An ordinal optimization theory-based algorithm for large distributed power systems

Authors:
Shieh-Shing Lin;Ch'i-Hsin Lin;Shih-Cheng Horng
Affiliations:
Department of Electrical Engineering, St. John's University, Taipei, Taiwan, ROC;Department of Electronics Engineering, Kao Yuan University, Kaoshiung, Taiwan, ROC;Department of Computer Science and Information Engineering, Chaoyang University of Technology, Taichung, Taiwan, ROC
Venue:
Computers & Mathematics with Applications
Year:
2010

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Abstract

In this paper, we propose an ordinal optimization (OO) theory-based algorithm to solve the yet to be explored distributed state estimation with continuous and discrete variables problems (DSECDP) of large distributed power systems. The proposed algorithm copes with a huge amount of computational complexity problem in large distributed systems and obtains a satisfactory solution with high probability based on the OO theory. There are two contributions made in this paper. First, we have developed an OO theory-based algorithm for DSECDP in a deregulated environment. Second, the proposed algorithm is implemented in a distributed power system to select a good enough discrete variable solution. We have tested the proposed algorithm for numerous examples on the IEEE 118-bus and 244-bus with four subsystems using a 4-PC network and compared the results with other competing approaches: Genetic Algorithm, Tabu Search, Ant Colony System and Simulated Annealing methods. The test results demonstrate the validity, robustness and excellent computational efficiency of the proposed algorithm in obtaining a good enough feasible solution.