Integrating Solar Photovoltaic Power Source and Biogas Energy-Based System for Increasing Access to Electricity in Rural Areas of Tanzania
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International Journal of Photoenergy publishes original research and review articles focused on all areas of photoenergy, including photochemistry and solar energy utilization.
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Chief Editor, Giulia Grancini, is based at the University of Pavia, Italy. Her current research work aims at solving the stability and toxicity issues of developing multi-dimensional hybrid interfaces as lego-bricks for a new efficient, stable, and environmentally-friendly solar technology.
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More articlesNumerical Simulation of High Efficiency Environment Friendly CuBi2O4-Based Thin-Film Solar Cell Using SCAPS-1D
In this research work, a copper bismuth oxide- (CuBi2O4-) based thin-film solar cell has been proposed for the lead and toxic-free (Al/ITO/TiO2/CuBi2O4/Mo) structure simulated in SCAPS-1D software. The main aim of this work to make an ecofriendly and highly efficient thin-film solar cell. The absorber layer CuBi2O4, buffer layer TiO2, and the electron transport layer (ETL) ITO have been used in this simulation. The performance of the suggested photovoltaic devices was quantitatively evaluated using variations in thickness such as absorber, buffer, defect density, operating temperature, back contact work function, series, shunt resistances, acceptor density, and donor density. The absorber layer thickness is fixed at 2.0 μm, the buffer layer at 0.05 μm, and the electron transport layer at 0.23 μm, respectively. The CuBi2O4 absorber layer produces a solar cell efficiency of 31.21%, an open-circuit voltage () of 1.36 V, short-circuit current density () of 25.81 mA/cm2, and a fill factor (FF) of 88.77%, respectively. It is recommended that the proposed CuBi2O4-based structure can be used as a potential for thin-film solar cells that are both inexpensive and highly efficient.
A New High-Performance Photovoltaic Emulator Suitable for Simulating and Validating Maximum Power Point Tracking Controllers
Photovoltaic (PV) research is rapidly growing, and the need for controlled environments to validate new MPPT controllers is becoming increasingly important. Currently, researchers face several challenges in testing MPPT algorithms due to the unpredictable nature of solar PV power generation. In this paper, we propose a new photovoltaic emulator (PVE) that could replace solar panels and ensure a highly controllable environment suitable for testing photovoltaic (PV) systems. In this PVE, the complex nonlinear equations of the PV cell/module are fast computed and resolved by a new linearization technique which involves the systematic breakdown of the current-voltage (-) curve of the PV into twelve linear segments. Based on input environmental conditions, an artificial neural network (ANN) was constructed to assist the linearization process by predicting the current-voltage boundary coordinates of these segments. Using simple linear equations, with the segment boundary coordinates, a reference voltage was generated for the PVE. A nonlinear backstepping controller was designed to exploit the reference voltage and stabilize the power conversion stage (PCS). The PVE was optimized using particle swarm optimization (PSO). Several tests have shown that the proposed nonlinear controller provides better dynamic and robust performance than the PI controller, the most reputable and recurrent control method in the area of PVE. The PVE was coupled with a recently proposed integral backstepping MPPT controller and analyzed under several dynamic conditions, including the MPPT test specified by EN 50530. It was found that the accuracy of the proposed PVE measured by its relative error is less than 0.5%, with an MPPT efficiency of greater than 99.5%. The attractive results achieved by this PVE make it especially suitable for simulating and validating MPPT controllers.
Design and Simulation of a Cooling System for FTO/I-SnO2/CdS/CdTe/Cu2O Solar Cells
The temperature in solar cells is one of the main factors affecting their efficiency. Increasing the temperature in solar cells reduces efficiency. According to previously published and recently published studies by our team, with increasing temperature in 5-layer FTO/i-SnO2/CdS/CdTe/Cu2O solar cells, the efficiency has decreased by 8.86% per 100 K. In this research, phase change materials have been used to control the temperature in 5-layer solar cells. Our overall goal in this study is to control the temperature in FTO/i-SnO2/CdS/CdTe/Cu2O solar cells to increase their efficiency. The results obtained using simulations and numerical analysis and comparative analysis show that if one layer is used as a cooling arrangement in 5-layer FTO/i-SnO2/CdS/CdTe/Cu2O solar cells, it reduces the surface temperature of solar cells and increases efficiency.
