Sitting and sizing of capacitors in distribution system using adaptive quantum inspired evolutionary algorithm

Abstract

The deficits of power at load centers are mainly occurring due to the losses in transmission and distribution network. The structure of distribution network is complex and large. It may produce high power losses and poor voltage regulation. In present power sector scenario the reduction of power losses in the distribution system can significantly improve the reliability and overall efficiency of power network. Therefore, several methods have been implemented for reduction of power losses in the distribution system. The power losses are reduced by optimization of conductor size, load management of distribution transformers, voltage correction etc. One such method of reduction of power losses is placement of capacitors. Reduced power tariff with improved quality of power is the benefit gained by the consumer. Sizing and placement of capacitors in distribution system is a difficult combinatorial optimization problem. Efficient deterministic techniques are not available, hence metaheuristic are used for finding optimal solution. In this paper an adaptive quantum inspired evolutionary algorithm (AQiEA) is used for finding the optimal sizing and location of capacitance. For test case studies two networks, 33 bus system and 69 bus system are considered and the results are compared with the other algorithms in the literature. Experimental results are compared with some 'State of Art' existing algorithms, which show that the proposed technique outperforms some of the existing techniques.