混合智能优化技术(HIOT)驱动的FOPID控制器在电力系统负荷频率控制中的应用

R. K. Pandey, D. Gupta, Geetanjali Dei
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引用次数: 0

摘要

本文提出了在放松管制环境下处理多源多区混合电力系统频率和联络线控制的新概念。在解除管制制度下运行的试验系统有火力发电站、水力发电站、风力发电站、燃气轮机发电站等多种来源。报告的工作主要集中在有效地减少频率、联络线和区域控制误差随各种操作班次的变化。由于频率的调节对系统的稳定性至关重要,因此分数阶PID (FOPID)控制器的适当整定对于具有振荡阻尼是非常重要的。为了克服传统控制器在负载频率控制(LFC)中的缺点,实现了一种混合智能算法,以最小化ITAE为目标函数来调整FOPID控制器的控制器增益。该智能技术利用了重力搜索算法(GSA)、萤火虫算法(FA)和粒子群优化(PSO)技术的主要特点。对放松管制环境下不同电力协议和负荷变化情况下的多源多区系统进行了仿真。
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Hybrid Intelligent Optimization Technique (HIOT) Driven FOPID Controller for Load Frequency Control of Deregulated Power System
This paper presents the novel concept to deal with frequency and tie-line control for multi-source multi-area hybrid power systems in a deregulated environment. The test system that operates under deregulated regime has various sources such as thermal power plants, hydroelectric systems, wind energy sources, and gas turbine-based power plants. The reported work mainly focuses on effectively minimizing the variations in frequency, tie-line, and area control error with various operational shifts. Since the regulation of frequency is essential for system stability, therefore proper tuning of Fractional Order PID (FOPID) controllers is very important in order to have oscillation damping. To overcome the disadvantage of conventional controllers in load frequency control (LFC), a hybrid intelligent algorithm has implemented to tune the controller gains of FOPID controllers by minimizing ITAE as an objective function. The proposed intelligent technique utilizes the main features of Gravitational Search Algorithm (GSA), Firefly Algorithm (FA), and Particle Swarm Optimization (PSO) techniques. Simulations are carried out for multi-source multi-area systems under deregulated environment with different power agreements and load change scenarios.
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