Title :
Swarm intelligence for hybrid cost dispatch problem
Author :
EL-Gallad, A.I. ; El-Hawary, M. ; Sallam, A.A. ; Kalas, A.
Author_Institution :
Dept. of Electr. & Comput. Eng., Dalhousie Univ., Halifax, NS, Canada
Abstract :
The paper presents a modified particle swarm optimizer (PSO) to solve the economic power dispatch problem with piecewise quadratic cost function. Practically, operating conditions of many generating units require that the cost function be segmented as piecewise quadratic functions instead of using one convex function for each generator. The proposed technique is applied to a case study of multiple intersecting cost functions for each unit. Unlike the hierarchical method, the proposed algorithm finds combination of power generation that minimizes the total cost function while exactly satisfying the total demand
Keywords :
evolutionary computation; optimisation; power generation dispatch; power generation economics; convex function; cost function segmentation; economic power dispatch problem; generating units; hierarchical method; hybrid cost dispatch problem; modified particle swarm optimizer; multiple intersecting cost functions; operating conditions; optimisation; piecewise quadratic cost function; power generation; proposed technique; total cost function minimisation; Constraint optimization; Cost function; Evolutionary computation; Fuel economy; Genetic mutations; Hybrid power systems; Particle swarm optimization; Power engineering computing; Power generation economics; Power system economics;
Conference_Titel :
Electrical and Computer Engineering, 2001. Canadian Conference on
Conference_Location :
Toronto, Ont.
Print_ISBN :
0-7803-6715-4
DOI :
10.1109/CCECE.2001.933536