簡易檢索 / 詳目顯示

研究生: 彭彥博
Peng, Yan-Bo
論文名稱: 以隨機協商的方式解決智慧電網中的復電問題
A Stochastic Negotiation Approach to Power Restoration Problems in a Smart Grid
指導教授: 蘇豐文
Soo, Von-Wun
口試委員: 蘇豐文
陳朝欽
蔡孟伸
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: 2011
畢業學年度: 99
語文別: 英文
論文頁數: 51
中文關鍵詞: 隨機協商復電問題多代理人系統
相關次數: 點閱:1下載:0
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • 因為天災或人為疏失所造成的意外,停電是無法避免的。如何能在意外發生之後,盡可能的恢復停電區域的電力,稱之為復電問題。在本論文中,我們將傳統的電力輸配系統視為一個智慧電網,在智慧電網中的每一個元件亦皆可視為一個智慧代理人。我們以決策理論為基礎建立了一個隨機協商的機制,透過這個機制,我們可以在連續的決策中避免陷入區域最佳化的情形,在智慧電網中的代理人會利用此機制彼此協議來解決復電問題。我們會證明我們的系統可以正常運作,並且可以解決許多特殊的復電問題。我們也會證明我們的系統效能比使用委員會導向的多代理人系統更好。在某些情況下,復電問題是非常急迫且有時間限制的,因此,我們最後會分析回復電力的區域比率和復電作業執行時間之間的關係,以期找出一個較適當的時間限制。


    Because of the accidents, the outages of electrical power service occur inevitably. How to restore the out-of-service zones after a fault occurs is called the power restoration problem. In this thesis, we treat the electrical power grid as a smart grid so that devices in the smart grid can be treated as agents. We build a stochastic negotiation protocol based on the decision theory. This stochastic negotiation protocol can avoid trapping into local optimal in sequential decision making. Agents in the smart grid can negotiate with each other using the stochastic negotiation protocol to solve the power restoration problem. We show that our system is workable and capable to solve subtle cases. We also show that the performance of our system is better than a committee-based negotiation multi-agent system. Under some conditions, the power restoration problem is emergent and has a time limit. For this reason, we finally analyze the relationship between the restoration rate and the execution time so that we may find a more proper time limit.

    Abstract I 中文摘要 II Table of Contents III List of Figures IV List of Tables VI 1 Introduction 1 1.1 Power Restoration Problem 1 1.2 Paper Review 3 1.3 Objective 4 2 Methods 7 2.1 Decision theory and Maximum Expected Utility 8 2.2 Probability Maximum Expected Utility 9 2.3 Stochastic Negotiation Protocol 11 2.4 Termination Condition and Any-time Algorithm 18 3 Implementation 20 3.1 Java Agent Development Framework (JADE) 20 3.2 Initialization 21 3.3 Race Condition in Multi Negotiation 22 3.4 Inconsistent Information in Asynchronous Message Passing 24 4 Experiments and Results 27 4.1 Formulation of ZDF and PDF 27 4.2 Reliability Test 33 4.3 Performance Test 36 4.4 Flexibility Test 38 5 Conclusions and Future Works 40 Reference 42 Appendix 45

    1. Adibi, M.M. and R.J. Kafka, Power system restoration issues. Computer Applications in Power, IEEE, 4(2): p. 19-24, 1991.

    2. Hsiao, Y.T. and C.Y. Chien, Enhancement of restoration service in distribution systems using a combination fuzzy-GA method. IEEE Transactions on Power Systems, 15(4): p. 1394-1400, 2000.

    3. Lambert-Torres, G., et al., Particle Swarm Optimization Applied to System Restoration. 2009 IEEE Bucharest Powertech, Vols 1-5, 1992-1997, 2009.

    4. Luan, W.P., M.R. Irving, and J.S. Daniel, Genetic algorithm for supply restoration and optimal load shedding in power system distribution networks. IEE Proceedings-Generation Transmission and Distribution, 149(2): p. 145-151, 2002.

