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Democratic joint operations algorithm for optimal power extraction of PMSG based wind energy conversion system

机译：基于PMSG的风能转换系统最优功率提取的民主联合运算算法。

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摘要

This paper proposes a novel military philosophy inspired meta-heuristic algorithm called democratic joint operations algorithm (DJOA), which attempts to find the optimal parameters of proportional-integral-derivative (PID) controllers of permanent magnetic synchronous generator (PMSG) based wind energy conversion system (WECS), such that a maximum power point tracking (MPPT) under different wind speed profiles can be achieved. In order to realize a deeper optimum search, an additional deputy officer is introduced into the democratic defensive operations of each military unit, in which the soldiers can wisely seek a more optimal defensive position following the consensus/compromise of the officer and deputy officer. Furthermore, the shuffling strategy of shuffled frog leaping algorithm (SFLA) is employed for the shuffling regroup operations of DJOA, which effectively avoids the local optimum trapping by sharing the global position information among all the soldiers. Three case studies are carried out, e.g., step change of wind speed, low-turbulence stochastic wind speed variation, and high-turbulence stochastic wind speed variation, respectively. Simulation results verify that an improved optimal power extraction can be realized by DJOA compared with that of other five typical meta heuristic algorithms.
机译：本文提出了一种新颖的军事哲学启发式元启发式算法，称为民主联合作战算法（DJOA），试图找到基于永磁同步发电机（PMSG）的风能转换比例-积分-微分（PID）控制器的最优参数。系统（WECS），从而可以实现不同风速曲线下的最大功率点跟踪（MPPT）。为了实现更深入的最优搜索，在每个军事单位的民主防御行动中都增加了一名副官，士兵可以在军官和副官的共识/妥协之后明智地寻求更好的防御阵地。此外，在DJOA的改组重组操作中采用了改组蛙跳算法（SFLA）的改组策略，通过在所有士兵之间共享全局位置信息，有效避免了局部最优陷阱。进行了三个案例研究，例如风速的阶跃变化，低湍流随机风速变化和高湍流随机风速变化。仿真结果证明，与其他五种典型的元启发式算法相比，DJOA可以实现改进的最优功率提取。

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