DocumentCode :
2220645
Title :
Constrained economic dispatch by micro genetic algorithm based on migration and merit order loading solutions
Author :
Ongsakul, W. ; Tippayachai, J.
Author_Institution :
Dept. of Electr. Eng., Thammasat Univ., Pathumthani, Thailand
fYear :
2000
fDate :
2000
Firstpage :
510
Lastpage :
517
Abstract :
In this paper, a micro genetic algorithm based on migration and merit order loading solutions (MGAM-MOL) for solving the ramp rate constrained economic dispatch (ED) problems for combined cycle (CC) units with linear decreasing and staircase incremental cost (IC) functions is proposed. MGAM-MOL uses a merit order loading (MOL) solution as a base solution in order to reduce the micro genetic algorithm (MGA) search effort towards the optimal solution region. As transmission losses are included, the solutions are near the optimal solutions and are less expensive than those obtained from MGA, simple genetic algorithm (SGA), and MOLs especially for a large number of CC units, thereby leading to substantial fuel cost savings. Moreover, MGAM-MOL can easily facilitate the parallel implementation to reduce the computing expenses without sacrificing the quality of the solution
Keywords :
combined cycle power stations; costing; genetic algorithms; power generation dispatch; power generation economics; power generation planning; combined cycle generating units; constrained economic dispatch; fuel cost savings; linear decreasing cost function; micro genetic algorithm; migration/merit order loading solutions; ramp rate constraints; staircase incremental cost function; transmission losses; Cost function; Encoding; Fuel economy; Genetic algorithms; Large-scale systems; Magneto electrical resistivity imaging technique; Medical services; Optimal scheduling; Power generation economics; System testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electric Utility Deregulation and Restructuring and Power Technologies, 2000. Proceedings. DRPT 2000. International Conference on
Conference_Location :
London
Print_ISBN :
0-7803-5902-X
Type :
conf
DOI :
10.1109/DRPT.2000.855717
Filename :
855717
Link To Document :
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