid electricity. Grid electricity. South Africa’s energy is supplied by a huge governmental organization. Statistical analyses indicate that projected increase of the cost of grid electricity in South Africa is about 30% per annum for the next five years. Our research show that Photo-Voltaic (PV) technology can offer a viable alternative, provided a large initial capital outlay can be made. The technology is user-friendly and easy to operate. It is calculated that the cost of electricity, capitalized over 20 years, considering an 80 % supply of needs and assuming 20 sunny days per month, is about 2.80 ZAR. The study also shows that utilizing a hybrid combination of renewable energies, such as combining PV supply with solar thermal energy absorbers, and converting thermal energy to electricity, as energy supply systems, could reduce the current cost of electricity per household in South Africa to about half of national grid supply prize, R1,50 per kWhr. The study also shows that water provides as a most viable medium to store energy, instead of using expensive battery technology to perform such functions.

The artificial solar saltwork fields of Hon Khoi are important industrial and biodiversity resources in southern Vietnam. Most hypersaline environments in this area are characterized by saturated salinity, nearly neutral pH, intense ultraviolet radiation, elevated temperatures and fast desiccation processes. However, the extreme halophilic prokaryotic communities associated with these stressful environments remain uninvestigated. To fill this gap, a metabarcoding approach was conducted to characterize these communities by comparing them with solar salterns in northern Vietnam as well as with Italian salterns. Sequencing analyses revealed that the multiple reuses of crystallization ponds apparently create significant perturbations and structural instability in prokaryotic consortia. However, some interesting features were noticed when we examined the diversity of ultra-small prokaryotes belonging to Patescibacteria and DPANN Archaea. Surprisingly, we found at least five deeply branched clades, two from Patescibacteria and three from DPANN Archaea, which seem to be quite specific to Hon Khoi saltwork fields ecosystem and can be considered as a part of biogeographical connotation. Further studies are needed to characterize these uncultivated taxa, to isolate and cultivate them, which will allow us to elucidate their ecological role in these hypersaline habitats and to explore their biotechnological and biomedical potential.

Background: Many risk-modifying factors affect cancer incidence and mortality rates. Solar UVB reduces cancer risk by producing vitamin D, which has many mechanisms to reduce risk of cancer incidence, progression, and metastasis. Obesity increases cancer risk through several mechanisms, including increased inflammation. Method and Materials. We present an ecological study (a type of observational study) of incidence and/or mortality rates for cancers during 2007–2016 of 17 anatomical sites with respect to solar ultraviolet-B (UVB) doses and obesity prevalence. Data were averaged for 12 geographical regions. Results: Solar UVB doses were significantly inversely correlated with incidence rates for three types of cancer for males. They were inversely correlated with mortality rates for five cancers for males and four for females. Obesity prevalence was directly correlated with mortality rates for three cancers for males and seven for females. Discussion: The ecological approach has certain limitations, such as its sensitivity only to regional variations in relation to specific risk-modifying factors. In this study, these limitations include numerous factors influencing cancer risk and the fact that the data are averaged across entire regional populations, which may not reflect individual risks. Despite this, the study reveals important correlations. Specifically, it found that solar UVB exposure is linked to a lower risk of certain cancers, while obesity is associated with an increased risk of some cancers in France. These findings are consistent with results from a similar study in the United States on cancer rates between 2016 and 2020. The association between obesity and cancer risk aligns with other observational studies. However, it is uncertain to what extent higher solar UVB exposure or elevated serum 25-hydroxyvitamin D levels might mitigate the impact of obesity on cancer risk. Reducing cancer mortality in France may be achievable through vitamin D supplementation and efforts to lower obesity prevalence.

The development of solar energy on a regional scale necessitates a thorough understanding of available resources. Cuba, facing prolonged economic, environmental, and energy crises, urgently needs to enhance its sustainability through solar energy. While solar resource mapping is widespread, Cuba lacks extensive field measurements, often relying on models that may not be ideally suited for large regions like Matanzas province. Spanning over 12,000 km² with nearly 150 km between its northern and southern extremes, Matanzas presents challenges for high-resolution solar mapping. This study introduces a methodology that integrates various methods and databases to achieve maximum resolution in the resulting solar map. The approach is designed for large areas where conventional high-resolution models fall short. By optimizing calculation times and parameterizing the entire surface latitudinally, a high-resolution solar resource map for Matanzas has been developed. This map significantly enhances the understanding of solar resources in Cuba and proposes new methodologies for analyzing solar potential in similarly large regions.

Psoriasis is a multifactorial, chronic, and inflammatory disease that severely impacts patients’ quality of life. The disease is caused by genetic irregularities affected by the epigenetic and environmental factors. Some of these factors may include the seasonal changes, such as solar radiation, air pollution and humidity, and changes in circadian rhythm, especially in the temporal and polar zones. Thus, some psoriasis patients report seasonal variability of symptoms. Through a comprehensive review, we aim to delve deeper into the intricate interplay between seasonality, environmental factors, and the genetic and epigenetic landscape of psoriasis. By elucidating these complex relationships, we strive to provide insights that may inform targeted interventions and personalized management strategies for individuals living with psoriasis.

It’s very well known that the world's attention is currently focused on the energy transition. The energy security, in addition to the drive to reduce greenhouse gas emissions in order to limit global warming, and the generalization of the access to energy, have contributed to adoption of the Moroccan Energy Strategy with a strong focus on Renewable Energies (RE). Morocco is notoriously poor in conventional fossil primary energy resources with an energy dependence on the order of 90%. The energy crisis and that resulted from Covid-19 pandemic and the geopolitical conflicts, combined compounded with steady increase in demand have heavily affected the security and the stability of the country's energy situation. The transition to RE, by strongly engaging in the implementation of several solar, wind and hydro energy projects benefiting from the country's excellent solar and wind energy potential, has made the country the leader in RE in Africa. By 2030, the share of RE in the installed capacity is expected to reach 52%. In this work, an overview of the current situation of RE (particularly solar energy) in Morocco is provided, including, the potentials, obstacles and challenges, and future perspectives. Thanks to its high solar potential location, it’s predictable that Morocco effort will be focused on this field: the Erasmus Plus Innomed Project is a virtuous example of international cooperation, aiming at create a Solar Energy Network, in synergy with EU Partners.

Jordan is classified as a low- to-middle-income, in which the primary energy sources are imported crude oil and natural gas. The energy expenses represent a high percentage of the country's GDP. Meanwhile, due to its geographical location and its climate, Jordan ranks very high among the world countries with respect to solar energy exploitation potential. Therefore, solar energy is a key resource that can be utilized to significantly improve both the country’s economy and energy security. It has to be highlighted that Jordan focus on a network dedicated to solar energy and it has to be mentioned the Erasmus Plus INNOMED Project based on virtual classrooms, which aims to promote innovative technologies and applications of solar energy in MENA Countries. This paper presents an overview of the solar energy resources in Jordan that includes: the current situation, the potential, and future expectations.

Lotions with or without 28% ascorbyl glucoside arginine complex (AGAC) were applied twice daily for 24 weeks in a double‐blind half‐face study of 27 Japanese females with solar lentigos (SLs). Pigmentation scores were evaluated using a photo‐scale and skin colors were assessed using a color difference meter and a Mexameter. Treatment with the test lotion elicited a significant decrease in pigment scores at 24 weeks compared to week 0; with a significant decrease in pigment scores at 24 weeks compared to the placebo lotion‐treated SLs. In the test lotion‐treated SLs; the L values and melanin index (MI) significantly (p<0.0001) increased and decreased; respectively; at 12 and 24 weeks of treatment compared to week 0. Comparisons of increased L (△L) values or decreased MI (△MI) values between test and placebo lotion‐treated SLs demonstrated that the test lotion‐treated SLs had significantly higher △L or △MI values than the placebo lotion‐treated SLs both at 12 and 24 weeks of treatment. The sum of our results strongly indicates that AGAC is distinctly effective in ameliorating the hyperpigmentation levels of SLs at a visibly recognizable level by the subjects without any hypo‐pigmenting effects or skin irritation.

Electric mobility is a global trend and necessity, with electric and solar boats offering a promising alternative for transportation electrification and carbon emission reduction, especially in the Amazon region. This study analyzes the system of a solar boat from the SIMA project, to be implemented at UFPA, using MATLAB software for modeling. The Simulink tool was utilized to model the system, focusing on operational parameters such as module voltage, converter voltage, and speed. Results indicate that the solar boat's operational cost is significantly lower compared to a similar internal combustion model, considering diesel's high consumption and cost. The environmental impact is also reduced, with nearly 72 tons of CO2 emissions avoided annually, thanks to Brazil's renewable energy matrix. Simulations confirmed the project's parameters, demonstrating the efficiency of digital twin technology in monitoring and predicting system performance. The study underscores the importance of digital twins and renewable energy in promoting sustainable transportation solutions, advocating for the replication of such projects globally. Future research should focus on further advancing digital twin applications in electric mobility to enhance predictive maintenance and operational efficiency.

The transition to renewable energy sources is critical for sustainable development, particularly in rural regions with limited access to electricity. Solar-powered microgrids offer a promising solution for rural electrification by providing reliable, clean energy that can enhance economic opportunities and improve quality of life. This paper presents a techno-economic analysis of solar-powered microgrids for rural areas, evaluating their feasibility, costs, and benefits. The analysis encompasses technological aspects, such as solar panel efficiency, battery storage, and grid management, alongside economic factors including initial investment, maintenance costs, and potential returns. Additionally, the study assesses the social impact of solar-powered microgrids, exploring their effects on local communities, including improvements in education, health, and economic activities. The findings indicate that solar microgrids can be a viable and impactful solution for rural electrification, with significant long-term benefits for both economic development and social well-being.

An energy production system consisting solar collector, biogas dry reforming reactor and solid oxide fuel cell (SOFC) was assumed to be installed in Kolkata, India. This study aims to understand the impact of climate condition on the performance of solar collectors with different lengths of parabolic trough solar collector (dx) and mass flow rate of heat transfer fluid (m). In addition, this study has evaluated the amount of H2 produced by biogas dry reforming (GH2), the amount of power generated by SOFC (PSOFC) and the maximum possible households (N) whose electricity demand could be met by the energy system proposed, considering the performance of solar collector with the different dx and m. As a result, the optimum dx was found to be 4 m. This study revealed that temperature of heat transfer fluid (Tfb) decreased with the increase in m. Tfb in March, April and May was higher than that in other months, while Tfb from June to December was the lowest. GH2, PSOFC and N in March, April and May were higher than that in other months irrespective of m. The optimum m was 0.030 kg/s.

The technical feasibility of solar photovoltaic (PV) direct current (DC) nanogrids are well-established, but the components of nanogrids are primarily commercially focused on alternating current (AC)-based systems. Thus, DC converter-based designs at the system level require personnel with high degree of technical knowledge and this results in high costs. To enable a democratization of the technology by reducing the costs this study provides a novel modular plug-and-play open source DC nanogrid. The system can be customized according to consumer requirements, enabling the supply of various voltage levels to accommodate different device voltage needs. The step-by-step design process of the converter, controller, data logger, and assembly of the complete system is provided. A time-domain simulation and stability analysis of the designed system were conducted in MATLAB/Simulink as well as experimental validation. The results show transforming the nanogrid from a distribution network to a device makes it suitable for various user-specific applications, such as remotely supplying power to campsites, emergency vehicles like ambulances, and small houses lacking grid electricity. The modular DC nanogrid includes all the features available in a DC distribution network as well as data logging, which enhances the user experience and promotes the use of solar-powered DC grid systems.

