Optimum Dynamic Performance of Wind Power System Using Multi-Objective Grey Wolf Optimizer

Mustafa M. Atiyah, K. Al-Anbarri, A. Mahdi
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Abstract

A modified strategy by multi-objective grey wolf optimizer is implemented for improving the dynamic performance of a wind power system. The proposed wind power system includes a permanent magnet synchronous generator mechanically coupled with a wind turbine to inject active power to grid via power electronic converters. The controller parameters of the generator side and grid side are optimally tuned to stabilize wind generation under the variations of wind speeds and load. The performance index (to be minimized) is the integral time square error of the PI regulators. Simulation results reveal that PI based grey wolf optimizer is faster and more efficient compared with the traditional PI regulator.
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基于多目标灰狼优化算法的风电系统动态性能优化
为了提高风电系统的动态性能,提出了一种改进的多目标灰狼优化策略。所提出的风力发电系统包括与风力涡轮机机械耦合的永磁同步发电机,通过电力电子变流器向电网注入有功功率。对发电机侧和电网侧的控制器参数进行优化调整,使风力发电在风速和负荷变化下保持稳定。性能指标(要最小化)是PI调节器的积分时方误差。仿真结果表明,与传统的PI调节器相比,基于PI的灰狼优化器速度更快,效率更高。
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