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The intermittent power generation of renewable energy sources (RESs) interrupts the balance between power generation and demand load due to the increased frequency fluctuation, which challenges the frequency stability analysis and control synthesis of power generation systems. This paper proposes a robust distributed load frequency control (DLFC) scheme for multi-area power systems. Firstly, a multi-area power system is constructed by integrating photovoltaic (PV) and battery energy storage systems (BESSs). Then, by employing the linear matrix inequality (LMI) technique, the sufficient condition capable of ensuring that the proposed controller satisfies H ∞ robust performance in the sense of asymptotic stability is derived. Finally, testing is conducted on a four-area renewable power system, and results verify the strong robustness of the proposed controller against load disturbance and intermittence of RESs. [ABSTRACT FROM AUTHOR]

In this research, the design and simulation of a heat sink for photovoltaic panels were carried out using aluminum and copper, the most commonly used materials in heat dissipation systems. This heat sink consisted of fins that were tested both perforated and non-perforated to improve heat dissipation efficiency. This research stems from the need to reduce the temperature of photovoltaic panels during operation, as scientific evidence shows that photovoltaic panels experience a decrease in efficiency as the temperature increases, taking as a reference the temperature under standard test conditions. The simulations of photovoltaic panels with aluminum and copper fins, both perforated and non-perforated, followed a rigorous methodology. For validation, the simulation results were compared with field data, yielding a mean absolute percentage error of 1.71%. The findings indicate that copper fins reduced the temperature of the photovoltaic panel by 2.62 K, resulting in a 1.31% increase in efficiency. Similarly, aluminum fins reduced the temperature by 2.10 K, with a 1.05% increase in efficiency. Perforated copper fins achieved a temperature reduction of 3.07 K, increasing efficiency by 1.54%, while perforated aluminum fins reduced the temperature by 2.49 K, contributing to a 1.25% increase in efficiency. [ABSTRACT FROM AUTHOR]

This study focuses on microgrid systems incorporating hybrid renewable energy sources (HRESs) with battery energy storage (BES), both essential for ensuring reliable and consistent operation in off-grid standalone systems. The proposed system includes solar energy, a wind energy source with a synchronous turbine, and BES. Hybrid particle swarm optimizer (PSO) and a genetic algorithm (GA) combined with active disturbance rejection control (ADRC) (PSO-GA-ADRC) are developed to regulate both the frequency and amplitude of the AC bus voltage via a load-side converter (LSC) under various operating conditions. This approach further enables efficient management of accessible generation and general consumption through a bidirectional battery-side converter (BSC). Additionally, the proposed method also enhances power quality across the AC link via mentoring the photovoltaic (PV) inverter to function as shunt active power filter (SAPF), providing the desired harmonic-current element to nonlinear local loads as well. Equipped with an extended state observer (ESO), the hybrid PSO-GA-ADRC provides efficient estimation of and compensation for disturbances such as modeling errors and parameter fluctuations, providing a stable control solution for interior voltage and current control loops. The positive results from hardware-in-the-loop (HIL) experimental results confirm the effectiveness and robustness of this control strategy in maintaining stable voltage and current in real-world scenarios. [ABSTRACT FROM AUTHOR]

Background: Pemphigus vulgaris (PV) is a life-threatening autoimmune blistering disease caused mainly by IgG autoantibodies (auto-abs) against the cadherintype adhesion molecules desmoglein (Dsg) 1 and 3. Pathogenic anti-Dsg3 autoabs bind to different Dsg3 epitopes, leading, among others, to signalling that is involved in pathogenic events, such as Dsg3 depletion. As central tools in research on PV, a limited number of antibodies such as AK23 are frequently used by the autoimmune bullous disease community. Methods: Previously, we have introduced a novel Dsg3 EC5-binding antibody termed 2G4 that may potentially serve as a superior tool for numerous PV related analysis. The purpose of this study was to develop a quality-controlled production and verification process that allows I) a continuous quality improvement, and II) a verified and comprehensible overall quality with regard to pathogenic antigenspecific binding in a variety of pemphigus assays for each batch production. Results: Thus, a workflow based on a standardized operating procedure was established. This includes the verification of purity and in-vitro binding capacity (SDS-page, direct and indirect immunofluorescence) as primary parameters, and size analysis by mass-spectrometry and ex-vivo pathogenicity by monolayer dissociation assay. Conclusion: We here present an extensive point-by-point quality controlled IgG production protocol, which will serve as a basis for a standardized antibody assessment in PV research. [ABSTRACT FROM AUTHOR]

In Ethiopia, where millions rely on biomass, charcoal, and animal dung for energy, the predominant use is in baking injera, constituting over 50% of energy consumption. This traditional practice adversely affects the health of women and children and hampers education. To address this, solar energy is explored as a sustainable alternative. However, the intermittent nature of solar power poses challenges. A solution involves integrating a thermal storage system, ensuring a consistent and reliable energy supply for the crucial task of baking injera, ultimately improving lives and empowering communities. This study investigates the thermal characteristics of the charging and discharge processes and main heat transfer processes in the injera baking system with PV which was integrated with the thermal storage system. Our study journey began with exploring relevant papers and system designs, collecting and analyzing data, and, in addition, performing mathematical and numerical models. A numerical simulation was conducted using a finite‐difference computational model for the thermal storage containing PCM and thermal oil. The thermal oil was used to store energy and transfer heat; furthermore, the developed computational models were analyzed using MATLAB programming software. The numerical simulation result by using solar radiation data from Addis Ababa showed that the thermal storage has the capacity to store about 33.03 MJ during charging using constant heat flux which was from the PV. The amount of energy discharged from the PCM was 13.1 MJ, and from the thermia oil, it was 3.50 MJ using natural convection heat transfer, and the discharging and overall efficiency of the system were about 50.2% and 46.67%, respectively. Also, the baking pan surface temperature stayed between 220°C and 146.4°C for about 3 h. This result was compared with different papers, and it can be concluded that the numerically investigated solar‐powered injera baking integrated with thermal storage showed a promising result. [ABSTRACT FROM AUTHOR]

A photovoltaic thermal panel (PV/T) is an integrated module that harnesses both photovoltaic and solar thermal technologies to convert solar energy into electricity and heat, thereby enhancing overall energy efficiency. This paper aims to explore the suitability of PV/T solar heat pump systems across various climate zones and assess their potential for widespread application. By analyzing the operating principles of an indirect expansion PV/T solar heat pump system in conjunction with the climate characteristics of different regions, MATLAB R2019b/Simulink software was employed to evaluate the photoelectric performance of PV and PV/T systems in representative cities across five distinct climate zones in China during typical winter days. Key metrics, such as power generation, hot water storage tank temperature, indoor temperature, and system COP, were chosen to assess the heating performance of the PV/T solar heat pump system. The findings indicate that the winter ambient temperature significantly affects the photoelectric efficiency of both the PV and PV/T systems. While higher latitudes with lower ambient temperatures yield greater photoelectric efficiency, the southern regions exhibit higher power generation during winter. The winter heating effectiveness of the PV/T solar heat pump system is mainly influenced by indoor and water tank temperatures, with Harbin's system performing the poorest and failing to meet heating demands, whereas Nanjing's system shows the best results. [ABSTRACT FROM AUTHOR]

