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    Please use this identifier to cite or link to this item: http://ir.lib.ksu.edu.tw/handle/987654321/19663

    Title: 電力系統考慮FACTS之新型虛功/實功潮流控制策略之研究
    Authors: 黃昭明
    Keywords: 電力潮流
    Power flow
    Reactive power flow control
    Active power flow control
    Flexible AC transmission system
    Differential evolution
    Ant system
    Date: 2012-09-24
    Issue Date: 2013-07-30 12:01:06 (UTC+8)
    Publisher: 行政院國科會:專題研究計畫
    Abstract: 彈性交流輸電系統(FACTS)是一項先進的技術,經由多年的研究與發展,已證實FACTS 能夠被應用在動態穩定度和穩態的控制上。本計畫主要著重在穩態控制上,包含FACTS 設備的裝設位置與數值的調整。為進行FACTS 設備的最佳化搜尋,本計畫應用改良型差分演化法以求解此問題。差分演化法是一種隨機搜尋的最佳化工具,它具有快速收斂與易於實現的優點,然而,單一種突變運算與一對一的競爭選取方式使得差分演化法在最佳化過程中容易陷入局部最佳解。為改善上述缺點,本計畫中結合螞蟻系統與「多重突變」運算機制使系統能隨族群收斂狀況而適時調整突變運算方法,以提升整體搜尋效果。另為使選取機制能更具有多樣性,以提升全域搜尋能力,本計畫中進一步利用進化規劃法中競爭的概念,以隨機競爭的方式做為「選取」後代的運算機制。本計畫以IEEE 30-bus 系統為例進行研究,所提出的方法與基本的差分演化法及粒子群最佳化方法進行比較,以驗證所提出方法在最佳化搜尋上的能力。
    The flexible AC transmission system (FACTS) is an advanced technique. After many years’ studies and realizations, FACTS has shown its capabilities in dynamic stability and steady-state control. This project aims at the study of steady-state control which tries to search the optimal location of FACTS devices and their associated values in the transmission lines. To determine the optimal solution of FACTS, this project proposes an improved differential evolution (IDE) approach to solve this problem. DE is a stochastic search and optimization tool. It has rapid convergence and easy implementation natures. However, the methods of single mutation and one-to-one competition operations used in DE may easy to fall into local minima. To improve the drawbacks in DE, this project combines ant system and multiple mutation operation to adaptively adjust the mutation operation and enhance its global search capability. In addition, to have the selection operation more diverse, this project employs random competition concept used in the evolutionary programming (EP) approach in order to replace the selection operation in DE. The proposed method was implemented using the IEEE 30-bus system. The proposed method will be compared with basic DE and particle swarm optimization (PSO) methods to verify its search capability of optimization.
    Appears in Collections:[電機工程系所] 研究計畫

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