Quantitative Decision-Making Model for Distribution System Restoration

Distribution system restoration is a process of finding backup feeders to restore the load in out-of-service zones by switching operations. A feasible restoration plan must satisfy some practical objectives under operational constraints. Since there may be a tradeoff between objectives, and decision preferences vary from one situation to another, how to evaluate and choose a suitable restoration plan under system emergency has become a real challenge in modern power system operation. Conventional approaches can find feasible restoration plans but fail to identify their relative performance as it is unable to make a quantitative comparison among them. In this paper, we propose a quantitative evaluation framework for ranking restoration plans with their performance indexes, using the analytical hierarchy process-based fuzzy-grey approach. Experimental results showed that the proposed method was effective and helpful in assisting operators during the restoration process.

[1]  I. S. Sariyildiz,et al.  The analytical hierarchy process applied for design analysis , 2005 .

[2]  J. Deng,et al.  Introduction to Grey system theory , 1989 .

[3]  Wen-Hui Chen,et al.  A grey‐based approach for distribution network reconfiguration , 2005 .

[4]  Jin-O Kim,et al.  Optimal service restoration and reconfiguration of network using Genetic-Tabu algorithm , 2004 .

[5]  Wen-Hui Chen,et al.  Distribution system restoration using the hybrid fuzzy-grey method , 2005, IEEE Transactions on Power Systems.

[6]  Wen Xishan,et al.  Study on the fault diagnosis of transformer based on the grey relational analysis , 2002, Proceedings. International Conference on Power System Technology.

[7]  Y. Fukuyama,et al.  Comparative study of modern heuristic algorithms to service restoration in distribution systems , 2002, 2002 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.02CH37309).

[8]  Yo-Ping Huang,et al.  The integration and application of fuzzy and grey modeling methods , 1996, Fuzzy Sets Syst..

[9]  Ming Dong,et al.  Fault diagnosis of power transformer based on model-diagnosis with grey relation , 2003, Proceedings of the 7th International Conference on Properties and Applications of Dielectric Materials (Cat. No.03CH37417).

[10]  Sushil Kumar,et al.  Analytic hierarchy process: An overview of applications , 2006, Eur. J. Oper. Res..

[11]  Chyun-Shin Cheng,et al.  Grey Neural Network , 1998 .

[12]  Y.-Y. Hsu,et al.  A heuristic based fuzzy reasoning approach for distribution system service restoration , 1994 .

[13]  Deng Ju-Long,et al.  Control problems of grey systems , 1982 .

[14]  Y.-Y. Hsu,et al.  Distribution system service restoration using a heuristic search approach , 1991 .

[15]  A. G. Phadke,et al.  Artificial neural networks in power system restoration , 2002 .

[16]  Yogendra Kumar,et al.  Service restoration in distribution system using non-dominated sorting genetic algorithm , 2006 .

[17]  Y.-T. Hsiao,et al.  Enhancement of restoration service in distribution systems using a combination fuzzy-GA method , 2000 .

[18]  A. Ahuja,et al.  An AIS-ACO Hybrid Approach for Multi-Objective Distribution System Reconfiguration , 2007, IEEE Transactions on Power Systems.

[19]  S. S. Venkata,et al.  An expert system operational aid for restoration and loss reduction of distribution systems , 1988 .

[20]  S. L. Muchlinski,et al.  Operational experience and maintenance of an on-line expert system for customer restoration and fault testing , 1991, [Proceedings] Conference Papers 1991 Power Industry Computer Application Conference.

[21]  Chao-Ming Huang.  Multiobjective service restoration of distribution systems using fuzzy cause-effect networks , 2003 .

[22]  M.-S. Tsai,et al.  Operational experience and maintenance of an on-line expert system for customer restoration and fault testing , 1991 .

[23]  Xingying Chen,et al.  A hybrid particle swarm optimization approach for distribution network reconfiguration problem , 2008, 2008 IEEE Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century.

[24]  T. Saaty.  How to Make a Decision: The Analytic Hierarchy Process , 1990 .