Title :
Solving the economic dispatch problem with an integrated parallel genetic algorithm
Author :
Fung, C.C. ; Chow, S.Y. ; Wong, K.P.
Author_Institution :
Sch. of Electr. & Comput. Eng., Curtin Univ. of Technol., Perth, WA, Australia
Abstract :
The application of an integrated parallel genetic algorithm (GA) incorporating simulated annealing (SA) and tabu search (TS) techniques to the economic dispatch (ED) problem is reported in this paper. The integrated genetic algorithm is implemented in both parallel and cluster structures. The parallel computing platform is based on a network of interconnected personal computers (PC) using TCP/IP socket communication facilities. Results from a case study of determining the optimal loading of 13 generators using a network of ten Pentium II-350 computers are presented. The proposed approach has the potential to be applied to other power engineering problem such as unit commitment and maintenance scheduling
Keywords :
genetic algorithms; parallel algorithms; power generation dispatch; power generation economics; power system analysis computing; search problems; simulated annealing; Pentium II-350 computers; TCP/IP socket communication facilities; cluster structures; economic dispatch; integrated parallel genetic algorithm; interconnected personal computers; optimal loading; parallel computing platform; parallel structures; simulated annealing; tabu search; Computational modeling; Computer networks; Genetic algorithms; Microcomputers; Parallel processing; Power engineering computing; Power generation economics; Simulated annealing; Sockets; TCPIP;
Conference_Titel :
Power System Technology, 2000. Proceedings. PowerCon 2000. International Conference on
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-6338-8
DOI :
10.1109/ICPST.2000.898150