In the context of energy conversion from renewable sources to distribution grids (insulated or not), a converter is often required to transfer energy from a low voltage source towards three-phase grids. This paper presents the HW design, the simulation results, and the conversion performance of a CSI converter intended to interface low-voltage renewable sources to three-phase grids. The main focus of this paper is to obtain the best performance in terms of voltage increase towards the output stage while maximizing the conversion efficiency. In comparison with the currently used energy conversion systems for small photovoltaic systems, hereafter some solutions were adopted to level and maximize the energy flow from the source to the DC-link and improve the quality of current supplied in terms of harmonic distortion. The proposed system is composed of two conversion stages: the first, voltage-to-current, the second current-to-current via a three-phase CSI bridge modulated with the SVM technique. The stages are not completely decoupled from an electrical point of view; therefore, in order to mitigate the effects of these interactions, synchronization strategies have been adopted. [ABSTRACT FROM AUTHOR]

Copyright of Duzce University Journal of Science & Technology is the property of Duzce University Journal of Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The photovoltaic (PV) industry experienced a drastic overcapacity, leading to heightened market competition in 2009. After the overcapacity, the EU and the USA initiated trade barriers targeting Chinese PV goods in 2011, stimulating China to seek alternative markets. In 2013, China announced the Belt and Road Initiative (BRI). Although the BRI is a framework of international cooperation instead of a specific strategy that aims at PV industry, its role in helping Chinese PV firms deal with the trade sanction should be addressed. Based on the data from Chinese Custom Trade Statistics spanning 2009 to 2016, this paper precisely quantifies the extent of PV trade deflection from China to BRI markets that can be ascribed to the BRI effects. Employing spatial analysis, we manifest the trade deflection on maps. Moreover, we adopt the linear probability models and panel logit models to investigate the impact of BRI on China's PV export expansion. The results show that BRI markets provide a buffer area for Chinese PV enterprises to alleviate their loss caused by trade sanctions. The BRI facilitated 4751 million more PV products conveyed from China to BRI markets from 2013 to 2016, occupying about 33.25% of the total export from China to BRI markets. Chinese PV firms prefer to explore the BRI markets than the rest of the world. Compared to state-owned enterprises (SOEs), non-SOEs are more active in entering BRI countries. However, no significant difference had been detected in BRI effects on SOEs and non-SOEs. It was noted that a robust local industrial basement related to the PV industry can potentially ease firms' transition to BRI markets. Comparatively, firms situated in central China have benefited more from the BRI than their counterparts in the coastal and western regions. Furthermore, the BRI encourages Chinese PV enterprises to venture into countries with low economic complexity. This paper provides novel insights into BRI by validating BRI's effects on Chinese PV firms' export expansion. On the one hand, unlike previous BRI research that rarely considers the unstable external environment, we validate that the BRI can provide a spare market for China when it competes with developed countries. On the other hand, by investigating the roles of firms, regions and destinations, our results are enlightening for renewable energy industrial and trade policymakers. [ABSTRACT FROM AUTHOR]

Many countries are adopting renewable energy (RE) and electric vehicles (EVs) to achieve net-zero emissions by 2050. The indicators of RE and EV potentials are different. Decision-makers want to introduce RE and EVs; however, they need a method to find suitable areas. In addition, this is required in the time-series analysis to provide a detailed resolution. In this study, we conducted a time-series analysis in Japan to evaluate suitable areas for the combined use of RE and EVs. The results showed the surplus RE areas and shortage RE urban areas. The time-series analysis has quantitatively shown that it is not enough to charge EV batteries using surplus RE. Moreover, a ranking methodology was developed for the evaluation based on electric demand and vehicle numbers. This enables the government's prioritization of prefectures and the prefectures' prioritization of municipalities according to their policies. [ABSTRACT FROM AUTHOR]

Abstract This paper proposes a new energy management system to combine Fuel Cells (FC) and photovoltaic (PV) panels as primary power sources. Also, battery and Super Capacitor (SC) banks are considered as secondary energy systems. The high power density and the fast dynamics of SCs combined with the high energy density and medium dynamics of batteries would be an ideal combination for FC vehicles. The high step-up DC/DC converter is used along with the implementation of the maximum power point tracking algorithm (MPPT) to adapt the low power of PV panels with the high power of DC-Link. Also, an evolutionary optimization algorithm is proposed along with the FOPI controller to improve the output of the energy management algorithm and control the sources more efficiently. The simulation results are validated for a standard urban driving cycle. It indicates for the case of the sustained presence of a PV source during a typical driving cycle, the source delivers about 55% of its maximum power.

Abstract This study proposes a distinct coordination control and power management approach for hybrid residential microgrids (MGs). The method enhances the feasibility of hybrid MGs by reducing power loss on ILBCs. The MG has been modeled with solar and wind generators. The MG comprises multiple direct current (DC) and alternating current (AC) sub-microgrids (SMGs) with varying voltage levels. The coordination control and power management strategies for autonomous hybrid MGs with primary and secondary control levels. A novel technique is proposed to ensure seamless and precise power transfer among SMGs while minimizing the constant operation of ILBCs in islanded mode, with a focus on the secondary control level. The study uses MATLAB/Simulink to analyze on-grid, off-grid, and transient mode power transfer among MG. The MG has been operative during transient/faulty conditions. The results indicate that the proposed method demonstrates excellent adaptability in managing power flow.

