An Efficient Non-dominated sorting Genetic algorithm II (NSGA II) for Optimal Operation of Micro grid

The paper deals with minimization of the economic problem occurs in a Microgrid. It is a technology arising now a day to satisfy the nearby load demand and to reduce the expenses. Generally, Microgrid consist of renewable resources such as Wind Turbine, Solar Panels, Fuel cell, Micro turbine, CHP etc. In case of crisis in emergency situations, Microgrid can be able to activate Diesel Engine generator(DEG) as a power backup or it can purchase power from the microgrid. The main objective of the paper is to minimize the Operating cost, Fuel cost of DEG, the power transaction cost and to reduce Voltage deviation by finding the best location for connecting the Microgrid. The load constraints and operational constraints are considered. Based on the load demand available excess power can be sold to the Main grid or required power can be purchased from the main grid. The sharing of power between microgrid and main grid reduces the total operational cost. The problem has been implemented with Non-dominated sorting Genetic algorithm II (NSGA II).