Terminal Node of Active Distribution Network Correlation Compactness Model and Application Based on Complex Network Topology Graph

Peng Jiang, Xihao Dou, Jun Dong, Hexiang Huang and Yuanyuan Wang ()
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Peng Jiang: Department of Economic Management, North China Electric Power University, Beijing 102206, China
Xihao Dou: Department of Economic Management, North China Electric Power University, Beijing 102206, China
Jun Dong: Department of Economic Management, North China Electric Power University, Beijing 102206, China
Hexiang Huang: Department of Economic Management, North China Electric Power University, Beijing 102206, China
Yuanyuan Wang: Department of Economic Management, North China Electric Power University, Beijing 102206, China

Sustainability, 2022, vol. 15, issue 1, 1-18

Abstract: Multiple nodes (such as distributed generation (DG), electric vehicles (EV), energy storage (ES), flexible loads (FL), etc.) are connected to the active distribution network (ADN), which changes its original operational mode. According to the bidirectional current and low-voltage transmission mode, this study proposed a multi voltage and multi electricity flat loop network, AC/DC (Alternating Current/ Direct Current) hybrid network, unified interface and flexible self-organizing network based on Complex network theory. First, the ADN complex network topology of various nodes is established based on the actual grid connected terminal nodes and power flow sensitivity algorithm. Second, using the TOPSIS model, the influence factor matrix of weighted directed network is established. The matrix can be used to guide the formulation of the distribution network operation mode, and the robustness and reliability of this paper are verified by using the standard multi voltage level main distribution hybrid model provided by the Panda Power website as the verification method. Finally, using the influence maximization calculation model of the New Creedy algorithm, the node correlation matrix is expanded to form a super family region set of active distribution network. The results show that the seven nodes in this paper have high correlation, while the other nodes have low correlation. In addition, the change of reactive power has little impact on other nodes, for a node with a change rate of 0, it is obviously not in the same power supply family as node 1, and theoretically it may not have a topological relationship, be a power generation node, or be completely independent. Analyzing the relationship between nodes has a guiding significance for power supply recovery and interaction in distribution network reconfiguration.

Keywords: complex network; correlation tightness; new greedy; power flow sensitivity; topology analysis; TOPSIS (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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