A Novel Probabilistic Risk-Based Energy Management Model in the Smart MicroGrids

Nowadays, the smart MicroGrid (MG) is known as a challenging and interesting concept to effectively solve the problems and issues of the power system. In this paper, a novel probabilistic risk base optimization model has been proposed to manage the operation cost and risk cost of the smart MG. The electrical and thermal Demand Response (DR) has been considered in the proposed structure. The Probability Distribution Function (PDF) has been used to model the uncertainty of the model. Also, the K-means and Mixed Integer Linear Programming (MILP) scenario reduction methods have been used to decrease the number of scenarios. Furthermore, the objective function of the proposed optimization is modeled as MILP. The CPLEX solver in the GAMS environment is used to solve the problem. Results show that the electrical and thermal DR causes a decrease in the risk cost of the smart MG.