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For ensuring a greener and low carbon future; renewable energies sources such as solar energy stands out as a prominent solution for generating sustainable and clean electricity due to its accessibility, abundance and numerous benefits. The use of solar panel also called as photovoltaic systems has more importance in the world for their ability to convert sun irradiation into electricity while they have significant drawbacks like the nonlinearity of Pv panel. The efficiency and performance of Photovoltaic (PV) systems can be influnced by various factors, like climate fluctuations during the day. Therefore, it is so important to optimize the power capturing from PV panels. To optimize the energy created by photovoltaic modules, it is necessary to carefully select a DC-DC converter with MPPT control. This guarantees that the maximum power is extracted from the solar power plant and sent to the demand side in less time and with greater effectiveness. This paper introduces a super twisting sliding mode control technique for achieving maximum power point tracking (MPPT) in a photovoltaic (PV) system. The Single Ended Primary Inductor Converter (SEPIC) is proposed as a superior alternative to the conventional boost dc-dc converter, as it enables the extraction of the highest possible power from the photovoltaic panels array. Upon doing a thorough comparison of the suggested control with the P&O algorithm in various scenarios using the MATLAB/SIMULINK tool, it was found that the provided STC (Synchronous Tracking Control) for the SEPIC converter demonstrates greater efficiency and reduced oscillation around the Maximum Power Point (MPP). [ABSTRACT FROM AUTHOR]

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]

The limitation of renewable energy is its fluctuation with time, season, and peak load demand. Hence, most of the research was carried using demand side management to reduce the actual consumption load to lower the peak load. This will also hamper the basic energy need of the facility. Therefore, the objective of the present study is to model a hybrid renewable energy system (HRES) to attain the specific consumption of a community health centre (CHC) in Yomcha, Arunachal Pradesh, with load shedding. The optimization of HRES is performed on HOMER® Pro software along with the demand side management algorithm and a maximum annual capacity shortage of 5%. Three different cases were compared based on feasibility, economics, and environmental basis to estimate the performance of the HRES. The results show that the proposed model is appropriate for the CHC over the previously proposed system. Moreover, HRES with (design-side management) DSM will reduce the overall cost and increase efficiency and reliability with an net present value of Rs. 3013482 and a cost of energy of Rs. 5.42/kW, renewable fraction 78%, internal rate of return 70%, return of investment 66%, and payback period of 1.4 years. Moreover, it reduces emissions, controls overloading during peak hours, and decreases load shifting. The study also supports the sustainable development goal (SDG)-7 set by the United Nation SDG Committee. [ABSTRACT FROM AUTHOR]

Hydrogen has become an essential element in the pursuit of sustainable and clean energy solutions. Especially with the fast-paced advancement in demand, supply, and policy environment, its impact on hybrid renewable energy (HRE) management is becoming increasingly relevant. Efficient energy consumption, cost reduction, and enhanced user comfort are now critical factors in energy optimization. The production of green hydrogen, which is generated through water electrolysis using renewable energy sources (RES), has shown great potential as a sustainable energy solution. It offers several advantages, such as zero greenhouse gas emissions, high energy density, and versatile applications. This paper presents a detailed study on the power management and control of a hybrid renewable system (HRES) equipped with a diesel generator (DG) as a backup power source. The main objectives of the hybrid system are to satisfy the load power demand, ensure the most efficient use of the HRES, and keep the battery bank charged to prevent blackouts and extend the battery's life. To guarantee the system's reliability, the DG should be sized to meet the peak load demand when the RES generates less electricity than the load demand. This study explores the feasibility of modified versions of the load following and cycle charging control strategies to overcome the limitations of managing generation and storage systems' operations in different operating modes and to enhance the performance of an HRES with a DG that supplies electricity to a small and remote location. The proposed method not only maximizes the use of RES production but also enables multi-energy source management under different power generation and load demand scenarios. The study's outcomes demonstrate the feasibility of this proposed power dispatch strategy in a remote location environment. The paper includes a detailed discussion of overall control, mathematical models, energy storage in the battery model, and energy dispatching based on load following. To design and simulate the hybrid model system, MATLAB-SIMULINK is used, and the results are analyzed to identify the appropriate operation requirements, component selection, and energy management of the hybrid renewable energy system. [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]

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny 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.)

