Data-Driven Coordinated Voltage Control Strategy for Distribution Networks with High Proportion of Renewable Energy Based on Voltage–Power Sensitivity

Ziwei Cheng (), Lei Wang, Can Su, Runtao Zhang, Xiaocong Li and Bo Zhang
Additional contact information
Ziwei Cheng: State Grid Hebei Electric Power Research Institute, Shijiazhuang 050021, China
Lei Wang: State Grid Hebei Electric Power Research Institute, Shijiazhuang 050021, China
Can Su: State Grid Hebei Electric Power Research Institute, Shijiazhuang 050021, China
Runtao Zhang: State Grid Hebei Electric Power Research Institute, Shijiazhuang 050021, China
Xiaocong Li: Key Laboratory of Distributed Energy Storage and Micro-Grid of Hebei Province, North China Electric Power University, Baoding 071003, China
Bo Zhang: Key Laboratory of Distributed Energy Storage and Micro-Grid of Hebei Province, North China Electric Power University, Baoding 071003, China

Sustainability, 2025, vol. 17, issue 11, 1-18

Abstract: In order to achieve rapid and accurate voltage regulation in active distribution networks, this paper proposes a data-driven coordinated voltage control strategy for active distribution networks based on voltage–power sensitivity. Firstly, we establish a BP neural network regression prediction model for voltage–power sensitivity to depict the nonlinear mapping relationship between power and node voltage and achieve rapid acquisition of voltage–power sensitivity. Secondly, based on the principle of stepwise regulation of voltage–power sensitivity, a voltage coordination control framework for a high-proportion photovoltaic active distribution network is constructed by using a two-stage voltage regulation mode of reactive power compensation and active power reduction to achieve efficient and rapid regulation of node voltages in the active distribution network. Finally, the correctness and effectiveness of the proposed method are verified through simulation calculation and analysis of typical power distribution systems of IEEE 33-nodes and IEEE 141-nodes.

Keywords: BP neural network; data-driven; voltage–power sensitivity; coordinated voltage control; active distribution network (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/17/11/4955/pdf (application/pdf)
https://www.mdpi.com/2071-1050/17/11/4955/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:17:y:2025:i:11:p:4955-:d:1666448

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().