Energy Management of a Microgrid Using Multi Objective Genetic Algorithm

In present scenario, the generation system is directed towards Hybrid Renewable Energy System (HRES) due to the depleting nature of fossil fuel. So HRES provides a better alternative to conventional energy sources. The microgrid consisting of PV, wind, fuel cell, micro turbine and battery as a backup device is considered for analysis under grid connected mode and islanding mode. The composition of microgrid is formulated as a non-linear, constraint multi objective optimization problem to minimize the operating cost and pollutant treatment cost along with reliability. The Non-dominated sorting genetic algorithm II (NSGA II) is used as an optimization tool and it is implemented using MATLAB for hour-wise data of Zaragoza, Spain and test results are furnished.