Performance optimization of photovoltaic and solar cells via a hybrid and efficient chimp algorithm

Solar Energy - Tập 253 - Trang 343-359 - 2023
Chao Yang1, Chang Su1, Haiting Hu1, Mostafa Habibi2,3,4, Hamed Safarpour5, Mohamed Amine Khadimallah6,7
1School of Advanced Manufacturing, Guangdong University of Technology, Jieyang 522000, Guangdong, China
2Institute of Research and Development, Duy Tan University, Da Nang, 550000, Viet Nam
3Faculty of Electrical – Electronic Engineering, Duy Tan University, Da Nang 550000, Viet Nam
4Center of Excellence in Design, Robotics, and Automation, Department of Mechanical Engineering, Sharif University of Technology, Azadi Avenue, P.O. Box 11365-9567, Tehran, Iran
5Faculty of Engineering, Department of Mechanics, Imam Khomeini International University, Qazvin, Iran
6Prince Sattam Bin Abdulaziz University, College of Engineering, Civil Engineering Department, Al-Kharj, 16273, Saudi Arabia
7Laboratory of Systems and Applied Mechanics, Polytechnic School of Tunisia, University of Carthage, Tunis, Tunisia

Tài liệu tham khảo

Abbassi, 2019, An efficient salp swarm-inspired algorithm for parameters identification of photovoltaic cell models, Energy conversion and management, 179, 362, 10.1016/j.enconman.2018.10.069 Abd Elaziz, 2018, Parameter estimation of solar cells diode models by an improved opposition-based whale optimization algorithm, Energy conversion and management, 171, 1843, 10.1016/j.enconman.2018.05.062 Alam, 2015, Flower pollination algorithm based solar PV parameter estimation, Energy Conversion and Management, 101, 410, 10.1016/j.enconman.2015.05.074 AlRashidi, 2011, A new estimation approach for determining the I-V characteristics of solar cells, Solar Energy, 85, 1543, 10.1016/j.solener.2011.04.013 Al-Shamma’a, A.A., et al., Parameter Estimation of Photovoltaic Cell/Modules Using Bonobo Optimizer. Energies, 2022. 15(1): p. 140. Askarzadeh, 2012, Parameter identification for solar cell models using harmony search-based algorithms, Solar Energy, 86, 3241, 10.1016/j.solener.2012.08.018 Askarzadeh, 2013, Artificial bee swarm optimization algorithm for parameters identification of solar cell models, Applied energy, 102, 943, 10.1016/j.apenergy.2012.09.052 Askarzadeh, 2013, Extraction of maximum power point in solar cells using bird mating optimizer-based parameters identification approach, Solar energy, 90, 123, 10.1016/j.solener.2013.01.010 Azhdari, 2020, Power Consumption Optimization in Underwater Wireless Sensor Networks Based on EECRU Clustering Algorithm for Routing, Iranian Journal of Marine Science and Technology, 24, 1 Babu, 2016, Parameter extraction of two diode solar PV model using Fireworks algorithm, Solar energy, 140, 265, 10.1016/j.solener.2016.10.044 Bao, 2000, Numerical solution of diffraction problems by a least-squares finite element method, Mathematical methods in the applied sciences, 23, 1073, 10.1002/1099-1476(200008)23:12<1073::AID-MMA152>3.0.CO;2-D Cárdenas, 2016, Experimental parameter extraction in the single-diode photovoltaic model via a reduced-space search, IEEE Transactions on Industrial Electronics, 64, 1468, 10.1109/TIE.2016.2615590 Chen, 2020, Parameters identification of photovoltaic cells and modules using diversification-enriched Harris hawks optimization with chaotic drifts, Journal of Cleaner Production, 244, 10.1016/j.jclepro.2019.118778 Chin, 2016, An accurate modelling of the two-diode model of PV module using a hybrid solution based on differential evolution, Energy conversion and management, 124, 42, 10.1016/j.enconman.2016.06.076 Dali, A., A. Bouharchouche, and S. Diaf. Parameter identification of photovoltaic cell/module using genetic algorithm (GA) and particle swarm optimization (PSO). in 2015 3rd International Conference on Control, Engineering & Information Technology (CEIT). 