Abstract:Based on the improved moth flame optimization algorithm, a parameter identification method of inverter circuit is proposed. Aiming at the shortcomings of the moth flame algorithm,at the early stage, the improved algorithm makes the moth move to the optimal position in a straight line and speeds up the convergence speed of the algorithm. At the later stage, the Levy flight is used to enhance the diversity of the population and improve the global search ability of the algorithm. The results of parameter identification show that the parameters identified by the improved algorithm are very close to the actual values, and the error is very small. The improved moth flame algorithm can effectively realize the accurate identification of inverter circuit parameters, and can be used in parameter fault diagnosis, operation status monitoring and predictive maintenance.
[1]Shetty P, Mylaraswamy D, Ekambaram T, et al. A hybrid prognostic model formulation system identification and health estimation of auxiliary power units[C]//IEEE. Proceedings of the IEEE Aerospace Conference, Big Sky, Montana, USA, 2006: 10.
[2]陈妤. 电力电子电路参数辨识新方法与故障预测算法研究[D]. 南京: 南京航空航天大学, 2012.
[3]Han W, Wang H H, Wang C L, et al. Parameter identification based fault diagnosis model of photovoltaic modules[J]. Power System Technology, 2015, 39(5): 1198-1204.
[4]Askarzadeh A, Rezazadeh A. Extraction of maximum power point in solar cells using bird mating optimizer-based parameters identification approach[J]. Sol Energy, 2017, 151: 107-115.
[5]Askarzadeh A, Rezazadeh A. Artificial bee swarm optimization algorithm for parameters identification of solar cell models[J]. Applied Energy, 2013, 102(2): 943-949.
[6]Alam D F, Yousri D A, Eteiba M B. Flower pollination algorithm based solar PV parameter estimation[J]. Energy Conversion and Management, 2015, 101: 410-22.
[7]Guo L, Meng Z, Sun Y, et al. Parameter identification and sensitivity analysis of solar cell models with cat swarm optimization algorithm[J]. Energy Conversion and Management, 2016, 108: 520-528.
[8]马皓, 毛兴云, 徐德鸿. 基于混杂系统模型的DC/DC电力电子电路参数辨识[J]. 中国电机工程学报, 2005, 25(10): 50-54。
Ma H, Mao X Y, Xu D H. Parameter identification of DC/DC power electronic circuits based on hybrid system model[J]. Proceedings of the CSEE, 2005, 25(10): 50-54.
[9]孙凤艳, 王友仁, 林华, 等. 基于频域建模与遗传算法的电力电子电路参数辨识方法[J]. 电工技术学报, 2011, 26(11): 99-104.
Sun F Y, Wang Y H, Lin H, et al. Parameter identification of power electronic circuit based on transfer function model and genetic algorithm [J]. Transactions of China Electronic Technical Society, 2011, 26(11): 99-104.
[10]李荣宇, 王颖. 基于莱维飞行的改进粒子群算法[J]. 系统仿真学报, 2017, 8(29): 1685-1691.
Li R Y, Wang Y. Improved Particle Swarm Optimization based on Levy Flights[J]. Journal of System Simulation, 2017, 8(29): 1685-1691.
[11]刘浩然,崔静闯,卢泽丹,等. 一种改进的雁群扩展粒子群算法研究[J]. 计量学报, 2019, 40(3): 498-504.
Liu H R, Cui J C, Lu Z D, et al.Study on An Improved Extended PSO Algorithm Based on Geese Flight[J]. Acta Metrologica Sinica, 2019, 40(3): 498-504.
[12]刘彬,刘泽仁,赵志彪,等.基于速度交流的多种群多目标粒子群算法研究[J]. 计量学报, 2020, 41(8): 1002-1011.
Liu B, Liu Z R, Zhao Z B,et al.Research on Multi-population Multi-objective Particle Swarm Optimization Algorithm Based on Velocity Communication[J]. Acta Metrologica Sinica,2020, 41(8): 1002-1011.
[13]程泽, 董梦男, 杨添剀, 等. 基于自适应混沌粒子群算法的光伏电池模型参数辨识[J]. 电工技术学报, 2014, 29(9): 245-25.
Cheng Z, Dong M N, Yang T K, et al. Extraction of Solar Cell Model Parameters Based on Self-Adaptive Chaos Particle Swarm Optimization Algorithm[J]. Transactions of China Electrotechnical Society, 2014, 29(9): 245-252.
[14]Wu Z Q, Yu D Q, Kang X H. Parameter identification of Solar Cell Model based on improved ant lion optimizer[J].Energy Conversion and Management, 2017, 151: 107-115.
[15]Ali M, Elhameed M A, Farahat M A. Effective parameters identification for polymer electrolyte membrane fuel cell models using Grey Wolf optimizer[J]. Renewable Energy, 2017, 11(1): 455-462.
[16]Mirjalili S. Moth-flame optimization algorithm: a novel nature-inspired heuristic paradigm[J]. Know-Based System, 2015:S0950705115002580.
[17]杨会敏, 宋建成. 基于双环控制的单相电压型PWM逆变器建模与仿真[J]. 电气传动自动化, 2009, 31(1): 15-18.
Yang H M, Song J C. Modeling and simulation of a single-phase voltage PWM inverter based on dual-loop control[J]. Electric Drive Automation, 2009, 31(1): 15-18.
[18]Allam D, Yousri D, Eteiba M. Parameters extraction of the three diode model for the multi-crystalline solar cell/module using Moth-Flame Optimization Algorithm[J]. Energy Conversion and management, 2016, 123: 535-48.
[19]Pertik Garg, Ashu Gupta. Adaptive optimized open shortest path first algorithm using enhanced Moth Flame Algorithm[J]. Indian Journal of Science and Technology, 2017, 10(23): 1-7.