Optimal Environmental and Economic Load Dispatch of Power Systems Based on the Pareto Front of Particle Swarm Optimization

DOI

10.2991/amcce-15.2015.93How to use a DOI?

Keywords

environmental and economic load dispatch; pareto front; improved PSO; multi-objective

Abstract

Currently, most of multi-objective problems in power systems are changed into a single objective problem by weighting. This paper adopts Pareto front to solve the multi-objective problems in power systems. In order to solve this problemeffectively, we present the particle swarm optimization(PSO) algorithm. In addition, we improve PSO with the random black hole strategy, The dynamic update of inertia weight and learning factor, leading particles selection, small probability random mutation. The proposed algorithm can search the Pareto front of the multi-objective functions quickly, and the solutions have the diversity and uniformity. Finally, The algorithm is applied to solve the environmental and economic load dispatch problem of power systems. Considering the environmental impact of emissions and the minimum fuel consumption costs of generators, we get the optimal dispatch of generators output depending on the every period load demands.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Chaofan Zong
AU  - Zhigang Lu
AU  - Jie He
PY  - 2015/04
DA  - 2015/04
TI  - Optimal Environmental and Economic Load Dispatch of Power Systems Based on the Pareto Front of Particle Swarm Optimization
BT  - Proceedings of the 2015 International Conference on Automation, Mechanical Control and Computational Engineering
PB  - Atlantis Press
SP  - 496
EP  - 504
SN  - 1951-6851
UR  - https://doi.org/10.2991/amcce-15.2015.93
DO  - 10.2991/amcce-15.2015.93
ID  - Zong2015/04
ER  -