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研究生: 裴家佑
Pei, Chia-Yu
論文名稱: 在電力系統中用多代理人做電壓的模糊控制
Multi-Agent Fuzzy Voltage Control in Power Systems
指導教授: 蘇豐文
Soo, Von-Wun
口試委員: 蔡孟伸
Tsai, Men-Shen
孫宏民
Hung-Min Sun
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: 2014
畢業學年度: 102
語文別: 中文
論文頁數: 32
中文關鍵詞: 電力系統電壓控制分散式系統多代理人系統模糊控制
外文關鍵詞: power system, voltage control, decentralized system, multi-agent system, fuzzy control
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  • 在現今時日,我們生活與電力息息相關,我們使用智慧電網來實作現在的電力系統,它可以即時監控系統狀態及自動回復並實現市場機制,在這個智慧電網下,電壓控制這個議題就能在這裡實作,為了要避免系統崩潰,維持電壓的穩定是必需的,而虛功的變化會直接影響到電壓,虛功則由靜態同步補償器(STATCOM)或是分散式發電廠提供。為了增加系統的穩健度和減少系統的時間複雜度,我們使用了多代理人系統和模糊控制實作分散式的控制,而我們並不只單純考慮系統虛功的出力以解決當時的問題,並同時考慮系統未來的穩定度和未來可能的問題。這篇論文討論選擇控制裝置對系統未來的影響,並同時選擇最好的控制裝置來做電壓控制,並且透過模擬實驗證實其選擇和模糊控制的正確性。


    Power is very important in our life. Today, we use smart grids to implement our power system. It can monitor power system states in real time, automatic self-healing and market-enabling. So, there are energy management issues like voltage control that can be implemented in smart grid. To avoid power system crash, we need to keep the system voltage stable by voltage control. The change of reactive power will affect voltage. The reactive power is provided by distributed generators or static synchronous compensators (STATCOMs). To improve the robustness of system and reduce the complexity of system, we implement the system in a decentralized system based on multi-agent system and use fuzzy control concept to reach a faster and decentralized decision. We don’t only consider how to save power to remove instability at current time but also consider the stability in the future time. This paper discusses the future impacts of the selection of a control device on the power system stability and proposes a method to select the best voltage control device. And we prove the correction of the fuzzy control method by different kinds of simulation.

    摘要 I Abstract II 1. Introduction 1 2. The system architecture 4 2.1 Voltage control 4 2.2 Voltage sensitivity and Single bus voltage control 5 2.3 Multi-bus voltage control 7 3. A multi-agent system 9 3.1 A centralized control system 9 3.2 Multi-agent systems 9 4. Fuzzy control 12 4.1 Fuzzy logic 12 4.2 Membership functions 13 5. Program flow 19 6. Simulation 21 6.1 Case 1 21 6.2 Case 2 23 6.3 Case 3 26 7. Conclusion 30 8. References 31

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