Title :
Particle swarm optimizer for constrained economic dispatch with prohibited operating zones
Author :
El-Gallad, A. ; El-Hawary, M. ; Sallam, A. ; Kalas, A.
Author_Institution :
Dept. of Electr. & Comput. Eng., Dalhousie Univ., Halifax, NS, Canada
Abstract :
Practically, not all the operating zones of generation units are available always for load allocation due to some physical operation limitations. Accordingly, these prohibited zones divide the operating region between the minimum and the maximum generation limits into disjoint convex subsets. Units with prohibited operating zones transform the ordinary economic dispatch to a nonconvex optimization problem where the conventional Lagrangian multiplier based methods cannot be directly applied. The paper introduces the particle swarm optimizer (PSO) for solving this nonconvex economic dispatch problem. A 15-unit system with 4 units having prohibited operating zones is used for the application. The results are compared with those obtained by both conventional methods and the Hopfield neural network.
Keywords :
concave programming; power generation dispatch; power generation economics; 15-unit system; Hopfield neural network; Lagrangian multiplier based methods; constrained economic dispatch; disjoint convex subsets; generation units; maximum generation limits; minimum generation limits; nonconvex optimization problem; particle swarm optimizer; prohibited operating zones; Constraint optimization; Cost function; Electrical engineering computing; Hopfield neural networks; Lagrangian functions; Optimization methods; Particle swarm optimization; Physics computing; Power generation; Power generation economics;
Conference_Titel :
Electrical and Computer Engineering, 2002. IEEE CCECE 2002. Canadian Conference on
Print_ISBN :
0-7803-7514-9
DOI :
10.1109/CCECE.2002.1015178