Customer interruption cost minimization based on graph theory in smart distribution grid

In this paper, a novel method based on graph theory is proposed to determine the optimum number of fault indicators (FIs) with remote access in order to decrease the customer outage costs in a radial power distribution system. The objective function seeks to minimize total cost of reliability, which is obtained from sum of customers interruption cost and investment cost on fault indicators. Distribution system is modeled as a graph and is partitioned into subgraphs by installing fault indicators in some parts of the network. In this manner, outage cost reduction can be performed in all subgraphs simultaneously. The basis of optimization is an Immune genetic algorithm, and a specific coding is used for modeling the network and applying it to the algorithm. In order to evaluate the proposed method, a real Iranian distribution network is used and the obtained results are discussed.