    5. Shin, D.J., et al., Optimal service restoration and reconfiguration of network using Genetic-Tabu algorithm. Electric Power Systems Research, 71(2): p. 145-152, 2004.

    6. Li, X.D., Y.Q. Xu, and L. Zhang. Distribution service restoration with DGs based on multi-agent immune algorithm. In Power Electronics and Intelligent Transportation System (PEITS), 2009 2nd International Conference on. 2009.

    7. Solanki, J.M., S. Khushalani, and N.N. Schulz, A multi-agent solution to distribution systems restoration. Ieee Transactions on Power Systems, 2007. 22(3): p. 1026-1034.

    8. Wu, J.S., et al., An autonomous decision approach for fault allocation and service restoration in electrical distribution systems by multi agent system. In Proceedings of the Ninth International Conference on Hybrid Intelligent Systems, Vol 3, 89-94, 2009.

    9. Nagata, T. and H. Sasaki, A multi-agent approach to power system restoration. IEEE Transactions on Power Systems, 17(2): p. 457-462, 2002.
    10. Pipattanasomporn, M., H. Feroze, and S. Rahman, Multi-Agent systems in a distributed smart grid: design and implementation. IEEE/PES Power Systems Conference and Exposition, Vols 1-3, 1629-1636, 2009.

    11. Faratin, P., C. Sierra, and N.R. Jennings, Negotiation decision functions for autonomous agents. Robotics and Autonomous Systems, 24(3-4): p. 159-182, 1998.

    12. Durfee, E.H., Trends in cooperative distributed problem solving. IEEE Transactions on Knowledge and Data Engineering, 1: p. 63-83, 1989.

    13. Sandholm, T.W., Contract types for satisficing task allocation: I theoretical results. AAAI, 1998.

    14. Andersson, M.R. and T.W. Sandholm, Contract types for satisficing task allocation: II experimental results. AAAI, 1998.

    15. Sankaran, S. and T. Bui. A stochastic negotiation model for organizational choice. in System Sciences, 2004. Proceedings of the 37th Annual Hawaii International Conference on. 2004.

    16. Stuart Russell, P.N., Artificial Intelligence: A modern approach. second ed,2003.

    17. Levy, H. and H.M. Markowitz, Approximating expected utility by a function of mean and variance. American Economic Review, 69(3): p. 308-317, 1979.

    18. Anders Levander, L.N., A stochastic negotiation model. Gnosie, Stockholm, 2007.

    19. Caire, G. JADE TUTORIAL: JADE PROGRAMMING FOR BEGINNERS. 2000, Available from: http://jade.tilab.com/doc/tutorials/JADEProgramming-Tutorial-for-beginners.pdf.

    20. Fabio Bellifemine, G.C., Tiziana Trucco, Giovanni Rimassa. JADE PROGRAMMER'S GUIDE. 2000, Available from: http://jade.tilab.com/doc/programmersguide.pdf.
    21. Fabio Bellifemine, G.C., Tiziana Trucco, Giovanni Rimassa, Roland Mungenast. JADE ADMINISTRATOR'S GUIDE. 2000, Available from: http://jade.tilab.com/doc/administratorsguide.pdf.

    22. Abraham Silberschatz, P.B.G., Greg Gagne, Operating System Concepts. Eighth ed,2005.

    23. James F. Kurose, K.W.R., computer networking: A TOP-DOWN APPROACH FEATURING THE INTERNET. third ed,2005.

    24. Von-Wun Soo, M.-S.T., Wan-Yu Yu, Yen-Bo Peng, Coordination of a society of agents for automatic distribution system restoration: toward a smart grid. 2010 International Conference on Technologies and Applications of Artificial Intelligence, p. 110-115, 2010.

    無法下載圖示 全文公開日期 本全文未授權公開 (校內網路)
    全文公開日期 本全文未授權公開 (校外網路)

    QR CODE