Two-stage robust optimization model for park integrated energy system based on dynamic programming

Abstract

The promotion and construction of park integrated energy system (PIES) has strengthened the interaction among electric, gas, heating and cooling systems. However, the static programming strategy (SPS) of PIES results in problems such as lower system economics and poorer reliability of energy supply. Therefore, a suitable planning method is required to promote the economic operation of PIES under multiple uncertainties. Based on the background, this study proposes a two-stage robust optimization model based on dynamic programming strategy (DPS) for PIES. Firstly, the coupled devices and energy networks in the system are analyzed in detail to comprehensively identify the complex interactions among multiple energy carriers. Moreover, a DPS is introduced to improve the economic efficiency of PIES. Then, a two-stage robust model is established to solve the heterogeneous uncertainties in the planning strategy. Specifically, the column and constraint generation (C&CG) algorithm is used to solve the optimization model thereby obtain the equipment configuration scheme for each planning phase. Finally, the effectiveness of the proposed method is verified by comprehensive case studies on a test system.