To address the difficulty of aggregating and applying flexible resources in large urban power grids
a resource cluster optimization configuration algorithm is proposed. Firstly
a hierarchical partitioned clustering strategy based on the characteristics of flexible resources and auxiliary service demand is proposed
and the density-based spatial clustering of applications with noise (DBSCAN) clustering algorithm is used to cluster the resources to participate in the virtual power plant tasks with resource clusters. Secondly
according to the regulated power required by the virtual power plant and the capacity potential of the resource cluster
optimize the time period for its participation in tasks to maximize the resource utilization efficiency and the operational benefits of the virtual power plant. And then
the state potential game theory and penalty mechanism are introduced to optimize the resource allocation in the time period to ensure the stability and reliability of the task process. Finally
an arithmetic example is given to prove that under this scheme
the large-scale flexible resources of the virtual power plant can be efficiently optimized and allocated
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