A MULTIOBJECTIVE DYNAMIC PARTICLE SWARM OPTIMIZER FOR ENVIRONMENTAL/ECONOMIC DISPATCH PROBLEM

El-hosseini, Mostafa A.; El-Sehiemy, Ragab A.; H, Amira Y.

doi:10.21608/erjm.2014.66945

A MULTIOBJECTIVE DYNAMIC PARTICLE SWARM OPTIMIZER FOR ENVIRONMENTAL/ECONOMIC DISPATCH PROBLEM

Document Type : Original Article

Authors

¹ Department, Faculty of Engineering- Mansoura University

² Electrical Engineering Departments, Faculty of Engineering-Kafrelsheikh University,

10.21608/erjm.2014.66945

Abstract

This paper proposes a multi-objective Dynamic Random Neighborhood PSO (DRN-PSO) dynamic search based optimization algorithm for solving dual security constrained economic load dispatch problem in modern power systems. The proposed algorithm uses dynamically adjusted Inertia weight to balance global exploration and local exploitation. Numerical results were conducted on IEEE 30-bus test systems and compared to other optimization techniques that reported in the literature. The obtained results demonstrate the superiority of the proposed DRN-PSO compared to other optimization techniques. Additional economic benefits with secure settings are fulfilled, while preserving all system constraints within their permissible limits. The proposed algorithm improves the economic issue as well as enhancing the power system operation in the technical point of view with acceptable levels of emissions. So, it can be considered as a promising alternative algorithm for solving problems in practical large scale power systems.
Keywords: constrained economic load dispatch, dynamic random neighborhood, environmental emission, multiobjective, Particle swarm optimization, transmission security.