The integration of solar energy systems with agricultural practices, known as agrivoltaic systems, presents a promising solution for advancing sustainable food and energy production. This approach involves installing photovoltaic panels on agricultural lands, which allows for simultaneous crop cultivation and energy generation. Agrivoltaic systems offer a dual benefit: they enhance land use efficiency by utilizing the same area for both solar power generation and crop production, and they contribute to sustainable energy transitions. This abstract explores the benefits and challenges associated with agrivoltaic systems. Key advantages include increased land productivity, reduction in water usage due to shading effects, and potential economic gains from dual income streams. Furthermore, these systems can mitigate land use conflicts by combining food production with renewable energy generation. However, there are challenges to address, including the potential for decreased crop yields under solar panels, the need for appropriate system design to balance energy generation and agricultural needs, and the economic feasibility of initial investment and maintenance. The integration of agrivoltaic systems represents a critical step toward achieving sustainable development goals by promoting environmental stewardship and resource efficiency. Future research and advancements in technology are essential to optimize system performance and maximize benefits for both agriculture and energy sectors.

Perovskite-silicon tandem solar cells represent a significant advancement in photovoltaic technology, aiming to overcome the efficiency limitations of traditional silicon-based solar cells. This paper explores recent developments in the fabrication and optimization of these tandem cells, focusing on improving both efficiency and long-term stability. The combination of perovskite materials with silicon allows for broader spectrum absorption, which enhances the overall power conversion efficiency. Key strategies include optimizing the perovskite layer's composition, improving the interface between layers to reduce recombination losses, and incorporating advanced encapsulation techniques to mitigate degradation from environmental factors such as moisture and UV exposure. The review also highlights the challenges faced in scaling up production while maintaining high performance and stability. Emerging trends in material engineering and device architecture are discussed, providing insights into future directions for making perovskite-silicon tandem solar cells a viable commercial technology. This study underscores the potential of these hybrid systems to significantly boost the efficiency of photovoltaic systems, offering a promising pathway towards more sustainable and costeffective solar energy solutions.

Solar radiation corresponds to fundamental parameters for solar photovoltaic (PV) technology. Reliable solar radiation prediction became valuable to design solar PV systems, performance, operatively efficient planning, safety operation, grid dispatch and financial characteristics. However, high quality ground-based solar radiation measurements are scarce, especially for very short-term time horizon. Most of the existent studies trained the machine learning (ML) model used dataset with time horizon of 1-hour or day, very fewer studies have been reported using a dataset with a 1-mitute time horizon. In this study, a comprehensive evaluation of nine ensemble learning algorithms (ELA) is performed to estimate the solar radiation in Santo Domingo with a 1-minute time horizon dataset collected from a local weather station. The ensemble learning evaluated included seven homogeneous ensembles; Random Forest (RF), Extra Tree (ET), Adaptive Gradient Boosting (AGB), Gradient Boosting (GB), Extreme Gradient Boosting (XGB), Light Gradient Boosting (LGBM), Histogram-based Gradient Boosting (HGB) and heterogeneous ensemble named as Voting and Stacking. RF, ET, GB, HGB were combined to develop Voting and Stacking and Linear Regression (LR) was adopted in the second layer of the Stacking. Five technical metrics, Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE) and Coefficient of Determination (R2) were used as criteria to determine the prediction quality of the developed ensemble algorithms. Comparison of the results indicates that the HGB algorithm offers superior prediction performance among the homogeneous ensemble learning and overall, the Stacking provides the best accuracy with metric values of MSE=3218.27, RMSE= 56.73, MAE=29.87, MAPE=10.60, R2=0.964.

The efficiency of organic solar cells (OSCs) is influenced by various factors, among which environmental temperature plays a significant role. Previous studies have shown that the thermal stability of these cells can be enhanced by incorporating a third component into their structure. Ternary organic solar cells, in particular, have shown promising results in improving thermal stability. A well-designed electron transport layer (ETL) can significantly bolster thermal stability by facilitating efficient charge transport and reducing charge recombination. In this study, we investigated the effect of temperature on the efficiency of inverted ternary structures, ranging from 300 K to 400 K. The structures examined include FTO/SnO2/PM6:D18:L8-BO/PEDOT: PSS/Ag, FTO/Spiro-OMeTAD/PM6:D18:L8-BO/PEDOT: PSS/Ag, and FTO/PC60BM/PM6:D18:L8-BO/PEDOT: PSS/Ag. Through simulations employing three different electron transport layers—SnO2, Spiro-OMeTAD, and PC60BM—we observed that at 340 K (65°C) these structures maintained 92% of their original high efficiency of ~20% at 300 K, which represents a high level of thermal stability under the high PCE condition.

Renewable energy especially insights into solar energy are crucial in the energy business cycle. In this paper, an impact study of meteorological variables on solar energy production is conducted. The paper discusses the pipeline of data analysis specific to the case study and exploits open-source machine-learning algorithms to build predictive models. RandomForestRegressor and XGBoosting regressors are used to build the predictive model. The application code is integrated into an analytic software service (Power BI) and tested on Solar energy Open Data of Saudi Arabia. The solar energy production is found to be high between 800-1000 barometric pressure locations. Global Horizontal Irradiation is found to increase when the atmospheric temperature is more than 34∘ C. The impact of relative humidity is that the produced energy is high at lower humidity points. The wind speed effect is that the produced energy is significant between 2 to 4 m/s and reaches its maximum at 2.4 m/s. The predictive models produce nearly real-time predictions with Random Forest with R²: 0.909. The paper provides Global Horizontal Irradiation estimation equations using meteorological coefficients generated by the trained regressor. The paper presents implementation methodologies and records various instances of test results. It highlights the efficacy of machine learning in predictive modeling for renewable energy applications.

Alpha emitters like plutonium pose severe health risks when ingested, damaging DNA and potentially causing cancer. Traditional detection methods require proximity within millimeters of the contamination source, presenting safety risks and operational inefficiencies. Long-range detection through alpha radioluminescence (RL) offers a promising alternative. However, most of the previous experiments have been carried out under controlled conditions that preclude the overwhelming effect of ambient light. This study demonstrates successful detection of a 3 MBq alpha emitter in an open environment using a newly developed, lightweight compact alpha camera. This camera incorporates a deep-cooled CCD and a specially designed lens system with a low f-number to maximum the signal intensity. The lens was also designed to minimize blue shift effects of filters. Nighttime imaging was achieved with a dual-filter system using a sandwich filters assembly centered at 337 nm and 343 nm for capturing alpha RL and subtracting background light, respectively. At night, the alpha source was detected from 1 meter away within one minute. The system was also evaluated under simulated urban lighting conditions. For daytime imaging, a stack of tilted 276 nm short pass filters minimized sunlight interference, enabling clear detection of the alpha source at 70 cm within 10 minutes under indirect sunlight. This research not only underscores the viability of long-range optical detection of alpha emitters for environmental monitoring and scientific research but also highlights its ability to enhance nuclear safety and public health in real-world settings.

The effect of doublet state metalloradical complex in a solar cell inside the common active layer poly(3-hexylthiophene)/ [6,6]-phenyl-C61-butyric acid methyl ester (P3HT/PC60BM) is explored. In this work is demonstrated that the role of the Bis-[1,3-Bis-(2,6-diisopropylphenyl)-4,5-dichloroimidazol-2-ylidene]palladium(I) hexafluoridophosphate dopant, [Pd(IPrCl)2][PF6], is crucial because, by having a stable unpaired electron in the molecule, it significantly improves the optoelectronic performance of the devices. We found the optimal concentration of this molecule in the active layer, and we demonstrated that the presence of this additive in the active layer helps to significantly improve the morphology of the device. The improvements in optoelectronic and morphological parameters are associated with a remarkable increase of photocurrent generation due to more favourable mechanisms of charge separation at the donor/acceptor (D/A) interfaces of the active layer and reduced recombinations. Moreover, the presence of this additive improves the stability of the unencapsulated solar cell against photochemical degradation produced by sunlight.

This paper focuses on distributed generation (DG) controller of a PV based Micro Grid. An independent DG controller (IDGC) is designed for PV applications to improve maximum power point tracking (MPPT) in Micro Grid (MG). Extreme learning machine (ELM) based MPPT method exactly estimate the reference input of converter control. They are voltage and current at MPP. Feedback controls employ linear PI schemes or nonlinear, intricate techniques. Here the converter controller, IDGC is improved by measuring directly converter outputs like duty cycle. PWM index in a single DG PV-based MG. It introduces a fast learning Extreme Learning Machine (ELM) using Moore-Penrose pseudo-inverse and an online-sequential ridge re method for robust CR estimation. The approach ensures the stability of the microgrid during PV uncertainties. Internal DG control approach (IDGC) improves the strength of the Micro Grid during, three-phase faults at load bus, partial shading, irradiance change, islanding operation and load change. The model is designed and simulated in MATLAB/SIMULINK platform and some of the results are validated in hardware in simulation (HIL) platform.

Green hydrogen is a fuel that in the coming years will play a very important role in the energy transition process in developed countries, especially those seeking to reach a level of zero emis-sions, for which reason its demand is expected to increase significantly. This article analyzes the fundamentals to produce hydrogen, with a focus on the oxidation reaction of a thermochemical solar cycle for the dissociation of water vapor. Solar thermochemical cycles have been extensively investigated, but it is still in the development stage by groups of researchers who have focused on finding the right materials and conditions to improve the efficiency of the process, especially at high temperatures. The theoretical foundations are analyzed, compiled from exhaustive scientific investigations related to the oxidation of iron in water vapor, the relationship with the activation energy of the corrosive process, thermodynamic aspects and the kinetic model according to a heterogeneous reaction. In addition, some high temperature oxidation mechanisms, pH effects, reactors and materials (fluidized beds) used are presented. The scientific review indicates that the production of hydrogen through a thermochemical cycle is more efficient than electrochemical processes (electrolysis), if the limitations of the reduction stage of the cycle are overcome.

We present an analysis of high-resolution, near-infrared (NIR) spectra relative to the solar transit of Venus of 5-6 June 2012, as observed with the Facility Infrared Spectropolarimeter (FIRS) at the Dunn Solar Telescope in New Mexico. These observations offer the unique opportunity to probe the upper layers (between ∼84 and 150 km in altitude) of a thick, CO2-dominated atmosphere with the transmission spectroscopy technique – a proxy for future studies of highly-irradiated atmospheres of Earth-sized exoplanets. We were able to visually identify absorption lines from the two most abundant CO2 isotopologues, and from the main isotopologue of CO in the retrieved spectrum of Venus. Furthermore, we perform a cross-correlation analysis of the transmission spectrum using transmission templates generated with petitRADTRANS. With the cross-correlation technique, it was possible to confirm detections of both CO2 isotopologues and CO. Additionally, we retrieve a cross-correlation signal for O3 on Venus. We demonstrate the feasibility of high-resolution, ground-based observations to study the chemical inventory of planetary atmospheres, employing techniques commonly used in exoplanet characterization.

Hydrogen has emerged as a promising energy carrier, offering a viable solution to address our current global energy demands. Solar energy stands out as a primary source of renewable power and has the potential to produce hydrogen through the utilization of solar cells. The quest for efficient, durable, and cost-effective photocatalysts is imperative for the advancement of solar-driven hydrogen generation. Copper slag, a by-product stemming from copper smelting and refining processes, primarily consists of metal oxides like hematite, silica, and alumina. This composition renders it a compelling secondary resource for deployment as a photocatalyst, thereby diverting copper slag from landfills. This review aims to comprehensively examine copper slag as a photocatalytic material, exploring its chemical, physical, photocatalytic, and electrochemical properties. Furthermore, it assesses its suitability for water treatment and its potential as an emerging material for large-scale solar hydrogen production.

The daily path of the Sun across longitude yields night and day, but the Sun also travels across latitude on a belt 47° wide. The Sun meridian declination explains the annual budget of natural beam irradiance (NBI), which is the irradiance delivered to the Earth’s surface as a normal projec-tion from the Sun. Data for the sun meridian declination data were obtained from the geometric model. The distribution of NBI was weighed between the Tropics of Cancer and Capricorn. The variation patterns of the solar declination conform to the dynamics of pendular motion. The joint distributions of velocity or acceleration of meridian declination against declination fit circular graphs. The NBI budget fluctuates in inverse proportion to the velocity of declination, yielding 18 sun-paths per degree for latitudes above 20°, and 6 sun-paths per degree for latitudes under 20°. All sites of the planet, whose latitude coincide, whether within or between hemispheres, accumu-late an equivalent budget of NBI.

