Refined binary particle swarm optimization and application in power system

Authors:
Po-Hung Chen;Cheng-Chien Kuo;Fu-Hsien Chen;Cheng-Chuan Chen
Affiliations:
Department of Electrical Engineering, St. John's University, Taipei, Taiwan, R.O.C.;Department of Electrical Engineering, St. John's University, Taipei, Taiwan, R.O.C.;Department of Electrical Engineering, St. John's University, Taipei, Taiwan, R.O.C.;Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, R.O.C.
Venue:
WSEAS TRANSACTIONS on SYSTEMS
Year:
2009

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Abstract

This paper presents new solution methods and results based on a refined binary particle swarm optimization (RBPSO) for solving the generation/pumping scheduling problem within the power system operation with pumped-storage units. The proposed RBPSO approach combines a basic particle swarm optimization (PSO) with binary encoding/decoding techniques. Complete solution algorithms and encoding/decoding techniques are proposed in the paper. The optimal schedules of both pumped-storage and thermal units are concurrently obtained within the evolutionary process of evaluation functions. Significantly, no hydro-thermal iteration is needed. The proposed approach is applied with success to an actual utility system, which consists of four pumped-storage units and 34 thermal units. The results indicate the attractive properties of the RBPSO approach in practical application, namely, a highly optimal solution cost and more robust convergence behavior.