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.

Under the background of the rapid development of green economy and new energy, renewable energy power supply has been developed rapidly. In order to deal with the problems of high volatility and weak anti-interference ability of distributed energy, it is of great significance to explore the operation strategy of independent power supply microgrid group dominated by renewable energy. According to the planning and construction of microgrid and the corresponding control mode, the independent operation and interconnected operation strategies of microgrid are proposed. In order to reduce the phenomenon of abandoned wind and light in the independent operation of microgrid and improve its economic benefits, this paper established a bi-level optimization model covering the internal and inter-microgrid scheduling with the goal of minimizing the independent operation cost of microgrid and maximizing the social benefits of microgrid interconnected operation. The alternating direction multiplier (ADM) method is used to solve the problem iteratively to obtain the renewable energy output power, the energy storage output power, and the electricity purchase and sale strategy that take into account the overall operation efficiency of each micro-network body and its group. Finally, through the simulation analysis of 14-node independent power supply microgrid group, the rationality of the proposed model and the effectiveness of the method are verified.