Steady-state Security Region-based Chance-constrained Optimization for Integrated Energy Systems

Abstract

The power injection uncertainties caused by renewable power generations and demand response dramatically affect the operation optimization of integrated energy systems (IESs). Then, how to coordinate the energy hubs in the systems to meet this challenge has become a key issue. Although the chance-constrained method is a workable solution, the determination for chance-constraints is complex, which leads to great difficulty in solving the model. Therefore, the steady-state security region (SSSR) method is applied into the optimization in this paper. First, a SSSR-based model for IESs is established. Second, the power inputs of energy hubs are set as variables and linear chance-constrained expressions are fast generated by using a Cornish-Fisher expansion-based method. Because the variables in both constraints and the objective are identical, the computation of optimization is greatly reduced. Third, a linear model is established with the minimum total cost of IESs, and the calculation speed is very fast when using the linear programming method. Optimization results for the test combined IEEE 33-node power system with 13-node gas system and the test combined PG&E 69-node power system with Belgian gas system are given to verify the effectiveness of the proposed method.