Parameter Identification Model of Photovoltaic Module Based on Improved Manta Ray Optimization Algorithm
JIAN Xian-zhong1,WANG Peng1,WANG Ru-zhi2
1. School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
2. School of Materials Science and Engineering, Beijing University of Technology, Beijing 100020, China
Abstract：In order to solve the problems of low parameter identification accuracy and poor stability in the current photovoltaic module model, a three-diode photovoltaic module parameter identification model (RLMRFO-TDM) based on manta ray foraging optimization algorithm and the refraction learning mechanism is proposed. The model integrates the differential evolution mechanism into the population updating link of MRFO algorithm, improves the local exploration ability of MRFO algorithm and speeds up the convergence speed of MRFO algorithm. The introduction of refraction learning mechanism improves the randomness of MRFO algorithm, the discreteness of population in the search area and the global search ability of MRFO algorithm. The benchmark function is used to verify the effectiveness of RLMRFO algorithm. The data sets of STP6-120/36 and STM6-40/36 photovoltaic modules are used to test the performance of parameter identification of RLMRFO-TDM model. Compared with other models, RLMRFO-TDM model has the best identification accuracy, stability and convergence speed.
简献忠,王鹏,王如志. 基于改进蝠鲼优化算法的光伏组件参数辨识模型[J]. 计量学报, 2023, 44(1): 109-119.
IAN Xian-zhong,WANG Peng,WANG Ru-zhi. Parameter Identification Model of Photovoltaic Module Based on Improved Manta Ray Optimization Algorithm. Acta Metrologica Sinica, 2023, 44(1): 109-119.
Emad D, EL-Hameed M A, Yousef M T, et al. Computational methods for optimal planning of hybrid renewable microgrids: a comprehensive review and challenges［J］. Archives of computational methods in engineering, 2019, 27(7): 1297-1319.
Wu Z Q, Liu C Y. Parameter identification of photovoltaic cell engineering model based on IHHO algorithm［J］. Acta Metrologica Sinica, 2021, 42(2): 221-227.
［5］
Yu K J, Liang J J, Qu B Y, et al. Parameters identification of photovoltaic models using an improved JAYA optimization algorithm［J］. Energy Conversion and Management, 2017, 150: 742-753.
［7］
Qais M H, Hasanien H M, Alghuwainem S. Enhanced salp swarm algorithm: application to variable speed wind generators［J］. Engineering Applications of Artificial Intelligence, 2019, 80: 82-96.
［9］
Abdel-Basset M, Mohamed R, El-Fergany A, et al. Parameters identification of PV triple-diode model using improved generalized normal distribution algorithm［J］. Mathematics,2021, 9(9): 955-955.
［10］
Elazab O S, Hasanien H M, Elgendy M A, et al. Parameters estimation of single- and multiple-diode photovoltaic model using whale optimisation algorithm［J］. IET Renewable Power Generation, 2018, 12(15):1755-1761.
Wu Z Q, Shen D D, Shang M Y, et al. Parameter identification of photovoltaic cell model based on improved Grasshopper Optimization algorithm［J］. Acta Metrologica Sinica, 2020, 41(12): 1536-1543.
［4］
Drouiche I, Harrouni S, Arab A H. A new approach for modelling the aging PV module upon experimental Ⅰ-Ⅴ curves by combining translation method and five-parameters model［J］. Electric Power Systems Research, 2018, 163: 231-241.
［6］
Qais M H, Hasanien H M, Alghuwainem S. Identification of electrical parameters for three-diode photovoltaic model using analytical and sunflower optimization algorithm［J］. Applied Energy, 2019, 250(1): 109-117.
［8］
Soliman M A, Hasanien H M, Alkuhayli A. Marine predators algorithm for parameters identification of triple-diode photovoltaic models［J］. IEEE Access, 2020, 8(99): 155832-155842.
［11］
Aoun N, Bailek N. Evaluation of mathematical methods to characterize the electrical parameters of photovoltaic modules［J］. Energy Conversion and Canagement, 2019, 193(4): 25-38.
［12］
El-Hameed M A, Elkholy M M, El-Fergany A A. Three-diode model for characterization of industrial solar generating units using manta-rays foraging optimizer: analysis and validations［J］. Energy Conversion and Management, 2020, 219(1): 8-10.
［14］
Qais M, Hasanien H M, Alghuwainem S, et al. Coyote optimization algorithm for parameters extraction of three-diode photovoltaic models of photovoltaic modules［J］. Energy, 2019, 187(8): 116001-116001.
［16］
Elazab O S, Hasanien H M, Alsaidan I, et al. Parameter estimation of three diode photovoltaic model using grasshopper optimization algorithm［J］. Energies, 2020, 13(2): 497-512.
［18］
Hassan M H, Houssein E H, Mahdy M A, et al. An improved manta ray foraging optimizer for cost-effective emission dispatch problems［J］. Engineering Applications of Artificial Intelligence, 2021, 100(2): 1-1.
［21］
Long W, Wu T, Jiao J, et al. Refraction-learning-based whale optimization algorithm for high-dimensional problems and parameter estimation of PV model［J］. Engineering Applications of Artificial Intelligence, 2020, 89(3): 103457.1-103457.14.
［13］
Soliman M A, Al-Durra A, Hasanien H M. Electrical parameters identification of three-diode photovoltaic model based on equilibrium optimizer algorithm［J］. IEEE Access, 2021, 9(99): 41891-41901.
［15］
Qais M H, Hasanien H M, Alghuwainem S. Parameters extraction of three-diode photovoltaic model using computation and harris hawks optimization ［J］. Energy, 2020, 195(4): 117040.1-117040.13.
［17］
Zhao W, Zhang Z, Wang L. Manta ray foraging optimization: an effective bio-inspired optimizer for engineering applications ［J］. Engineering Applications of Artificial Intelligence, 2020, 87: 103300.1-103300.25.
［19］
Izci D, Ekinci S, Eker E, et al. Improved manta ray foraging optimization using opposition-based learning for optimization problems［C］//2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications, Ankara, Turkey, 2020.
［20］
Deng W, Shang S, Cai X, et al. An improved differential evolution algorithm and its application in optimization problem［J］. Soft Computing, 2021, 25(1): 5277-5298.
［23］
Hu Z, Gong W, Li S. Reinforcement learning-based differential evolution for parameters extraction of photovoltaic models［J］. Energy Reports, 2021, 7(7): 916-928.
［22］
Gao W, Liu S, Huang L. A novel artificial bee colony algorithm based on modified search equation and orthogonal learning［J］. IEEE Transactions on Cybernetics, 2013, 43(3): 1011-1024.
［24］
Tong N T, Pora W. A parameter extraction technique exploiting intrinsic properties of solar cells［J］. Applied Energy, 2016, 176(5): 104-115.
2023, Vol. 44 
