Optimal scheduling strategy of a regional integrated energy system considering renewable energy uncertainty and heat network transmission characteristics
Haipeng Chen, Lin Gao, Yongling Zhang, Chang Zhao
Abstract
In order to overcome the curtailment of wind energy caused by “power determined by heat” of combined heat and power units, this study proposes an integrated demand response strategy and optimization method for heat-electric energy dispatching in a regionally integrated energy system. Firstly, a scenario analysis algorithm based on Latin Hypercube Sampling (LHS) and Backward Reduction (BR) is applied to characterize the probability characteristics of wind power output. In addition, a novel integrated demand response scheduling model with the consideration of transmission characteristics of the heating network, aiming at minimizing the operation cost, is proposed for a regional integrated energy system. To solve this model, the thermos-electric coupling relationship is evaluated and the proportion of thermoelectric demand response is also weighted. The user satisfaction and economy will finally reach a more optimal level, and thereby is solved via CPLEX solver in MATLAB. The simulation results on a actual integrated energy system reveal that the proposed method is capable of optimizing energy consumption and lowering operational costs while maintaining user satisfaction with the uncertain wind generation by leveraging thermal inertia of the integrated energy system.