scholarly journals Identification of Parameters in Photovoltaic Models through a Runge Kutta Optimizer

Mathematics ◽  
2021 ◽  
Vol 9 (18) ◽  
pp. 2313
Author(s):  
Hassan Shaban ◽  
Essam H. Houssein ◽  
Marco Pérez-Cisneros ◽  
Diego Oliva ◽  
Amir Y. Hassan ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Solar Cell ◽  
Renewable Energy Sources ◽  
Cell Models ◽  
Unknown Parameters ◽  
Cell Parameters ◽  
Hunger Games ◽  
Sine Cosine Algorithm ◽  
Swarm Algorithm ◽  
Runge Kutta

Recently, the resources of renewable energy have been in intensive use due to their environmental and technical merits. The identification of unknown parameters in photovoltaic (PV) models is one of the main issues in simulation and modeling of renewable energy sources. Due to the random behavior of weather, the change in output current from a PV model is nonlinear. In this regard, a new optimization algorithm called Runge–Kutta optimizer (RUN) is applied for estimating the parameters of three PV models. The RUN algorithm is applied for the R.T.C France solar cell, as a case study. Moreover, the root mean square error (RMSE) between the calculated and measured current is used as the objective function for identifying solar cell parameters. The proposed RUN algorithm is superior compared with the Hunger Games Search (HGS) algorithm, the Chameleon Swarm Algorithm (CSA), the Tunicate Swarm Algorithm (TSA), Harris Hawk’s Optimization (HHO), the Sine–Cosine Algorithm (SCA) and the Grey Wolf Optimization (GWO) algorithm. Three solar cell models—single diode, double diode and triple diode solar cell models (SDSCM, DDSCM and TDSCM)—are applied to check the performance of the RUN algorithm to extract the parameters. the best RMSE from the RUN algorithm is 0.00098624, 0.00098717 and 0.000989133 for SDSCM, DDSCM and TDSCM, respectively.

scholarly journals Parameter Identification of Photovoltaic Cell Model Using Modified Elephant Herding Optimization-Based Algorithms

2021 ◽  
Vol 11 (24) ◽  
pp. 11929
Author(s):  
Amer Malki ◽  
Abdallah A. Mohamed ◽  
Yasser I. Rashwan ◽  
Ragab A. El-Sehiemy ◽  
Mostafa A. Elhosseini
Keyword(s):  
Solar Cell ◽  
Cell Model ◽  
Optimization Algorithms ◽  
Metaheuristic Algorithms ◽  
Local Optimum ◽  
Cell Models ◽  
Unknown Parameters ◽  
Solar Module ◽  
Cell Parameters ◽  
Pv Cell

The use of metaheuristics in estimating the exact parameters of solar cell systems contributes greatly to performance improvement. The nonlinear electrical model of the solar cell has some parameters whose values are necessary to design photovoltaic (PV) systems accurately. The metaheuristic algorithms used to determine solar cell parameters have achieved remarkable success; however, most of these algorithms still produce local optimum solutions. In any case, changing to more suitable candidates through elephant herd optimization (EHO) equations is not guaranteed; in addition, instead of making parameter α adaptive throughout the evolution of the EHO, making them adaptive during the evolution of the EHO might be a preferable choice. The EHO technique is used in this work to estimate the optimum values of unknown parameters in single-, double-, and three-diode solar cell models. Models for five, seven, and ten unknown PV cell parameters are presented in these PV cell models. Applications are employed on two types of PV solar cells: the 57 mm diameter RTC Company of France commercial silicon for single- and double-diode models and multi-crystalline PV solar module CS6P-240P for the three-diode model. The total deviations between the actual and estimated result are used in this study as the objective function. The performance measures used in comparisons are the RMSE and relative error. The performance of EHO and the proposed three improved EHO algorithms are evaluated against the well-known optimization algorithms presented in the literature. The experimental results of EHO and the three improved EHO algorithms go as planned and proved to be comparable to recent metaheuristic algorithms. The three EHO-based variants outperform all competitors for the single-diode model, and in particular, the culture-based EHO (CEHO) outperforms others in the double/three-diode model. According the studied cases, the EHO variants have low levels of relative errors and therefore high accuracy compared with other optimization algorithms in the literature.

scholarly journals POTENSI DAYA DARI SOLAR CELL TERPASANG SESUAI DENGAN POLA ATAP RUMAH BERBASIS ARSITEKTUR BALI

2019 ◽  
Vol 6 (1) ◽  
pp. 21
Author(s):  
I Nyoman Apriana Arta Putra ◽  
Wayan Arta Wijaya ◽  
I.G.N Janardana
Keyword(s):  
Renewable Energy ◽  
Solar Cell ◽  
Renewable Energy Sources ◽  
Average Power ◽  
Solar Panels ◽  
The North ◽  
Southern Side ◽  
Maximum Warming ◽  
North And South

This study was conducted to determine the potential power obtained at home with the Balinese roof pattern when developed with renewable energy sources. Solar energy as a source of renewable energy has enormous potential, especially in Indonesia. Balinese architecture-based roof pattern has 4 fields, the north and south side are trapezoidal and the east and west sides are triangular with 350 roof inclination angle. One of Bali's traditional buildings is Bale Sari, which is a case study with an area of ??32.64 m2, length 6.40m and width 5.10m. Bale Sari's roof has a pyramid pattern, each side having the same length and width. Methods performed in this study with manual calculations to find the potential maximum power. The total number of solar panels used is 234 pieces. With this amount, obtained the best potential results on the southern side, with an average power gained of 667.67 Watt. The results are obtained when the sun is at a maximum warming point or precisely when the weather is sunny. The result of the average power potential analysis obtained by solar cell installed on the roof of the Balinese architecture house is 1,935.49 Watt.

