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This paper focuses on the design and use of a control system for a renewable energy production plant based on hydrogen. The proposed control system aims at ensuring the stability and smooth functionality of the plant, which consists of a (i) photovoltaic system connected to an electrolyzer through a battery, (ii) a DC/DC step down transformer, and (iii) an electrolyzer heat exchange system. In this study, solar irradiance is the main system input, and hydrogen production the main output. Since the system utilizes solar energy as input, it depends on the random input of solar irradiance, ambient temperature, and wind flow. Furthermore, the electrolyzer's functionality is subject to several operational variables including cell voltage, current, temperature, and pressure. The electrolyzer heat exchange system operates at specified water temperatures and flow rates. The DC/DC output voltage, and therefore the voltage supplied to the electrolyzer, is regulated by changing its duty cycle. To regulate hydrogen production in the renewable energy production plant, an efficient control system is required. Accordingly, in this work, a control system is designed accounting for three different electrolyzer technologies, alkaline, PEM (proton exchange membrane), and E-TAC (electrochemical - thermally activated chemical water splitting). Subsequently, the effectiveness of the control system is analyzed using Matlab and Simulink models. The main results indicate that the battery is a crucial element in the whole system as it supplies the necessary energy to the electrolyzer. By regulating the appropriate components, the proposed control system proved capable of minimizing power fluctuations and increasing system efficiency up to 20% depending on ambient conditions. Additionally, the results indicate E-TAC and PEM efficiencies 13% and 7% higher than alkaline, respectively. [Display omitted] • Design of a control system for three different electrolyzer technologies. • Use of control systems for electrolyzer voltage and heat exchange. • Photovoltaic system connected to an electrolytic one through a battery. • Proposed control system increases system efficiency up to 20%. [ABSTRACT FROM AUTHOR]

In recent times, the escalating global demand for sustainable and renewable energy sources has catalyzed the exploration and development of innovative technologies, among which floating photovoltaic (FPV) systems emerge as a particularly promising solution. These systems exploit solar energy by deploying PV panels on water surfaces. These systems, offer several advantages, including their independence from land use constraints, enhanced energy efficiency due to the cooling effect of water, and the potential for synergy with various energy sources. Expanding on prior literature reviews, this paper provides a focused review of the latest developments in FPV systems, cutting-edge technologies, challenges faced the FPV in marine settings, extending to an economic analysis for comprehensive feasibility assessment, and market potential from diverse angles. The primary objective is to promote additional research and applications of FPV to guarantee the safety and stability of FPV systems under challenging marine environmental conditions, aiming to enhance overall efficiency, reliability, and the widespread adoption of FPV projects, while concurrently reducing investment costs. Highlighting its importance for energy-deficient African countries, the paper underscores the significance of integrating FPV systems into the continent's energy strategies for widespread adoption, to bolster energy security and environmental sustainability across the continent. [ABSTRACT FROM AUTHOR]

This paper discusses a methodology, specifically for solar power potential areas, to effectively design and develop solar photovoltaic power plants integrated with battery banks connected to the utility grid as an additional backup to maintain power stability and reliability. To prove the effectiveness of this method regarding its use for the design and development of the proposed system, Kinshasa city in Democratic Republic of the Congo with a huge (5425 MWh) energy deficit has been considered as a case study. In fact, the method employed in this study has considered weather data, site selection, hourly load power and energy demand analysis, specifications of PV technologies and other components of the system. Economic analysis has also been carried out for the proposed system viability assessment. With a competitive LCOE, SPP < 10 years, NPV˃0, SIR˃1, and ROI ˃10 %, and a yearly PV energy output greater than the city's energy deficit, the system proposed has been found to be feasible and viable. In a search for better performance, higher efficiency and better economic values, the proposed method is highly recommended and can be regarded as one of the most effective and the easiest for sizing large-scale PV systems. • Grid-connected solar PV plants with storage batteries running as a base unit can much help maintain power supply continuity. • An effective design method is of great interest for the sizing of large-scale grid-connected PV systems. • Using PV systems for utility applications can now be regarded as a cheaper and fast option to address electricity challenges in most African countries, in particular DRC. [ABSTRACT FROM AUTHOR]

