政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/57579

政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/57579

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政大機構典藏 > 資訊學院 > 資訊科學系 > 學位論文 > Item 140.119/57579

請使用永久網址來引用或連結此文件: https://nccur.lib.nccu.edu.tw/handle/140.119/57579

題名:	以代理人基方法之基礎設施互依性模擬 Infrastructure Interdependency Simulation Using Agent-Based Modeling
作者:	劉治宏 Liu, Chih Hung
貢獻者:	李蔡彥 Li, Tsai Yen 劉治宏 Liu, Chih Hung
關鍵詞:	代理人基模擬電力網路互依性分析 Agent-Based Modeling Power grid Interdependency
日期:	2012
上傳時間:	2013-04-01 14:39:04 (UTC+8)
摘要:	基礎設施是民生不可或缺的元素之一。重要基礎設施通常由許多節點構成，也因為彼此之間相依性極高，所以也被視為一種典型的複雜系統。近年來以資訊科技輔助分析這類重點基礎設施的研究也越來越多，從文獻上來看主要可以分為兩大類：(1)互依性分析(2)系統分析。前者著重於使用像拓樸分析這類數值分析的方式，找出弱點基礎設施；而後者則是使用大量模擬的方式來找尋潛在的弱點基礎設施，並模擬不同情境的危機情境。常見的基礎設施分析，多以拓樸分析為基礎找出弱的節點，並套用蒙地卡羅演算法到模型內，做為模擬的依據，但較少見到以基礎設施的各項屬性和規則當作模型的模擬。因此，本篇論文的貢獻是希望以台灣電力公司之電力基礎設施運轉規章、基礎設施的屬性等這些資料為例，當作建立模型的基礎，將Push-Relabel演算法的步驟分散至各代理人上，作為電力調度平衡的計算方式，並採用Repast Simphony作為我們代理人基模擬的工具。藉由操作這些節點的狀態，我們設計了七個不同情境的模擬，並以IEEE指標做為結果的評估方式，藉以說明我們可以透過代理人基模擬找出基礎設施中的弱點，並能夠建立不同的情境模擬各式的危機和災難，進而提供預防的機會。此外，我們的模擬工具亦提供不同的視覺化呈現結果，讓使用者能夠簡單的看出模擬過程的變化，並能夠將結果儲存並重現。 Infrastructure is important to our lives. Most infrastructure facilities consist of nodes and edges of high dependency. These kinds of facilities are considered as traditional complex systems. The research of using computer technologies to analyze such systems has grown recently. We can classify recent research into two categories: 1. Dependency analysis, and 2. System dynamic analysis. The former focuses on computation methods such as topology analysis to find vulnerable nodes while the latter focuses on large-scale simulation to find potential vulnerable infrastructure facilities. Common dependency analysis uses topology analysis to find vulnerable nodes and apply the Monte-Carlo method to their model. However, it merely applies an infrastructure’s parameters and rules to their model. In this thesis, our contributions are on applying such parameters and rules to our model by taking Taiwan Power Company as an example. On this basis, we use agent-based modeling to simulate the context. We used the Push-Relabel algorithm to dispatch the power flow. And we used Repast Simphony as a tool of agent-based modeling. We established different situations to simulate different disasters such as earthquake or tsunami, and to provide a chance estimate and reduce the damages of such a disaster in advance. Besides, we also used indices of an IEEE standard to evaluate our result. In other words, we can find the vulnerable nodes or potential threat in a power grid with agent-based simulation. Besides, we provided various user interfaces for users to observe the information of the power grid more easily and efficiently. Our user interfaces can dynamically present the change of information on the power grid, and the result can be saved and loaded for future uses.
參考文獻:	http://www.taipower.com.tw/left_bar/power_life/power_flow.htm. [2] S.M. Rinaldi, J.P. Peerenboom, T.K. Kelly, Identifying, Understanding, and Analyzing Critical Infrastructure Interdependencies, IEEE control systems magazine., 21 (2001) 11-25. [3] C.M. Macal, M.J. North, Agent-based Modeling and Simulation, Winter Simulation Conference, (2009). [4] L. Hagen, A.B. Kahng, New Spectral Methods for Ratio Cut Partitioning and Clustering IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, (1992). [5] L. CIUPALA, The Cost Scaling Algorithm for Bipartite Network, Bulletin of the Transilvania University of Brasov, 2 (2009) 8. [6] P. Crucitti, V. Latora, M. Marchiori, Model for Cascading Failures in Complex Networks, Physical Review E, 69 (2004). [7] P. Crucitti, V. Latora, M. Marchiori, A Topological Analysis of the Italian Electric Power Grid, Physica A, 338 (2004) 92-97. [8] P. Crucitti, V. Latora, M. Marchiori, Locating Critical Lines in High-Voltage Electrical Power Grids, Fluctuation and Noise Letters, 5 (2005). [9] F. Cadini, E. Zio, C.-A. Petrescu, Using Centrality Measures to Rank the Importance of the Components of a Complex Network Infrastructure, in: R. Setola, S. Geretshuber (Eds.) Critical Information Infrastructure Security, (Springer Berlin / Heidelberg, 2009), 155-167. [10] I. Eusgeld, W. Kröger, G. Sansavini, M. Schläpfer, E. Zio, The Role of Network Theory and Object-Oriented Modeling within a Framework for the Vulnerability Analysis of Critical Infrastructures, Reliability Engineering & System Safety, 94 (2009) 954-963. [11] E. Zio, C.