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An Evolutionary Generation Scheduling in an Open Electricity Market
Dahal, Keshav P. Siewierski, T.A. Galloway, S.J. Burt, G.M. McDonald, J.R.
Dahal, Keshav P.
Siewierski, T.A.
Galloway, S.J.
Burt, G.M.
McDonald, J.R.
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2004
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© 2004 IEEE. Reprinted from Proceedings of the Congress on Evolutionary Computation - CEC 2004.
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Abstract
The classical generation scheduling problem defines on/off decisions (commitment) and dispatch level of all available generators in a power system for each scheduling period. In recent years researchers have focused on developing new approaches to solve nonclassical generation scheduling problems in the newly deregulated and decentralized electricity market place. In this paper a GA-based approach has been developed for a system operator to schedule generation in a market akin to that operating in England and Wales. A generation scheduling problem has been formulated and solved using available trading information at the time of dispatch. The solution is updated after information is obtained in a rolling fashion. The approach is tested for two IEEE network-based problems, and achieves comparable results with a branch and bound technique in reasonable CPU time.
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Dahal K.P., Siewierski T.A., Galloway S.J., Burt G.M. and McDonald J.R. (2004). An Evolutionary Generation Scheduling in an Open Electricity Market. Congress on Evolutionary Computation (CEC). Portland, Oregon, USA. 19-23 June 2004. Proceedings of the Congress on Evolutionary Computation. Vol. 1., pp. 1135 - 1142.
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