Constrained dynamic economic dispatch by simulatedannealing/genetic algorithms
Ongsakul, W.; Ruangpayoongsak, N.
Power Industry Computer Applications, 2001. PICA 2001. Innovative Computing for Power - Electric Energy Meets the Market. 22nd IEEE Power Engineering Society International Conference on
Volume , Issue , 2001 Page(s):207 - 212
Digital Object Identifier 10.1109/PICA.2001.932349
Summary:This paper proposes a genetic algorithm based on simulated
annealing solutions (GA-SA) to solve ramp rate constrained dynamic
economic dispatch (DED) problems for generating units with
nonmonotonically and monotonically increasing incremental cost (IC)
functions. Genetic algorithm (GA) uses a simulated annealing (SA)
solution as a base solution in order to reduce the search effort towards
the optimal solution. The developed GA-SA algorithm is tested on the
generating unit systems in the range of 10 to 40 over the entire
dispatch periods. As transmission line losses are included, the
solutions are near the optimal solutions of zoom brute force (ZBF) and
zoom dynamic programming (ZDP), and are less expensive than those
obtained from SA, local search (LS), GA based on merit order loading
solutions (GA-MOL) and merit order loading (MOL), thereby leading to
substantial fuel cost savings. The proposed GA-SA is effective in
solving constrained dynamic economic dispatch in terms of the quality of
solution
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