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Data-Driven Predictive Voltage Control for Distributed Energy Storage in Active Distribution Networks

Integration of distributed energy storage (DES) is beneficial for mitigating voltage fluctuations in highly distributed generator (DG)-penetrated active distribution networks (ADNs). Based on an accurate physical model of ADN, conventional model-based methods can realize optimal control of DES. Howe...

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Published in:CSEE Journal of Power and Energy Systems 2024-09, Vol.10 (5), p.1876-1886
Main Authors: Yanda Huo, Peng Li, Haoran Ji, Hao Yu, Jinli Zhao, Wei Xi, Jianzhong Wu, Chengshan Wang
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container_title CSEE Journal of Power and Energy Systems
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creator Yanda Huo
Peng Li
Haoran Ji
Hao Yu
Jinli Zhao
Wei Xi
Jianzhong Wu
Chengshan Wang
description Integration of distributed energy storage (DES) is beneficial for mitigating voltage fluctuations in highly distributed generator (DG)-penetrated active distribution networks (ADNs). Based on an accurate physical model of ADN, conventional model-based methods can realize optimal control of DES. However, absence of network parameters and complex operational states of ADN poses challenges to model-based methods. This paper proposes a data-driven predictive voltage control method for DES. First, considering time-series constraints, a data-driven predictive control model is formulated for DES by using measurement data. Then, a data-driven coordination method is proposed for DES and DGs in each area. Through boundary information interaction, voltage mitigation effects can be improved by inter-area coordination control. Finally, control performance is tested on a modified IEEE 33-node test case. Case studies demonstrate that by fully utilizing multi-source data, the proposed predictive control method can effectively regulate DES and DGs to mitigate voltage violations.
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subjects data-driven
distributed energy storage (DES)
distributed generators (DGs)
Distribution network
predictive voltage control
title Data-Driven Predictive Voltage Control for Distributed Energy Storage in Active Distribution Networks
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