Optimal sizing of distributed generation by using quantum-inspired evolutionary programming

Abstract

The paper proposes a novel evolutionary programming inspired by quantum mechanics, called a quantum-inspired evolutionary programming (QIEP). The proposed algorithm consists of three levels, quantum individuals, quantum groups and quantum universes. The proposed algorithm is implemented to determine the optimal sizing of distributed generation (DG) for loss minimization at the optimal location. The location of the distributed generation was identified using the sensitivity indices. In order to demonstrate its performance, comparative studies are performed with conventional evolutionary programming in terms of loss minimization and computation time. The installation of single DG and multiple DG also presented and the results shows better improvement in terms of loss minimization and voltage profile. The proposed study was conducted on the IEEE 69-bus test system.