Synergistic Operation Framework for the Energy Hub Merging Stochastic Distributionally Robust Chance-Constrained Optimization and Stackelberg Game

Abstract

As the increasing complexity and uncertainty of integrated energy systems, the cooperative interaction under uncertainty between the energy hub (EH) and multi-energy users has become crucial for the efficient operation of energy systems. This paper proposes a unified collaborative and interactive framework to optimize operations between the EH and multi-energy users under uncertainty. Firstly, in the horizontal dimension, the stochastic distributionally robust chance-constrained (S-DRCC) optimization method with the Wasserstein metric is proposed to hedge against the uncertainty of EH considering the multiple scenarios and moment information of uncertain variables. Then in the vertical dimension, a bilevel Stackelberg game model is developed for EH and users to facilitate the collaborative interaction for multi-agents. Furthermore, several efficient methods are leveraged to reformulate the originally intractable framework into a tractable mixed-integer linear programming (MILP) model that can be directly solved using commercial solvers. Finally, the effectiveness of the proposed model and method are demonstrated by numerical case studies and corresponding simulation results.