In the present investigation, the crank-slider and crank-rocker off-center mechanisms are used to control 1-DOF in a solar tracker focused on improving the conversion of solar to electrical energy. Likewise, the kinematic equations of these mechanisms are presented that allow us to know their operating pattern in the work range of the follower and their comparative analysis between them. Finally, the scale construction with 3D printing is shown to verify the functionality of each 4-bar system.

A low cost, scalable and robust process has been proposed as innovative method for coating solar mirrors with a self-cleaning, transparent in the full solar range and versatile material based on auxetic aluminium nitrides, previously obtained on the laboratory scale. This work presents the scaling-up of fabrication process from laboratory to prototypal scale and pre-liminary results of outdoor self-cleaning solar mirror prototypes testing in the demonstrative CSP plant ENEASHIP located in Casaccia (Rome) ENEA research centre. Prototypes 50x40cm have shown stability in external conditions: no degradation occurs during the test campaign. Their washing restores the initial reflectance affected by soiling and the self-cleaning performance allows the utilization of a reduced quantity of water for cleaning operations with respect to uncoated glass of back surface mirrors. A similar self-cleaning AlN coating could be utilized on other solar components affected by soiling, such as glass envelopes of heat collecting elements, PV panels and everywhere are required self-cleaning performance combined to optical ones.

Quantum machine learning applications have become viable with the recent advancements in quantum computing. Merging ML with the power of quantum computing holds great potential for data-driven decision-making, as well as the development of more powerful models capable of handling more complex datasets with faster processing time. This area offers potential for improving the accuracy of real-time forecasting renewable energy production. However, the literature on this topic is sparse. Addressing this knowledge gap, this study aims to design, implement, and evaluate the performance of a quantum neural network forecast model for solar irradiance up to 3-hours ahead. The proposed model was compared with Support Vector Regression, Group Method of Data Handling, and Extreme Gradient Boost classical models. Using the best quantum neural network configuration found, the proposed framework could provide competitive results when compared to its competitors, considering forecasting intervals of 5- to 120-minutes ahead, where it was the fourth best-performing paradigm. For 3-hours ahead predictions, the QNN was able to overcome its clas-sical counterparts, but the XGBoost. This fact can be an indication that the quantum model may identify and retrieve relevant spatiotemporal information from the input dataset in such a manner not attainable by the current classical approaches.

Color change is the most obvious characteristic of tomato ripening stage and an important indicator of tomato ripening condition, which directly affects the commodity value of tomato. To visualize the color change of tomato fruit in mature stage, a gated recurrent unit network with an encoder-decoder structure that dynamically simulates tomato growth and development with time-dependent lines using tomato color and shape as real-time data was proposed in this paper. Firstly, the .json file was converted into a mask.png file, the tomato mask was extracted, and the tomato was separated from the complex background environment, and the tomato growth and development data set was successfully constructed. Then, a network of gated recurrent units with encoder-decoder structure was constructed to predict the future growth trend of tomato under different greenhouse temperatures. The experimental results showed that for the gated recurrent unit network of encoder-decoder structure proposed, when the hidden layer number was 1 and hidden layer number was 512, a high consistency and similarity between the model predicted image sequence and the actual growth and development image sequence would be realized, and the structural similarity index measure was 0.746. It was proved that when the average temperature was 24.93℃, the average soil temperature was 24.06℃, and the average light intensity was 11.26 Klux, the environment was the most suitable for tomato growth. The environmental data-driven tomato growth model was constructed to explore the growth status of tomato under different environmental conditions, thus to understand the growth status of tomato in time. The statement provided a theoretical foundation for determining the optimal greenhouse environmental conditions to achieve tomato maturity. And it offered recommendations for investigating the growth cycle of tomatoes, as well as technical assistance for standardized cultivation in solar greenhouses.

To control the volatility and reduce the electricity costs for indoor farming, the agrivoltaics agrotunnel introduced here uses: 1) high insulation for a building dedicated to vertical growing, 2) high-efficiency LED lighting, 3) heat pumps (HPs), and 4), solar photovoltaics (PV) provide known electric costs for 25 years. In order to size the PV array, this study develops a thermal model for agrotunnel load calculations and validates it using the Hourly Analysis Program and measured data so the effect of plants’ evapotranspiration can be included. HPs are sized, plug loads (i.e., water pump energy needed to provide for the hybrid aeroponics/hydroponics system, DC power running the LEDs hung on grow walls, and dehumidifier assisting in moisture condensation in summer) are measured/modeled. Ultimately, all models are combined to establish an annual load profile for an agrotunnel that is then used to model the necessary PV to power the system throughout the year. The results find that agrivoltaics to power an agrotunnel range from 40 to 50kW and make up an areas from 3.2 to 10.48 m²/m² of an agrotunnel footprint. Net zero agrotunnels are technically viable although future work is needed to deeply explore the economics of localized vertical food growing systems.

The solar energy can mitigate the power supply shortage in remote regions for portable irrigation systems. The accurate prediction of solar irradiance is crucial for determining the quantity of solar panels and the power capacity of photovoltaic power generation (PVPG) systems for mobile sprinkler machines. In this study, a prediction method is proposed to forecast the solar irradiance of typical irrigation areas. The impact of the meteorological parameters on the solar irradiance is studied, and four different parameter combinations are formed and considered as input to the prediction model. Based on meteorological data provided by ten typical radiation stations uniformly distributed nationwide, an Extreme Gradient Boosting (XGBoost) model optimized using the Whale Optimization Algorithm (WOA) is developed to predict the solar radiation. The prediction accuracy and stability of the proposed method are then evaluated for different input parameters through training and testing. The differences between the prediction performances of models trained based on single-station data and mixed data from multiple stations are also compared. The obtained results show that the proposed model achieves the highest prediction accuracy when the maximum temperature, minimum temperature, sunshine hours ratio, relative humidity, wind speed, and extraterrestrial radiation are used as the input parameters. The prediction effectiveness is also verified based on measured data. The WOA-XGBoost model has higher prediction accuracy than the XGBoost model, with predicted values falling within acceptable ranges. The model developed using mixed data of multiple stations can be applied for forecasting solar irradiance in different regions. This study provides a foundation for the optimization of the configuration of PVPG systems for mobile sprinkler machines.

The environmental conditions to which dams are exposed play a major role in dictating the progression and manifestation of the alkali-aggregate reaction (AAR). However, in the numerical thermal-mechanical simulation of AAR affected dams, the solar radiation and its associated shadow effects have received little attention. The spatiotemporal distribution of the solar radiation incidence on the dam surfaces has often been addressed in a simplified way or has just been neglected. Yet, far less attention has been given to shadows cast by the dam’s own geometry or the slopes. To illustrate the influence of the nonuniform temperature distribution on dam surfaces due to solar radiation and shading, the analysis of an AAR affected arch dam is presented in this paper.

The studied solar pot is a recent invention, which gained a utility model protection in 2021 from the Hungarian Intellectual Property Office under patent number 5489. The device is made for environmentally friendly cooking or heating (by utilizing solar energy) of foods and liquids. Its structure is similar to a double pipe heat exchanger, it has an outer mantle and an inner cooking tank. The goals of the paper are proposing a new physically-based mathematical model describing the solar pot and carrying out computer experiments with it, assembling an experimental system of the pot connected with a solar collector and performing measurements on it. Based on the results, the solar pot can successfully be used for cooking or sterilizing foods or liquids during the studied time period, in Hungary.

Ghana, blessed with abundant solar resources and has strategically invested in solar photovoltaic (PV) technologies to diversify its energy mix and reduce the environmental impacts of traditional energy technologies. The 50 MW solar PV installation by the Bui Power Authority exemplifies the nation's dedication to utilizing clean energy for sustainable growth. This study seeks to close the knowledge gap by providing a detailed analysis of the system's performance under different weather conditions, particularly on days with abundant sunshine and those with cloudy skies. The research consists of one-year monitoring data of the climatic and AC energy output fed into the grid. This data was used to analyze PV performance on each month's sunniest and cloudiest days. The results show that the total amount of AC energy output fed into the grid each month on the sunniest day varies between 229.3 MWh in December and 278.0 MWh in November, while the total amount of AC energy output fed into the grid each month on the cloudiest day varies between16.1 MWh in August and 192.8 MWh in February. Also, the percentage variation in energy produced between the sunniest and cloudiest days within a month ranges from 16.9% (December) to 94.1% (August). The reference and system yield analysis showed that the PV plant has a high conversion efficiency of 91.3%; however, only the sunniest and overcast days had an efficiency of 38% and 92%, respectively. The BPA plant's performance can be enhanced by using this analysis to identify erratic power generation on sunny days and schedule timely maintenance to keep the plant's performance from deteriorating. Optimizing a solar PV system's design, installation, and operation can significantly improve its AC energy output, performance ratio, and capacity factor on sunny and cloudy days.

Building integrated photovoltaics (BIPV) consists of PV panels that are integrated into the building as part of the construction. This technology has advantages such as the production of electricity without necessary additional land area. This paper provides a literature review about the recent developments in urban building energy modelling, including tools and methods, and how they can be used to predict the effect of PV systems on building outdoor and indoor environments. It is also intended to provide a critical analysis on how PV systems affect the urban environment, both from an energy and a comfort point of view. The microclimate, namelly the urban heat island concept, is introduced and related with the existence of PV systems. It is concluded that urban building energy modelling (UBEM) can be effective to study the performance of PV systems in the urban environment. It allows to simultaneously predict the building energy performance and the microclimate effect. However, there is a need to develop new methodologies to overcome the challenges associated to UBEM, especially in what concerns non-geometric data, which leads to a major source of errors. and to find an effective method to predict the effect of PV systems in the urban environment.

Recurrent sunspot groups were studied by using the Debrecen Photoheliographic Data (DPD) which covers more than 40 years. For this task it is necessary to make unambiguous the identification of the returning solar active regions. It starts with an algorithmic listing of possible returns, then the candidates of the algorithmic identifications are checked by the unique HTML-feature of the DPD. The final check is the application of an asymmetric Gaussian function introduced in previous articles to describe the development of short-lived sunspot groups observed continuously from start to end on the visible solar disc. The data of correctly identified recurrent sunspot groups fit surprisingly well to this function throughout the rotations enabling the reconstruction of the development also on the far side of the sun. The primary goal was to find any relationship between the maximum area and the lifetime deduced from the data of the asymmetric curves. This relationship is more complex than earlier results in the literature for short-lived groups. The lifetimes exhibit weak dependencies on the heliographic latitude and solar cycle phase. An apparently returning active area is rather an active nest if its data do not fit to the asymmetric Gaussian.

Photovoltaic modules should pass series of tests and examinations, verifying the electrical and thermal characteristics of the module, before being released to the market, examining the properties of the modules should undergo appropriate durability and efficiency tests under real outdoor conditions with exposure to climatic conditions and under laboratory conditions. The performance of photovoltaic cells depends on many factors, such as solar irradiance, module operating temperature, installation location, weather conditions and module shading. In this paper, three selected photovoltaic modules were examined using a large-scale steady-state solar simulator. The current-voltage (I-V) characteristics of the photovoltaic modules were experimentally tested and analyzed. The next step was to implement a three-layer artificial neural network model (MLP). The experimental data obtained in the previous step coupled with output data from MLP were then used in global sensitivity analysis (GSA). Experiments carried out on a large-scale stationary solar simulator showed differences between the values declared by the manufacturer and the values obtained from measurements of PV modules. The first module tested achieved the maximum power point greater than that specified by the manufacturer, while the other two showed power drops; it was 85-87% for the second module, and 95-98% for the third, respectively. The performed global sensitivity analysis (GSA) for the MLP model showed that the parameters: eff (22.9) and Voc/V (14.19) have the largest effect on the power-voltage relationship, while U (7.29) has the smallest effect. The usefulness of machine learning (ML) methods in the comparative analysis of PV modules has been proved.

