Simultaneous Application of Distributed Generator and Network Reconfiguration for Power Loss Reduction using Adaptive Quantum inspired Evolutionary Algorithm

Abstract

In power system networks, a common problem encountered by distribution utilities is power losses from their respective networks. Independent implementation of DG and network reconfiguration are majorly used techniques to reduce the losses. In this study, two different scenarios are created with different cases to reduce losses. In Scenario I, simultaneous placement and sizing of DG along with network reconfiguration is used. In Scenario II, an investigation has been performed to reduce the power losses with increased number of small sized DGs. Five cases have been created by operating different DGs, i.e., other than three in parallel with network reconfiguration. An adaptive quantum inspired evolutionary algorithm (AQiEA) is used to maximise the percentage loss reduction and improve voltage profile. The effectiveness of AQiEA is demonstrated and computer simulations are carried out on two IEEE standard benchmark test bus systems. Experimental results indicate that AQiEA has better performance as compared with other algorithms.