In this paper, renewable energy (RE) policies are evaluated to draw up recommendations for the energy sector stakeholders. The good potential of RE exists in Palestine, especially solar and biomass resources. Structural frameworks and targets are established for RE penetration in Palestine. Some strategies for the enhancement of RE systems are already in place; however, sustainable policies are still needed. To accomplish this task, a comprehensive integrated approach, involving all consumed energy forms (e.g., electricity, heating and cooling, and transport sectors) is anticipated. Energy security in Palestine over the upcoming 20 years is investigated using a Monte-Carlo simulation model that applies different RE adoption scenarios. In order to meet the Palestinian population's electrical energy needs in the near future, RE sources should be growing at an annual rate of about 5–10%. Few incentives exist for photovoltaic systems, yet sufficient funds must be allocated to the other forms of RE. Licensing and permitting procedures must be simplified and made more attractive for investors in the RE sector. Specifications and codes relevant to the utilization of RE need to be developed and enforced, including RE system identification and grid connection. It is crucial to designate a certain institution that can monitor and evaluate RE policies and collect relevant data to promote RE implementation in Palestine. A policy framework is proposed to achieve future energy sustainability for Palestine. • Adequacy between energy needs and renewable energy supply is studied. • Good renewable energy potential in Palestine is well recognized. • Current energy and renewable energy policies are proved to be insufficient when compared with international practices. • Policy gaps are identified, while recommendations and a framework for renewable energy policies in Palestine are outlined. [ABSTRACT FROM AUTHOR]

The realization of dc-dc converters performs a vital function in exploiting renewable energy sources such as solar photovoltaic (PV) and fuel cell applications. This paper demonstrates a single-switch unidirectional buck-boost dc-dc converter for continuous power flow control, excluding the hybrid switched-capacitor. The proposed converter utilizes a limited number of passive components, only four diodes and three inductors required, in addition to six capacitors. The converter can operate at a wide input voltage range with continues input current. The converter has experimented under real-time conditions with 660 W PV system. The obtained efficiency ranges from 93% to 98%. Furthermore, the converter has interfaced with 550 W fuel cell operated under different fuel pressure. The realized efficiency ranges from 91% to 97%. The maximum measured inductance current ripple is limited to under 0.70 A in both scenarios, whereas 0.16 V is the maximum output voltage ripple. • A Boost-buck DC-DC converter with a single switch is proposed. • The proposed converter is integrable with fuel cell and photovoltaic systems. • The converter has a minimum inductance current ripple and power losses. • The proposed converter efficiency ranges from 91% to 98%. • The converter performance is compared with classical methodologies. [ABSTRACT FROM AUTHOR]

There has been tremendous growth in the use of renewable energy sources (RES) over the last few years. Solar systems, because of their unique properties, such as being noiseless, eco-friendly, and free of pollutants, are the most feasible source of energy among all RESs. However, a major drawback of photovoltaic (PV) systems is their low energy conversion efficiency, unstable and intermittent nature. In order to extract electrical energy from solar panels, it is necessary to connect them to the power system through DC-DC converters. As a result, maximum power point tracking (MPPT) algorithms are necessary in order to increase the amount of power harvested from solar PV systems. Accordingly, a method is presented in this paper for the design of an MPPT control approach for PV systems using fuzzy gain scheduling for proportional-integral-derivative (FGS-PID) controllers coupled with adaptive scaling factors for fuzzy input signals. The developed adaptive FGS-PID controller uses a two-level control system structure that incorporates the advantages of fuzzy logic and conventional PID control. Additionally, to fine-tune the member functions (MFs) of FGS, an integration of the fuzzy logic controller (FLC) and the modified fluid search optimization (MFSO) algorithm is employed. In order to evaluate the efficiency of the developed control systems, MATLAB software has been chosen for the simulations. The developed approach has proven highly effective in automatically regulating the triangular MFs of inputs and outputs and has shown superior performance. One of the key benefits of the proposed technique is that it enables fast and accurate tracking of the PV system's highest generated power in a short period of time. [ABSTRACT FROM AUTHOR]

