The generation expansion planning of the utility in a deregulated environment

In this paper, an improved genetic algorithm (IGA) is presented to determine the generation expansion planning of the utility in a deregulated market. The utility has to take both the IPPs' participation and environment impact into account when a new generation is expanded. The CO/sub 2/emission also took into account, while satisfying all electrical constraints simultaneously. IGA was conducted by an improved crossover and mutation mechanism with a competition and autoadjust scheme to avoid prematurity. Tabu lists with heuristic rules were also employed in the searching process to enhance the performance. Testing results shows that IGA can offer an efficient way in determining the generation expansion planning. Results can offer utilities for determining the optimal expansion planning.

[1]  Kit Po Wong,et al.  Combined genetic algorithm/simulated annealing/fuzzy set approach to short-term generation scheduling with take-or-pay fuel contract , 1996 .

[2]  S. Hao.  A study of basic bidding strategy in clearing pricing auctions , 1999, Proceedings of the 21st International Conference on Power Industry Computer Applications. Connecting Utilities. PICA 99. To the Millennium and Beyond (Cat. No.99CH36351).

[3]  Jong-Bae Park,et al.  A hybrid genetic algorithm/dynamic programming approach to optimal long-term generation expansion planning , 1998 .

[4]  Mo-Yuen Chow,et al.  A review of emerging techniques on generation expansion planning , 1997 .

[5]  Kit Po Wong,et al.  Power markets analysis using genetic algorithm with population concentration , 2000, PowerCon 2000. 2000 International Conference on Power System Technology. Proceedings (Cat. No.00EX409).

[6]  Fred Glover,et al.  Tabu Search - Part II , 1989, INFORMS J. Comput..

[7]  R. Yokoyama,et al.  An effective DP solution for optimal generation expansion planning under new environment , 2000, PowerCon 2000. 2000 International Conference on Power System Technology. Proceedings (Cat. No.00EX409).

[8]  A. Tsuji.  Optimal Fuel Mix and Load Dispatching Under Environemental Constraints , 1981, IEEE Transactions on Power Apparatus and Systems.

[9]  G. P. Granelli,et al.  Emission constrained dynamic dispatch , 1992 .

[10]  S. A. Al-Baiyat,et al.  Economic load dispatch multiobjective optimization procedures using linear programming techniques , 1995 .

[11]  J. W. Lamont,et al.  Strategic bidding in an energy brokerage , 1997 .

[12]  Yoshikazu Fukuyama,et al.  Parallel genetic algorithm for generation expansion planning , 1996 .

[13]  A. A. El-Keib,et al.  Economic dispatch in view of the Clean Air Act of 1990 , 1994 .