Optimization of Microgrid Using Quantum Inspired Evolutionary Algorithm

This paper presents a generalized formulation for determining the optimal operating strategy and cost optimization scheme as well as reducing the emissions of a MicroGrid (MG). In this article a microgrid including a wind turbine, pv array and a CHP system consisting of fuel cells and a microturbine is studied and then the modeling of various DERs is conducted and the objective functions and constraints are developed. The model takes into consideration the operation and maintenance costs as well as the reduction in emissions of NOx, SO2, and CO2 In the end the Quantum-Inspired Evolutionary Algorithm is employed to solved the optimal model and an operation scheme is achieved while meeting various constraints on the basis of tariff details, equipment performance, weather conditions and forecasts, load details and forecasts and other necessary information and then the economic costs and environmental impacts are analyzed and a conclusion that the QEA can achieve high environmental benefits and spend as low operation cost as possible. according to power Output functions and cost function of the various units , can be achieve to minimize cost.