2015. IEEE. Ebrahimi, 2019, Parameters identification of PV solar cells and modules using flexible particle swarm optimization algorithm, Energy, 179, 358, 10.1016/j.energy.2019.04.218 Elattar, 2019, Environmental economic dispatch with heat optimization in the presence of renewable energy based on modified shuffle frog leaping algorithm, Energy, 171, 256, 10.1016/j.energy.2019.01.010 El-Naggar, 2012, Simulated annealing algorithm for photovoltaic parameters identification, Solar Energy, 86, 266, 10.1016/j.solener.2011.09.032 Elyaqouti, 2021, Parameters identification and optimization of photovoltaic panels under real conditions using Lambert W-function, Energy Reports, 7, 9035, 10.1016/j.egyr.2021.11.219 Fathy, 2017, Parameter estimation of photovoltaic system using imperialist competitive algorithm, Renewable Energy, 111, 307, 10.1016/j.renene.2017.04.014 Gao, 2018, Parameter extraction of solar cell models using improved shuffled complex evolution algorithm, Energy conversion and management, 157, 460, 10.1016/j.enconman.2017.12.033 Ginidi, 2021, Supply demand optimization algorithm for parameter extraction of various solar cell models, Energy Reports, 7, 5772, 10.1016/j.egyr.2021.08.188 Grabitz, 2005, A multi-diode model for spatially inhomogeneous solar cells, Thin Solid Films, 487, 14, 10.1016/j.tsf.2005.01.027 Guan, 2019, A flower pollination algorithm for the double-floor corridor allocation problem, International Journal of Production Research, 57, 6506, 10.1080/00207543.2019.1566673 Hachana, 2013, Comparison of different metaheuristic algorithms for parameter identification of photovoltaic cell/module, Journal of renewable and sustainable energy, 5, 10.1063/1.4822054 Hafez, 2018 Hejri, 2014, On the parameter extraction of a five-parameter double-diode model of photovoltaic cells and modules, IEEE Journal of Photovoltaics, 4, 915, 10.1109/JPHOTOV.2014.2307161 Ibrahim, 2022, A hybrid wind driven-based fruit fly optimization algorithm for identifying the parameters of a double-diode photovoltaic cell model considering degradation effects, Sustainable Energy Technologies and Assessments, 50, 10.1016/j.seta.2021.101685 Imani, 2018, The impact of customers’ participation level and various incentive values on implementing emergency demand response program in microgrid operation, International Journal of Electrical Power & Energy Systems, 96, 114, 10.1016/j.ijepes.2017.09.038 Ishaque, 2011, An improved modeling method to determine the model parameters of photovoltaic (PV) modules using differential evolution (DE), Solar energy, 85, 2349, 10.1016/j.solener.2011.06.025 Ismail, 2013, Characterization of PV panel and global optimization of its model parameters using genetic algorithm, Energy Conversion and Management, 73, 10, 10.1016/j.enconman.2013.03.033 Jacob, 2015, Solar PV modelling and parameter extraction using artificial immune system, Energy Procedia, 75, 331, 10.1016/j.egypro.2015.07.375 Kaidi, 2022, Dynamic Levy Flight Chimp Optimization, Knowledge-Based Systems, 235, 10.1016/j.knosys.2021.107625 Khanna, 2015, A three diode model for industrial solar cells and estimation of solar cell parameters using PSO algorithm, Renewable Energy, 78, 105, 10.1016/j.renene.2014.12.072 Khishe, 2019, Passive sonar target classification using multi-layer perceptron trained by salp swarm algorithm, Ocean Engineering, 181, 98, 10.1016/j.oceaneng.2019.04.013 Khishe, 2019, Improved whale trainer for sonar datasets classification using neural network, Applied Acoustics, 154, 176, 10.1016/j.apacoust.2019.05.006 Khishe, 2018, Chaotic fractal walk trainer for sonar data set classification using multi-layer perceptron neural network and its hardware implementation, Applied Acoustics, 137, 121, 10.1016/j.apacoust.2018.03.012 Khishe, 2021, Evolving Deep Learning Convolutional Neural Networks for early COVID-19 detection in chest X-ray images, Mathematics, 9, 1002, 10.3390/math9091002 Khishe, 2020, Chimp optimization algorithm, Expert Systems with Applications, 10.1016/j.eswa.2020.113338 