Daily Prediction Model of Photovoltaic Power Generation Using a Hybrid Architecture of Recurrent Neural Networks and Shallow Neural Networks
In recent years, photovoltaic energy has become one of the most implemented electricity generation options to help reduce environmental pollution suffered by the planet. Accuracy in this photovoltaic energy forecasting is essential to increase the amount of renewable energy that can be introduced to existing electrical grid systems. The objective of this work is based on developing various computational models capable of making short-term forecasting about the generation of photovoltaic energy that is generated in a solar plant. For the implementation of these models, a hybrid architecture based on recurrent neural networks (RNN) with long short-term memory (LSTM) or gated recurrent units (GRU) structure, combined with shallow artificial neural networks (ANN) with multilayer perceptron (MLP) structure, is established. RNN models have a particular configuration that makes them efficient for processing ordered data in time series. The results of this work have been obtained through controlled experiments with different configurations of its hyperparameters for hybrid RNN-ANN models. From these, the three models with the best performance are selected, and after a comparative analysis between them, the forecasting of photovoltaic energy production for the next few hours can be determined with a determination coefficient of 0.97 and root mean square error (RMSE) of 0.17. It is concluded that the proposed and implemented models are functional and capable of predicting with a high level of accuracy the photovoltaic energy production of the solar plant, based on historical data on photovoltaic energy production.
Investigating the Cost-Effectiveness of Solar Electricity Compared to Grid Electricity in the Capitals of Middle Eastern Countries: A Residential Scale Case Study
Despite of being rich in fossil fuels, the Middle East is currently the main energy consumer and is projected to have the highest growth in energy demand in the world. Due to its great potential in the Middle East, solar energy can play an important role in the plans of energy decision-makers in the region. According to the studies done so far, no study has been done to show the potential benefit of using home-scale solar systems in the Middle East. Therefore, in this work for the first time, the potential of solar electricity production in the capitals of Middle Eastern countries has been studied using HOMER V2.81 software. The investigations are technical, economic, energy, and environmental, and the studied solar system is connected to the national electricity grid. The results showed that in Nicosia, due to the sale of electricity to the grid, the levelized cost of electricity (LCOE) is equal to -0.759 $, which is the lowest price for produced electricity and leads to a return on investment time of 5.69 years for this system. The solar fraction for the Nicosia station is 92%, which prevents the emission of more than 8 tons of CO2 pollutants during the year. The highest value of LCOE with the amount of $0.25 is related to Sana’a, whose investment return time, solar fraction, and annual CO2 emission prevention amount are 14.1 years, 53%, and 1162 kg, respectively. Ranking analysis was done on the results of 5 outputs of the HOMER software as well as 3 other influential parameters using 4 multicriteria decision-making (MCDM) methods. TOPSIS, GRA, WSM, and AHP methods were used, and the final ranking of each station was considered the average of the 4 methods. According to the results, Cyprus and Kuwait stations were the best and worst, respectively.
Application of Photovoltaic Systems in Field Observation and Research Stations: Research on the Relationship between Power Generation Scale and Electricity Consumption to Improve Photovoltaic Application in Field Observation Stations
Most field scientific observation and research stations are located at the end of power grids which are usually not extended to such areas. Consequently, the power supply of equipment in field observation stations cannot be guaranteed. Meanwhile, regions with poor ecosystem stability are relatively sensitive to environmental changes and thus prone to degradation and succession due to external interference. In this paper, the photovoltaic (PV) power generation system of a grassland ecohydrological field scientific observation and research station was taken as the research object. Two kinds of distributed PV power generation systems were simulated and analyzed by use of PVsyst software. The total power of laboratory equipment, PV power generation efficiency, and system cost of the field observation station were calculated and analyzed. The design scheme and scale of PV power generation systems suitable for field observation stations were determined. Finally, a PV power generation test system was set up, and PV power generation data were sorted out. The feasibility of the design scheme of PV power generation systems was verified by analyzing the relationship between the simulated and actual power generation of systems and that between the daily energy use proportions of field observation stations. Besides, the environmental benefits of PV systems were analyzed, and their amount of energy saving and emission reduction was calculated. This study can solve the issue of the low power supply guarantee rate of field observation stations, provide a design basis and beneficial reference for the construction of environment-friendly field laboratory stations, and realize green energy saving and the sustainable use of energy while protecting the ecosystem from being destroyed.