Optimization analysis of multienergy cloud storage integrated with energy conversion systems

Aiming at the increasing energy storage users and diversified energy storage methods, this paper proposes a multi-energy cloud energy storage optimal configuration model with demand side response based on electricity, heat and gas. Collect the historical data of the study area. Predict the future scenery contribution by Monte Carlo method. Then we construct a two-layer optimization model. The upper layer constructs the user charging and discharging energy decision model with the objective function of the lowest user cost. The lower level builds the operator decision model with the total profit maximization of the operator as the objective function. With the fixed investment, operation and maintenance, and carbon emission penalty of the multi-energy complementary system as the constraints, CPLEX optimization solver using the YALMIP toolbox in Matlab. Solving the equipment capacity and power configuration in the three scenarios. Comparing the user costs and operator benefits of the three scenarios. The effectiveness of the proposed method is verified.