Abstract：To overcome the shortcomings of grasshopper optimization algorithm, such as easily falling into local optimum and insufficient convergence accuracy, an improved grasshopper optimization algorithm (IGOA) is proposed. Combing grasshopper optimization algorithm with chaotic algorithm, chaotic initialization is carried out to improve the quality of initial population. Then the differential strategy of differential evolution algorithm is introduced to maintain the diversity of the population through the process of mutation, crossover and selection, and increase the possibility of the algorithm jumping out of the local optimum, so that the algorithm can search for better solutions. The method of particle swarm optimization is introduced in the part of position updating. To accelerate the convergence speed of the algorithm, the current particle optimum value is used as the target. IGOA is used to identify the parameters of polycrystalline silicon solar cells. Compared with other intelligent optimization algorithms, the effectiveness and superiority of IGOA are verified. The effectiveness of IGOA to identify parameters of solar cell under different illumination is also verified by experiments.
［1］Diner F. The analysis on photovoltaic electricity genera-tion status, potential and policies of the leading countries in solar energy ［J］. Renewable & Sustainable Energy Reviews, 2011, 15 (1): 713-720.
［2］吴忠强, 尚梦瑶, 申丹丹, 等. 基于 BSA-ＲELM 的纯电动汽车锂离子电池 SOC 估计［J］. 计量学报, 2019,40(4): 693-699.
Wu Z Q, Shang M Y, Shen D D, et al. Estimation of SOC of li-ion battery in pure electric vehicle by BSA-RELM［J］. Acta Metrologica Sinica, 2019, 40(4): 693-699.
［3］Hirata Y, Noro S, Aoki T. Diagnosis photovoltaic failure by simple function method to acquire I-V curve of phot-ovoltaic modules string［C］// IEEE. Photovoltaic Specialists Conference. Austin, TX, USA ,2012:001340-001343.
［4］De Soto W. Improvement and Validation of a Model for Photovoltaic Array Performance ［J］. Solar Energy, 2006, 80 (1): 78-88.
［5］Saleem H, Karmalkar S. An analytical method to extract the physical parameters of a solar cell from four points on the illuminated J-V curve ［J］. IEEE Electron Device Letters, 2009, 30 (4): 349-352.
［6］Yadir S, Benhmida M, Sidki M, et al. New method forex tracting the model physical parameters of solar cells using explicit analytic solutions of current-voltage equation［C］// IEEE. International Conference on Microelectronics. Marrakech, Morocco, 2009:349-352.
［7］孙晨昕, 金海彬, 丁明理, 等. 卫星电源动态参数测试系统设计［J］. 计量学报, 2020, 41(3):339-343.
Sun C X, Jin H B, Ding M L, et al. Design of dynamic parameter testing system for satellite power［J］. Acta Metrologica Sinica, 2020, 41(3):339-343.
［8］Chan D S H, Phang J C H. Analytical methods for the extraction of solar-cell single-and double-diode model parameters from I-V characteristics ［J］. IEEE Trans-actions on Electron Devices, 1987, 34 (2): 286-293.
［9］Easwarakhanthan T, Bottin J, Bouhouch I, et al. Nonli-near Minimization Algorithm for Determining the Solar Cell Parameters with Microcomputers ［J］. International Journal of Solar Energy, 1986, 4 (1): 1-12.
［10］Jain A, Kapoor A. Exact analytical solutions of the parameters of real solar cells using Lambert W-function ［J］. Solar Energy Materials & Solar Cells, 2004, 81 (2): 269-277.
［11］Oliva D, Cuevas E, Pajares G. Parameter identification of solar cells using artificial bee colony optimization ［J］. Energy, 2014, 72 (7): 93-102.
［12］Gong W, Cai Z. Parameter extraction of solar cell mo-dels using repaired adaptive differential evolution ［J］. Solar Energy, 2013, 94 (4): 209-220.
