计算机科学
模糊逻辑
变量(数学)
鲸鱼
网格
算法
控制器(灌溉)
优化算法
控制理论(社会学)
断层(地质)
控制(管理)
人工智能
数学优化
数学
数学分析
渔业
地震学
地质学
生物
农学
几何学
作者
Mohammed H. Qais,Hany M. Hasanien,Saad Alghuwainem
标识
DOI:10.1016/j.engappai.2019.103328
摘要
Abstract Due to the extensive penetration of wind power plants (WPPs) into the grid, grid codes have been imposed such that the WPPs stay linked to the grid during faults for a period to maintain the grid stability. This paper designs optimal Sugeno fuzzy logic controllers (FLCs) to improve the fault ride-through (FRT) ability of grid-connected WPPs. The meta-heuristic algorithm, whale optimization algorithm (WOA), is utilized to design the control rules and the Gaussian memberships of eight Sugeno FLCs, simultaneously, by minimizing the high dimensional multi-objective fitness function. The WOA-FLCs and the grid-connected gearless permanent magnet synchronous generator driven by a variable-speed wind turbine (VSWT-PMSG) are modeled using PSCAD/EMTDC environment. The effectiveness of the FRT ability of grid-connected VSWT-PMSG is investigated during balanced and unbalanced grid fault conditions. The simulation results of using WOA-FLCs revealed fast time response, less overshoot, and small steady-state error compared with those achieved by using a genetic algorithm (GA) and grey wolf optimizer (GWO).
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