[Introduction] The rapid development of new energy vehicles (NEVs) brings higher requirements for the power demand of highways. Based on the analysis of the power loads of highways, the photovoltaic endowment, and the energy storage technologies suitable for highway service areas in China, this paper explores the self-consistency of the highway transportation and energy integration mode of the PV-Storage-Charging integrated development path, and combines practical engineering project to demonstrate and analyze the feasibility of the highway transportation and energy integration mode. [Method] By analyzing the total mileage of highways in China, the market penetration rate of NEVs, and the PV & energy storage resources of highway transportation, based on the potential increase in highway power load due to the growth of NEVs and the utilization space of photovoltaic resources in highway transportation, a comprehensive energy utilization mode of PV-Storage-Charging for highway service areas was proposed. Combined with existing projects of self-consistent modes of transportation and energy integration, suggestions were proposed for the integrated development mode of highway PV-Storage-Charging. [Result] Data indicates that by 2025, the national stock of NEVs will exceed 25 million, consuming 37.5 TWh of electricity, showing tremendous potential for electricity demand. At the same time, the abundant photovoltaic resources along and around roads in China have a photovoltaic generation potential of approximately 1022.8 TW, while the calculated annual energy consumption of highway infrastructure is approximately 17.99 TW. [Conclusion] The main path of integration between transportation and energy should start with developing wind and photovoltaic natural resource endowments based on the infrastructure of road transportation itself, and forming a self-consistent supply of transportation energy systems, thereby constructing a distributed, green, renewable, and net zero-emission energy supply system for transportation systems. The integrated development path of PV-Storage-Charging transportation and energy integration can consume renewable energy locally, alleviate grid pressure while promoting the clean energy utilization of highways, showing immense potential. This paper can provide theoretical support and reference for the development of highway transportation and energy integration in China.

Australia aims to achieve net zero emissions by 2050, with an interim target of reducing emissions to 43% below 2005 levels by 2030. Electrification of industry processes currently reliant on fossil fuels is a necessary step to achieve these emission reduction goals. This study investigates electrification of steam generation relevant to major industrial operations in the southwest of Western Australia using different renewable energy input levels. The designed system incorporates thermal storage to ensure continuous steam generation. The optimized technology mix, including wind, PV, and concentrated solar thermal (CST) systems for each renewable energy input target, is presented. The optimization process also identifies optimal locations for new renewable energy plants. In summary, the optimization tends towards favouring the development of large CST plants near a demand point. This avoids the use of the transmission network by direct use of the CST system for heating of the storage media, to address the costs and efficiency reductions arising from electrical heating, but the scope of CST use is expected to be limited by site constraints. The levelized cost of heat (LCOH) for the studied renewable energy input targets (i.e., 30–90%) ranges from 15.34 to 36.92 AUD/GJ. This is promising for the 30% renewable energy target, as future natural gas prices in Western Australia are likely to match or exceed the expected LCOH. Cost reductions for renewable generation and storage technologies with further implementation at a large scale in the future may result in more competitive LCOH at higher decarbonization levels, but it is likely that additional technologies will be required for cost competitiveness at very high decarbonization levels.

Abstract This study investigates the viability of hybrid photovoltaic (PV), wind, and fuel cell (FC) systems for on‐grid and off‐grid operations for the Ashrayan‐3 housing project in Bangladesh, with an increased focus on sustainable energy solutions. Motivated by the issue of the delivery of proper and sustainable energy services to remote locations, we conducted an extensive analysis of load demand and found that an average daily demand of 46,176.65 kWh exists, with a peak load of 4852.8 kW. In this research, the HOMER software has been used to make a simulation of five different hybrid system configurations with differing mixes of renewable technologies. From the analyses, the systems based 100% on renewable resources suffer more initial capital costs, with a total net present cost increase of up to 20%, in comparison to conventional systems. On the other hand, the systems give much lower operational costs and cost of energies (COEs) of a minimum of $0.0253/kWh, reported from the on‐grid PV‐based system. On the other hand, the off‐grid PV–FC–wind turbine system showed a COE of $0.286/kWh, along with a decrease in CO2 emissions by about 15,000 kg/year, showing a 30% decrease, compared with on‐grid systems. The results form a basis for the conclusion that such hybrid renewable energy systems are both economically and environmentally feasible. They can reduce COEs by up to 70% in off‐grid systems. This proves that the quality of life and energy security in developing regions will be highly increased, supporting the goals of sustainable development.

Li-ion batteries can be charged with different techniques according to the charging time and required capacity usage. Most charging techniques face difficulties when implemented in PV systems due to the intermittent and unpredictable nature of the power supply. This paper addresses the issue of determining the appropriate charging technique for Li-ion batteries in a PV system. We have developed a mode-selective control approach that determines the optimal charging mode according to the given SOC and solar irradiation, aiming to maximize the utilization of the generated PV power. The developed control approach has been implemented using a dual-switched buck converter in the MATLAB/Simulink environment. The key control algorithm focused on regulating current, with different references being used based on the selected charging mode. Three references for charging current were set: the maximum current, the required current assigned based on the given SOC, and the pulsed current. The pulsed current reference was employed during a stage of the charging process to accelerate charging and prevent dissipation of PV power. Furthermore, a gain-scheduled controller with carefully picked control parameters was used to ensure stable operation across different modes. The results proved the effectiveness of the proposed control in reducing charging time and minimizing PV power dissipation without resorting to the use of harmful charging currents.

Among the various renewable energy-based technologies, photovoltaic panels are characterized by a high rate of development and application worldwide. Many efforts have been made to study innovative materials to improve the performance of photovoltaic cells. However, the most commonly used crystalline panels also have significant potential to enhance their energy yield by providing cooling and cleaning solutions. This paper discusses the possibility of introducing a dedicated direct-water cooling and cleaning system. As assumed, detailed schedules of the operation of the developed direct water cooling and cleaning system should be fitted to actual weather conditions. In this context, different cooling strategies were proposed and tested, including different intervals of opening and closing water flow. All tests were conducted using a dedicated experimental rig. 70 Wp monocrystalline panels were tested under laboratory conditions and 160 Wp polycrystalline panels were tested under real conditions. The results showed that introducing a scenario with a 1-min cooling and a 5-min break allowed for proving the panel's surface temperature lower than 40 °C. In comparison, the temperature of the uncooled panel under the same operating conditions was close to 60 °C. Consequently, an increase in power generation was observed. The maximum power increase was observed in July and amounted to 15.3%. On the other hand, considering selected weeks in May, July, and September, the average increase in power generation was 3.63%, 7.48%, and 2.51%, respectively. It was concluded that the division of photovoltaic installation allows reasonable operating conditions for photovoltaic panels with a lower amount of energy consumed to power water pumps. [ABSTRACT FROM AUTHOR]

Copyright of Southern Energy Construction is the property of Southern Energy Construction Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Australia aims to achieve net zero emissions by 2050, with an interim target of reducing emissions to 43% below 2005 levels by 2030. Electrification of industry processes currently reliant on fossil fuels is a necessary step to achieve these emission reduction goals. This study investigates electrification of steam generation relevant to major industrial operations in the southwest of Western Australia using different renewable energy input levels. The designed system incorporates thermal storage to ensure continuous steam generation. The optimized technology mix, including wind, PV, and concentrated solar thermal (CST) systems for each renewable energy input target, is presented. The optimization process also identifies optimal locations for new renewable energy plants. In summary, the optimization tends towards favouring the development of large CST plants near a demand point. This avoids the use of the transmission network by direct use of the CST system for heating of the storage media, to address the costs and efficiency reductions arising from electrical heating, but the scope of CST use is expected to be limited by site constraints. The levelized cost of heat (LCOH) for the studied renewable energy input targets (i.e., 30–90%) ranges from 15.34 to 36.92 AUD/GJ. This is promising for the 30% renewable energy target, as future natural gas prices in Western Australia are likely to match or exceed the expected LCOH. Cost reductions for renewable generation and storage technologies with further implementation at a large scale in the future may result in more competitive LCOH at higher decarbonization levels, but it is likely that additional technologies will be required for cost competitiveness at very high decarbonization levels. [ABSTRACT FROM AUTHOR]