Perovskite solar cells (PSCs) are vital for their optical and electrical properties, with lead-based PSCs reaching a remarkable efficiency of 26.1%, while tin-based counterparts achieve 18.71%. Due to lead's toxicity, there's a push for alternatives like tin. However, tin-based PSCs suffer from stability issues and high defect density states, necessitating the development of cost-effective, high-performance, and eco-friendly alternatives. In this study, we designed a hetero-junction architecture using MASnI3-based Perovskite, opti-mized with SCAPs-1D. After exhaustive analysis, our device achieved a power conversion efficiency of 24.18%, with enhanced parameters including Voc of 0.09323V, Jsc of 30.8360 mA/cm2, and FF of 84.10%. Recombination rates, particularly Shockley-Read Hall recom-bination, were significantly reduced. Parametric analyses, encompassing absorber layer thickness, band gap, defect density, doping concentration, and operating temperature, in-dicate potential efficiency enhancements. This underscores the viability of Sn-based PSCs as a cost-effective, efficient, and environmentally benevolent alternative to lead-based counterparts, promising advancements in future research and development efforts.

This study was based on the corresponding elemental abundances of carbonaceous - chondrites and the Solar photospheric elemental abundances [1]. The comparative analysis between the average magnesium, silicon and iron abundances of the Solar System and the abundances of these elements in potential nearby planetary systems was based on the Mg, Si and Fe abundances of host stars, which are in the Galactic thin disk within 25 parsecs distance from the Sun. The stellar abundance data had been taken from the Hypatia Catalog, which contains high precision data of chemical elements. We show that in general there are no significant differences between the molar Mg/Si and Fe/Si ratios of the most examined stars and the corresponding elemental ratios of the Solar System. However, the comparative study also shows that a significant fraction of the nearby extrasolar terrestrial planets may have higher bulk Mg/Si ratio than Solar, but the Solar Fe/Si ratio can relatively be frequent. We conclude that the medium - sized metallic cores can relatively be common in the rocky planetary interiors, while the mantle mineralogy for most of the rocky exoplanets in the Solar neighborhood may differ from that of Earth.

The bulk planetary compositions are thought to be linked to the chemical abundances of their host stars. The abundances of 8 key rock-forming elements and the key planetary abundance ratios in G– and F–type main sequence stars located in the Solar neighborhood within 50 pc were statistically analyzed. The averaged C/O, Mg/Si, and Fe/Si elemental ratios of the planetary systems have a crucial role in the chemical composition and the mineralogy of a rocky planet's interior. We also studied the variation of the calculated Ca/Si, Al/Si, Na/Si and Fe/Si ratios in the samples of the examined stars using the Ca, Al, Na, and Fe abundances from the catalog and then attempt to constitute plausible occurrence trends of the analyzed abundance ratios for the rocky planet population in the near – solar galactocentric distances. Considering these results, we provide simple predictions for the most likely bulk compositions of the potential rocky planets. We further apply our results to compare them to the solar averaged abundance ratios, finding that the key elemental ratios for rocky planet composition in the Solar System are not typical amongst most of the studied stellar samples.

Effective solar forecasting has become a critical topic in the scholarly literature in recent years due to the rapid growth of photovoltaic energy production worldwide and the inherent variability of this source of energy. Due to the technological and econonomic limitations of energy storage solutions, using other, mosty conventional, sources to cover energy shortfalls and at the same time utilising solar surpluses production becomes necessary. The need to optimize energy systems, ensuring power continuity, and balancing energy supply and demand has led to the development of various forecasting methods and approaches based on meteorological data or photovoltaic plant characteristics. This article presents the results of a meta-review of the solar forecasting literature, including the current state of knowledge and methodological discussion. It presents a comprehensive set of forecasting methods, evaluates current classifications, and proposes a new synthetic typology. The article emphasizes the increasing role of artificial intelligence (AI) and machine learning (ML) techniques in improving forecast accuracy, alongside traditional statistical and physical models. It explores the challenges of hybrid and ensemble models, which combine multiple forecasting approaches to enhance performance. The paper addresses the emerging trends in solar forecasting research, such as the integration of big data and advanced computational tools. Additionally, from a methodological perspective, the article outlines a rigorous approach to the meta-review research procedure, addresses the scientific challenges associated with conducting bibliometric research, and highlights best practices and principles. This includes defining research questions, selecting eligibility criteria, literature search, data extraction, synthesis, and assessing bias and quality. The article contributes to the solar forecasting field by providing up-to-date knowledge, along with insights on the emerging trends, future research directions, and anticipating implications for the theory and practicce.

The application of the latest technological innovations has been promoted worldwide to increase farm productivity, including in salt farming. This research aims to determine the determinants of adoption decisions for salt production technology called geomembrane and estimate the adoption impact on technical efficiency. The data in this study is cross-sectional from 215 small-scale salt farmers on Madura Island, East Java, Indonesia. The data was analyzed using logistic regression to identify which factors influenced farmers’ decisions to use geomembrane. The influence of adoption on farmers' technical efficiency was then assessed using propensity score matching (PSM) and data envelopment analysis (DEA). The findings indicate that age and the dummy variables of gender, land ownership, profit-sharing involvement, and membership in the People's Salt Business Group (KUGAR) all had a significant impact on adoption rates. The findings of controlling matched samples using the PSM process reveal that geomembrane application improves and greatly increases farmers' technical efficiency. Those who used geomembranes displayed greater technical efficiency than those who did not. These findings imply that salt production technology should be promoted more to increase productivity, especially geomembrane adoption, through outreach and dissemination of information, including for landowners involved in the profit-sharing system.

Solar energy has emerged as a promising alternative to traditional fossil fuels due to its abundant availability and sustainability. Solar cells, the fundamental units of solar energy conversion, have undergone significant advancements in fabrication techniques to enhance their efficiency, durability, and cost-effectiveness. This review aims to provide a comprehensive overview of various methods employed in the preparation of solar cells, including thin-film, crystalline silicon, organic, and perovskite-based technologies. By analyzing recent research developments, challenges, and future prospects, this article sheds light on the evolving landscape of solar cell fabrication, contributing to the ongoing efforts in achieving widespread adoption of solar energy.

Cirina forda caterpillars are a significant protein source in Central Africa, yet their preservation and consumption pose challenges. This study investigates the drying of Cirina forda caterpillars to enhance preservation methods and product quality. Caterpillars were subjected to drying experiments at temperatures ranging from 40°C to 70°C, using tunnel and oven dryers. The drying kinetics was analyzed using mathematical models, revealing a water diffusion-limited mechanism in all the tested conditions. The Newton model provided adequate estimations of the drying behavior, facilitating further practical dryer design. Shrinkage analysis indicated a two-step process independent of the drying conditions. Achieving a moisture content suitable for prolonged storage resulted in substantial volume loss, highlighting the challenges of preserving dried caterpillars. These findings shed light on how to optimize drying processes for Cirina forda caterpillars, crucial for sustaining protein sources in Central Africa.

A flat-plate unglazed solar water heater (SWH) with polymer thermal absorber was developed and tested. Polymer thermal absorber as a viable alternative to metal thermal absorber that is found in most SWH systems. The performance of this polymer SWH system is measured based on inlet and outlet water temperature, water flowrate, ambient air temperature and solar irradiance. The polymer thermal absorbers are hollow Polyvinyl Chloride (PVC) pipes with 20mm external diameter and 3 mm thick, painted in black to enhance radiation absorption. The pipes are arranged in a rectangular spiral inward-outward opposing-flow (RSioof). The collector pipes are placed in a 1 m2 square enclosure with bottom insulation and reflective surface for better radiation capture. Water circulation is a closed loop with a 16-liter uninsulated storage tank, driven by a pump and controlled by valves to maintain a mass flow rate of 0.00031 to 0.00034 kg/s. The test was conducted under partially clouded sky from 9 am to 5 pm, with solar irradiance between 105 and 1003 W/m2 and 27-36oC ambient air temperature. The SHW produced outlet hot water at 65oC by mid-day and maintained the storage temperature at 63oC until the end of test duration. Photo-thermal energy conversion was recorded with 23% maximum value. Results indicate that a flat plate solar water heater with polymer thermal absorber in RSioof design can be an effective alternative to the metal thermal absorber solar water heater and can be further optimized with glazing and tube sizing.

Solar radiation impacts diverse aspects of city life, such as harvesting energy with PV panels, passive heating of buildings in winter, cooling loads of air-conditioning systems in summer, and urban microclimate. Urban digital twins and 3D city models can support solar studies in the process of urban planning and provide valuable insights for data-driven decision support. This study examines the calculation of solar incident radiation at the city scale in Sofia using remote sensing data for the large shading context in a mountainous region and 3D vector building data. The building footprints and the terrain are preprocessed using GIS. The solar calculation uses a raytracing algorithm in 3D CAD at the city scale. To evaluate the performance, two cases were considered at the city and district scale, respectively. The total face count of meshes for the simulations constituted approximately 2 000 000 faces. 64379 roofs for the whole city and 4796 buildings for one district were selected. All calculations were performed in one batch and visualized in a 3D web platform. Using a 3D CAD environment establishes a seamless process of updating 3D models and simulations while preprocessing in GIS ensures working with large-scale datasets. The proposed method showed moderate computation time for both cases and could be extended to include reflected radiation and dense photogrammetric meshes in the future.

The layer-by-layer (LBL) fabrication method allows for controlled microstructure morphology and vertical component distribution, and also offers a reproducible and efficient technique for fabricating large-scale organic solar cells (OSCs). In this study, polymer D18 and PYIT-OD are employed to fabricate all-polymer solar cells (all-PSCs) using the LBL method. Morphological studies reveal that the use of additives optimizes the microstructure of the active layer, enhancing the crystallinity and charge transport capability. The optimized device with 2% CN additive significantly reduces bimolecular recombination and trap-assisted recombination. All-PSCs fabricated by the LBL method based on D18/PYIT-OD deliver a power conversion efficiency (PCE) of 15.07%. Our study demonstrates the great potential of additive engineering via LBL fabrication method in regulating microstructure of active layers, suppressing charge recombination, and enhancing the photovoltaic performance of devices.

The study conducts a comparative analysis of solar radiation estimation methods, assessing the efficacy of the Heliosat-2 algorithm against ground measurements across seven distinct countries: Netherlands, Spain, Japan, Namibia, South Africa, Saudi Arabia, and India. To achieve this, it utilizes two distinct satellite data sources—Himawari-8 for Japan and Metosat Second Generation-MSG for the rest of the countries—spanning the years Jan 2022 to April 2024. A robust methodology for determining albedo parameters specific to Heliosat-2 was developed. During cloudy days, the estimates provided by Heliosat-2 generally exceeded the ground measurements in all the countries. Conversely, on clear days, there was a tendency for underestimation, as indicated by the median value of the mean bias (MB) across most of the countries. The Heliosat-2 model slightly underestimates daily radiation values, with a median MB ranging from −27.5 to +10.2 W.m⁻². Notably, the median root mean squared error (RMSE) on clear days is significantly lower, with values ranging from 24.8 to 108.7 W.m⁻², compared to cloudy days where RMSE values lie between 75.3 and 180.2 W.m⁻². In terms of R² values, both satellites show a strong correlation between the estimated and actual values, with a median value consistently above 0.86 on a monthly scale and over 92% of daily data points falling within ±2 standard deviation.

