A new particle swarm optimization for non-convex economic dispatch

• Published in: European transactions on electrical power 2011-01, Vol.21 (1), p.656-679
• Main Authors: Niknam, Taher, Mojarrad, Hasan Doagou, Meymand, Hamed Zeinoddini
• Format: Article
• Language: English
• Subjects: Algorithms; Cost function; economic dispatch; Economics; Fuzzy; new adaptive particle swarm optimization (NAPSO); Optimization; prohibited operating zones (POZ); Searching; self-adaptive and adaptive parameter; Tuning
• ISSN: 1430-144X; 1546-3109; 1546-3109
• DOI: 10.1002/etep.468

This paper proposes a novel heuristic optimization approach for a constrained economic dispatch (ED) problem using the new adaptive particle swarm optimization (NAPSO) algorithm. The proposed algorithm easily takes care of different constraints, such as transmission losses and prohibited operating zones, and also accounts for non‐smooth/non‐convex cost functions due to valve point loading effects. Particle swarm optimization (PSO) can be used to solve static ED problems. However, appropriate tuning of its parameters is cumbersome and usually converges to local solutions. To overcome the drawbacks of the original PSO algorithm, this paper presents the NAPSO algorithm. In the proposed algorithm, the inertia weight is tuned by using fuzzy IF/THEN rules and the cognitive and the social parameters are self‐adaptively adjusted. In addition, to improve the global searching capability and prevent the convergence to local minima, a new mutation is proposed. To achieve the actual economic operation, the proposed algorithm is tested on a number of sample systems with units possessing prohibited zones and valve‐point loading effects. The results reveal that the proposed approach is computationally efficient and would be a competent method for solving economic load dispatch problems. Copyright © 2010 John Wiley & Sons, Ltd.