Optimal Reconfiguration Along with Optimal Sizing of Renewable Energy Based Micro- Grid in Distribution System Using Teaching Learning-Based Optimization algorithm

Reconfiguration of distribution networks is necessary for maintaining power supply for example during networkmaintenance and for restoring power after an outage and before the fault leading to it has been repaired. It is alsothe basis of avoiding overloads and minimizing resistive losses. Our search space is a collection of networkconfigurations, characterized by the open/closed status of all switches in the network. This low-level stateencoding is converted into a more structured representation, which identifies feeders and isolated regions thatneed to be resupplied with power. As said earlier, the cost of a switching plan is defined as the sum of the costsof the individual switching actions. Different actions can have different costs. For example, one can considermonetary costs reflecting the wear and tear of the switching devices, and the cost incurred by delays whenrecovering from outages. Variable action costs allow to encode a problem more realistically but, on the otherhand, they often tend to increase the difficulty of a cost-optimal search. As a particular case, if all switchingactions in a given network happen to have the same cost, then minimizing the cost of a plan is equivalent tominimizing the number of actions in the plan. In this study the objective function is minimizing the total costwhich contains the switching cost and renewable enery cost in the micro-grid. Wind and solar energy are themost commonly used renewable energy sources in a hybrid system. Conventional distributed generation sources(DGs) such as; gas turbines, diesel generators, fuel cells (FCs), and also battery banks can be used with a wind–PV generation system in order to improve the overall system performance.