The paper presents a proposal for an in-house mathematical model of a liquid flat-plate solar collector. The proposed model is a one-dimensional distributed parameter model enabling simulations of the collector operation under arbitrarily variable boundary conditions. The model is based on the solution of energy balance equations for all components of the collector. The formulated differential equations are solved iteratively using an implicit difference scheme. In order to obtain a stable numerical solution, it is necessary to use appropriate steps of the time and spatial division. These were found by comparing the results obtained from the model with the results of the analytical solution available in the literature for the transient state, which constitutes the novelty of the present study. The accuracy of the results obtained from the model was verified experimentally by comparing the measured and the calculated history of the fluid temperature at the outlet of the collector. The calculation of the collector time constant is proposed in the paper as an example of the model practical application. The results of the time constant calculation were compared with the values obtained experimentally on the test stand. This is another novelty of the presented research. The analysed collector instantaneous efficiency was then calculated for selected outdoor conditions. The presented mathematical model can also be used to verify the correctness of the collector operation. Comparing, on an ongoing basis, the measured and the calculated values of the fluid temperature at the collector outlet, conclusions can be drawn about the process of solar glass fouling or glycol gelling. The model's simplicity and the low computational demands enable such comparisons in an online mode.

The accurate forecasting of solar power output is essential for ensuring the stable and efficient operation of grid-connected photovoltaic (PV) systems, especially when faced with variable weather patterns. This research focuses on the integration of Machine Learning (ML) methodologies and climatic parameters to predict solar panel energy generation, with a specific emphasis on addressing consumption-production imbalances. Leveraging a dataset sourced from the Kaggle platform, the study is conducted in the context of Estonia, aiming to optimize solar energy utilization in this geographic region. The dataset, obtained from Kaggle, encompasses comprehensive information on climatic variables, including sunlight intensity, temperature, and humidity, alongside corresponding solar panel energy output. Leveraging machine learning algorithms, including XGBoost regression and neural networks, our model aims to identify complex patterns and relationships within the datasets. By tailoring the model to Estonia's climatic nuances, we seek to enhance the accuracy of energy production forecasts and, consequently, better manage the challenges associated with consumption-production imbalances. Furthermore, the research investigates the adaptability of the proposed model to diverse climatic conditions, ensuring its applicability for similar endeavors in other geographical locations. The performance of the forecasting model will be evaluated using error metrics like mean absolute error (MAE) and root mean squared error (RMSE). This study leverages a comprehensive dataset from Kaggle and utilizes advanced machine learning techniques to generate valuable insights. These insights can inform the development of sustainable energy policies and practices, ultimately leading to a more efficient and reliable renewable energy infrastructure.

Solar pasteurization, as a means of treating milk in remote rural areas without electrical power, is based on using solar energy to thermally inactivate pathogenic microorganisms at temperatures below the boiling point to maintain or improve milk quality. A solar milk pasteurizer of flat‐plate water‐heating glass acting as the solar collector, connected to a stainless-steel cylindrical milk vat, was constructed and evaluated in Navrongo, in the tropical savanna zone of Ghana, West Africa. The novel approach taken in this project is to integrate the solar collection and heat exchanger into a single unit using materials and fabrication techniques readily available in the developing world. The vat comprises a 1.5 mm thick stainless steel cylindrical tank, a 2.2 cm wide hot water jacket, and an outer layer of 5.0 mm thick aluminium foil insulation. Hot water produced by the collector was used for pasteurizing milk. The optimum quantity of milk that this device could pasteurize under the study conditions was 8 L. The device could pasteurize raw milk to a maximum temperature of 74 °C at 14:00 h GMT. The ambient temperature during the pasteurization ranged from 30 °C to 43 °C. The microbial analysis before and after the pasteurization was done, and the result shows that the total bacteria count before pasteurization was 6.6x10⁶ log CFU/mL per unit volume, and the total bacteria count after pasteurization was 1.0x10² log CFU/mL. By acceptable standards, the total bacteria count after pasteurization is within a safe range for consumption, and coliform counts were negative. The solar milk pasteurization system is cost-effective. Hence, it is appropriate for milk producers in arid pastoral areas without electricity to adopt the solar pasteurizer as an alternative to firewood as a fuel source for milk pasteurization. This approach can potentially create a cottage industry that may also play a crucial role as a water treatment technology that will improve the health of rural populations.

Origin, mechanics and properties of the Solar System are analysed in the framework of the Complete Relativity theory (by the same author). According to Complete Relativity, everything is relative. Any apparent absolutism (notably invariance to scale of dimensional constants, absolute elementariness, invariance to time) is an illusion stemming from limits imposed by [or on] polarized observers that will inevitably lead to misinterpretation of phenomena (another illusion) occurring on non-directly observable scales or even on observable but distant scales in space or time. If everything is relative, reference frames will exist where particles are planets and where planets are living beings. Earth is, therefore, analysed here in more detail, both as a particle and, as a living evolving being (of, hypothesized, extremely introverted intelligence). The analysis confirms the postulates and hypotheses of the theory (ie. existence of discrete vertical energy levels) with a significant degree of confidence. During the analysis, some new hypotheses have emerged. These are discussed and confirmed with various degrees of confidence. To increase confidence or refute some hypotheses, experimental verification is necessary. Main conclusions that stem from my research and are further confirmed in this paper are: universes are, indeed, completely relative; Solar System is a scaled (inflated, in some interpretations) Carbon isotope with a nucleus in a condensed (bosonic) state and components in various vertically excited states; life is common everywhere, albeit extroverted complex forms are present on planetary surfaces only during planetary neurogenesis; anthropogenic climate change is only a part (trigger from one perspective) of bigger global changes; major extinction events on a surface of a planet are relative extinctions, a regular part of transformation and transfer of life in the process of planetary neurogenesis.

This research aimed to determine the most viable locations for establishing solar energy facilities in Yemen through the utilization of the Analytical Hierarchy Process (AHP), Best-Worst Method (BWM), and Geographic Information System (GIS). A total of twelve key criteria were meticulously selected and evaluated based on their impact on the appropriateness of sites for solar power plants. These criteria were amalgamated using a weighted overlay tool, resulting in a map that classified regions as either optimal, highly suitable, or suitable. The findings of the study indicated that the eastern, southern, and northern parts of Yemen are prime candidates for solar energy installations due to their moderate climate and flat topography. On the other hand, the western regions were deemed less favorable. The breakdown of site classifications revealed that 38% of areas were optimal, 61% were highly suitable, and only 1% were considered suitable, based on the assigned weights from the AHP and BWM methodologies. Moreover, a sensitivity analysis was carried out to evaluate the impact of adjusting the weights of Global Horizontal Irradiance (GHI) and slope on site classifications. A minor increase in the weights of GHI (from 30% to 31%) and slope (from 10% to 11%) resulted in a significant alteration in the suitability categories, highlighting the importance of weight adjustments in multi-criteria decision-making processes. In conclusion, the study emphasizes the effectiveness of AHP, BWM, and GIS in assessing site suitability for solar energy facilities, as well as the significance of sensitivity analyses. These approaches provide valuable insights for decision-makers, aiding in strategic planning and fostering sustainable energy development in Yemen.

In the quest for more efficient solar thermal systems, accurately determining the thermal emittance of low-emissive materials is crucial in determining the power losses. This paper describes the calorimetric method designed to precisely measure the thermal emittance of Selective Solar Absorbers (SSAs) to be used in High Vacuum Flat Plate Collectors (HVFPCs). The method's capability is demonstrated through the successful correction of thermal emittance values for copper samples of varying sizes, including dimensions down to 49 cm². Results highlight the method's potential to significantly reduce measurement errors associated with small-size and/or low-emittance samples, providing a path forward to improve the design and efficiency of SSAs. This research marks a significant step in advancing solar thermal technology by enabling emittance measurements with a precision better than 0.003, which is essential for the development of high-performance solar thermal absorbers. The method has also been applied to correct the thermal emittance value of SSA measured in previous measurement campaigns, and it allows a better estimation of the SSA efficiency conversion curve.

This paper deals with the problem of determining the optimal capacity of Concentrated Solar Power (CSP) plants, especially in the context of hybrid solar power plants. This work presents an innovative analytical approach to optimize the capacity of concentrated solar plants. The proposed method is based on the use of additional non-dimensional parameters, in particular the design factor and the solar multiple factor. The paper presents a mathematical optimization model that focuses on the capacity of concentrated solar power plants where thermal storage plays a key role in the energy source. The analytical approach provides a more complete understanding of the design process for hybrid power plants. In addition, the use of additional factors and the combination of the proposed method with existing numerical methods allows for a more refined optimization, which allows for a more accurate selection of the capacity for specific geographical conditions. Importantly, the proposed method significantly increases the speed of computation compared to traditional numerical methods. Finally, the authors present the results of the analysis of the proposed system of equations for calculating the levelized cost of electricity (LCOE) for hybrid solar power plants. The nonlinearity of the LCOE on the main calculation parameters is shown.

In areas with a deep floor plan, the distribution of natural light is not uniform. Consequently, relying solely on daylight may not suffice to meet the space's lighting requirements, necessitating the use of artificial lighting in darker areas. Therefore, a lighting system is needed that not only controls the glare near the windows but also increases the light at the end of the room and provides uniform daylight. One of the widely used systems is the “light shelf“which has three main functions: shading, increasing the depth of light penetration and reducing glare. Review articles about light shelves have been done in 2015 and 2017, while more than 80% of the studies have been carried out since 2016 and light shelves with more diverse forms and dynamic elements and many consolidations were proposed. Therefore, there is a need for a more comprehensive review. The main question of this research is how different parameters (including climate, material, ceiling and integrated systems) can help to increase the efficiency of light shelves. By using a systematic review, studies in the past three decades were classified in order to determine the effect of these parameters on improving lighting performance and controlling solar heat gain.

This work focuses on short-term forecasting of PV output power. The multilayer perception (MLP), convolutional neural networks (CNN), and k-nearest neighbour (kNN) neural networks have been used singly or in a hybrid (with other algorithms) to forecast solar PV power or global solar irradiance with good success. Their performances in forecasting PV power have been compared with other algorithms but not with themselves. The study aims to compare performance of a number of neural network algorithms in solar PV energy yield forecasting under different weather conditions. The performance of MLPNN, CNN and kNN are being compared using solar PV (hourly) energy yield data for Grahamstown, Eastern Cape, South Africa. The choice of location is part of the study parameters to provide insight into renewable energy power integration in specific areas in south Africa that may be prone to extreme weather conditions. The kNN algorithm was found to have RMSE value of 4.95% and MAE value of 2.74% at its worst performance, and RMSE value of 1.49% and MAE value of 0.85% at its best performance. It outperformed the others by a good margin and kNN could serve as a fast, easy, and accurate tool to forecast solar PV output power.

