This paper describes the application of an evolutionary algorithm, Restart Covariance Matrix Adaptation Evolution Strategy (RCMA-ES) to the Generation Expansion Planning (GEP) problem. RCMA-ES 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.
K. Karthikeyan1, S. Kannan2, S. Baskar3, and C. Thangaraj4
1,2Kalasalingam University, India,3Thiagarajar College of Engineering, India,4Anna University of Technology Chennai, India
Constraint Handling, Dynamic Programming, Generation Expansion Planning, Restart Covariance Matrix Adaptation Evolution Strategy, Virtual Mapping Procedure | Published By :
ICTACT
Published In :
ICTACT Journal on Soft Computing
( Volume: 3 , Issue: 1 )
Date of Publication :
October 2012
|