Optimal Scheduling Strategy of Distributed Energy Storage Aggregation Based on Clustering

To address the issue that distributed energy storage is difficult to meet the online real-time dispatching requirements of aggregators due to its large quantity, geographical dispersion, and strong uncertainty in responding to the demands of multiple user entities, a clustering-based aggregation optimization dispatching strategy for distributed energy storage is proposed. Firstly, the holographic state model of energy storage is established by considering the physical state parameters and electrical location information of energy storage, based on which the energy storage is clustered by K-Means++ algorithm. Secondly, the frequency modulation, peak regulation, distributed energy trading and voltage regulation demands of multi-user subjects are constructed, and the corresponding service consolidated indicators of energy storage clusters are designed to determine the collection of energy storage with excellent performance to be optimised for each demand. Subsequently, taking into account the revenue of the aggregator participating in demand response of multi-user subjects and the cost of leasing energy storage, the energy storage to be optimised is optimally scheduled with the objective of optimal economic benefit of the aggregator. Finally, the feasibility of this paper’s optimal scheduling strategy for aggregation is verified through a simulation experiment.