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]

Microgrids are a growing segment of the energy industry, representing a paradigm shift from remote central station power plants toward more localized, distributed generation. An efficient energy management structure is essential for a DC Microgrid with a PV system combined with a Hybrid Energy Storage System (HESS) of Battery and Supercapacitor. The combined supercapacitor and battery storage system provides a quick control for the DC-link voltage. It stabilizes the system and helps achieve smooth PV power delivery to loads. The boost converter used for the PV system is controlled by a Maximum Power Point Tracking (MPPT) method to extract maximum power and maintain a constant voltage at the DC bus despite the daily change in solar power. The boost-buck converter is used to control the charging and discharging processes of the BESS to maintain a constant voltage at the DC bus. To achieve the seamless operation of DC Microgrid with HESS during the power fluctuations, this work proposes power coordination and control scheme has been proposed. To analyse the performance and efficacy of the proposed DC Microgrid with HESS are implemented in MATLAB/SIMULINK. [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.

Through the use of fuel cells and photovoltaic (PV) solar cells, green energy has become one of the most popular developments in electricity generation in recent years. Accurate modeling of fuel cell and PV cell is critical in the simulation and analysis of energy systems that use both sources. Due to the complexity and nonlinearity of these hybrid systems, the model must be optimized under different operating conditions. In this article, a novel metaheuristic efficient hybrid algorithm is proposed for this purpose. A Hybrid Chaotic Particle Swarm Optimization and Slime Mould Algorithm (HCPSOSMA) has been proposed to estimate the PV/fuel cell system parameters. The hybrid HCPSOSMA algorithm is superior to other algorithms in terms of higher accuracy in searching for optimal solutions and better explorative capability. The problem formulation is based on minimizing the Root Mean Square Error (RMSE) between the calculated values and measured values for both the triple-diode PV model and the proton exchange membrane (PEM) fuel cell. The results show that the hybrid algorithm outperforms other algorithms in determining the best PV/PEMFC parameters that produce accurate V–I and P–I characteristic curves and the RMSE is about 4 × 10–12. Finally, non-parametric tests based on Friedman's ranking, Wilcoxon's rank sum test and Kruskal-Wallis test are implemented to prove the superiority of the proposed hybrid algorithm in the parameter estimation. [ABSTRACT FROM AUTHOR]

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.)

The instability and intermittence of photovoltaic (PV) power generation challenge the large-scale integration of PV power generation systems into the power grid and the development of energy storage systems. To accurately predict the output power of PV power generation, a power prediction model based on the optimized variational modal decomposition (OVMD)-adaptive t-distribution sparrow search algorithm (tSSA)-least squares support vector machine (LSSVM) algorithm was built. The performance of the model was then verified by three-year meteorological data and real-time PV output power data of two different climatic regions in China. The mean absolute percentage error (MAPE) and root mean square error (RMSE) of this model were less than 3.1% and 0.40, respectively, and the determination coefficient (R2) of this model was greater than 95%. Moreover, the prediction accuracy was greatly improved compared to models based on the support vector machine (SVM), LSSVM, variational modal decomposition (VMD)-LSSVM, and VMD-SSA-LSSVM algorithms. Finally, by performing dimension reduction of meteorological variables related to PV output power, the performance of the proposed OVMD-tSSA-LSSVM model was further improved. [ABSTRACT FROM AUTHOR]

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]