The efficiency of solar systems, in particular photovoltaic panels, is typically low. Various environmental parameters affect solar panels, including sunlight, the ambient and module surface temperatures, the wind speed, humidity, shading, dust, the installation height, etc. Among others, the key players are indeed solar irradiance and temperature. The higher the temperature is, the higher the short-circuit current is, and the lower the open-circuit voltage is. The negative effect of lowering the open-circuit voltage is dominant, consequently lowering the power of the photovoltaic panels. Passive or active cooling systems can be provided to avoid the negative effect of temperature. This paper presents a prototype of an active cooling system dedicated to photovoltaics. The prototype of such a system was developed at the AGH University of Kraków and tested under laboratory conditions. The proposed system is equipped with air fans mounted on a plate connected to the rear part of a 70 Wp photovoltaic panel. Different configurations of the system were tested, including different numbers of fans and different locations of the fans. The artificial light source generated a irradiation value of 770 W/m2. This value was present for every variant tested in the experiment. As observed, the maximum power generated in the photovoltaic panel under laboratory conditions was approx. 47.31 W. Due to the temperature increase, this power was reduced to 40.09 W (when the temperature of the uncooled panel surface reached 60 °C). On the other hand, the power generated in the photovoltaic panel equipped with the developed cooling system was approx. 44.37 W in the same conditions (i.e., it was higher by 10.7% compared to that of the uncooled one). A mathematical model was developed based on the results obtained, and simulations were carried out using the ANSYS Workbench software. After the validation procedure, several configurations of the air cooling system were developed and analyzed. The most prominent case was chosen for additional parametrical analysis. The optimum fan orientation was recognized: a vertical tilt of 7° and a horizontal tilt of 10°. For the tested module, this modification resulted in a cost-effective system (a net power increase of ~3.1%). [ABSTRACT FROM AUTHOR]

Depending on the PV power, load power, and battery status, the system may operate in different modes. The control loop may have to switch between operating modes. In practice, it is difficult to implement control loop switching because the transition and dynamic process are difficult to control. As a result, this paper presents a generalized mode control method that avoids loop switching across modes. First, system structure and topology are introduced. The operating conditions for both grid-connected and off-grid modes are then divided into six sub-cases. Furthermore, the control architecture, control loop, and reference transition for various scenarios are described. Finally, an experimental platform is built, and the results are presented to verify the proposed method. [ABSTRACT FROM AUTHOR]

In people with multiple sclerosis (MS), newborn and surviving oligodendrocytes (OLs) can contribute to remyelination, however, current therapies are unable to enhance or sustain endogenous repair. Low intensity repetitive transcranial magnetic stimulation (LI-rTMS), delivered as an intermittent theta burst stimulation (iTBS), increases the survival and maturation of newborn OLs in the healthy adult mouse cortex, but it is unclear whether LI-rTMS can promote remyelination. To examine this possibility, we fluorescently labelled oligodendrocyte progenitor cells (OPCs; Pdgfrα-CreER transgenic mice) or mature OLs (Plp-CreER transgenic mice) in the adult mouse brain and traced the fate of each cell population over time. Daily sessions of iTBS (600 pulses; 120 mT), delivered during cuprizone (CPZ) feeding, did not alter new or pre-existing OL survival but increased the number of myelin internodes elaborated by new OLs in the primary motor cortex (M1). This resulted in each new M1 OL producing ~ 471 µm more myelin. When LI-rTMS was delivered after CPZ withdrawal (during remyelination), it significantly increased the length of the internodes elaborated by new M1 and callosal OLs, increased the number of surviving OLs that supported internodes in the corpus callosum (CC), and increased the proportion of axons that were myelinated. The ability of LI-rTMS to modify cortical neuronal activity and the behaviour of new and surviving OLs, suggests that it may be a suitable adjunct intervention to enhance remyelination in people with MS. [ABSTRACT FROM AUTHOR]

Tomato fruit is a source of many important nutrients. It is difficult to store it for a long time because it contains a high percentage of moisture. The moisture content could be reduced in different ways to restrict the high growth of fungi. This study mainly aims to manufacture a simple and easy-to-use solar dryer for drying tomato fruits with solar cell-based fans. This method can be adapted to dry a wide range of Vegetables and fruits. The measured factors in this study are solar radiation, ambient temperature, relative humidity, and drying time. Solar drying is an affordable method to soothe the negative impact of post harvest losses on cultivators in Iraq. A greenhouse dryer (1 × 0.5 × 0.5 m) was constructed using glass of (τ = 0.9 for 0.4 μm < λ < 0.7 μm and τ = 0.01 for λ > 0.7 μm). Two fans are used to force an airstream with an average velocity of 0.025 m/s at the tray section. A selected quantity of tomato was washed and ground, making 1 kg of puree to check the effectiveness of the dryer. An experiment conducted on 10-11 March 2023 showed that 14 drying hours are needed to bring the paste to an acceptable quality of 0.25 brix. The efficiency of the greenhouse has not exceeded 25% on average, accompanied by an average drying rate of 60 g/hr. It was found that converting the perishable tomato crop into paste is profitable for cultivators in Iraqi conditions. Using a solar dryer is particularly profitable for local farmers by reducing crop losses, as per 1 m2 land area, a production of 6 kg of tomatoes is expected with losses of about 1 kg, and a profit of 6 thousand IQD and losses of 1 thousand IQD. A land area of 1 m2 with a dryer produces 3.6 kg of tomatoes converted into 1.008 kg tomato paste producing 15 thousand IQD without losses. [ABSTRACT FROM AUTHOR]

Rural electrification is a crucial step for the socio-economic development of isolated communities. Decentralized power generation, typically more favorable for renewable energies, requires an accurate analysis of the different electrification options, whose convenience depends on multiple factors. The application of Geographical Information Systems (GISs) to energy planning allows the assessment at a local level, considering the variability and demand distribution of spatial resources. This work introduces IntiGIS-local, a GIS-based model implemented in the ArcGIS environment, designed to calculate the levelized energy cost (LEC) for different electrification options. The model allows the comparison between three power generation alternatives: solar system, diesel generator set and solar–diesel hybrid system. Configurations are adjustable through input variables, with a special focus on the confrontation between individual systems and microgrids. The objective is to provide an adequate groundwork for developing a decision-making tool to assess diverse rural electrification options in future studies. The model IntiGIS-local is tested in the case study of the Guasasa community (Cuba). [ABSTRACT FROM AUTHOR]

