双层EPSO用于最大化FACTS设备的可加载性

H. Mori, H. Fujita
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引用次数: 3

摘要

本文提出了一种通过柔性交流输电系统(FACTS)设备的优化配置实现电力系统负荷最大化的有效方法。近年来,光伏发电、风力发电等可再生能源被积极引入电力系统,以减少二氧化碳的排放。然而,由于天气条件的变化,这种发电机组倾向于提供可变输出。本文提出了一种混合元启发式方法来确定可变代下FACTS设备的最优分配和最优变量输出,以最大化指定节点上的负载性。提出了一种基于两层进化粒子群优化算法(TLEPSO)的非线性混合整数问题的FACTS设备优化配置方法。考虑光伏系统的不确定性,采用蒙特卡罗仿真方法,评估了概率电力系统条件下指定节点的可载性的概率特征。该方法成功地应用于一个样本系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Two-layered EPSO for maximizing loadability with FACTS devices
This paper proposes an efficient method for maximizing power system loadability with the optimal allocation of FACTS (Flexible AC Transmission System) devices. In recent years, renewable energy such as PV systems and wind power generation is positively introduced into power systems to reduce the emission of CO2. However, such generation units are inclined to provide variable output due to the change of weather conditions. In this paper, a hybrid meta-heuristic method is proposed to determine the optimal allocation and the optimal variable output of FACTS devices under variable generations to maximize loadability at the specified nodes. The proposed method is based on two-layered Evolutionary Particle Swarm Optimization (TLEPSO) to solve the nonlinear mixed integer problem of the optimal allocation of FACTS devices. To consider the uncertainty of PV systems, the Monte-Carlo simulation is carried out to evaluate the probabilistic characteristics of loadability at the specified node in probabilistic power system conditions. The proposed method is successfully applied to a sample system.
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