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Optimal VAR control for real power loss minimization using differential evolution algorithm
- Source :
- International Journal of Electrical Power & Energy Systems. 66:262-271
- Publication Year :
- 2015
- Publisher :
- Elsevier BV, 2015.
-
Abstract
- Differential evolution algorithm (DEA) is an efficient and powerful population-based stochastic search technique for solving optimization problems over continuous space, which has been proved to be a promising evolutionary algorithm for solving the ORPD problem and many engineering problems. However, the success of DEA in solving a specific problem crucially depends on appropriately choosing trial vector generation strategies (mutation strategies) and their associated control parameter values. This paper presents a differential evolution technique with various trial vector generation strategies based on optimal reactive power dispatch for real power loss minimization in power system. The proposed methodology determines control variable settings such as generator terminal voltages, tap positions and the number of shunts compensator to be switched, for real power loss minimization in the transmission systems. The DE method has been examined and tested on the IEEE 14-bus, 30-bus and the equivalent Algerian electric 114-bus power system. The obtained results are compared with two other methods, namely, interior point method (IPM), Particle Swarm Optimization (PSO) and other methods in the literature. The comparison study demonstrates the potential of the proposed approach and shows its effectiveness and robustness to solve the ORPD problem.
- Subjects :
- Engineering
education.field_of_study
Mathematical optimization
Optimization problem
business.industry
Population
Evolutionary algorithm
Energy Engineering and Power Technology
Particle swarm optimization
AC power
Electric power system
Control theory
Differential evolution
Electrical and Electronic Engineering
business
education
Interior point method
Subjects
Details
- ISSN :
- 01420615
- Volume :
- 66
- Database :
- OpenAIRE
- Journal :
- International Journal of Electrical Power & Energy Systems
- Accession number :
- edsair.doi...........3868130fb6fcaa66015c71a9df206af4