Improving self-healing of smart distribution network by allocating switches and distributed generation resources using soft computing

Expansion of distribution networks to increase the reliability due to change of behavior and type of customers is a requirement. On the other side, the concern about environment and climate changes has led to use of renewable energy sources as a replacement for fossil generation sources. DGs based on RES and control switches can play an important role in improving the reliability of the grid, decreasing the costs and mitigating environmental effects. The main purpose of this article is evaluating the remote control switches and manual control and sizing of RES-based DG units including solar cells and wind turbines and simultaneous placement of these units considering their generation uncertainty. The intended function is a bi-objective function that includes reducing network costs and improving the Side Reliability Index and technical and economic constraints are considered too. The intended function is modeled as a mixed integer nonlinear programming and four evolutionary algorithms are used to solve this problem and their results are compared. Roy Billinton 4-bus network is chosen as the test network in this article.