Khishe, 2020, Classification of underwater acoustical dataset using neural network trained by Chimp Optimization Algorithm, Applied Acoustics, 157, 10.1016/j.apacoust.2019.107005 Kler, 2017, PV cell and module efficient parameters estimation using Evaporation Rate based Water Cycle Algorithm, Swarm and evolutionary computation, 35, 93, 10.1016/j.swevo.2017.02.005 Kler, 2019, A novel approach to parameter estimation of photovoltaic systems using hybridized optimizer, Energy Conversion and Management, 187, 486, 10.1016/j.enconman.2019.01.102 Ma, 2013, Parameter estimation of photovoltaic models via cuckoo search, Journal of applied mathematics, 10.1155/2013/362619 Ma, 2022, Analytical modeling and parameter estimation of photovoltaic strings under partial shading conditions, Solar Energy Materials and Solar Cells, 235, 10.1016/j.solmat.2021.111494 Mahmoodzadeh, 2021, Presenting the best prediction model of water inflow into drill and blast tunnels among several machine learning techniques, Automation in Construction, 127, 10.1016/j.autcon.2021.103719 Malinowski, 2009, A survey on cascaded multilevel inverters, IEEE Transactions on industrial electronics, 57, 2197, 10.1109/TIE.2009.2030767 Mathew, 2017, Wind-driven optimization technique for estimation of solar photovoltaic parameters, IEEE Journal of Photovoltaics, 8, 248, 10.1109/JPHOTOV.2017.2769000 Mosavi, 2019, Multi-Layer Perceptron Neural Network Utilizing Adaptive Best-Mass Gravitational Search Algorithm to Classify Sonar Dataset, Archives of Acoustics, 44, 137 Mosavi, M., M. Kaveh, and M. Khishe. Sonar data set classification using MLP neural network trained by non-linear migration rates BBO. in The fourth Iranian conference on engineering electromagnetic (ICEEM 2016). 2016. Mosavi, 2017, Training a feed-forward neural network using particle swarm optimizer with autonomous groups for sonar target classification, Journal of Circuits, Systems and Computers, 26, 1750185, 10.1142/S0218126617501857 Mosavi, M., et al. Design and implementation a sonar data set classifier by using MLP NN trained by improved biogeography-based optimization. in proceedings of the second National Conference on marine technology. 2016. Mousavi, 2015, Classification of sonar targets using OMKC, Iranian Journal of Marine Science and Technology, 18, 25 Mousavi, 2016, Sonar Data Set Classification Using MLP Neural Network Trained By Modified Biogeography-Based Optimization, Iranian Journal of Marine Science and Technology, 20, 65 Naeijian, 2021, Parameter estimation of PV solar cells and modules using Whippy Harris Hawks Optimization Algorithm, Energy Reports, 7, 4047, 10.1016/j.egyr.2021.06.085 Nayak, 2019, Parameter estimation of single diode PV module based on GWO algorithm, Renewable Energy Focus, 30, 1, 10.1016/j.ref.2019.04.003 Nejad, 2015, A survey on performance of photovoltaic systems in Iran, Iranica Journal of Energy and Environment, 6, 77 Oliva, 2014, Parameter identification of solar cells using artificial bee colony optimization, Energy, 72, 93, 10.1016/j.energy.2014.05.011 Oliva, 2017, Parameter estimation of photovoltaic cells using an improved chaotic whale optimization algorithm, Applied energy, 200, 141, 10.1016/j.apenergy.2017.05.029 Orioli, 2019, A procedure to evaluate the seven parameters of the two-diode model for photovoltaic modules, Renewable energy, 139, 582, 10.1016/j.renene.2019.02.122 Patel, 2014, Extraction of solar cell parameters from a single current–voltage characteristic using teaching learning based optimization algorithm, Applied Energy, 119, 384, 10.1016/j.apenergy.2014.01.027 Pourmousa, 2019, Parameter estimation of photovoltaic cells using improved Lozi map based chaotic optimization Algorithm, Solar Energy, 180, 180, 10.1016/j.solener.2019.01.026 Qais, 2019, Identification of electrical parameters for three-diode photovoltaic model using analytical and sunflower optimization algorithm, Applied Energy, 250, 109, 10.1016/j.apenergy.2019.05.013 Qiao, W., M. Khishe, and S. Ravakhah, Underwater targets classification using local wavelet acoustic pattern and Multi-Layer Perceptron neural network optimized by modified Whale Optimization Algorithm. Ocean Engineering. 