Solar energy is one of the main renewable energies available to fulfill global clean energy targets. The main issue of solar energy like other renewable energies is its randomness and intermittency which affects power grids stability. As a solution for this issue, energy storage units could be used to store surplus energy and reuse it during low solar generation intervals. Also, in order to sustain stable power grid and better grid operation and energy storage management, photovoltaic (PV) power forecasting is inevitable. In this paper, new hybrid model based on deep learning techniques is proposed to predict short-term PV power generation. The proposed model incorporates convolutional neural network (CNN) and long short-term memory (LSTM) autoencoder network. The new model differentiates itself in accomplishing high prediction accuracy by extracting spatial features in time series via CNN layers and temporal features between the time series data through LSTM. The introduced model is tested on dataset of power generation from southern UK solar farm and the weather data corresponding to same location and time intervals; the forecasting performance of the suggested model is evaluated in metrics of root-mean-square error (RMSE) and mean absolute error (MAE). The used model is compared with different models from the literature either of pure type of network such as LSTM and gated recurrent unit (GRU) or hybrid combination of different networks like CNN-LSTM and CNN-GRU. The results show that proposed model provides enhanced results and reduces training time significantly compared to other competitive models, where the performance of the proposed model improved averagely by 5% to 25% in terms of RMSE and MAE performance metrics, and the execution time of training significantly reduced with almost 70% less compared to other models. [ABSTRACT FROM AUTHOR]

This study investigates the viability of hybrid photovoltaic (PV), wind, and fuel cell (FC) systems for on‐grid and off‐grid operations for the Ashrayan‐3 housing project in Bangladesh, with an increased focus on sustainable energy solutions. Motivated by the issue of the delivery of proper and sustainable energy services to remote locations, we conducted an extensive analysis of load demand and found that an average daily demand of 46,176.65 kWh exists, with a peak load of 4852.8 kW. In this research, the HOMER software has been used to make a simulation of five different hybrid system configurations with differing mixes of renewable technologies. From the analyses, the systems based 100% on renewable resources suffer more initial capital costs, with a total net present cost increase of up to 20%, in comparison to conventional systems. On the other hand, the systems give much lower operational costs and cost of energies (COEs) of a minimum of $0.0253/kWh, reported from the on‐grid PV‐based system. On the other hand, the off‐grid PV–FC–wind turbine system showed a COE of $0.286/kWh, along with a decrease in CO2 emissions by about 15,000 kg/year, showing a 30% decrease, compared with on‐grid systems. The results form a basis for the conclusion that such hybrid renewable energy systems are both economically and environmentally feasible. They can reduce COEs by up to 70% in off‐grid systems. This proves that the quality of life and energy security in developing regions will be highly increased, supporting the goals of sustainable development. [ABSTRACT FROM AUTHOR]

Li-ion batteries can be charged with different techniques according to the charging time and required capacity usage. Most charging techniques face difficulties when implemented in PV systems due to the intermittent and unpredictable nature of the power supply. This paper addresses the issue of determining the appropriate charging technique for Li-ion batteries in a PV system. We have developed a mode-selective control approach that determines the optimal charging mode according to the given SOC and solar irradiation, aiming to maximize the utilization of the generated PV power. The developed control approach has been implemented using a dual-switched buck converter in the MATLAB/Simulink environment. The key control algorithm focused on regulating current, with different references being used based on the selected charging mode. Three references for charging current were set: the maximum current, the required current assigned based on the given SOC, and the pulsed current. The pulsed current reference was employed during a stage of the charging process to accelerate charging and prevent dissipation of PV power. Furthermore, a gain-scheduled controller with carefully picked control parameters was used to ensure stable operation across different modes. The results proved the effectiveness of the proposed control in reducing charging time and minimizing PV power dissipation without resorting to the use of harmful charging currents. [ABSTRACT FROM AUTHOR]

The rising electricity costs, cost of space heating, and domestic hot water end up driving consumers toward reducing expenses by generating their electricity through devices like photovoltaic systems and efficient combined heat and power plants. When coupled with thermal systems via an energy management system (EMS) in a Multi-Energy System (MES), this self-produced electricity can effectively lower electricity and heating bills. However, MESs with EMSs can serve various purposes beyond cost reduction via self-consumption, such as reacting to variable electricity prices, meeting special grid connection conditions, or minimizing CO2 emissions. These diverse strategies create unique prosumer profiles, deviating significantly from standard load profiles. The potential threat to the power grid arises as grid operators lack visibility into which consumers employ which control strategies. This paper investigates the impact of controlled MESs on the power grid compared to average households and answers whether new control strategies affect the planning strategies of low voltage grids. It proposes a comprehensive four-step toolchain for the detailed simulation of thermal–electrical load profiles, MES control strategies, and grid dynamics. It includes a new method for the grid impact analysis of extreme and average bulk values. As a result, this study identifies three primary factors influencing distribution power grids by MESs. Firstly, the presence and scale of photovoltaic (PV) systems significantly affect extreme values in the grid. Secondly, MESs incorporating combined heat and power (CHP) and heat pump (HP) units impact the overall grid performance, mainly reflected in bulk values. Thirdly, the placement of an MES with heating systems, especially when concentrated in one feeder, plays a crucial role in grid dynamics. Despite the three distinct factors identified as impactful on the power grid, this study reveals that the various control strategies, despite leading to vastly different grid profiles, do not exhibit divergent impacts on buses, lines, or transformers. Remarkably, the impact of MESs remains consistently similar across the range of control strategies studied. Therefore, different control strategies do not pose an additional challenge to the grid integration of MESs. [ABSTRACT FROM AUTHOR]

To optimize the capacities and locations of newly installed photovoltaic (PV) and battery energy storage (BES) into power systems, a JAYA algorithm-based planning optimization methodology is investigated in this article. For this purpose, a series of mathematical models with constraint conditions are put forward to describe the dynamic properties of PVs and BES systems. Then, a general two-level planning model for maximizing the benefits of society is employed by introducing objective functions at the investment and operational levels from comprehensive influencing factors under different companies. To determine the optimal locations and capacities for configuring renewable energy sources, the proposed planning framework is solved using the JAYA algorithm. Finally, the effectiveness and reliability of the proposed configuration method are validated using an Institute of Electrical and Electronics Engineers (IEEE) 24-bus system with PVs and BES systems. Comparing the results of the various cases, it is obvious that the JAYA-based two-level planning optimization method can find the optimal configuration with minimum cost in shorter convergence times. Hence, the configuration strategy determined via the planning optimization method using the JAYA algorithm offers valuable guidance for the installation capacities and layouts of PVs and BES systems in power systems, which underscores their practical significance in energy management.

