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首页> 外文期刊>Renewable Power Generation, IET >Symbiotic organisms search algorithm-based optimal control strategy for efficient operation of variable-speed wind generators
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Symbiotic organisms search algorithm-based optimal control strategy for efficient operation of variable-speed wind generators

机译:基于共生生物搜索算法的变速风力发电机高效运行最优控制策略

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摘要

The penetration rate of grid-tied wind turbine generator systems (WTGSs) into the existing electricity networks is rapidly increasing worldwide. Huge efforts are exerted for improving the characteristics of variable-speed wind energy conversion systems. This study exhibits a novel symbiotic organisms search algorithm (SOSA)-based optimal control strategy for achieving efficient operation of a grid-connected WTGS. The optimal control strategy relies on proportional-integral (PI) controllers, which are properly fine-tuned using the SOSA. The simulation-based optimisation method is considered in the optimisation process, where the integration of the square error criterion is selected as a fitness function. To obtain realistic performances, practical wind speed data extracted from the Zaafarana power plant in Egypt are used in the analyses. The efficacy of the SOSA-based optimal PI control strategy is compared with that realized using the grey wolf optimiser algorithm (GWOA)-based PI control scheme, considering network disturbances. The feasibility of the proposed control strategy is validated using the simulation studies, which are implemented using MATLAB/Simulink software. Notably, the proposed SOSA-based optimal control strategy is considered to be a precise means of improving the behaviour of grid-tied WTGSs.
机译:并网风力涡轮发电机系统(WTGS)在现有电网中的普及率正在全球范围内迅速提高。为了改善变速风能转换系统的特性而付出了巨大的努力。这项研究展示了一种新颖的基于共生生物搜索算法(SOSA)的最优控制策略,可实现并网WTGS的高效运行。最佳控制策略依赖于比例积分(PI)控制器,可以使用SOSA对其进行适当的微调。在优化过程中考虑了基于仿真的优化方法,其中选择平方误差准则的积分作为适应度函数。为了获得逼真的性能,分析中使用了从埃及Zaafarana电厂提取的实际风速数据。考虑到网络干扰,将基于SOSA的最佳PI控制策略的效果与使用基于灰狼优化器算法(GWOA)的PI控制方案实现的效果进行了比较。通过使用MATLAB / Simulink软件实现的仿真研究,验证了所提出控制策略的可行性。值得注意的是,所提出的基于SOSA的最佳控制策略被认为是改善并网WTGS行为的精确方法。

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