Multi-objective Operation Optimization of a Micro-grid using Modified Honey Bee Mating Optimization Algorithm

Recently, it becomes the head of concern for the Micro-grid to derive an optimal operational planning with regard to energy costs minimization, pollutant emissions reduction and better utilization of renewable energy sources (RESs), which accompanied by a Wind Turbine/Fuel Cell/Photovoltaic and Battery hybrid power source to level the power mismatch or to store the surplus of energy when it's needed. In this paper, a new method based on multi-objective Modified Honey Bee Mating Optimization (MHBMO) algorithm is proposed and implemented to dispatch the generations in a typical micro-grid considering economy and emission as competitive objectives. The problem is formulated as a nonlinear constraint multi-objective optimization problem to minimize the total operating cost and the net emission simultaneously. The proposed algorithm is tested on a typical MG and its superior performance is compared to those from other evolutionary algorithms such as GA (Genetic Algorithm) and the original Honey Bee Mating Optimization (HBMO).