［13］Hengsi Q , Jonathan W. Parameter Determination of Photovoltaic Cells from Field Testing Data using Particle Swarm Optimization［C］// IEEE. Power & Energy Conference at Illinois. Urbana, IL, USA, 2011:1-4.
［14］Huang W, Jiang C, Xue L Y, et al. Extracting solar cell model parameters based on chaos particle swarm algor-ithm［C］//IEEE. International Conference on Electric Information & Control Engineering. Wuhan, China, 2011:1-5.
［15］Darmansyah D, Robandi I. Photovoltaic parameter estim-ation using Grey Wolf Optimization［C］// IEEE. International Conference on Control, Automation and Robotic. Nagoya, Japan, 2017: 593-597.
［16］Zhu A J, Xu C P, Li Z, et al. Hybridizing grey wolf optimization with differential evolution for global optim-ization and test scheduling for 3D stacked SoC ［J］. Journal of Systems Engineering and Electronics, 2015, 26 (2): 317-328.
［17］Wu Z Q, Yu D Q, Kang X H.
Parameter identification of photovoltaic cell model based on improved ant lion optimizer［J］. Energy Conversion and Management, 2017, 151: 107-115.
［18］Alam D , Yousri D A, Eteiba M B. Parameters Extr-action of the Three Diode Model for the Multi-crystalline Solar Cell Module Using Moth-Flame Optimization Algo-rithm ［J］. Energy Conversion & Management, 2016, 123: 535-548.
［19］Pertik G, Ashu G. Adaptive Optimized Open Shortest Path First Algorithm using Enhanced Moth Flame Algorithm ［J］. Indian Journal of Science and Technology, 2017, 23 (10): 1-7.
［20］吴忠强,申丹丹,尚梦瑶, 等. 基于改进飞蛾火焰算法的单相逆变器参数辨识［J］. 计量学报, 2020, 41(11):1416-1424.
Wu Z Q, Shen D D, Shang M Y, et al. Parameter Identification of Single-Phase Inverter based on Improved Moth Flame Optimization［J］. Acta Metrologica Sinica, 2020, 41(11):1416-1424.
［21］Saremi S, Mirjalili S, Lewis A. Grasshopper Optimisation Algorithm: Theory and application ［J］. Advances in Engineering Software, 2017, 105: 30-47.
［22］Crawford B, Soto R, Pea A, et al. A Binary Grasshopper Optimisation Algorithm Applied to the Set Covering Problem ［J］. Cybernetics and Algorithms in Intelligent Systems, 2018, 765: 1-12.
［23］Zhang X, Miao Q, Zhang H, et al.
A parameter-adaptive VMD method based on grasshopper optimization algorithm to analyze vibration signals from rotating machinery［J］. Mechanical Systems and Signal Processing, 2018, 108: 58-72.
［24］Aljarah I, Al-Zoubi A M, Faris H, et al. Simultaneous Feature Selection and Support Vector Machine Optimiz-ation Using the Grasshopper Optimization Algorithm ［J］. Cognitive Computation, 2018, 10 (3): 478-495.
［25］Wu J, Wang H, Li N, et al. Distributed trajectory optimization for multiple solar-powered UAVs target tracking in urban environment by Adaptive Grasshopper Optimisation Algorithm ［J］. Aerospace Science & Tech-nology, 2017, 70: 497-510.
［26］Ali A A H. Electrical characterisation of proton excha-nge membrane fuel cells stack using grasshopper opti-miser ［J］. Renewable Power Generation, 2018, 12 (1): 9-17.
［27］王玉玲,孙以泽,彭乐乐,等. 基于Lambert W 函数的太阳能电池组件参数确定法 ［J］. 物理学报,2012, 61 (24):525-530.
Wang Y L, Sun Y Z, Peng L L, et al. Parameter extraction for photovoltaic module based on LambertW function ［J］. Acta Physica Sinica, 2012, 61 (24):525-530.
2020, Vol. 41 
