Slime Mould Algorithm Based Fractional Order Cascaded Controller for Frequency Control of 2-Area AC Microgrid

S. Das, Sushil Kumar Bhoi, P. C. Nayak, R. Prusty
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引用次数: 2

Abstract

This study proposes a Slime Mould Algorithm (SMA) based Fractional Order (FO) cascaded controller (FOPI-FOPD) for frequency control of a two-area AC microgrid (MG) system. The multi-area MG system comprising of a diesel engine generator (DEG), wind turbine generator (WTG), photovoltaic cell (PV), microturbine (MT), along with electric vehicles (EV) and energy storage system like ultra-capacitor (UC). SMA is a novel bio-based optimization tool, which can be used to solve an eclectic real-world problem. This paper aims to incorporate the SMA optimization strategy to solve the Load Frequency Control (LFC) in a microgrid arising due to the ambiguous nature of solar, wind and random load variation. The supremacy of SMA has been vindicated by its comparison over two other intelligent tuning approaches like Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). Moreover, the effectiveness of SMA optimized FOPI-FOPD is validated through a comparative study with some classical controllers. Lastly, it is inferred from numerous simulated outcomes that recommended SMA based FOPI-FOPD controller is better concerning LFC of the MG system.
基于黏菌算法的分数阶级联控制器二区交流微电网频率控制
本研究提出一种基于黏菌算法(SMA)的分数阶级联控制器(FOPI-FOPD),用于两区交流微电网(MG)系统的频率控制。多区域MG系统包括柴油发动机发电机(DEG),风力发电机(WTG),光伏电池(PV),微型涡轮机(MT),以及电动汽车(EV)和超级电容器(UC)等储能系统。SMA是一种新型的基于生物的优化工具,可用于解决各种现实问题。本文旨在结合SMA优化策略来解决由于太阳能、风能和随机负荷变化的模糊性而产生的微电网负荷频率控制(LFC)。通过与遗传算法(GA)和粒子群优化(PSO)等其他两种智能调谐方法的比较,证明了SMA的优越性。此外,通过与经典控制器的对比研究,验证了SMA优化后的FOPI-FOPD的有效性。最后,从大量仿真结果推断,对于MG系统的LFC,推荐的基于SMA的FOPI-FOPD控制器是更好的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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