Work

Data-Driven Multi-Mode Adaptive Control for Distribution Networks with Multi-Region Coordination

Year: 2025

Type: article

Abstract: The high penetration of distributed generators (DGs) causes severe voltage fluctuations and voltage limit violations in distribution networks. Traditional control methods rely on precise line parameters, which are often unavailable or inaccurate, and therefore are limited in practical applications. This paper proposes a data-driven multi-mode adaptive control method with multi-region coordination to enhance the operational performance of distribution networks. First, the network is partitioned into multiple regions, each equipped with a local controller to formulate reactive power control strategies for DGs. Second, regions exchange voltage and current measurements to establish linear input–output relationships through dynamic linearization, thereby developing a multi-mode model for different control objectives. Finally, each region employs the gradient descent method to iteratively optimize its control strategy, enabling fast responses to changing operating conditions in distribution networks. Case studies on modified IEEE 33-node and 123-node test systems demonstrate that the proposed method reduces voltage deviation, load imbalance, and power loss by 31.25%, 19.17%, and 20.68%, respectively, and maintains strong scalability for application in large-scale distribution networks.

Source: Processes

DOI: 10.3390/pr13103046

Authors: Youzhuo Zheng, Hengrong Zhang, Zhi Long, Shiyuan Gao, Qihang Yang, Haoran Ji

Institutions: Guizhou Power Grid Co., Ltd. (China), Tianjin University

Language: English

Topic: Optimal Power Flow Distribution

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Affordable and clean energy

Open Access status: gold

Estimated APC paid: $2,896