Dynamic Aggregation of Multiple Flexible Resources in Virtual Power Plants to Meet Diverse Frequency Control Requirements

Abstract

To fulfill the frequency control requirements of the power system, virtual power plants (VPPs) need to aggregate and coordinate a large number of flexible resources. Traditional static aggregation methods, which fixed the composition and coordination strategy of flexible resources, face significant challenges with the diverse frequency control requirements. To address this issue, this paper proposes a dynamic aggregation of multiple flexible resources in VPPs to meet the evolving performance requirements of frequency control. First, a dynamic K-medoids clustering method is applied to reduce the dimension of large-scale resources, thereby reducing the complexity and difficulty of controlling a large number of resources. Then, considering that the intra-hour performance requirements of the frequency control as well as the resource pool of the VPPs are usually minor changing, this paper proposes a two-stage optimization model based on submodular optimization theory for dynamical aggregation, which enables rapid selection and allocation of flexible resources in VPPs. The effectiveness of the proposed method is validated on the IEEE 10-generator 39-bus system with 10,000 flexible resources. The results show that compared to existing techniques, the proposed method enhances the flexibility of large-scale resource aggregation and reduces the calculation time by almost 22 times while guaranteeing the aggregation performance.