Abstract: This article reports the results of an ecological study of cancer incidence rates by state in the US for the period 2016-2020. The goals of this study were to determine the extent to which solar UVB doses still reduced cancer risk compared to findings reported in 2006 for cancer mortality rates for the periods 1950–1969 and 1970-1794 as well as cancer incidence rates for the period 1998–2002 and to determine which factors were recently associated with cancer risk. The cancer data for non-Hispanic white (European American) men and women were obtained from the Centers for Disease Control and Prevention. Indices were obtained for solar UVB at the surface for July 1992, and alcohol consumption, and diabetes and obesity prevalence near the 2016–2020 period. Lung cancer incidence rates were also used in the analyses as a surrogate for smoking, diet, and air pollution. The cancers for which solar UVB is significantly associated with reduced incidence are bladder, brain (males), breast, corpus uteri, esophageal, gastric, non-Hodgkin’s lymphoma, pancreatic, and renal cancer. Lung cancer was significantly associated with colorectal, laryngeal, and renal cancer. Diabetes was also significantly associated with breast, liver, and lung cancer. Obesity prevalence was significantly associated with breast, colorectal and renal cancer. Alcohol consumption was associated with bladder and esophageal cancer. Thus diet has become a very important driver of cancer incidence rates. The role of solar UVB in reducing risk of cancer has been reduced due to people spending less time outdoors, wearing sunscreen that blocks UVB but not UVA radiation, and population increases in overweight and obesity, which lowers 25-hydroxyvitamin D concentrations and generates systemic inflammation, a risk factor for cancer. The dietary approach that would reduce the risk of diabetes, obesity, lung cancer, and, therefore cancer, would be one based mostly on whole-plants and restrictions on red and processed meats and ultraprocessed foods. Solar UVB exposure for a few minutes before applying sunscreen and taking vitamin D supplements would also help reduce risk of cancer.Keywords: alcohol consumption; cancer incidence;

In this research work, we describe the preparation process, characterization, and photo-physical studies of an ionic liquid (IL) based semiconductor Zinc Oxide (ZnO) nanoparticles synthesized by an economical wet chemical precipitation method. For the first time, an IL was synthesized with the help of a chemical reaction between triethylamine (TEA) and bromoacetic acid (BAA). A polyamide dye was prepared by a reaction between two monomers, ethylenediamine (EDA) and trimesoylchloride (TMC), under room temperature conditions. The polyamide dye was capped on ZnO nanoparticles, and the final product was divided into three different samples, A, B, and C, according to level of concentrations of IL and Polyamide dye. These samples were characterized with X-Ray Diffraction (XRD), Field Emission Scanning Electron Microscopy (FESEM), Dynamic Light Scattering (DLS) spectra, Ultraviolet-Visible (UV-Vis), and Fluorescence spectroscopies. The formation of polyamide linkages in the ionic liquid has been confirmed by a spectroscopic method using Fourier Transform Infrared (FTIR) spectroscopy. The capping of polyamide dye molecules on the surface of ZnO nanoparticles revealed two things: (i) improved UV absorption spectra and (ii) enhanced luminescence in the photoluminescence spectra. Hence, during investigations, broad absorption bands were observed at peaks 263 nm, 278 nm, and 276 nm respectively for samples A, B, and C. Further, IL was used as an electrolyte or redox mediator and polyamide as a dye material in the fabrication of ZnO Dye-Sensitized Solar Cells (DSSCs). The samples A, B, and C were used in the fabrication of photo-anode assemblies for ZnO DSSCs. The ZnO DSSCs were tested under strong simulated light at Air Mass (AM) 1.5 solar irradiations. The observed photovoltaic results shown that solar cell SCB generated a maximum power conversion efficiency (η) of 5.65%, higher than the power conversion efficiencies of solar cells SCA (3.99%) and SCC (4.46%) respectively. The Incident Photon to Current Conversion Efficiency (IPCE) spectra values of ZnO DSSCs shown a significant improvement in the incident photon to current conversion efficiency of solar cell SCB (IPCE=61%) as compared to SCC (enhanced by 6%) and SCA (enhanced by 4%). Such solar cell assemblies can be suitable for green and clean energy applications.

The assessment of Photovoltaic (PV) systems, a key component of sustainable energy solutions, is of paramount importance in the pursuit of a greener future. This abstract provides an overview of environmental assessments associated with PV systems, considering their life cycle, energy production, and ecological impact. The study explores various methodologies and tools employed in the evaluation of PV systems’ environmental performance, addressing issues such as material sourcing, manufacturing, installation, and end-of-life disposal. Additionally, it delves into the trade-offs and challenges in achieving sustainability objectives in the solar energy sector. By critically examining the environmental implications of PV systems, this research contributes to informed decision-making and the sustainable integration of solar power into our energy landscape.

To enable net zero sustainable thermal building energy this study develops an open-source thermal house model to couple solar photovoltaic (PV) and heat pumps (HP) for grid-connected residential housing. The calculation of both space heating and cooling thermal loads and the selection of HP is accomplished with a validated Python model for air-source heat pumps. The capacity of PV required to supply the HPs is calculated using an System Advisor Model integrated Python model. Self-sufficiency and self-consumption of PV and the energy imported/exported to the grid for a case study are provided, which shows that simulations based on the monthly load profile have a significant reduction of 43% for energy sent to/from the grid compared to the detailed hourly simulation and an increase from 30% to 60% for self-consumption and self-sufficiency. These results show the importance of more granular modeling and also indicate mismatches of PV generation and HP load based on hourly simulation datasets. The back-calculation PV sizing algorithm combined with HP and thermal loads presented in this study exhibited robust performance. The results indicate this approach can be used to accelerate the solar electrification of heating and cooling to offset the use of fossil fuels in northern climates.

The growing urgency for sustainable energy solutions necessitates a deeper understanding of the environmental impacts of renewable technologies. This article aims to synthesize and analyze Life Cycle Assessments (LCA) in this domain, providing a comprehensive perspective. We systematically categorize 2,923 articles into four communities: (1) Photovoltaic systems, (2) Wind energy systems, (3) Materials for auxiliary industry of photovoltaic and wind systems, and (4) Solar thermal systems. A comparative analysis is conducted to identify methodological consistencies and disparities across these communities. The findings reveal diverse methodological approaches and a range of environmental impacts, highlighting the complexities in assessing renewable energy systems. The article underscores the significance of material selection in photovoltaic and wind systems, providing a critical overview of the current state of LCA research in renewable energy and stressing the need for standardized methodologies. It also identifies gaps in recent research, offering insights for future studies focused on integrating environmental, economic, and social considerations in renewable energy assessments.As a case study, an LCA was used to evaluate two energy supply methods for a sensor network: one connected to the public grid and another powered by a photovoltaic panel. The off-grid system, while more environmentally friendly by reducing reliance on non-renewable energy sources, posed challenges due to the high environmental impact of battery production and disposal. Integrating environmental assessments provides a robust framework for making informed decisions on sustainable technologies. The findings are critical for projects that balance technological needs with sustainability goals.

A joint analysis of solar wind, geomagnetic field, and earthquake catalog data showed that before the catastrophic M7.8 and M7.5 Kahramanmaras earthquake sequence on February 6, 2023, the closed strong magnetic storm occurred on November 7, 2022, SYM/H=-117 nT. Storm started at 08:04 UT. At this time, the high latitudinal part of Turkey's longitudinal region of future epicenters was located under the polar cusp, where the solar wind plasma would directly access the Earth's environment. The time delay between storm onset and earthquake occurrence was ~91 days. We analyzed all seven strong (M7+) earthquakes from 1967 to 2020 to verify the initial findings. A similar pattern has been revealed for all events. The time delay between magnetic storm onset and earthquake occurrence varies from some days to some months. To continue these investigations, a retrospective analysis of seismic and other geophysical parameters just after preceded geomagnetic storms in the epicenter areas is desirable.

Novel far-red-sensitive symmetric squaraine (SQ) dyes with terminal alkyl-chain modifications were designed, synthesized and characterized aiming towards imparting multifunctionalities such as photosensitization, dye aggregation prevention and source of electrolyte components. The dye sensitizers SQ-77 and SQ-80 with the alkyl chain terminal modifications consisting of iodine and 1-methylimidazolium iodide, respectively, were designed and synthesized as new dye sensitizers for DSSCs based on the symmetric SQ-5 without any terminal modification used as reference. Upon adsorption on the mesoporous TiO2 surface, The SQ-77 depicted an enhanced dye loading and dye aggregation. On the other hand, SQ-80 demonstrated reduced dye aggregation and stronger binding on the TiO2 surface leading to enhanced durability of DSSCs. Apart from the most common photosensitization behaviour, the newly designed dye demonstrated multifunctionality such as aggregation prevention and electrolyte functionality utilizing iodine-based redox electrolyte in the presence and absence of I2 and LiI additives. In the absence of LiI and I2, a mixture of SQ-77 and SQ-80 demonstrated a photoconversion efficiency of 1.54 % under simulated solar irradiation, which was about 6 times higher as compared to reference dye SQ-5 (0.24 %) having no alkyl chai terminal modification.

Buildings’ thermal energy needs are inherently linked to climate conditions. Consequently, it is crucial to evaluate how climate changes affect these energy demands. Despite extensive analysis, a comprehensive assessment involving a diverse range of building types has not been consistently conducted. The primary objective of this research is to perform a coherent evaluation of the influence of climate changes, construction element properties, and the Heating, Ventilation, and Air Conditioning (HVAC) system type of control on the energy requirements of six buildings (residential, services, and commercial). The buildings are considered located in a temperate Mediterranean climate. Our focus is on the year 2070, considering three distinct climatic scenarios: (i) maintaining the current climate without further changes, (ii) moderate climate changes, and (iii) extreme climate changes. The buildings are distributed across three different locations, each characterized by unique climatic conditions. Buildings’ envelope features a traditional External Thermal Insulation Composite System (ETICS) and expanded polystyrene (EPS) serves as thermal insulation material. Two critical design factors are explored: EPS thickness ranging from 0 (no insulation) to 12 cm; and horizontal external fixed shading elements varying lengths from 0 (absence) to 150 cm. Six alternative setpoint ranges are assessed for the HVAC system control: three based on the Predicted Mean Vote (PMV) and three based on indoor air temperature (Tair). Results were obtained with a validated in-home software tool. They show that, even under extreme climate conditions, the application of thermal insulation remains energetically favorable, however its relative importance diminishes as climate severity increases. Then, proper insulation design remains important for energy efficiency. The use of external shading elements for glazing (e.g., overhangs, louvers) proves beneficial in specific cases. As climate changes intensify, the significance of shading elements grows. Thus, strategic placement and design are necessary for good results. The HVAC system’s energy consumption depends on the level of thermal comfort requirements, on the climate characteristics and on the building’s type of use. As climate change severity intensifies, energy demands for cooling increase, while energy needs for heating decrease. However, it’s essential to recognize that the impact of climate changes on HVAC system energy consumption significantly depends on the type of building.

The literature shows that both in laboratory and in industrial conditions, photocatalytic oxidation method copes quite well with the degradation of the most organic substances, including environmental toxins and molecular components of pathogenic microorganisms. However, the effective utilization of photocatalytic processes for environmental decontamination and disinfection require significant technological advancement both in the area of semiconductor material synthesis and its application. Here we focused on the presence and ‘photocatalytic capability‘ of photocatalysts among soil minerals, and their potential contribution to the environmental decontamination in vitro and in vivo. (The issue is sketched from the perspective of chemists and environmental scientist.) Reactions caused by sunlight on the soil surface are involved in its normal redox activity. It appears that some of them may take part in the soil decontamination. However, their importance for decontamination in vivo cannot be overstated due to diversity of soils on the Earth caused by the environmental conditions, such as climate, parent material, relief, vegetation etc. The solar-light induced reactions are just a part of extremely complicated processes dependent on a plethora of environmental determinates. Such multiplicity of affecting factors, which we tried to sketch from the perspective of chemists and environmental scientist, makes us rather sceptical about the effectiveness of the photocatalytic processes in vivo. On the other hand, there is a huge potential of the soils as the alternative source of useful photocatalytic materials of unique properties

Solar energetic particles (SEPs) are bursts of high-energy particles that originate from the Sun and can last for hours or even days. The aim of this study is to understand how the characteristics of energetic particles was affected by the characteristic parameters of corotating interaction regions (CIRs). In particular, the particle intensity distribution with time and space in different CIRs are studied. The propagation and acceleration of particles are described by the focused transport equation (FTE). We used a three-dimensional magnetohydrodynamic (MHD) model to simulate the background field including CIRs. By changing the inner boundary conditions, we constructed CIRs with different solar wind speeds, angles between the polar axis and rotation axis, and the azimuthal widths of the fast streams. Impulsive particles are injected at the inner boundary. We then study the SEPs in different backgrounds. The results show that the CIR widths are related to the solar wind speed, tilt angles, and the azimuthal widths of the fast stream. The acceleration of particles in the reverse and forward compression regions is mainly influenced by the solar wind speed difference and the slow solar wind speed, respectively. Particles with lower energy (sub-MeV) are more sensitive to the parameters of CIRs. Different CIR parameters also greatly affect the spatio-temporal distribution of particle intensities in different ways. These results indicate that, it is crucial to consider the conditions of large-scale structure in interplanetary space when studying or predicting energetic particles. Additionally, our findings provide empirical guidance for forecasting the characteristics of SEPs.

