Distributed Chance-Constrained Optimal Dispatch for Integrated Energy System With Electro-Thermal Couple and Wind-Storage Coordination
Zhen-Wei Zhang, Yan Wang, Chengfu Wang, Yaxin Su, Yong Wang, Yong Dai, Can Cui, Wei Zhang
Abstract
Cross-regional long-distance transmission is a promising way for utilizing renewable energy sources (RESs) with geographically imbalanced distribution. However, the stochastic fluctuations of RESs will be transferred to the receiving energy networks, and the complex operating conditions of cross-regional transmission lines further affect energy delivery. In this paper, we propose a coordinated optimization model for an integrated energy system (IES) that considers the uncertain injection from long-distance wind farms. First, a dynamic capacity calculation model of overhead transmission lines (OTLs) is established, taking into account the electro-thermal couple characteristics and real-time ambient conditions. Second, an IES model integrating electricity and natural gas distribution networks is built and converted into second-order conic programming using the McCormick approach. Third, a distributed chance-constrained optimization framework is proposed to coordinate the wind-storage system and IES. The probabilistic constraints are converted into certain constraints based on stochastic scenario sampling. Besides, to maintain the variable consistency of the connection lines between cross-regional systems, we employ the virtual node approach to achieve a fast-distributed iterative solution. Finally, simulation results on a modified IEEE33-Belgium20 test system demonstrate the superiority of the proposed method in operational economy and RESs utilization.