-A. Petrescu, G. Sansavini, Vulnerability Analysis of a Power Transmission System, (2008). [12] E. Zio, R. Piccinelli, Randomized Flow Model and Centrality Measure for Electrical Power Transmission Network Analysis, Reliability Engineering & System Safety, 95 (2010) 379-385. [13] C.M.R. Sanseverino, E. Zio, Solving Advanced Network Reliability Problems by Means of Cellular Automata and Monte Carlo Sampling, Reliability Engineering & System Safety, 89 (2005) 219-226. [14] E. Zio, L. Podofillini, V. Zille, A Combination of Monte Carlo Simulation and Cellular Automata for Computing the Availability of Complex Network Systems, Reliability Engineering & System Safety, 91 (2006) 181-190. [15] M. Marseguerra, E. Zio, Monte Carlo Simulation for Model-Based Fault Diagnosis in Dynamic Systems, Reliability Engineering & System Safety, 94 (2009) 180-186. [16] S.A. Harp, S. Brignone, B.F. Wollenberg, T. Samad, SEPIA. A Simulator for Electric Power Industry Agents, Control Systems, IEEE, 20 (2000) 53-69. [17] P. Pederson, D. Dudenhoeffer, S. Hartley, M. Permann, Critical Infrastructure Interdependency Modeling A Survey of U.S and international research, (2006). [18] L. Tolbert, H. Qi, F. Peng, Scalable Multi-Agent System for RealTime Electric Power Management, in: Proc. Power Engineering Society Summer Meeting, (2001), 1676-1679. [19] M. Anim, Toward Self-Healing Energy Infrastructure Systems, Computer Applications in Power, IEEE, 14 (2001) 20-28. [20] S. Panzieri, R. Setola, G. Ulivi, An Agent Based Simulator for Critical Interdependent Infrastructures, (2004). [21] M. Schüle, R. Herrler, F. Klügl, Coupling GIS and Multi-Agent Simulation – Towards Infrastructure for Realistic Simulation, in: G. Lindemann, J. Denzinger, I. Timm, R. Unland (Eds.) Multiagent System Technologies, (Springer Berlin / Heidelberg, 2004), 228-242. [22] E. Casalicchio, E. Galli, S. Tucci, Federated Agent-Based Modeling and Simulation Approach to Study Interdependencies in IT Critical Infrastructures, in: Proceedings of the 11th IEEE International Symposium on Distributed Simulation and Real-Time Applications, (IEEE Computer Society, 2007), 182-189. [23] E. Casalicchio, E. Galli, S. Tucci, Modeling and Simulation of Complex Interdependent Systems: A Federated Agent-Based Approach, in: Critical Information Infrastructure Security, (Springer-Verlag, 2009), 72-83. [24] R.C. Mihailescu, M. Vasirani, S. Ossowski, Towards Agent-Based Virtual Power Stations via Multi-Level Coalition Formation, in: First International Workshop on Agent Technologies for Energy Systems, (2010). [25] A. Saleem, M. Lind, M.M. Veloso, Multiagent-Based Protection and Control in Decentralized Electric Power Systems, in: First International Workshop on Agent Technologies for Energy Systems, (2010). [26] W. Lam, A.M. Segre, A Distributed Learning Algorithm for Bayesian Inference Networks IEEE Transactions on Knowledge and Data Engineering, (2002) 13. [27] M. Hoefer, Strategic Cooperation in Cost Sharing Games, 6th International Workshop, WINE, (2010) 17. [28] SWARM, http://www.swarm.org. [29] MASON, http://cs.gmu.edu/~eclab/projects/mason/. [30] Repast Simphony, http://repast.sourceforge.net/. [31] A.V. Goldberg, R.E. Tarjan, A New Approach to the Maximum Flow Problem, Proceeding STOC `86 Proceedings of the eighteenth annual ACM symposium on Theory of computing (1986) 11. [32] J.D. Glover, M.S. Sarma, T.J. Overbye, Power System Analysis and Design, Fifth Edition, (2011). [33] I.P.E. Society, IEEE Guide for Electric Power Distribution Reliability Indices, (2012). [34] 台灣電力公司, 超高壓系統之來臨－南北第一路～第三路345kV幹線暨超高壓變電所 http://taipower.pcc.gov.tw/files/15-1002-234,c88-1.php. [35] Gordoncheng`s Blog,電力系統負載曲線, http://gordoncheng.wordpress.com/2010/09/06/%E9%9B%BB%E5%8A%9B%E7%B3%BB%E7%B5%B1%E8%B2%A0%E8%BC%89%E6%9B%B2%E7%B7%9Aload-curve/ [36] Y.H. Liu, Computational Large-Scale Complex Networks : Competition Network and Power Grid, in: Graduate Institute of Applied Physics, (National Chengchi University, 2012), 73.
描述:	碩士國立政治大學資訊科學學系 98753003 101
資料來源:	http://thesis.lib.nccu.edu.tw/record/#G0098753003
資料類型:	thesis
顯示於類別:	[資訊科學系] 學位論文

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