Minimization of Power Losses in Distribution System With Variation in Loads Using Adaptive Quantum inspired Evolutionary Algorithm

Abstract

Network reconfiguration (Nr) is defined as changing the topological structure of network by altering the status of tie line/sectionalizing switches in distribution network (DN). It is mainly used to improve the percentage power loss reduction by altering the power flow. Improvement in voltage profile, smoothening the peak demands and network reliability are the major benefits of network reconfiguration. Traditional network reconfiguration method does not consider the variation in load viz., a fixed network is assumed to be unchangeable, but in actual practice load varies during the day. In this paper, variation in load (nominal, light, heavy) with different scenarios are considered. Minimization of power losses is assumed to be the main objective for the proposed methodology. Improper opening of sectionalizing switches in distribution system may lead to poor voltage regulation and high power losses in distribution system. Nr is a difficult non linear, non differentiable combinatorial optimization problem. Adaptive Quantum inspired Evolutionary Algorithm (AQiEA) is used to find the best candidate solution or optimal switching configuration in DN with minimum power losses. To test the effectiveness and performance of the proposed algorithm, it is applied on IEEE-33 bus system. Simulated result in the table demonstrates that, AQiEA is performing better in comparison with other algorithms (GA, PSO and GSA) which are available in the literature.