In photovoltaic (PV)-based power generation systems, the conventional and interleaved boost converter undertakes a pivotal task by augmenting its low output voltage to high voltage level. These converters have some prominent drawbacks like low voltage gain, high current ripple, unsmooth dc voltage and insufficient efficiency. This paper aims to propose an innovative high-gain multi-stage non-isolated step-up converter (HGNISUC) to triumph over these drawbacks. The proposed structure has been generally constructed using a high-voltage gain dc-dc converter and a classic rectifier which can provide high voltage gain based on dual-winding coupled-inductor (DWCI). Its cost is significantly reduced due to utilization of only one switch and one medium frequency transformer. Since the proposed structure has been operated in the PV system, an optimal interval type-2 fuzzy system based maximum power point tracking (OIT2FS-MPPT) has been designed to transfer the maximum power of solar-energy module to the load side. Due to the multi-objective nature of the control problem, multi-objective grey wolf optimizer (MOGWO) is used to optimally tune the controller parameters. Finally, the performance of the proposed converter has been validated under both MATLAB simulation and lab prototype tests.

The basolateral amygdala (BLA) is a key site where fear learning takes place through synaptic plasticity. Rodent research shows prominent low theta (~3–6 Hz), high theta (~6–12 Hz), and gamma (>30 Hz) rhythms in the BLA local field potential recordings. However, it is not understood what role these rhythms play in supporting the plasticity. Here, we create a biophysically detailed model of the BLA circuit to show that several classes of interneurons (PV, SOM, and VIP) in the BLA can be critically involved in producing the rhythms; these rhythms promote the formation of a dedicated fear circuit shaped through spike-timing-dependent plasticity. Each class of interneurons is necessary for the plasticity. We find that the low theta rhythm is a biomarker of successful fear conditioning. The model makes use of interneurons commonly found in the cortex and, hence, may apply to a wide variety of associative learning situations.

Forest wildfire disturbance information extracting − extracting the changes in vegetation and the condition of the burned areas − is essential for post-fire management and effective forest recovery. This study derived ecological indicators from remote sensing time series data. Time series analysis methods and change detection algorithms were applied to assess these indicators, enabling the identification of spatiotemporal information of fire disturbances. We selected the Sen + Mann-Kendall model, Coefficient of variation, Hurst exponent and Slope trend analysis to analyze the long-term impacts of the indicators extracted from Landsat images, including photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV), bare rocky (BR) and normalized burn ratio (NBR). We determined the spatial distribution and timing of wildfires by analyzing the variations and fluctuations in indicators. The variation patterns of the indicators following the fires are as follows: PV and NBR decreased, while NPV and BR initially increased and subsequently decreased. By analyzing the time series analysis results of PV, NPV, BR, and NBR, the spatio-temporal information of the fires could be determined. Additionally, we used the stacked convolution long short-term memory (Stacked ConvLSTM) neural network to extract the burned area. The area extraction accuracy of this algorithm is approximately 98.43 %. Finally, the ensemble empirical mode decomposition (EEMD) was utilized to unmix the monthly mean PV, thereby obtaining the periods of vegetation recovery over multiple years. The recovery period of vegetation post-fire ranges from 3 to 12 months. This study proposes a method for comprehensively extracting information on forest wildfire disturbances at a spatiotemporal scale and discusses the recovery period of vegetation following the wildfires, as well as future development trends. It’s crucial for evaluating the impacts on the ecological environment and subsequent restoration.

This research focuses on the development and simulation analysis of heat-dissipating fins made of copper, integrated into photovoltaic panels, with the aim of mitigating temperature increases during operation. This initiative arises from evidence that solar panels experience a reduction in energy efficiency when operating at temperatures higher than standard test conditions. The photovoltaic panel was simulated both without fins and with fins under standard test conditions and extreme conditions. The simulation consists of the following steps: design, meshing, selection of physical models and materials, assignment of boundary conditions, validation of the simulation, and interpretation of the results. During validation, results obtained via simulation were compared experimentally, yielding a mean absolute percentage error of 0.28%. It was concluded that the fins with the greatest heat dissipation relative to their area are those of 40 mm height; with this height, the temperature of the photovoltaic panel is reduced by 2.64 K, which represents an efficiency increase of 1.32%. Furthermore, it was concluded from the analyzed data that the efficiency of the fins increases at high temperatures.

Rooftop solar photovoltaics can significantly contribute to global energy transitions by providing clean, decentralized energy without the need for new land, thereby avoiding land-use conflicts. It serves as a valuable complement to other renewable-energy sources and is expected to play a crucial role in future electricity systems. Due to the spatiotemporal variability in the solar radiation on roof surfaces, it is essential to determine the potentials of the rooftop photovoltaics and its variations in specific regions. In Germany, this potential was assessed in 5 km × 5 km zones, as well as at the federal-state and national levels. High-quality satellite and reanalysis data were used to determine the power output of the solar photovoltaics. Additionally, high-resolution (2 m × 2 m) European Settlement Map data, calibrated with solar cadastre data, were utilized to evaluate different scenarios. The results show that the potential is concentrated in larger urban areas and the southwestern part of Germany due to the availability of rooftop space and solar radiation. Overall, the national rooftop areas are substantial across all scenarios, ranging from 2100 to 4500 km2. The applied methods and scenarios provide a straightforward way to reveal the spatiotemporal variability and define realistic ranges of the solar photovoltaic potential without requiring detailed information about each building. However, assessing the rooftop photovoltaic potential remains challenging and uncertain due to the lack of large-scale, high-resolution data on building characteristics and the complexity of the solar radiation distribution in urban environments. [ABSTRACT FROM AUTHOR]

This paper investigates grid export constraints applicable to photovoltaic (PV) and wind farm (WF) installations, both with and without behind-the-meter storage, aimed at enhancing grid hosting capacity. The study focuses on static output power limitations, i.e., simple export constraints that are preventively imposed on renewable energy source (RES) plants regardless of the prevailing network congestion conditions. These constraints are easy to apply, implemented ex ante and out of market, and do not require additional investments in energy storage or advanced devices. They also yield a measurable increase in hosting capacity and grid utilization, with their impact on RES plant operation and return of investment straightforwardly calculable. Analysis defines the level and shape of these constraints assuming an indicative acceptable curtailment level of 5% for each RES technology attributed to the preventing action of the imposed limitations, while the respective implications for RES energy yield and investment viability are explored. The findings indicate that an export power limitation of ca. 68% is effective for stand-alone PVs, while a stepwise static limitation is necessary for stand-alone WFs and WFs with integrated storage to manage midday solar generation peaks. PV plants tightly coupled with storage facilities can handle static limitations as low as 35% with minimal impact on the economic feasibility of the investments. [ABSTRACT FROM AUTHOR]

