Two-stage dispatching strategy for park-level integrated energy systems based on a master-slave-cooperative hybrid game model

Integrated Energy Systems (IES) represent an effective strategy for increasing the use of renewable energy sources. However, the inherent uncertainty in forecasting both renewable energy generation and loads significantly impacts the accurate dispatching of IES. This paper proposes a two-stage dispatching strategy for Park-Level Integrated Energy Systems (PIES) based on a master-slave-cooperative hybrid game model. This approach aims to address the aforementioned challenges and achieve cooperative optimization in dispatching across Multiple Park Integrated Energy Systems (MPIES). The strategy comprises two key components: a day-ahead master-slave game model incorporating demand response and energy storage, and a real-time cooperative game model based on energy sharing. In the day-ahead stage framework, price signals are used to optimize the energy supplier's output and devise the customer's energy consumption plan, thereby achieving economic dispatch. In the real-time stage, the optimization target is shifted to the load aggregator, which employs cooperative game theory to refine certain plans established during the day-ahead stage. Validation using an MPIES consisting of three PIESs showed that the model can accelerate real-time response time by 7 s, achieve 100 % dispatch accuracy, and reduce energy procurement costs by 3.46 % for the PIESs compared to other dispatch models.