臺灣博碩士論文加值系統

電力系統的架構主要分為發電系統，輸電系統與配電系統三大部份。配電系統在正常的運轉下，操作人員在調度時除了讓配電系統運轉可以達到有效的電力分配與電力資源應用最大化之目的外，同時必須確保不會違反相關限制條件。這些限制條件如放射狀之拓樸架構、最大電壓降百分比、導線上的容量等。為了能夠有效調度電力資源並符合上列相關的限制條件，饋線重構的操作是常用的技術之一。饋線重構的目的主要分為兩大部份：首先，電力系統正常運轉時，調度員會以平衡饋線負載量、降低線路損失與提高供電品質為主要目標，預期可以提升系統運轉效能；其二，電力系統發生緊急情況時，快速找出故障點並快速隔離故障區域，縮小停電範圍。饋線重構的操作方式是利用改變饋線上的開關投切狀態完成。當系統上的開關狀態發生改變時，系統拓撲也會異動。配電系統所屬的每條饋線上所安裝的開關數量都不一定會相同，隨著配電系統的規模增大，饋線上之開關數量亦相對增加。為了在正常運轉模式下能夠達到更經濟有效的電力品質或在故障發生時即時完成故障區域的隔離，如何決定每個開關狀態的啟閉將是問題的關鍵。由於需要決定開關的投切狀態，因此，饋線重構操作方式可以歸類為一典型的組合型最佳化問題。一般而言，系統調度人員在進行操作時，都會考慮不同的目標。常見的目標包含有降低開關切換的次數、減少饋線的實功損失、提昇系統的平衡度及最小化最大電壓降百分比等。
本論文提出使用帶電粒子系統搜尋演算法以求解饋線重構問題。帶電粒子系統搜尋演算法中，每個粒子都代表一個系統拓撲。為了有效增進演算法之搜尋效能，本論文提出以實數編碼機制進行系統拓撲之描述與分析。透過本論文所提出之實數解碼機制，系統拓樸得以維持系統放射狀的特性而不需要額外進行驗證程序。為了證明所採用的編解碼程序與帶電粒子系統搜尋演算法的有效性，本論文先以單目標問題驗證，目標函數則考慮饋線損失最小化的系統拓樸。並使用三種不同的系統進行驗證。其次，探討多目標饋線重構問題之求解。在多目標問題上，考慮饋線損失、電壓降百分比與開關切換次數三個目標函數，以說明本論文所提方法的有效性。結果顯示、透過本論文所採用的演算法並搭配合適的編解碼操作程序，能有效有效解決單目標與多目標饋線問題最佳化。

Power system architecture is divided into three parts: generation, transmission and distribution. In distribution system, to achieve proper and effective operations, it is necessary to ensure no violation of the constraints exists. The operation constraints include maintaining radial topology, reducing voltage drop percentage and limiting conductor current. In order to dispatch power resources more effectively and avoid any violations of the constraints, feeder reconfiguration is one of the commonly used techniques. The goals of feeder reconfiguration include two parts. First, during normal operation, the dispatchers try to operate the system in a more economical way. Secondly, when an emergency situation occurs, identifying and isolating the problems becomes more important issues. In this case, applying the feeder reconfiguration to isolate the faulted zones, reduce the outage area, and restore the largest customer is a common practice by dispatchers.
Feeder reconfiguration is achieved by changing the statuses of the switches. When the statuses of the switches change, the topology of distribution system is altered In a typical distribution system, the number of switches may be large. To either achieve an economical operation during normal operation; or to isolate the faulted areas during an occurrence of a fault, determining the status of these switches is a difficult task. Thus, feeder reconfiguration can be classified as a typical combination optimization problem. When dealing with the distribution system problems, the dispatchers consider different goals during normal or emergency operations when system reconfiguration needs to be performed. These goals include reducing the number of switches actions, reducing the real power losses, improving the inter-feeder balancing and minimizing the voltage drop percentage.
This dissertation applied the Charged System Search algorithm (CSS) for solving the feeder reconfiguration problem. Each charge particle in the CSS represents a solution which represents a specific distribution system topology. To improve the search efficiency, a novel real-number string decoding technique is proposed. The proposed decoding method maps a particle coordination to a valid radial topology without verification. In order to illustrate the effectiveness of the proposed decodingtechnique with CSS algorithm, a single-objective problem is applied first. Different power topologies (33-Bus, 66-Bus and 248-Bus) are used. Secondly, multi-objective CSS is used for solving three objective problems. The objectives in this dissertation includes primary feeder losses, the voltage drop percentage and the number of switches operations. The results show that the proposed decoding technique integrated with CSS algorithm is able to identify the best solutions comparing with other mean-heuristic algorithms. For the multi-objective problems, the Pareto Front identified by the proposed approach achieves a better one than other algorithms.

