基于电能质量调节器的分数阶 PID 控制器,采用混合水母搜索和粒子群算法提高电能质量

Abdallah Aldosary
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摘要

电能质量 (PQ) 是当今电力系统中的一个主要问题,对电力公司和用户都有影响。电力电子设备、智能电网技术和可再生能源(RES)的普及都是当今电力系统出现电能质量问题的原因。统一电能质量调节器(UPQC)是一种多功能工具,可用于解决由不规则电压、电流或频率引起的配电网问题。然而,一些调整参数限制了分数阶比例积分微分(FOPID)控制技术的有效性,而该技术是为提高 UPQC 性能而提出的。为了突破这些限制,找到 FOPID 控制器问题的最优解,我们采用了一种混合优化策略,即混合水母搜索优化器和粒子群优化器(HJSPSO)。为满足 PQ 问题期间的负载要求,建议的模型将可再生能源纳入电网系统。无论是线性负载还是非线性负载,该设计都能将 PQ 问题降至最低。此外,还将 FOPID 控制技术与其他控制器进行了比较。结果表明,采用所提出的 FOPID 控制方法的并网可再生能源系统的 PQ 问题较少。采用 HJSPSO 策略的 UPQC 性能明显优于其他方法,计算时间最短为 127.474 秒,目标函数值为 1.423。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Power Quality Conditioners-Based Fractional-Order PID Controllers Using Hybrid Jellyfish Search and Particle Swarm Algorithm for Power Quality Enhancement
Power quality (PQ) is a major issue in today’s electrical system that affects both utilities and customers. The proliferation of power electronics devices, smart grid technology, and renewable energy sources (RES) have all contributed to the emergence of PQ concerns in today’s power system. The Unified Power Quality Conditioner (UPQC) is a versatile tool that can be used to fix distribution grid issues caused by irregular voltage, current, or frequency. Several tuning parameters, however, restrict the effectiveness of the Fractional-Order Proportional Integral Derivative (FOPID) control technique, which is proposed to improve UPQC performance. To move beyond these restrictions and find the optimal solution for the FOPID controller problem, a hybrid optimization strategy called the Hybrid Jellyfish Search Optimizer and Particle Swarm Optimizer (HJSPSO) is employed. To meet the load requirement during PQ issue periods, the suggested model incorporates a renewable energy source into the grid system. Whether the load is linear or non-linear, the design maintains PQ problems to a minimum. Furthermore, the FOPID control technique is compared with other controllers. Results show that grid-connected RES systems using the proposed FOPID control approach for UPQC have fewer PQ problems. The presented UPQC with HJSPSO strategy significantly outperformed, with the shortest computing time of 127.474 s and an objective function value of 1.423.
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