One of the challenges of renewable energy is its uncertain nature. Community shared energy storage (CSES) is a solution to alleviate the uncertainty of renewable resources by aggregating excess energy during appropriate periods and discharging it when renewable generation is low. CSES involves multiple consumers or producers sharing an energy storage system. This work presents an optimal strategy for CSES operators and community members to determine their optimal energy trading strategy based on social welfare maximization. Energy communities contain diverse resources, demand patterns, and constraints. The Alternating Direction Method of Multipliers (ADMM) technique is an iterative nature that decomposes the original problem into smaller sub-problems and enables parallel processing of these sub-problems. The final decomposed subproblems enable community agents to determine their optimal strategies independently decreasing the solving time, speeding up convergence to the optimal solution, and improving the scalability. The performance of the proposed model is evaluated by a case study. The presented model demonstrates that by leasing the capacity of CSES, community members could decrease their energy supply costs. Moreover, the CSES can supply the required charging and discharging power of community members from the local grid. [ABSTRACT FROM AUTHOR]

This research focuses on the development and simulation analysis of heat-dissipating fins made of copper, integrated into photovoltaic panels, with the aim of mitigating temperature increases during operation. This initiative arises from evidence that solar panels experience a reduction in energy efficiency when operating at temperatures higher than standard test conditions. The photovoltaic panel was simulated both without fins and with fins under standard test conditions and extreme conditions. The simulation consists of the following steps: design, meshing, selection of physical models and materials, assignment of boundary conditions, validation of the simulation, and interpretation of the results. During validation, results obtained via simulation were compared experimentally, yielding a mean absolute percentage error of 0.28%. It was concluded that the fins with the greatest heat dissipation relative to their area are those of 40 mm height; with this height, the temperature of the photovoltaic panel is reduced by 2.64 K, which represents an efficiency increase of 1.32%. Furthermore, it was concluded from the analyzed data that the efficiency of the fins increases at high temperatures. [ABSTRACT FROM AUTHOR]

In unpredictable weather circumstances, a maximum power point tracking (MPPT) approach is critical for ensuring maximum photovoltaic (PV) output power is extracted. In this paper, we will compare the incremental conductance algorithm (IC), perturb and observe (p&o), and fuzzy logic controller (FLC) as maximum power point tracking (MPPT) techniques. The three algorithms were used on a photovoltaic energy conversion system that was linked to a grid. The suggested methodologies investigate the photovoltaic (PV) system's solar energy conversion performance under various irradiance and temperature circumstances. Lastly, a performance comparison between IC, P O, and FLC has been performed, demonstrating the superiority of the fuzzy controller over the other approaches. FLC converts photovoltaic electricity readily, reducing fluctuations, and it responds quickly to variations in solar irradiation (the shading effect). The simulation results demonstrate that the controller using fuzzy logic performs well, allowing the inverter to convert the electricity provided by the solar panels. [ABSTRACT FROM AUTHOR]

Electric vehicle (EV) charging facilities are essential to their development and deployment. These days, autonomous microgrids that use renewable energy resources to energize charging stations for electric vehicles alleviate pressure on the public electricity grid. Nevertheless, controlling and managing such charging stations' energy is difficult due to the nonlinearity and irregular character of renewable energy sources. The current research recommends using a Brain Emotional Learning Intelligent Control (BELBIC) controller to enhance an autonomous EV charging station's performance and power management. The charging station uses a battery to store energy and is primarily powered by photovoltaic (PV) solar energy. The principles of BELBIC are dependent on emotional cues and sensory inputs, and they are based on an emotion processing system in the brain. Noise and parameter variations do not affect this kind of controller. In this study, the performance of a conventional proportional–integral (PI) controller and the suggested BELBIC controller is evaluated for variations in solar insolation. The various parts of an EV charging station are simulated and modelled by the MATLAB/Simulink framework. The findings show that, in comparison to the conventional PI controller, the suggested BELBIC controller greatly enhances the transient responsiveness of the EV charging station's performance. The EV keeps charging while the storage battery perfectly saves and keeps steady variations in PV power, even in the face of any PV insolation disturbances. The suggested system's simulation results are provided and scrutinized to confirm the concept's suitability. The findings validate the robustness of the suggested BELBIC control versus parameter variations. [ABSTRACT FROM AUTHOR]

In recent years, the rapid development of the photovoltaic (PV) industry has resulted in a saturation of research on onshore PV power plant construction. However, current studies on the impact of marine PVs on the marine environment remain limited and scarce. In order to facilitate the implementation of carbon reduction goals and promote the sustainable development of the offshore PV industry, this study analyzes the environmental impact of PV sea-use resources based on spatial information technology in the western part of Gaotang Island. The findings show that the MIKE21FM model provides relatively accurate simulations of tidal flow and tide level in the marine PV area. Flow velocity in the marine PV area exhibits a decreasing trend, with an average decrease ranging from 0.03 to 0.07 m/s. This decrease minimally affects surrounding navigational channels and large-scale flow fields. The resulting siltation is also deemed less significant, with an annual deposition from 0.03 to 0.06 m/a. Moreover, offshore PV construction resulted in a total intertidal biological loss of 123.45 t. The suspension of sediment during cofferdam construction and removal has a potential effect on zooplankton and fishery resources. Overall, it is proposed that careful planning, prudent site selection, and the execution of countermeasures during marine PV construction will combine to minimize the impact on the marine environment. [ABSTRACT FROM AUTHOR]

A controller is modelled and designed to optimize the power transfer in microgrid-connected hybrid renewable energy systems using an integrated DC/DC converter. To maximize the converter's output power and minimize the switching losses of the converter, a model is developed by including a simplified high conversion ratio converter, a maximal power point tracker, and an optimal controller with an effective control strategy. The proposed control system is a combination of the Artificial Transgender Longicorn Algorithm (ATLA) and the Gradient Boosting Decision Tree (GBDT) algorithm, named the ATLA-GBDT method. In the suggested technique, the ATLA is used as an assessment method to build up accurate control signals for the system and to improve the control signals database for offline use while considering the power exchange between the source and load. In addition, for training a GBDT system online, the data set received from the sensor is used to develop a control system for faster response. In addition, the goal function is defined by the system data, which is subject to equality and inequality constraints. Various constraints considered in the problem formulation are the output of renewable energy sources, power requirements, and the state of charge of storage components. The proposed control system is simulated using the MATLAB/Simulink platform, and the implementation is compared with the existing techniques. Various performance metrics like accuracy, specificity, recall and precision, RMSE, MAPE, and MBE of the proposed method and existing methods in the literature are presented. [ABSTRACT FROM AUTHOR]

