ICTACT Journal on Soft Computing

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Application of Restart Covariance Matrix Adaptation Evolution Strategy (RCMA_-ES) to Generation Expansion Planning Problem


Affiliations
1 Department of Electrical and Electronics Engineering, Kalasalingam University, India
2 Department of Electrical and Electronics Engineering, Thiagarajar College of Engineering, India
3 Anna University of Technology, Chennai, India
     

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This paper describes the application of an evolutionary algorithm, Restart Covariance Matrix Adaptation Evolution Strategy (RCMAES) to the Generation Expansion Planning (GEP) problem. RCMAES is a class of continuous Evolutionary Algorithm (EA) derived from the concept of self-adaptation in evolution strategies, which adapts the covariance matrix of a multivariate normal search distribution. The original GEP problem is modified by incorporating Virtual Mapping Procedure (VMP). The GEP problem of a synthetic test systems for 6- year, 14-year and 24-year planning horizons having five types of candidate units is considered. Two different constraint-handling methods are incorporated and impact of each method has been compared. In addition, comparison and validation has also made with dynamic programming method.

Keywords

Constraint Handling, Dynamic Programming, Generation Expansion Planning, Restart Covariance Matrix Adaptation Evolution Strategy and Virtual Mapping Procedure.
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  • Application of Restart Covariance Matrix Adaptation Evolution Strategy (RCMA_-ES) to Generation Expansion Planning Problem

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Authors

K. Karthikeyan
Department of Electrical and Electronics Engineering, Kalasalingam University, India
S. Kannan
Department of Electrical and Electronics Engineering, Kalasalingam University, India
S. Baskar
Department of Electrical and Electronics Engineering, Thiagarajar College of Engineering, India
C. Thangaraj
Anna University of Technology, Chennai, India

Abstract


This paper describes the application of an evolutionary algorithm, Restart Covariance Matrix Adaptation Evolution Strategy (RCMAES) to the Generation Expansion Planning (GEP) problem. RCMAES is a class of continuous Evolutionary Algorithm (EA) derived from the concept of self-adaptation in evolution strategies, which adapts the covariance matrix of a multivariate normal search distribution. The original GEP problem is modified by incorporating Virtual Mapping Procedure (VMP). The GEP problem of a synthetic test systems for 6- year, 14-year and 24-year planning horizons having five types of candidate units is considered. Two different constraint-handling methods are incorporated and impact of each method has been compared. In addition, comparison and validation has also made with dynamic programming method.

Keywords


Constraint Handling, Dynamic Programming, Generation Expansion Planning, Restart Covariance Matrix Adaptation Evolution Strategy and Virtual Mapping Procedure.