Multi-objective quantum-inspired Artificial Immune System approach for optimal network reconfiguration in distribution system

Abstract

This paper presents a new technique for indentifying optimal network reconfiguration. The proposed technique was developed based on the hybridization of quantum mechanics concepts with the Artificial Immune System (AIS) optimization and it is named as Quantum-inspired Artificial Immune System (QI-AIS). Network reconfiguration is performed by altering the topological structure of the distribution feeder. It provides an efficient way to control the tie-line and sectionalizing switches. By reconfiguring the network, voltage stability can be improved and at the same time system total losses can also be minimized for particular set of loads in a distribution system. Throughout the research, the total loss minimization and voltage stability improvement are the objective functions used to indicate the optimal network reconfiguration. This paper utilized IEEE 69-bus system in this research. Other than having loss minimization and voltage stability improvement as the objective function, this research also looked into multi objective function which is combination of loss minimization and voltage stability improvement using the weighted sum technique. Simulation results show that QI AIS optimization technique gave a better total loss minimization and it also provides a better computation time compared to AIS optimization technique. The results from the multi objective function also outperformed the loss minimization and voltage stability improvement considered individually.