Multiobjective quantum-inspired evolutionary programming for optimal load shedding

This paper present new technique namely Quantum-Inspired Evolutionary Programming (QIEP) to determine the optimal location and optimal amount of load to be shed for undervoltage load shedding schemes. This approach is based on 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 in order to improve the speed of the algorithm. The QIEP is employed to search for the best location and amount of load to be shed based on multiobjective functions which are power loss minimisation, voltage profile improvement and power interruption cost minimisation. The effectiveness of multiobjective QIEP optimisation technique is illustrated in IEEE 33-bus distribution test system, IEEE 69-bus distribution test system and 141-bus distribution system. The results were also compared with other techniques in terms of fitness values and computation time.