Membrane gas absorption technology and solar-assisted regeneration system are two promising approaches to reduce high energy consumption associated with carbon dioxide capture from coal fired power plants. In the present study, a solar-assisted hollow fiber membrane contactor (SOL-HFMC) power plant is proposed to capture and desorb CO₂ in hollow fiber membrane contactors with the assistance of solar thermal collectors. Techno-economic assessment and sensitivity analysis of the proposed system is carried out in three studied locations with different weather conditions for a 580 MWe pulverized coal power plant. Research results show that, the output capacity and net efficiency of the SOL-HFMC power plant are significantly higher than those of the reference power plant regardless whether TES system is applied or not. In addition, CEI of the SOL-HFMC power plant with TES system is 4.36 kg CO₂/MWh, 4.45 kg CO₂/MWh and 4.66 kg CO₂/MWh lower than that of the reference power plant. The prices of membrane, vacuum tube collector and phase change material should be reduced to achieve lower LCOE and COR values. Specifically for SOL-HFMC power plant with TES system, the corresponding vacuum tube collector price shall be lower than 25.70 $/m² for Jinan, 95.20 $/m² for Xining, and 128.70 $/m² for Lhasa, respectively. To be more competitive than solar-assisted ammonia-based post-combustion CO₂ capture power plant, the membrane price in Jinan, Xining and Lhasa shall be reduced to 0.012 $/m, 0.015 $/m and 0.016 $/m for the sake of LCOE, and 0.03 $/m, 0.033 $/m and 0.034 $/m for the sake of COR, respectively. The findings can provide guidance for decision-making and risk management strategies.

This paper examines the response of the ionosphere to the impact of two moderate geomagnetic storms observed in January 17 and 26-27, 2013 under conditions of strong sudden stratospheric warming. The study uses data from ground-based ionosonde measurements at the Alma-Ata ionospheric station (43.25 N, 76.92 E) combined with optical observation data (The Spectral Airglow Temperature Imager (SATI)). Ionosonde data showed that the geomagnetic storms under consideration do not generate ionospheric storms, but demonstrate some unusual types of diurnal foF2 variations with large (up to 60%) deviations of foF2 from median values observed during the night/morning periods on 13-15 and 20-23 January which do not have any relation to solar or geomagnetic activity. Wave-like disturbances in foF2, h’F and daily averaged foF2 values with quasi-period of 5-8 days and peak-to-peak amplitude from about 1MHz to 2 MHz (from 20% to 40%) and ~40 km are observed during the 9-28 January, after registration the occurrence of the major SSW event on 6-7 January. The observed variations in the OH emission rate are found to be quite similar to those observed in the ionosheric parameters that assume a community of processes in the stratosphere/mesosphere/ionosphere system. The study shows that the F-region of the ionosphere is influenced by processes in the lower ionosphere, in this case by processes associated with sudden stratospheric warming SSW-2013, which led to modification of the structure of the ionosphere and compensation of processes associated with the development of the ionospheric storms.

The pointing accuracy of large radio telescopes is affected by antenna structure errors, installation errors, servo errors, gravity, and varying environmental factors. It is hard to estimate the pointing error of radio telescopes under solar radiation via the traditional multi-parameter static pointing models, due to the time-varying characteristics of the dynamic pointing error. There is still no effective way to estimate the dynamic pointing error of large radio telescopes under solar radiation up to now. To estimate the dynamic pointing error of large radio telescopes under solar radiation, a new way based on digital twin(DT) is tried in this paper. The operational framework of the DT system of large radio telescopes is introduced first. Then, the Wuqing 70-m radio telescope(WRT70) is taken as the research object, the digital models of which are created. Finally, the reliability of the WRT70's DT system is verified and the dynamic pointing error of WRT70(staying at the position of the elevation angle of 90° and the azimuth angle of 180°) on two sunny days in different seasons is estimated by the created DT system. The research results show that the pointing error of large radio telescopes under solar radiation fluctuates greatly and the seasonal differences are very striking. The maximum elevation pointing error of WRT70 under solar radiation around the winter solstice is over 40 arcsec, which should never be ignored. The way is feasible to estimate the dynamic pointing error of large radio telescopes staying at a specific position under solar radiation via constructing a DT system in this paper, but it is not yet able to estimate effectively the dynamic pointing error of large radio telescopes being in action. It is expected to establish a dynamic pointing error model and calibrate the dynamic pointing errors of large radio telescopes being in action by DT technology in the future.

The spectra and global distributions of the X-ray emissions generated by the solar wind charge-exchange (SWCX) process in the terrestrial magnetosheath are investigated based on a global hybrid model and a global geocoronal hydrogen model. The solar wind O6+ ions which are the primary charge state for oxygen ions in solar wind are considered. The line emissivity of the charge-exchange born O5+ ions are calculated by Spectral Analysis System for Astrophysical and Lab oratory (SASAL). It is found that the emission lines from the O5+ ranges from 105.607 to 118.291 eV with the strong line at 107.047 eV. We then simulated the magnetosheath X-ray emission intensity distributions with a virtual camera at two positions of north pole and dusk at six stages during the passing of a perpendicular interplanetary shock combined with a tangential discontinuity structure through the Earth’s magnetosphere. During this process, the X-ray emission intensity increases with time, and the maximum value is 27.11 keV cm-2 s-1 sr-1 on the dayside, which is 4.5 times that before the solar wind structure reaches the Earth. A clear shock structure can be seen in the magnetosheath and moves earthward. The maximum emission intensity seen at dusk is always higher than that seen at north pole.

This paper investigates an innovative photovoltaic cell configuration, denoted as “Au/CuSCN/RbGeI3/CdTe/ZnO/TiO2/FTO", using SCAPS-1D simulation. The research focuses on optimizing device performance by analyzing key components, including ZnO as the electron transport layer (ETL), RbGeI3 as the perovskite absorber layer, CuSCN as the hole transport layer (HTL), and CdTe as the active buffer layer. A comparison is made with the standard “Au/CuSCN/CH3NH3SnI3/CdTe/ZnO/TiO2/FTO" configuration under dark and illuminated conditions. Through an in-depth investigation involving temperature effects, generation rate analysis, RbGeI3 absorber layer thickness, Nd level, and interface defect levels, an optimized design for a unit area is achieved. The proposed solar cell demonstrates outstanding performance metrics, including an open circuit voltage (Voc) of 0.94V, a short circuit current density (Jsc) of 34.52mA/cm2, a fill factor (FF) of 77.77%, and an energy conversion efficiency (η) of 25.40%. These values significantly outperform the reference models with energy conversion efficiencies of 10.11% and 21.09%. Real-world applicability is validated by implementing these optimized characteristics in a photovoltaic system for Pakistan’s geographical location using PVSyst software. The suggested solar cell achieves a remarkable performance ratio (PR) of 85.6%, surpassing the PR of the reference basic solar cell model at 83%. The findings of this research offer a promising and superior solar cell design, incorporating innovative materials and optimization techniques to achieve exceptional energy conversion efficiency and overall performance. This study’s outcomes have the potential to advance photovoltaic technology and contribute to sustainable energy solutions worldwide.

Organic solar cells are contributing extensively to the production of future large area and cost-effective sources of renewable energy with a compact environmental impact. Moreover, due to tunable optical properties of the active medium, the semi-transparent organic solar cell can be fabricated and become a promising nominee for building Integrated Photovoltaics (BIPV), vehicles, and mobile electronic devices. Therefore, three newly synthesized polymers used as were host materials for the active medium and blended with beetroot dye. Hence, based on BHJ structure two ternary systems have been constructed and utilized to fabricate semitransparent solar cells and characterized. The results show that the natural dye has a crucial impact on solar cell characteristic parameters. Consequently, large value of V_OC close to 1V were obtained for ternary systems and acceptor material named PINDOLE exhibits potentials for electron transport layer (ETL) and shows an improvement in both fill factor and device efficiency.

Presently, Jordan confronts a double substantial challenge of enhancing energy security and mitigating greenhouse gas emissions. One of the most encouraging avenues to attain the objectives of sustainable development, energy security, and environmental conservation is to enhance the integration of renewable energy into the generation of electricity. In pursuit of this goal, the Jordanian government intends to expand investments in the green energy sector, with solar and wind energy poised to play a key role in satisfying energy demands and cultivating an environmental sustainability. This paper aims to examine the distinctive dynamics, challenges, obstacles, and potential solutions corresponding to the establishment of community solar and wind farms in Jordan suburban areas. It aims to highlight the opportunities and barriers influencing the track of sustainable energy adoption in the country. Through a comprehensive analysis of the Jordanian context, the goal is to extract insights that can guide policies and practices. Additionally, the findings may serve as a valuable benchmark for other regions confronting similar challenges on their pursuit for a sustainable energy future.

This paper provides a study on the development of solar energy, its prospects, and its impacts in Africa. Although the main focus is on technologies adopted for different uses (solar farms, mini-grids, off-grid, solar houses, irrigation, lighting, etc.), we also consider some aspects that increase the adoption of solar energy, such as legislation and business models. Finally, we will examine current and future solar projects managed by NGOs and international companies and how they benefit to leveraging social and economic standards, quality of life as well as capacity building in Africa. This study shows the plethoric interest of institutions outside Africa in the market of solar energy in the continent and that there is no African strategy to increase its independency toward a sustainable development particularly through energy transition.

The research develops and validates new decomposition models for DNI estimations from Southern African data. The results demonstrated improved DNI estimation accuracy compared to the baseline models across all testing and validation datasets. These outcomes suggest that utilising a localised model can significantly enhance DNI estimations for Southern Africa and potentially for developing similar models in diverse geographic regions worldwide. Furthermore, clustered models highlighted the potential advantages of grouping data based on shared geographical and climatic attributes. This clustering approach could enhance decomposition model performance, particularly when local data is limited or data is available from multiple nearby stations. The Southern African decomposition model, which encompasses a wide spectrum of climatic regions and geographic locations, exhibited notable improvements over the baseline models despite occasional overestimation or underestimation. The overall metrics affirm the substantial advancement achieved with the Southern African model. This study focused on validating the model for hourly DNI in Southern Africa within a range of clearness index-intervals from 0.175 to 0.875. Implementing accurate decomposition models in developing countries can accelerate the adoption of renewable energy sources, diminishing reliance on coal and fossil fuels.

Solar flares are characterized by sudden bursts of electromagnetic radiation from the Sun’s surface, and caused by the changes in magnetic field states in solar active regions. Earth and its surrounding space environment can suffer from various negative impacts caused by solar flares ranging from electronic communication disruption to radiation exposure-based health risks to the astronauts. In this paper, we address the solar flare prediction problem from magnetic field parameter-based multivariate time series (MVTS) data using multiple state-of-the-art machine learning classifiers that include MINImally RandOm Convolutional KErnel Transform (MINIROCKET), Support Vector Machine (SVM), Canonical Interval Forest (CIF), Multiple Representations SEQuence Learner (Mr-SEQL), and Long Short-Term Memory (LSTM)-based deep learning model. Our experiment is conducted on the on the Space Weather ANalytics for Solar Flares (SWAN-SF) benchmark data set, which is a partitioned collection of MVTS data of active region magnetic field parameters spanning over 9 years of operation of the Solar Dynamics Observatory (SDO). The MVTS instances of the SWAN-SF dataset are labeled by GOES X-ray flux-based flare class labels, and attributed to extreme class imbalance because of the rarity of the major flaring events (e.g., X and M). As a performance validation metric in this class-imbalanced dataset, we used the true skill statistic (TSS) score. Finally, we demonstrate the advantages of the MVTS learning algorithm MINIROCKET, which outperformed the aforementioned classifiers without the need for essential data preprocessing steps such as normalization, statistical summarization, and class imbalance handling heuristics.

The result of the multidisciplinary collaboration of researchers from different areas of knowledge to validate a solar radiation model is presented. The MAPsol is a 3D local-scale adaptive solar radiation model that allows to estimate direct, diffuse and reflected irradiance for clear sky conditions. The model includes the adaptation of the mesh to complex orography and albedo, and considers the shadows cast by the terrain and buildings. The surface mesh generation is based on surface refinement, smoothing and parameterisation techniques and allows the generation of high quality adapted meshes with a reasonable number of elements. Another key aspect of the paper is the generation of a high-resolution digital elevation model (DEM). This high-resolution DEM is constructed from LiDAR data and its resolution if two times more accurate than the publicly available DEMs. The validation process uses direct and global solar irradiance data obtained from pyranometers at the University of Salamanca located in an urban area affected by systematic shading from nearby buildings. This work provides an efficient protocol for studying solar resources, with particular emphasis on areas of complex orography and dense buildings where shadows can potentially make solar energy production facilities less efficient.