Photovoltaic systems have a reliable method to generate electrical power from direct solar irradiance. Their efficiency is only up to 20% in real operating circumstances and is affected adversely by the inevitable temperature rise in their surface. Passive, active or combined cooling methods are applied to reduce operating temperature to a suitable level, depending on specific application. A Great body of literature has been investigating different PV cooling methods and techniques to reach optimized system efficiency and cooling effect. It is critical for both researchers and practitioners to have a thorough understanding and awareness of the most recent advances and existing gaps. Although there are certain review papers in this field, it is necessary to have up-to-date reviews of the most recent progress and research since the previous ones. In the present work, the main focus was to provide a review of the most recent studies and to compare their outcomes to provide a reference for practitioners and researchers. The holistic classification and evaluation of all the possible cooling technologies were provided in order to draw a comparison between various cooling approaches. Based on the analysis obtained, cooling techniques can ensure improvement in electrical efficiency in a range from 1% to 53% with expected decrease in the photovoltaic panel's surface operating temperature from 1.8 °C to 46 °C. It was also found that spectrum filtering and jet impingement indicated highly remarkable enhancements. The other factors, such as the size of the examined photovoltaic panel, photovoltaic technology, as well as climate circumstances have a strong impact on the cooling performance besides the selection of the specific coolant. The necessity for integral evaluation (performance, economic and environmental) of cooling techniques was also identified as key issue. • Cooling technologies enhance the performance, durability, and lifetime of photovoltaic technologies. • Passive cooling techniques have less performance improvement when compared to active ones. • The size of the PV panel can strongly affect cooling performance. • The economic and environmental aspects were weakly investigated. [ABSTRACT FROM AUTHOR]

Floating photovoltaic systems (FPV) can be a more sustainable alternative for the energy transition than ground-mounted photovoltaic systems, as they avoid occupying useable land and the power generation is more distributed. This paper presents the first study that calculates the FPV technical potential at the province/municipality level, focusing on water irrigation ponds, which it is a novelty in the literature that usually focuses on large water infrastructures in a national approach. In the province of Jaén (Spain), more than 3000 ponds dedicated to agricultural irrigation have been identified and their surface area and location was obtained. The results, calculated for each pond, reveal that, in a conservative scenario, in which only 25% of their surface area is covered, a minimum of 490 MWp can be installed, which can provide 251% of the province agricultural electricity consumption and 27% of the total electricity needs. This analysis has also been performed at the municipal level, where all possible FPV plants have been aggregated and compared with consumption that would be covered at this scale. Furthermore, this technology brings additional benefits, as it avoids the occupation of 12 km2 of useable land, 8.8·106 m3/year of water evaporated, while creating more than 7000 jobs. • A Technical floating PV potential assessment on water irrigation ponds is done • A Technical floating PV potential assessment at a municipal level is done • A calculation of Multi-benefits of floating PV installation is done • An energy consumption coverage assessment at municipal level with floating PV is done [ABSTRACT FROM AUTHOR]

[Display omitted] • Three water/power generation configurations were designed, modeled, and optimized. • Damage to human health and the ecosystem caused by diesel generator were estimated. • Division algorithm was more accurate and faster than the genetic algorithms. • Desalination with photovoltaic panel/wind turbine was environmentally efficient. • Desalination with the photovoltaic panels was economically the best configuration. Although freshwater is necessary for the well-being of humankind, increasing population growth and limited resources lead to a serious crisis to supply freshwater. Since the Earth is surrounded by seawater, desalination based on electrical power is introduced as a promising technology to provide freshwater. It is well documented that the connection of remote areas that usually do not have access to freshwater into the electricity grid is not affordable and eco-friendly. Hence, the efforts to design and construct high reliability, cost-effective, and eco-friendly stand-alone hybrid renewable energy system in remote areas. In line with this, this paper describes a novel energy management system for the optimized operation of a stand-alone hybrid energy system based on photovoltaic panels, wind turbines, batteries, and diesel generator. For this purpose, a multi-objective optimization problem is formulated by combining three objective functions, i.e., minimum the total life cycle cost as well as environmental impacts on human health and ecosystems and the maximum system reliability that can conflict with each. To solve the multi-objective optimization problem, a division algorithm is proposed that is more flexible and faster compared with conventional algorithms such as genetic algorithm. In order to show the proposed framework, a real case study in Larak Island, Iran, with appropriate solar and wind is considered. The effectiveness of the applied approach compared with optimization results of genetic algorithm and the artificial bee swarm optimization algorithm that was previously used successfully to solve optimization problems related to desalination integrated with the renewable energy system. The optimization is performed based on different diesel fuel price amounts (0.2, 0.5, and 1 $/liter). It is seen that at fuel price set to 0.2 and 0.5 $/liter, the seawater reverses osmosis desalination/photovoltaic/diesel generator/battery is the most cost-effective energy system, and when fuel price is 1 $/liter, the seawater reverses osmosis desalination/photovoltaic/wind turbine/diesel generator/battery is the most cost-effective hybrid system. While at fuel price set to 0.2, 0.5, and 1 $/liter, the seawater reverse osmosis desalination /photovoltaic/wind turbine/diesel generator/battery is the most eco-friendly. Finally, the results of this study show proposed algorithm is faster and more accurate (100 iterations, 98.36% accuracy) than the genetic algorithm (1000 iterations, 83.03% accuracy) and the artificial bee swarm optimization (300 iterations, 95.49% accuracy). [ABSTRACT FROM AUTHOR]

