A Two-Layer Voltage Coordination Control Strategy for Active Distribution Network Considering Photovoltaic Uncertainty and Network Partitioning

Abstract

In the active distribution networks (ADNs) with high proportion photovoltaic (PV) access, current coordinated control methods based on real-time operating data or forecast data cannot meet the requirements of cost minimization and accuracy maximization at the same time. First, the traditional PV probability density function is optimized by a random simulation method. The expected matrix of electric distance between nodes is obtained by discretizing the characteristics of PV output probability distribution. The ADN system is partitioned using the Affinity Propagation (AP) clustering algorithm. On this basis, an upper-layer scheduling method aiming at minimizing the operating cost of the ADN system is proposed, and day-ahead scheduling plans are developed for devices such as on-load tap changer (OLTC) and capacitor banks (CBs) in each cluster. At the lower layer, real-time operational data are utilized to develop cluster voltage control strategies with the goal of maximizing the tracking of day-ahead scheduling plans, ensuring the economic and safe operation of the ADN while compensating for the shortcomings caused by forecast errors. The proposed method is tested on IEEE-123-bus ADN systems. The simulation results fully verify that the control strategy described in this paper has faster solving speed, better optimization effect, and more feasibility. © 2025 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.