Bi-level optimization model for regional energy system planning under demand response scenarios

Abstract

To improve the flexibility of energy systems, a bi-level optimization model with operation feedback under demand response scenarios was proposed, with the aim of determining a planning program for regional energy systems. The upper level was the planning optimization whose purpose is to minimize its total cost and maximize its average exergy efficiency. The lower level was the operation optimization whose purpose is to make a self-test and achieve the optimal operation benefit. Based on the economic, operational, and environmental benefits, an evaluation index system was established to evaluate the operation performance of a planned energy system. The NSGA-II algorithm and the interior point method were implemented to solve the model. The proposed model was verified in a real-world case study located in Wuhan, China. The results suggest maximizing the capacity of the ground source heat pump (GSHP) for a region suited for its use. The planning program with the precooling/preheating + temperature reset strategy is found to achieve the best benefits. The smaller the capacity of the electric chiller and the larger the capacities of GSHP and thermal energy storage, the higher the levelling rate of the electric network curve.