Multiobjective quantum-inspired evolutionary programming for optimal location and sizing of distributed generation

This paper presents Quantum-Inspired Evolutionary Programming (QIEP) technique to determine the optimal locations and sizing of multiple distributed generations (DG) in a distribution system. QIEP is an algorithm that employs the concept of quantum mechanics in the Evolutionary Programming (EP). Quantum-Inspired is implemented according to three levels defined by quantum individuals, quantum groups and quantum universe. The problem formulation is based on a multiobjective model in which the multiobjective are defined as reducing power losses, increasing maximum loadability limits and cost minimisation. Three cases are considered to test the effectiveness of the proposed technique namely single objective function, multiobjective function with fixed weighted sum and multiobjective function with randomly optimised weighted sum. The performances of the multiobjective QIEP optimisation technique were compared with those obtain from conventional evolutionary programming in terms of fitness values and computation time. The proposed study was conducted on the IEEE 69-bus distribution test system and the 141-bus distribution system.