ORIGINAL RESEARCH article
Front. Energy Res.
Sec. Smart Grids
Volume 13 - 2025 | doi: 10.3389/fenrg.2025.1702010
This article is part of the Research TopicGrid Stability and Optimized Operation in Renewable Energy Grid SystemsView all 6 articles
Source-Network-Load-Storage Based Coordinated Fault-Tolerant Control for Active Distribution Network Under Sensor Faults
Provisionally accepted
- 1China 15th Metallurgical Construction Group Co., Huangshi, China
- 2Smart Health Big Data Analysis and Location Services Engineering Lab of Jiangsu Province, Nanjing University of Posts and Telecommunications, Nanjing, China
- 3GuoXia Technology Co., Wuxi, China
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This paper investigates the problem of fault-tolerant control in source-network-load-storage (SNLS) based active distribution networks under sensor faults, which pose a significant risk to system stability and reliable operation. To address such issues, a model-free fault estimation method based on deep neural networks (DNN) is proposed, enabling accurate reconstruction of faulty sensor signals without requiring explicit system models. The recovered measurements are integrated into a distributed control framework to maintain voltage and frequency regulation, as well as proportional reactive power sharing among distributed generators (DGs) distributed energy resources. Compared with existing model-based and rule-driven approaches, the proposed method achieves higher estimation accuracy, improved adaptability, and seamless control integration. Finally, simulation results validate the robustness and effectiveness of the proposed method under both normal and faulty scenarios.
Keywords: Fault-tolerant control, deep neural networks, sensor faults, Source-network-load-storage, Active distribution network
Received: 09 Sep 2025; Accepted: 09 Oct 2025.
Copyright: © 2025 Li, Feng, Liu and zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Lizheng Feng, fenglizheng_guoxia@163.com
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