Design and analysis of Multi-stage TDF/(1+TI) controller for Load-frequency control of A.C Multi-Islanded Microgrid system using Modified Sine cosine algorithm

D. Mishra, P. C. Nayak, Sushil Kumar Bhoi, R. Prusty
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引用次数: 1

Abstract

This research work presenting an innovative approach to design AC off-grid Multi Microgrid system and proposing an analytical aspect of load frequency control using the Modified sine cosine algorithm based Multi-stage tilt TDF/(1+TI) controller. A Multi Micro-Grid system unites distinctive advantages identical to RES (Renewable energy sources), photovoltaic system model, wind turbine model, etc. The asymmetrical property of RES causes a contradiction between the load ultimatum and the source of the Multi Microgrid system. This asymmetrical property of renewable energy sources affects the system frequency adversely. So, nowadays there is a major challenge to stabilize the frequency oscillations in a Multi Microgrid system. Despite all these complications, this paper proposes an approach to stabilize the system frequency by a Modified sine cosine algorithm (MSCA) tuned Multi-stage tilt TDF/(1+TI) controller. To enhance the modern power system capability to meet the recent nonlinear load demand, Microgrid plays an important component to fulfill the critical loading effectively. To establish the efficacy of the proposed Multi-stage tilt TDF/(1+TI) controller, it has been analyzed by the dynamic responses of the classical PI & PID controller. The effectiveness of the MCSA has been validated by the comparative analysis of responses over the most popular responses obtained by the GA & PSO method.
基于改进正弦余弦算法的交流多岛微电网负荷-频率多级TDF/(1+TI)控制器设计与分析
本研究提出了一种设计交流离网多微电网系统的创新方法,并提出了基于改进正弦余弦算法的多级倾斜TDF/(1+TI)控制器负载频率控制的分析方面。Multi微电网系统具有与RES(可再生能源)、光伏系统模型、风力涡轮机模型等相同的独特优势。RES的不对称特性导致了多微网系统负荷最后通牒与源之间的矛盾。可再生能源的这种不对称特性对系统频率有不利影响。因此,如何稳定多微电网系统的频率振荡是目前面临的主要挑战。尽管存在这些问题,但本文提出了一种通过修正正弦余弦算法(MSCA)调谐多级倾斜TDF/(1+TI)控制器来稳定系统频率的方法。为了提高现代电力系统满足非线性负荷需求的能力,微电网是有效实现临界负荷的重要组成部分。为了验证所提出的多级倾斜TDF/(1+TI)控制器的有效性,通过经典PI & PID控制器的动态响应分析了该控制器。通过对遗传算法和粒子群算法得到的最常见的响应进行对比分析,验证了MCSA的有效性。
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