Optimal undervoltage load shedding using Quantum-Inspired Evolutionary Programming

This paper presents a new technique to determine optimal undervoltage load shedding in a distribution system with load variation. The proposed technique is based on multiobjective approach namely Quantum-Inspired Evolutionary Programming (QIEP). This approach utilised 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. The result was also compared with other technique in terms of fitness values. The proposed technique also applied for IEEE 69-bus distribution test system and 141-bus distribution system with the variation of loading condition on the load curve.