Energy Management of Smart Microgrid in Presence of Renewable Energy Sources Based on Real-time Pricing

In this paper, we propose a novel approach for energy management of a renewable based smart microgrid by applying real-time pricing program. The main purpose is maximizing the profit of the operation with respect to specific constraints. Hence, we consider a residential smart microgrid which is equipped with a large scale of wind and solar power supply, micro gas turbine generators and also, smart homes, which are capable of responding to real-time prices (RTP). We apply price-based and indirect load control which is more pleasant to residential customers. The mathematical optimization model is defined as a mixed integer non-linear problem (MINLP) and through solving this problem, the day-ahead schedule for the operation of the microgrid is determined. Regarding to the complexity and difficulty of solving this type of problems, the benders decomposition (BD) algorithm is applied. The proposed model is evaluated through simulation in various scenarios with different elasticity matrixes. The obtained results of microgrid operation costs, revenues and profit were compared before and after management. The simulation outcomes demonstrate the effective and efficient performance of the proposed methodology and its brilliant impact on improvement of microgrid operation.