Reliability assessment model for virtual power plants incorporating dynamic clustering and capacity degradation characteristics of energy storage systems

With the large-scale integration of distributed photovoltaic (PV) and wind power, the operational reliability of VPPs faces significant challenges. To address this issue, this paper proposes a reliability assessment model for VPPs incorporating dynamic clustering and capacity degradation characteristics of energy storage systems. Firstly, a heterogeneous energy storage system is dynamically constructed based on the real-time capacity status of storage units and user response willingness, and a distributed dynamic clustering algorithm is then introduced to achieve a hierarchical coordination control strategy for high-frequency regulation and low-frequency energy support. Secondly, to address the degradation of energy storage device capacity over time, an energy storage capacity degradation index is established. Finally, considering the uncertainties of PV and wind power outputs, a probabilistic output model is developed using the Monte Carlo method, and corresponding response reliability indices are constructed. Building upon this, a VPP reliability assessment model incorporating decision-dependent risk is proposed. Case study simulation results demonstrate that the proposed model not only enhances the reliability of the VPP but also maintains operational economy, which provides theoretical support for the reliable operation of VPPs amidst high penetration of distributed energy resources.