Two-stage Robust Optimal Scheduling of Regional Integrated Energy System Considering Network Constraints and Uncertainties in Source and Load

Regional integrated energy system (RIES) is an important carrier to achieve the ubiquitous electric internet of things and energy internet. Uncertainties from distributed energy and load, analysis of multi-energy network constraints and their coupling characteristics are the main challenges for RIES operation issues. In this paper, network models of electricity-gas-heat system are established with linearization methods proposed for distribution-level RIES. Considering the extreme scenarios of uncertain load and wind power, a two-stage robust optimization (TRO) model for day-ahead scheduling is constructed, and iteratively solved with column and constraint generation algorithm (C&CG). Results from case study prove effectiveness of the established TRO model in improving system robustness, wind power accommodation and risk-averse effect against real-time compensatory electricity price fluctuation. Economical and computational efficiency improvement considering heat loss of the distributed heat network in the TRO model is also testified. Research results reflect the benefits of multi-energy complementarity and coordinative optimization in RIES uncertain operation. © 2019, Power System Technology Press. All right reserved.