Early adversity, the loss of the inhibitory GABAergic interneuron parvalbumin, and elevated neuroinflammation are associated with depression. Individuals with a maltreatment history initiate medicinal cannabis use earlier in life than non-maltreated individuals, suggesting self-medication. Female rats underwent maternal separation (MS) between 2 and 20 days of age to model early adversity or served as colony controls. The prelimbic cortex and behavior were examined to determine whether MS alters the cannabinoid receptor 2 (CB2), which has anti-inflammatory properties. A reduction in the CB2-associated regulatory enzyme MARCH7 leading to increased NLRP3 was observed with Western immunoblots in MS females. Immunohistochemistry with stereology quantified numbers of parvalbumin-immunoreactive cells and CB2 at 25, 40, and 100 days of age, revealing that the CB2 receptor associated with PV neurons initially increases at P25 and subsequently decreases by P40 in MS animals, with no change in controls. Confocal and triple-label microscopy suggest colocalization of these CB2 receptors to microglia wrapped around the parvalbumin neuron. Depressive-like behavior in MS animals was elevated at P40 and reduced with the CB2 agonist HU-308 or a CB2-overexpressing lentivirus microinjected into the prelimbic cortex. These results suggest that increasing CB2 expression by P40 in the prelimbic cortex prevents depressive behavior in MS female rats. [ABSTRACT FROM AUTHOR]

Fossil fuels, the predominant energy source in the United States, have been identified as major contributors to environmental pollution through the release of harmful emissions. As a countermeasure, there has been an increasing focus on the exploration and development of cleaner energy alternatives to alleviate the environmental degradation caused by fossil fuels and to satisfy the growing energy needs. This study conducted scenario analyses to evaluate the impact of integrating solar energy into specific US power grids on reducing carbon emissions. The analysis encompassed electrical systems within California, New England, New York, and the Southwest, utilizing datasets from the Energy Information Administration and National Renewable Energy Laboratory. The Energy Information Administration dataset includes information on net generation according to each source and carbon emissions according to fuel type, whereas the National Renewable Energy Laboratory dataset provides hourly projections for 6000 theoretical photovoltaic installations and detailed solar energy output data every five minutes over a year. Our findings indicated a notable decrease in carbon dioxide emissions following the introduction of solar power facilities. The most significant reductions were observed in the Southwest and California, attributed to solar plant integration. Conversely, New York and New England were identified as regions requiring additional policy measures and incentives to meet the emission reduction goals. [ABSTRACT FROM AUTHOR]

Featured Application: Artificial Neural Networks have confirmed applications in predicting PV system energetic efficiency. Solar energy is a promising and efficient source of electricity in countries with stable and high sunshine duration. However, in less favorable conditions, for example in continental, temperate climates, the process requires optimization to be cost-effective. This cannot be done without the support of appropriate mathematical and numerical methods. This work presents a procedure for the construction and optimization of an artificial neural network (ANN), along with an example of its practical application under the conditions mentioned above. In the study, data gathered from a photovoltaic system in 457 consecutive days were utilized. The data includes measurements of generated power, as well as meteorological records. The cascade-forward ANN was trained with a resilient backpropagation procedure and sum squared error as a performance function. The final ANN has two hidden layers with nine and six nodes. This resulted in a relative error of 10.78% and R2 of 0.92–0.97 depending on the data sample. The case study was used to present an example of the potential application of the tool. This approach proved the real benefits of the optimization of energy consumption. [ABSTRACT FROM AUTHOR]

The present investigation focuses on the Techno-Enviro-Economic assessment of a hybrid renewable energy system employing Homer software to identify an optimal system to power the Reverse Osmosis/Well (RO/Well) unit, with a capacity of 500 m3/d in the Salbukh region of Riyadh, Kingdom of Saudi Arabia (KSA). The proposed system encompasses photovoltaics (PV), a wind turbine (WT), fuel cells (FCs), a reformer (RF), an electrolyzer (Elec), a hydrogen tank (HT), and a battery (BT). The hybrid system, comprising 325 PV, 6 WT, 100 kW FCs, and a reformer that produces 6 kg of hydrogen (H2)/h, emerges as the most cost-effective and efficient solution, with a cost of energy (COE) amounting to $0.135/kWh. This configuration offers a balanced approach to energy generation, ensuring a more consistent energy supply, and enhancing system reliability. Although the 9 kg H2/hr RF-148 kW FCs system offers the lowest COE ($0.100/kWh), it relies entirely on fossil fuels, namely natural gas (NG). Conversely, the system is powered exclusively by renewable energy derived from PV planes, and WT records the highest COE ($0.199/kWh). The investigation provides valuable insights into developing sustainable energy solutions while taking cost-effectiveness, efficiency, and environmental considerations into account.

One of the disadvantages of solar systems is their low efficiency due to weather conditions such as dust and clouds that reduce their performance. Therefore, this article examines the impact of cloudy weather on the performance of the PV/solar chimney to demonstrate the performance of these solar systems under overcast weather conditions. The PV/solar chimney system was designed and built, and two days in December were chosen for testing: 27 December with clear weather without clouds and 28 December with cloudy weather.The results showed that cloudy weather has a clear effect on the performance of the PV/solar chimney where the intensity of solar radiation is low. Clouds act as a barrier preventing access to sunlight, as the electrical power generated on a clear weather day reached 341.92 W, while on a cloudy weather day, 187.88 Watts at noon. The kinetic energy on a clear weather day reached 17.212 mW, while on a cloudy weather day, it reached 9.47 mW at noon. The electrical efficiency on a clear weather day reached 15.96 %. In contrast, on a cloudy weather day, it reached 13.2 % when the test started at 9 a.m., after which the efficiency decreased with the increase in the intensity of solar radiation to become 13.574 % in clear weather while 12.12 % in cloudy weather at noon, and the thermal efficiency on a clear weather day reached 56.06 %. In contrast, on a cloudy weather day, 42 % at noon. The total efficiency in clear weather reached 69.65 %, while on a clear weather day cloudy by 54.12 % at noon.

Depending on the PV power, load power, and battery status, the system may operate in different modes. The control loop may have to switch between operating modes. In practice, it is difficult to implement control loop switching because the transition and dynamic process are difficult to control. As a result, this paper presents a generalized mode control method that avoids loop switching across modes. First, system structure and topology are introduced. The operating conditions for both grid-connected and off-grid modes are then divided into six sub-cases. Furthermore, the control architecture, control loop, and reference transition for various scenarios are described. Finally, an experimental platform is built, and the results are presented to verify the proposed method.