219: p. 108415. Qin, H. and J.W. Kimball. Parameter determination of photovoltaic cells from field testing data using particle swarm optimization. in 2011 IEEE Power and Energy Conference at Illinois. 2011. IEEE. Rajasekar, 2013, Bacterial foraging algorithm based solar PV parameter estimation, Solar Energy, 97, 255, 10.1016/j.solener.2013.08.019 Reis, L., J. Camacho, and D. Novacki. The Newton Raphson method in the extraction of parameters of PV modules. in Proceedings of the International Conference on Renewable Energies and Power Quality (ICREPQ’17), Malaga, Spain. 2017. Saffari, A. and M. Khishe, Classification of Marine Mammals Using Trained Multilayer Perceptron Neural Network With Whale Algorithm Developed With Fuzzy System. 2020. Saffari, 2022, Fuzzy Grasshopper Optimization Algorithm: A Hybrid Technique for Tuning the Control Parameters of GOA Using Fuzzy System for Big Data Sonar Classification, Iranian Journal of Electrical and Electronic Engineering, 18, 2131 Saffari, A., et al., Design of a fuzzy model of control parameters of chimp algorithm optimization for automatic sonar targets recognition. 2020. Shannan, 2013 Skoplaki, 2009, Operating temperature of photovoltaic modules: A survey of pertinent correlations, Renewable energy, 34, 23, 10.1016/j.renene.2008.04.009 Soon, 2015, Optimizing photovoltaic model for different cell technologies using a generalized multidimension diode model, IEEE Transactions on Industrial Electronics, 62, 6371, 10.1109/TIE.2015.2420617 Stornelli, 2019, A new simplified five-parameter estimation method for single-diode model of photovoltaic panels, Energies, 12, 4271, 10.3390/en12224271 Wang, 2020, Training RBF NN Using Sine-Cosine Algorithm for Sonar Target Classification, Archives of Acoustics, 753 Wang, 2021, Photovoltaic cell parameter estimation based on improved equilibrium optimizer algorithm, Energy Conversion and Management, 236, 10.1016/j.enconman.2021.114051 Wang, 2021, Binary Chimp Optimization Algorithm (BChOA): a New Binary Meta-heuristic for Solving Optimization Problems, Cognitive Computation, 13, 1297, 10.1007/s12559-021-09933-7 Wolpert, 1997, No free lunch theorems for optimization, IEEE transactions on evolutionary computation, 1, 67, 10.1109/4235.585893 Wu, 2017, Parameter identification of photovoltaic cell model based on improved ant lion optimizer, Energy Conversion and Management, 151, 107, 10.1016/j.enconman.2017.08.088 Yoon, 1988, Lower-upper symmetric-Gauss-Seidel method for the Euler and Navier-Stokes equations, AIAA journal, 26, 1025, 10.2514/3.10007 Yu, 2017, Parameters identification of photovoltaic models using an improved JAYA optimization algorithm, Energy Conversion and Management, 150, 742, 10.1016/j.enconman.2017.08.063 Yu, 2018, Multiple learning backtracking search algorithm for estimating parameters of photovoltaic models, Applied energy, 226, 408, 10.1016/j.apenergy.2018.06.010 Yu, 2019, A performance-guided JAYA algorithm for parameters identification of photovoltaic cell and module, Applied Energy, 237, 241, 10.1016/j.apenergy.2019.01.008 Yuan, 2014, Parameter extraction of solar cell models using mutative-scale parallel chaos optimization algorithm, Solar Energy, 108, 238, 10.1016/j.solener.2014.07.013 Zeng, 2021, Parameter identification of pv cell via adaptive compass search algorithm, Energy Reports, 7, 275, 10.1016/j.egyr.2021.01.069 Zeng, 2004, A guaranteed global convergence particle swarm optimizer, Journal of computer research and development, 41, 1333 Zhang, 2020, Orthogonal Nelder-Mead moth flame method for parameters identification of photovoltaic modules, Energy Conversion and Management, 211, 10.1016/j.enconman.2020.112764