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基于改进灰狼算法的最大功率点跟踪

Maximum power point tracking based on improved grey wolf algorithm
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摘要 当光伏阵列处于局部阴影状态下时,功率特性曲线呈现多峰状态,原有的最大功率点跟踪方法已不再适用。所以在局部遮阴条件下应用一种改进的灰狼算法,此法将原有算法中收敛因子线性递减方式改成非线性递减,且引入动态权重调整,改进了原算法的不足之处。试验采用Simulink模型仿真,仿真数据在V-SUN-S4000型发电实训平台进行数据测试,结果表明改进后的灰狼算法收敛速度更快,搜索时间更短,且有效解决全局搜索与局部搜索不平衡的问题。 When the PV array is in a partially shaded state,the power characteristic curve exhibits a multi-peak state,and the original maximum power point tracking method is no longer applicable. Therefore,under the condition of partial shading,an improved grey wolf algorithm is applied in this paper. This method changes the linear decreasing method of convergence factor in the original algorithm to nonlinear decrement,and introduces dynamic weight adjustment to improve the deficiency of the original algorithm. This experiment adopts Simulink model simulation,and the simulation data is tested on the V-SUN-S4000 power generation training platform. The results show that the improved gray wolf algorithm has faster convergence speed,shorter search time,and effectively solves the global search and local search problems in imbalances.
作者 杨丽丽 孙荣霞 王硕南 Yang Lili;Sun Rongxia;Wang Shuonan(College of Electronic Information Engineering,Hebei University,Baoding 071002,China)
出处 《信息技术与网络安全》 2018年第9期97-100,共4页 Information Technology and Network Security
基金 国家级光伏技术虚拟仿真试验教学中心项目(2016GFJG005) 太阳能电池生产关键设备中射频电源装置的国产化研究(11213910D)
关键词 灰狼算法 收敛因子 动态权重 局部阴影 最大功率点跟踪 grey wolf algorithm convergence factor dynamic weight local shadow maximum power point tracking
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