The statistical analysis of impact of the top 50 solar flares of X-class (1997-2023) on the global seismic activity, as well as on the earthquake preparation zones located in illuminated part of the globe and in the area of 5000 km radius around the subsolar point was carried out. It is shown by a method of epoch superposition that for all cases the increase of seismicity is observed, especially in the region around the subsolar point (up to 38%) during 10 days after the solar flare in comparison with preceding 10 days. The case study of aftershock sequence of strong M=9.1 earthquake (Su-matra-Andaman Islands, 26.12.2004) after the solar flare of X7.2 class (20.01.2005) demonstrated that the number of aftershocks with magnitude M≥2.5 increases more than 20 times after the solar flare with a delay of 7 days. For the case of the Darfield earthquake (M=7.1, 04.09.2010, New Zealand) it was shown that strong solar flares of class X and M probably triggered two strong aftershocks (M>6) with the same delay of 6 days on the Port Hills fault, which is the most sensitive to external electromagnetic impact from point of view of the fault electrical conductivity and orientation. Based on the obtained results the possible application of natural electromagnetic triggering of earthquakes is discussed for a short-term earthquake prediction using confidently recorded strong external electromagnetic triggering impacts on the specific earthquake preparation zones, as well as ionospheric perturbations due to aerosol emission from the earthquake sources recorded by satellites.

Photovoltaic materials convert light into electrical voltages. So far, most research in the field are focused on how to refine/improve the existing or standard photovoltaic cells to yield more efficient electricity, to reduce weight, to make more flexible shape, or to minimize costs under standard and uniform sunlight illuminations. In this project, we explore and demonstrate a hypothesis that non-uniform light illumination photovoltages can also be generated due to photo doping induced mobile charge carrier density gradient between light and dark areas in either p-type or n-type photo doping semiconductors. The term non-uniform light illumination was coined to refer to subjecting our photo sensing thin film devices to areas of high and low intensities of light illumination simultaneously, with an intention of creating a charge density gradient and therefore a voltage. Specifically, a polymeric composite thin film composed of P3HT (p-type photo doping semiconductor) and PCBM (photo doping electron acceptor and trap) at varying p-doping levels were studied. We observed that the fabricated photovoltaic cells with about 80% PCBM doped P3HT thin film devices exhibited 0.5-1.2 volts photovoltages under non-uniform light illuminations.

The quiet-time solar wind electrons feature non-thermal characteristics when viewed from the perspective of their velocity distribution functions. They typically have an appearance of being composed of a denser thermal “core” population plus a tenuous energetic “halo” population. At first, such a feature was empirically fitted with the Kappa velocity space distribution function, but ever since the ground-breaking work by Tsallis, the space physics community has embraced the potential implication of the Kappa distribution as reflecting the non-extensive nature of the space plasma. From the viewpoint of microscopic plasma theory, the formation of non-thermal electron velocity distribution function can be interpreted in terms of the plasma being in a state of turbulent quasi equilibrium. Such a finding brings forth the possible existence of a profound inter-relationship between the non-extensive statistical state and the turbulent quasi-equilibrium state. The present paper further develops the idea of solar wind electrons being in the turbulent equilibrium, but unlike the previous model, which involves the electrostatic turbulence near the plasma oscillation frequency (i.e., Langmuir turbulence), the present paper considers the impact of transverse electromagnetic turbulence, particularly, the turbulence in the whistler-mode frequency range. It is found that the coupling of spontaneously-emitted thermal fluctuations and the background turbulence leads to the formation of non-thermal electron velocity distribution function of the type observed in the solar wind during quiet times. This demonstrates that the whistler-range turbulence represents an alternative mechanism for producing the Kappa-like non-thermal distribution, especially close to the Sun and in the near-Earth space environment.

Redox mediators comprising I–, Co3+, and Ti3C2Tx MXene were applied to dye-sensitized solar cells (DSCs). In the as-prepared DSCs (I-DSCs), wherein hole conduction occurred via the redox reaction of I−/I3− ions, the power conversion efficiency (PCE) was not altered by the addition of Ti3C2Tx MXene. The I-DSCs were exposed to light to produce Co2+/Co3+-based cells (Co-DSCs), wherein the holes were transferred via the redox reaction of Co2+/Co3+ ions. A PCE of 9.01% was achieved in a Co-DSC with Ti3C2Tx MXene (Ti3C2Tx-Co-DSC), which indicated an improvement from the PCE of a bare Co-DSC without Ti3C2Tx MXene (7.27%). It was also found that the presence of Ti3C2Tx MXene in the redox mediator increased the hole collection, dye regeneration, and electron injection efficiencies of the Ti3C2Tx-Co-DSC, leading to an improvement in both the short-circuit current and the PCE when compared with those of the bare Co-DSC without MXene.

Solar photovoltaic (PV) generation suffers from multiple serious issues, for example shading effects directly affect the performance of installed PV arrays. By studying these issues, it can play a key role in improving the limitations and performance of PV panels. The study of PV arrays under partial shading conditions is mentioned in many papers as a part of other studies and as an independent phenomenon. Therefore, it is essential to improve these studies and update them with new research and study this problem in detail to know how to limit the effects of partial shading irradiance conditions on PV arrays performances, including economical aspects. This paper proposes to study the effects of different partial shading irradiance conditions for a PV array in various configurations. The analysis is proved in detail through the simulation of the proposed PV array in the Matlab/Simulink environment. The obtained results show the performances of interconnected PV arrays under different partial shading irradiance and temperature conditions, including the solar array I-V and P-V characteristics. In addition, different PV array configurations with and without bypass and blocking protection diodes improve and minimize the effect of partial shading conditions and avoid the reductions in output power.

This paper offers a theoretical and experimental examination of the concurrent production of electricity and heat using photovoltaic thermal (PV/T) technology. The efficiency performance of the PV/T system is meticulously analyzed using MATLAB/Simulink software environments. Notably, the proposed PV/T system shows reliable performance, and its validity is confirmed through experimental validation on a test stand with a single PV/T panel positioned at a 45-degree angle to the horizontal and a 0-degree azimuth angle.

With the popularity of solar energy in the electricity market, demand arises for data such as precise locations of solar panels for efficient energy planning, management, and distribution. However, this data is not easily accessible and in some cases, information such as precise locations does not exist. Furthermore, existing data sets for training semantic segmentation models of PV installations are limited, and their annotation is time-consuming and labor-intensive. Therefore, for additional remote sensing (RS) data creation, the pix2pix generative adversarial network (GAN) is utilized, enriching the original resampled training data of varying GSDs without compromising its integrity. Experiments done with the DeepLabV3 model, ResNet-50 backbone, and pix2pix GAN architecture were conducted to find the optimal configuration for an accurate RS imagery segmentation model. The result is a fine-tuned solar panel semantic segmentation model, trained using transfer learning and utilizing an optimal amount – 60% of generated RS imagery for additional training data, increasing model accuracy. The findings demonstrate the benefits of using GAN-generated images as additional training data, increasing the size of small data sets, and improving the capabilities of the segmentation model for solar panel detection in RS images.

The per capita availability of freshwater resources on a global scale is gradually decreasing due to population growth, rapid urbanization, industrialization, and modern lifestyles. In this situation, wastewater management becomes a major concern. Conventional treatment processes used to treat wastewater discharges are not adequate for the advanced removal of pollutants, especially refractory organic pollutants, which are mainly organic compounds that are not easily biodegradable in the environment. The use of photocatalytic membrane reactors (PMRs) for tertiary wastewater treatment has attracted much interest in recent periods, and various configurations have been investigated. The performance of a PMR using an iron doped titanium photo catalyst and Polysulfone-based polymeric membrane for municipal wastewater treatment was evaluated under natural and simulated solar light. Obtained results proved that solar driven PMRs can remove organic loading (COD) with high efficiencies and may represent a suitable alternative for the tertiary treatment step of municipal wastewater.

In this paper, the experimental results of the thermal sub-system of a reliable and cost-effective polygeneration solar system are presented. This polygeneration system produces heating, cooling and electricity from solar energy, which are used in an existing test-building. Heat is generated in four evacuated tube solar collectors (ETC). The heat may be used for space cooling, through a variable geometry ejector (VGE) heat pump. In order to reduce the mismatches between generation and consumption, two thermal storage tanks were added. The performance of a new thermal storage, with 400 l, able to storage both sensible and latent heat, was tested. Heating performances of the test-building were assessed. Ejector cycle tests were also performed.

Technological advancements must keep pace with earth’s rising demand for energy, while minimizing the carbon footprint on earth. One such option is using space based solar (SBS) radio frequency (RF) microwave power beaming. This innovative and novel technology is currently being explored to address terrestrial photovoltaic (PV) intermittency and provide a method to transmit power to other spacecraft in various orbits. This modality of power generation and distribution presents a new way to power terrestrial off-grid applications and earth orbiting spacecraft. In 1968, Dr. Peter Glaser published "Power from the Sun: Its Future", which serves as the foundation of this paper to revitalize scientific interest and efforts in this topic. This paper will primarily focus on the reliance of SBS initiatives on reusable launch vehicles (RLV) to place SBS spacecraft in a designated orbit, as well as the technological, economic, and operational challenges associated with power beaming to earth and other spacecraft. This includes a discussion of the variables from the operational environment that contribute or accelerate spacecraft end of life.

As the cost of conventional energy continues to rise, and concerns over the environment grow, there is a growing interest in sustainable energy. It is believed that conventional energy will only last for around 50 years, making it essential to find a renewable energy source that is safe and feasible to replace fossil fuels. Solar energy is a superior alternative to conventional energy, as it is renewable and produces green energy that can be used directly. The maritime industry has found itself at the forefront of an evolving environmental consciousness, driven by the imperative to mitigate the carbon footprint left in the wake of ships. In this journey towards sustainability, solar energy has emerged as a beacon of hope, harnessing the boundless energy of the sun to wean vessels off their dependence on fossil fuels. Technological advancements have made solar power more accessible, and we can now see the use of solar panels on large ships and small crafts to reduce fuel usage and emissions. Solar panels are also increasingly used to power homes and businesses, and many countries are implementing policies to encourage their use. Solar energy is a key solution in reducing our dependence on non-renewable energy sources and combating climate change. However, the adoption of solar energy is but a stepping stone towards maritime sustainability, as the integration of CO2 capture, utilization, and storage (CCUS) technologies promises to amplify the industry's environmental impact to unprecedented heights.

In the context of the French tertiary decree, it is crucial to reduce the energy consumption of buildings by first addressing the design of the electrical architecture. Implementing Direct Current (DC) nanogrids in buildings could offers a promising advantage for energy efficiency, significantly impacting overall energy consumption and sustainability goals. For an insulated area with a subtropical climate, such as La Réunion island, DC nanogrids could also facilitate the insertion of local renewable energy sources, especially solar energy. This article presents the deployment and efficiency evaluation of an end-to-end Low Voltage Direct Current (LVDC) nanogrid, from conception to real-world installation within a company. The nanogrid consists of a photovoltaic power plant, a Lithium-Iron-Phosphate (LFP) battery, and DC end-use equipment such as LED lighting and DC fans for two individual offices. An innovation is provided for the power supply and energy management of terminal equipment using the Power Over Ethernet (PoE) standard IEEE 802.3bt. The efficiency of the nanogrid is measured to be 40% higher than the efficiency of an installation powered by PV and distributed at 230 VAC. These results are obtained under certain deployment conditions, which are discussed in this article, in order to enhance the energy efficiency of buildings by using 48VDC. The nanogrid hardware and software infrastructure, the methodology employed for efficiency quantification and the measurement results are described in the paper.