Title :
Optimal power flow using evolutionary programming techniques
Author :
El Metwally, M.M. ; El Emary, A.A. ; El Bendary, F.M. ; Mosaad, M.I.
Author_Institution :
Electr. Power & Machines Dept. Fac. of Eng., Cairo Univ., Cairo
Abstract :
This paper presents comparisons between different methods used to solve Optimal Power Flow (OPF) problem economic dispatch (ED) problem. These methods are Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO) algorithm from the heuristic methods. Comparisons between these heuristic methods and conventional methods like Interior Point method (IPM) are introduced. The objective function, which consists of the fuel (generation) cost is minimized. Numerical examples typical to each method are introduced. The solutions obtained are quite encouraging and useful in the economic dispatch environment.
Keywords :
genetic algorithms; heuristic programming; load flow; particle swarm optimisation; power system economics; economic dispatch problem; fuel cost; genetic algorithms; heuristic methods; interior point method; optimal power flow problem; particle swarm optimization; Cost function; Environmental economics; Fuel economy; Genetic programming; Load flow; Power engineering and energy; Power generation; Power generation economics; Power system economics; Power system interconnection; Genetic Algorithms; Interior Point method; Optimal Power Flow and Particle Swarm Optimization;
Conference_Titel :
Power System Conference, 2008. MEPCON 2008. 12th International Middle-East
Conference_Location :
Aswan
Print_ISBN :
978-1-4244-1933-3
Electronic_ISBN :
978-1-4244-1934-0
DOI :
10.1109/MEPCON.2008.4562390