In this paper, an efficient three-layered p-In 0.6 Ga 0.6 N/p-In 0.7 Ga 0.7 N/n-In 0.7 Ga 0.7 N (PPN) solar cell was designed. The characteristics of the PPN-junction InGaN solar cell were simulated using the SCAPS-1D software. The effects of the thickness and carrier density of the PPN layer on solar cell performance were evaluated. The results were compared with those of the performance of the PN-junction solar cell. Results revealed that a thin top p-InGaN with a high carrier density had a considerable influence on the performance of the solar cell. Adding a p-InGaN layer as thin as 0.01 μ m on the top of the PN-junction solar cell substantially improved the conversion efficiency of the solar cell from 21.39% (PN) to 30.23% (PPN). [Display omitted] • p-In 0.6 Ga 0.6 N/p-In 0.7 Ga 0.7 N/n-In 0.7 Ga 0.7 N (PPN) solar cell with high conversion and quantum efficiency was developed. • The PPN solar cell achieved 30.23% conversion efficiency and 98.6% quantum efficiency. • Adding a thin p-InGaN layer on the top of the PN-junction solar cell drastically improved the conversion efficiency. • The top p-InGaN created a graded energy bandgap and increased the number of holes in the solar cell. [ABSTRACT FROM AUTHOR]

Along with the increasing rate of using renewable energies, following the finite amount of fossil fuel resources, and the associated pollution of these non-renewable energies, photovoltaic systems have recently achieved widespread acceptance to harness solar energy in the last decades. Since photovoltaic systems have a limited lifespan and cannot be used after a while, it seems imperative to pay attention to recycling and sustainability in the supply chain network design of these systems. In this respect, this paper first reviews the photovoltaic systems literature systematically. Thereinafter, a multi-objective, mixed-integer non-linear optimization model is deployed to design a photovoltaic supply chain network addressing the system's associated costs, environmental impacts, and social values. The concerned model also considers a reverse flow in addition to the typical forward flow in the proposed supply chain for special environmental and social issues. Likewise, to optimize the presented multi-objective model, the augmented ε-constraint method is employed, being capable of warranting the Pareto optimal solutions. Eventually, the model's efficiency is illustrated by discussing a real-world case in Iran, through which prominent managerial results are acquired. • The photovoltaic systems literature is systematically reviewed. • A multi-objective, mixed-integer non-linear programming model is proposed to design a sustainable photovoltaic supply chain network. • The concerned model is able to consider a reverse flow in addition to the typical forward flow in the proposed supply chain. • To solve the proposed multi-objective model, the augmented ε-constraint method is deployed. • The efficiency of the model is illustrated by discussing a real-world case in Iran. [ABSTRACT FROM AUTHOR]

[Display omitted] • A new hybrid model IF-ELM is developed for multi-step ahead forecasting of PV power. • Two different architectures of IF-ELM are proposed. • Three PV plants database are analyzed. • Proposed IF-ELM boost the forecasting performance of PV power output compared to existing approaches. Photovoltaic (PV) solar power, which is considered as the most competitive clean energy source, contributes to a significant percentage of electricity production in many developed countries. However, accurate PV power forecasting is necessary due to its high variation that can be caused by several factors. Hence, the intermittent nature of PV production represents a major challenge to integrate PV systems into the electric grid. The scope of this paper deals with this issue through developing a new integrated PV power forecasting model. The proposed model is based on the use of a new decomposition methodology, named Iterative Filtering for decomposing PV power into different intrinsic functions (IMFs), then Extreme Learning Machine (ELM) is used as essence predictor. To this end, the proposed IF-ELM model is evaluated on three solar PV power plants installed at three different sites, with different climatic conditions. Direct and recursive IF-ELM methodologies are examined for multi-step ahead forecasting in a very short time-scale (up to 60 min). Overall, the forecasting results show high precision performance for the studied forecasting horizons- in terms of different statistical metrics compared to stand-alone models. Also, the proposed IF method shows its high performance when compared to the recently developed decomposition method. complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) in improving the forecasting accuracy of a single model. Forecasting results with the IF-ELM model led to an error in nRMSE that is less than 10% and a Correlation Coefficient greater than 98% over all forecasting horizons. [ABSTRACT FROM AUTHOR]