The Optimal Operation Strategy of an Energy Community Aggregator for Heterogeneous Distributed Flexible Resources

The widespread integration of renewable energy into the grid emphasizes the issues of power system uncertainty and insufficient flexibility. Heterogeneous flexible distributed resources can address the above challenges by interacting with distribution networks. This paper proposes a multi-timescale optimal operation strategy for an energy community that aggregates multiple distributed resources. Based on flexibility indicators including the degree of load variation and task laxity, a tri-level structure involving distribution system operators (DSOs), aggregators, and the home energy management system (HEMS) is developed. The aggregator serves as mediator between customers and DSOs, gathering the end user's flexibility through the rescheduling of household appliances to leverage both upward and downward energy adjustments. According to different scenarios and application requirements, a multi-time-scale rolling optimal dispatch model is proposed. The day-ahead dispatch is combined with the Model Predictive Control (MPC) method to achieve fine-grained rolling adjustment of the power dispatch instructions of distributed resources with different time scales. Finally, a simulation experiment example is constructed to verify the effectiveness of the proposed method. The simulation results demonstrate that the economic benefits of end users and aggregators are improved with more grid-friendly load curves.