臺灣博碩士論文加值系統

本文提出應用粒子群演算法（Particle Swarm Optimization, PSO）
來求解基於電流注入法模型（Equivalent Current Injection, ECI）之預防式安全限制最佳化電力潮流（Predictor Security Constraint Optimal Power Flow, PSCOPF），而為了改善粒子群演算法容易陷入局部最佳解的問題，本文提出了模擬退火之粒子群演算法（Simulated Annealing Particle Swarm Optimization, SAPSO）及多重選擇式粒子群演算法（Multiple PSO, MPSO） 使其能快速且精確得到整體最佳解，更不失其粒子群演算法求解速度快之優點。求解基於電流注入法模型（ECI）之混合整數型最佳化電力潮流（MIOPF），本文所提之混合整數規劃問題包含連續及離數兩種不同型態之變數。其連續變數為傳統最佳化電力潮流之發電機實功輸出和發電機匯流排上的電壓，而離散變數為並聯電容組。在標準IEEE 30 Bus上進行測試，並和其他隨機搜尋演算法作比較。在事故發生前對系統進行規劃，發展系統的安全性分析（Security Analysis, SA）新法則，發展更有效率的新方法作設備與線路狀況的事故分析，將系統線路所有的脆弱部分分別找出並加以排序。除了傳統安全分析的排序功能外，在系統安全分析時更進一步提出預防式-安全調度的建議，確保系統遇到事故時亦能維持在安全運轉或避免壅塞的情況發生。

An Equivalent Current Injection（ECI）based Preventive Security-
Constrained Optimal Power Flow（PSCOPF）is presented in this paper
and a particle swarm optimization (PSO) algorithm is developed for
solving non-convex Optimal Power Flow (OPF) problems. This thesis
integrated Simulated Annealing Particle Swarm Optimization（SAPSO）
and Multiple Particle Swarm Optimization（MPSO）, enabling a fast
algorithm to find the global optimum. Optimal power flow is
solved based on Equivalent- Current Injection（ECIOPF）algorithm. This
OPF deals with both continuous and discrete control variables and is a
mixed-integer optimal power flow（MIOPF）. The continuous control
variables modeled are the active power output and generator-bus voltage
magnitudes, while the discrete ones are the shunt capacitor devices. The
feasibility of the proposed method is exhibited for a standard IEEE 30 bus
system, and it is compared with other stochastic methods for the solution
quality. Security Analysis is also conducted. Ranking method is used to
highlight the most severe event caused by a specific fault. A preventive
algorithm will make use of the contingency information, and keep the
system secure to avoid violations when fault occurs. Generators will be
used to adjust the line flow to the point that the trip of the most severe line
would not cause a major problem.

摘要…………………………………………………………….....……..Ⅰ
Abstract………………………………………………………..…………Ⅱ
目錄............................................................................................................Ⅲ
圖目錄………………………………………………………...…….........Ⅶ
表目錄…………………………………………………………….......….Ⅹ

第一章 緒論……………………………………………………………..1

1-1 研究背景...…..………………….……………….………....1
1-2 研究目的與方法…………………………………...……....2
1-3內容概述…………………….……………………….......…3

第二章 負載潮流工具與事故分析…………………….………….........5

2-1 前言……...……………………………………………....…5
2-2電流注入法負載潮流模型……………………...….......…...6
2-2-1具常數亞可比矩陣之負載潮流模型推導…………….…6
2-2-2 電壓控制匯流排模型推導…………... …………..............9

2-3系統的安全性分析或偶發事故分析…………...……....…14
2-3-1事故模型對系統模型之修正…...…....…………....16
2-4安全度分析特殊案例………………………………...…...18

第三章 粒子群演算法之探討與改良…...……………………….........…..19

3-1傳統基因演算法………….…………...………………..…....19
3-2傳統粒子群最佳化演算法….………………..….............…..23
3-3基於模擬退火之粒子群演算……………….............…......….28
3-4多重選擇之粒子群演法……………………………………..……..….32


第四章 混合整數問題之安全限制最佳化電力潮流…….………....…37

4-1 前言…………………………………………..………...…37
4-2忽略事故分析並不考慮整數問題之OPF…….....…….....40
4-3忽略事故分析並考慮整數問題之OPF…………………. 41
4-4考慮事故分析之預防式安全分析最佳調度…….……….42

第五章 系統測試與結果分析……………………...….........................46

5-1 前言……………………………………..…………..……46
5-2 系統之測試與分析.………………………………...……49
5-3系統加入整數問題之測試與分析………..….…...….......53
5-4 未考慮整數問題之SCOPF測試結果與分析……..........55
5-5 考慮整數問題之SCOPF測試結果與分析…….....….....61
5-6 MPSO之參數挑選….…………………….………….…68

第六章 結論與未來展望…………………………………..……....…..69

6-1 結論…………………………………….....………….…...69
6-2未來研究方向……………………………………….…….70

參考文獻……………………………………...…………..……………..71

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