Identification of unknown parameters of solar cell models: A comprehensive overview of available approaches

2018 ◽  
Vol 90 ◽  
pp. 453-474 ◽  
Author(s):  
Rabeh Abbassi ◽  
Abdelkader Abbassi ◽  
Mohamed Jemli ◽  
Souad Chebbi
Keyword(s):  
Solar Cell ◽  
Cell Models ◽  
Unknown Parameters ◽  
Comprehensive Overview

scholarly journals Theoretical and Experimental Analysis of Monocrystalline Solar Cell

10.29007/ndzx ◽  
2018 ◽  
Author(s):  
Mahesh Chauhan ◽  
Davit Dhruv ◽  
Sapana Solanki ◽  
Nikesh Shah
Keyword(s):  
Renewable Energy ◽  
Solar Cell ◽  
Renewable Energy Sources ◽  
Point Of View ◽  
Energy Sources ◽  
Atmospheric Conditions ◽  
Solar Simulator ◽  
Crystalline Solar Cell ◽  
Similar Kind ◽  
Analysis Point

Solar energy is most powerful and trending source among all renewable energy sources. For utility point of view, solar power is available at each place but problem is that the efficiency of solar cell is very low. In addition, the efficiency of solar cell under different atmospheric conditions like different temperature and irradiation, the power we get from the solar cell is different and same as that the efficiency is also changed so for analyzing the behavior of solar cell, we have analyzed mono-crystalline solar cell for different temperature and irradiation and results are taken. For analysis point of view, the mono crystalline solar cell is analyzed into solar simulator under different values of irradiation and temperature and then experimental results for the same are taken. For cross checking the results that we got from the solar simulator, we have done mathematical modelling of solar cell into MATLAB and then the simulated results are taken, the similar kind of results came from the simulation and experimental readings as well.

Fabrication of Organic Dye Sensitized Solar Cell

2014 ◽  
Vol 699 ◽  
pp. 516-521 ◽  
Author(s):  
Gomesh Nair ◽  
Syafinar Ramli ◽  
Muhammad Irwanto ◽  
Mohd Irwan Yusoff ◽  
Muhammad Fitra ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Solar Cell ◽  
Organic Dyes ◽  
Renewable Energy Sources ◽  
Energy Resource ◽  
Organic Dye ◽  
Dye Sensitized Solar Cell ◽  
Cell Efficiency ◽  
Dye Sensitized ◽  
Dragon Fruit

Renewable energy is rapidly gaining importance as an energy resource to help aid the national energy depletion crisis of fossil fuel and coal. One of the most potential renewable energy sources in Malaysia is hydropower followed by solar energy. This paper presents the fabrication of Dye Sensitized Solar Cell (DSSC) using organic dyes from dragon fruit and chlorophyll which is extracted from spinach. The fabrication of DSSC uses the Dr.blade method. Result shows that the efficiency by using dragon fruit as sensitizer at 40µm TiO2 Thickness is 6.45%, better than the usage of chlorophyll dye which is 4.23% at the same thickness. Result also shows that at 80µm by using the dyes from chlorophyll extract has higher solar cell efficiency compare to dragon fruit. This shows that both the chlorophyll extract and dragon fruit shows potential in the development of a feasible working organic dye.

scholarly journals OPF of Modern Power Systems Comprising Renewable Energy Sources Using Improved CHGS Optimization Algorithm

Energies ◽  
2021 ◽  
Vol 14 (21) ◽  
pp. 6962
Author(s):  
Mohamed A. M. Shaheen ◽  
Hany M. Hasanien ◽  
Rania A. Turky ◽  
Martin Ćalasan ◽  
Ahmed F. Zobaa ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Power Systems ◽  
Optimization Algorithm ◽  
Optimal Power Flow ◽  
Optimization Problem ◽  
Renewable Energy Sources ◽  
Wind Farms ◽  
Energy Sources ◽  
Hunger Games ◽  
Generation Costs

