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研究生: 歐千瑜
OU, Chien-Yu
論文名稱: 以多代理人於不同區域分割的配電系統下解決自動復電問題
Multi-Agent Power Restoration Based on Different Group Partitions in a Distribution System
指導教授: 蘇豐文
Soo, Von-Wun
口試委員: 周志遠
陳煥宗
學位類別: 碩士
Master
系所名稱: 電機資訊學院 - 資訊工程學系
Computer Science
論文出版年: 2013
畢業學年度: 101
語文別: 英文
論文頁數: 60
中文關鍵詞: 多代理人系統復電問題能源系統
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  • 隨著工商業及科技的發展,對於電力的依賴與日俱增。然而電力系統若無法正常運作,對於社會就會造成莫大的影響。如何能有效並迅速得恢復斷電區域的電力便成為近年來重要的議題。另外,隨著電力產業逐漸民營化的趨勢,電力系統將不再由同一個單位所控管,且還會被切割成許多獨立的區域由不同單位各自管轄,因此傳統只透過一個運算中心的解決方式對於未來不同單位需要彼此協調的情況將不適用。
    本論文提出了一個基於團隊架構的多代理人系統,並用來解決在被切割的電力網路下的復電問題。每一個團隊都是由一領導者代理人及多個成員代理人組成兩階層的組織。成員代理人代表電力網路上的元件;而領導者帶領人則代表著整個團隊,並且管理同一團隊中的所有成員代理人。
    依據實驗結果顯示,我們提出的方法可以在任何被任意切割的電力網路下解決復電問題,且也能迅速的找到解決復電問題的方案。另外,我們也提供在未來民營化的電力網路下能較有效率的切割建議。


    Restoring the de-energized area of power grid system quickly and efficiently is imperative in recent years. Besides, with the trend of deregulation in power grid system, the topology of power grid system will be partitioned into several regions which operate independently, so that the traditional centralized algorithm depends on one computing center won’t be feasible.
    In this thesis, we propose a team-architecture multi-agent system in order to solve the power restoration problem under deregulation situation. A team is a two level hierarchical organization of agents, consisted of one Leader Agent (LA) and several Member Agents (MAs). We treat the components in the power grid system as the MAs of the team and also define LA as the team that supervises the MAs in the team.
    From our results, it shows that our approach can reach a feasible solution under any kinds of the partitioned topologies, and also can quickly reach a feasible solution. Besides, we provide some advice of the partition rule in the topology.

    摘要 i Abstract ii Acknowledgement iii Table of Content iv List of Figures v List of Tables vi 1 Introduction 1 2 Background and Related Work 7 2.1 Background of Power Distribution System 7 2.2 Background of Power Restoration problem 8 2.3 Related Researches 9 3 Problem Formulations 12 3.1 Objectives 12 3.2 Constraints 13 4 Multi-agent System Framework 15 4.1 Team architecture 15 4.2 Agents 16 4.2.1 Member Agent (MA) 16 4.2.2 Leader Agents (LA) 18 5 Algorithm Design 19 5.1 Restoration Process 19 5.2 The Communication protocol 23 5.3 Local Search Method of a Leader Agent 27 5.4 Decision Making of a Leader Agent 29 6 Experimental results 30 6.1 Power Restorability under Different Partitions 30 6.2 The Number of Messages wrt. Different Size Partitions 34 6.2.1 Experiment of T1 35 6.2.2 Experiment of T2 38 6.2.3 Experiment of T3 40 6.3 Solution Quality with Respect to Running Time 43 7 Conclusions 52 Reference 54 Appendix 57

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