Virtual Power Plant Partition Strategy Based on Network Representation

Abstract

The virtual power plant (VPP) is an important technology for realizing smart grids. VPPs are not limited by geographical location, which greatly aggregates the distributed energy resources. To divide a VPP across regions, we no longer limit it to power lines. This paper proposes a three-stage strategy for the classification of VPPs that includes graph model construction, communication capacity assessment and cross-regional classification. To construct the VPP graph model, complex network theory and communication matrices are used. In addition, a network representation learning and clustering algorithm is used to classify the VPP decision areas. Then, the classification results are evaluated using modularity and network communication sequence entropy to identify VPP boundaries. Finally, the validity of the method is verified by simulating the test network and the real network.