Scaling up perovskite solar cells stands as one of the frontiers in advancing this rapidly growing technology. Yet, controlling perovskite thin‐film crystallization during and post‐printing differs significantly from lab‐scale processes that have yielded record device efficiencies. This study investigates antisolvent treatment for slot‐die‐coated perovskite solar cells using in situ optical spectroscopy and comparing among multiple antisolvents. The antisolvent bath used in slot‐die coating affects the perovskite crystallization and film quality differently when comparing to the established spin‐coating antisolvent treatment process. A novel dynamic antisolvent method, employing either vortex or laminar flow, is developed. It outperforms steady‐bath techniques in generating high‐quality, haze‐free films. Optimization studies identify critical treatment times. Implementing this novel antisolvent treatment leads to a peak average power conversion efficiency of 15.62% and the highest device efficiency of 18.57%, an excellent performance for slot‐die‐coated MAPbI3 devices printed and tested under ambient conditions. The method is validated for an alternative perovskite composition, FA0.9Cs0.1PbI3, and printing technique, blade coating. This research highlights the importance of in situ analysis for enhancing perovskite film quality and introduces scalable approaches for controlling large‐area film crystallization kinetics, driven by the demand for efficient and scalable manufacturing processes in the field of perovskite solar cells. [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]

Irrigation is the artificial application of water to soil through tubes, pumps, and sprays, used when natural sources and rain are insufficient, irregular, dry, or drought-prone areas. This study proposes a drip irrigation-based solar-powered system for home grown plants and greenhouse gardens, utilizing solar energy for electricity consumption. The system is highly efficient for providing water and nutrients to crops, ensuring optimal growth, and conserving resources like water, fertilizers, energy, and crop protection products. A water tank uses an Arduino ATmega328 microprocessor to detect plant moisture levels and supply water to plants through a water motor and sensor. The system employs drip irrigation to pump water through pipes using a DC motor. The automated irrigation system utilizes a boost DC-DC switching converter, to step up input voltage and increase the output voltage, enabling remote monitoring of humidity, water, and energy consumption in flowerpots. The converter achieves significant step-up voltage gain with a suitable duty ratio and minimal voltage stress on the power switches. It is an off-grid automatic control system that operates independently of human intervention. The system utilizes a boost converter to indirectly optimize the power of two series-connected PV cells, increasing overall efficiency. [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]

Palestine has limited energy sources and must import different fuels from neighboring countries, hence renewable energy sources like solar energy are necessary. One of the most important and promising clean renewable energy sources available today that also helps cut expenses and effort is solar energy. Solar energy is captured and stored by solar panels. Solar panels come in a wide variety now, and new kinds are always being developed to maximize solar energy absorption, require the least amount of maintenance, and endure a longer time. This study will compare the performance of the polycrystalline solar cell unit and the PERC unit, both of which will be impacted by Palestine's environment, by conducting an experimental investigation into the behavior of the unit. The PERC panel's temperature was lower than the polycrystalline panel's because of the addition of a heatreflecting layer, which increased the PERC panel's efficiency. The efficiencies of the two panels were compared at the same level of solar radiation. It has been demonstrated that PERC efficiency is higher when solar radiation is the same. The solar energy absorbed in the PERC panel actually increases because of the reflective coating that helps the PERC cell to optimize its benefit from the sun's radiation. When polycrystalline and PERC panels were compared, the former produced more electricity per unit of area. [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]

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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]

This article presents an energy system that enhances the quality of electrical energy by injecting photovoltaic (PV) renewable energy into the electrical network in the presence of a polluting load. This system is based on a new control approach known as Zero Direct Power Command (ZDPC). The innovative aspect of the proposed work is the addition of clean energy while simultaneously removing the unsettling harmonics produced by the nonlinear loads provided by distorted voltages. This approach combines a traditional Proportional Integrator (PI) controller for regulating the DC bus voltage with a clever technique (fuzzy logic) for tracking the Maximum Power Point Tracking (MPPT). The current has a harmonic distortion rate of about 1% with unity power factor due to the suppression of undesirable harmonics from the source currents. A PV panel connected in series with a chopper and managed by fuzzy logic via a two-state inverter ensures the injection of PV energy into the electrical network. Software called MATLAB/Simulink is used to model this system. The outcomes demonstrate the reliability and viability of the ZDPC control, which concurrently ensures harmonic current compensation, power factor correction, and the introduction of solar power into the electrical network despite distorted source voltages. [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.