This article introduces an application of the recently developed hunger games search (HGS) optimization algorithm. The HGS is combined with chaotic maps to propose a new Chaotic Hunger Games search (CHGS). It is applied to solve the optimal power flow (OPF) problem. The OPF is solved to minimize the generation costs while satisfying the systems’ constraints. Moreover, the article presents optimal siting for mixed renewable energy sources, photovoltaics, and wind farms. Furthermore, the effect of adding renewable energy sources on the overall generation costs value is investigated. The exploration field of the optimization problem is the active output power of each generator in each studied system. The CHGS also obtains the best candidate design variables, which corresponds to the minimum possible cost function value. The robustness of the introduced CHGS algorithm is verified by performing the simulation 20 independent times for two standard IEEE systems—IEEE 57-bus and 118-bus systems. The results obtained are presented and analyzed. The CHGS-based OPF was found to be competitive and superior to other optimization algorithms applied to solve the same optimization problem in the literature. The contribution of this article is to test the improvement done to the proposed method when applied to the OPF problem, as well as the study of the addition of renewable energy sources on the introduced objective function.

scholarly journals Application of Symbiotic Organisms Search Algorithm for Parameter Extraction of Solar Cell Models

2018 ◽  
Vol 8 (11) ◽  
pp. 2155 ◽  
Author(s):  
Guojiang Xiong ◽  
Jing Zhang ◽  
Xufeng Yuan ◽  
Dongyuan Shi ◽  
Yu He
Keyword(s):  
Solar Cell ◽  
Search Algorithm ◽  
Parameter Extraction ◽  
Cell Models ◽  
Unknown Parameters ◽  
Pv System ◽  
Symbiotic Interaction ◽  
Solution Quality ◽  
Symbiotic Organisms Search ◽  
Symbiotic Organisms

Extracting accurate values for relevant unknown parameters of solar cell models is vital and necessary for performance analysis of a photovoltaic (PV) system. This paper presents an effective application of a young, yet efficient metaheuristic, named the symbiotic organisms search (SOS) algorithm, for the parameter extraction of solar cell models. SOS, inspired by the symbiotic interaction ways employed by organisms to improve their overall competitiveness in the ecosystem, possesses some noticeable merits such as being free from tuning algorithm-specific parameters, good equilibrium between exploration and exploitation, and being easy to implement. Three test cases including the single diode model, double diode model, and PV module model are served to validate the effectiveness of SOS. On one hand, the performance of SOS is evaluated by five state-of-the-art algorithms. On the other hand, it is also compared with some well-designed parameter extraction methods. Experimental results in terms of the final solution quality, convergence rate, robustness, and statistics fully indicate that SOS is very effective and competitive.

scholarly journals Development of A Solar Panel Auxiliary System in Order to Extend Range

2018 ◽  
Vol 9 (1) ◽  
pp. 235-238
Author(s):  
Tibor Tóth
Keyword(s):  
Renewable Energy ◽  
Solar Cells ◽  
Solar Cell ◽  
Electric Vehicles ◽  
Renewable Energy Sources ◽  
Limited Range ◽  
Cell System ◽  
Energy Sources ◽  
Solar Powered ◽  
Leaf Model

Abstract The aim of this research is to find a solution that can contribute to the more widespread use of electric vehicles and, through development, promote the use of renewable energy sources. It aims to eliminate the disadvantages of electric vehicles, such as self-discharge, stationary charging and limited range. The focus is mainly a solar-powered solution, since small solar cells have already been implemented on the commercially available Nissan Leaf model to solve similar problems but with very little or no improvement. Encouraged by this attempt I have engineered a larger, more useful auxiliary solar cell system to improve the range of these vehicles.

scholarly journals Estimating PV models using multi-group salp swarm algorithm

2021 ◽  
Vol 10 (2) ◽  
pp. 398
Author(s):  
Mohammad Al-Shabi ◽  
Chaouki Ghenai ◽  
Maamar Bettayeb ◽  
Fahad Faraz Ahmad ◽  
Mamdouh El Haj Assad
Keyword(s):  
Solar Cell ◽  
Mean Squared Error ◽  
Absolute Error ◽  
Cell Models ◽  
Maximum Absolute Error ◽  
Swarm Optimization ◽  
Salp Swarm Algorithm ◽  
Squared Error ◽  
The Social ◽  
Swarm Algorithm

<span id="docs-internal-guid-ea798321-7fff-3e0c-24d7-776c9b1165b3"><span>In this paper, a multi-group salp swarm algorithm (MGSSA) is presented for estimating the photovoltaic (PV) solar cell models. The SSA is a metaheuristic technique that mimics the social behavior of the salp. The salps work in a group that follow a certain leader. The leader approaches the food source and the rest follows it, hence resulting in slow convergence of SSA toward the solution. For several groups, the searching mechanism is going to be improved. In this work, a recently developed algorithm based on several salp groups is implemented to estimate the single-, double-, triple-, Quadruple-, and Quintuple-diode models of a PV solar cell. Six versions of MGSSA algorithms are developed with different chain numbers; one, two, four, six, eight and half number of the salps. The results are compared to the regular particle swarm optimization (PSO) and some of its newly developed forms. The results show that MGSSA has a faster convergence rate, and shorter settling time than SSA. Similar to the inspired actual salp chain, the leader is the most important member in the chain; the rest has less significant effect on the algorithm. Therefore, it is highly recommended to increase the number of leaders and reduce the chain length. Increasing the number of leaders (number of groups) can reduce the root mean squared error (RMSE) and maximum absolute error (MAE) by 50% of its value.</span></span>

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