Title :
Scheduling of generators with a hybrid genetic algorithm
Author :
Orero, S.O. ; Irving, M.R.
Author_Institution :
Brunel Univ., Uxbridge, UK
Abstract :
In the new competitive electricity supply industry, there is a renewed interest in algorithms that can provide savings in operation costs. An optimal scheduling of generators can provide substantial annual savings in fuel costs, but this highly constrained nonlinear mixed integer optimisation problem can only be fully solved by complete enumeration, a process which is not computationally feasible for realistic power systems. An attempt has been made in this work to incorporate a priority list scheme in a hybrid genetic algorithm to solve the generator scheduling problem. Test results on networks with up to 110 generators are presented
Keywords :
electric power generation; electricity supply industry; genetic algorithms; power system analysis computing; scheduling; electricity supply industry; hybrid genetic algorithm; nonlinear mixed integer optimisation; optimal scheduling; priority list scheme; scheduling of generators;
Conference_Titel :
Genetic Algorithms in Engineering Systems: Innovations and Applications, 1995. GALESIA. First International Conference on (Conf. Publ. No. 414)
Conference_Location :
Sheffield
Print_ISBN :
0-85296-650-4
DOI :
10.1049/cp:19951049