中文摘要 i
英文摘要 iii
誌謝……………………. v
目錄……………. vi
表目錄 viii
圖目錄 ix
第一章 緒論 ix
1.1 研究動機 1
1.2 研究目的 3
1.3 文獻回顧 5
1.4 研究方法 7
1.5 論文架構 9
第二章 饋線重構 10
2.1 配電系統 10
2.1.1配電系統簡介 11
2.1.2配電自動化概說 13
2.2 配電系統重構 15
2.2.1配電系統之重構目的 15
2.2.2編碼方式與饋線重構 17
2.3電力潮流計算 22
2.3.1概念 22
2.3.2負載模型介紹 23
2.3.3電力潮流分析運算 25
2.4常用之配電系統重構目標函數 28
2.4.1配電系統之損失計算 28
2.4.2配電系統之最大末端壓降計算 28
2.4.3配電系統之平衡度計算 29
第三章 研究方法 30
3.1群體智慧與饋線重構關係概述 30
3.1.1群集演算法概念 31
3.1.2常見編碼與饋線重構的關係 32
3.1.3多目標最佳化問題與求解方式 35
3.1.4帶電粒子系統搜尋演算法與Pareto最佳化 40
3.2實數編碼設計 41
3.2.1開關實數編碼設計 42
3.2.2區域實數編碼設計 48
3.3帶電粒子系統搜尋演算法 56
3.3.1電磁場理論 56
3.3.2牛頓運動定律 58
3.3.3帶電粒子系統搜尋演算法 59
3.4改良型帶電粒子系統搜尋演算法 64
3.4.1粒子移動評估機制(Particle Moving Evaluation Mechnism, PMEM) 64
3.4.2實數字串-連絡開關-損失對照(RealString TieSwitch Loss Mapping, RTLM) 65
3.4.3改良型粒子系統搜尋演算法 67
3.5應用Pareto-帶電粒子系統搜尋演法於多目標饋線重構之探討 68
3.5.1目標函數向量化之最佳化問題分析 69
3.5.2 Pareto前緣與Pareto最佳解群 71
3.5.3非支配排序的帶電粒子系統搜尋演算法概述 72
3.5.4針對配電系統饋線重構之非支配排序的帶電粒子系統搜尋演算法 75
第四章 結果與分析 77
4.1以實數型帶電粒子系統搜尋演算法求解饋線重構問題 78
4.1.1 33-Bus配電系統 79
4.1.2 66-Bus配電系統 81
4.1.3 248-Bus 配電系統 83
4.2改良型演算法效能分析 87
4.2.1帶電粒子系統搜尋演算法與增強整數編碼粒子群集演算法的演算法分析 87
4.2.2 RTLM & PMEM於帶電粒子系統搜尋演算法的效能分析 88
4.3多目標饋線重饋 91
4.3.1 33-Bus系統 91
4.3.2 248-Bus系統 92
4.4 小結 94
第五章 結論 96
5.1結論 96
5.2未來展望 98
參考文獻…………………………………………………………………………………..100

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