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CSEE Journal of Power and Energy Systems 2023, 9(2): 548-560 https://doi.org/10.17775/CSEEJPES.2020.05920
Open Access | Issue | Published: 25 June 2021

Data-driven Inverter-based Volt/VAr Control for Partially Observable Distribution Networks

Show Author's Information Tong Xu1,2,  Wenchuan Wu3 ( ),  Yiwen Hong4,  Junjie Yu4,  Fazhong Zhang4
Southwest Electric Power Design Institute Co., Ltd. of China Power Engineering Consulting Group, Chengdu, Sichuan 610021, China
Tsinghua University, Beijing 100084, China
Department of Electrical Engineering, State Key Laboratory of Power Systems, Tsinghua University, Beijing 100084, China
Guangdong Power Grid Zhongshan Power Supply Bureau, Zhongshan 528400, China
Keywords:
Data-driven, distribution networks, Volt/VAr control, partial observation
Cite this article:
Xu T, Wu W, Hong Y, et al. Data-driven Inverter-based Volt/VAr Control for Partially Observable Distribution Networks. CSEE Journal of Power and Energy Systems, 2023, 9(2): 548-560. https://doi.org/10.17775/CSEEJPES.2020.05920
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Abstract Full text About this article

For active distribution networks (ADNs) integrated with massive inverter-based energy resources, it is impractical to maintain the accurate model and deploy measurements at all nodes due to the large-scale of ADNs. Thus, current models of ADNs usually involve significant errors or even unknown occurances. Moreover, ADNs are usually partially observable since only a few measurements are available at pilot nodes or nodes with significant users. To provide a practical Volt/Var control (VVC) strategy for such networks, a data-driven VVC method is proposed in this paper. First, the system response policy, approximating the relationship between the control variables and states of monitoring nodes, is estimated by a recursive regression closed-form solution. Then, based on real-time measurements and the newly updated system response policy, a VVC strategy with convergence guarantee is realized. Since the recursive regression solution is embedded in the control stage, a data-driven closed-loop VVC framework is established. The effectiveness of the proposed method is validated in an unbalanced distribution system considering nonlinear loads, where not only the rapid and self-adaptive voltage regulation is realized, but also system-wide optimization is achieved.


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About this article

Data-driven Inverter-based Volt/VAr Control for Partially Observable Distribution Networks

Show Author's information Tong Xu1,2, Wenchuan Wu3 ( ), Yiwen Hong4, Junjie Yu4, Fazhong Zhang4
Southwest Electric Power Design Institute Co., Ltd. of China Power Engineering Consulting Group, Chengdu, Sichuan 610021, China
Tsinghua University, Beijing 100084, China
Department of Electrical Engineering, State Key Laboratory of Power Systems, Tsinghua University, Beijing 100084, China
Guangdong Power Grid Zhongshan Power Supply Bureau, Zhongshan 528400, China

Abstract

For active distribution networks (ADNs) integrated with massive inverter-based energy resources, it is impractical to maintain the accurate model and deploy measurements at all nodes due to the large-scale of ADNs. Thus, current models of ADNs usually involve significant errors or even unknown occurances. Moreover, ADNs are usually partially observable since only a few measurements are available at pilot nodes or nodes with significant users. To provide a practical Volt/Var control (VVC) strategy for such networks, a data-driven VVC method is proposed in this paper. First, the system response policy, approximating the relationship between the control variables and states of monitoring nodes, is estimated by a recursive regression closed-form solution. Then, based on real-time measurements and the newly updated system response policy, a VVC strategy with convergence guarantee is realized. Since the recursive regression solution is embedded in the control stage, a data-driven closed-loop VVC framework is established. The effectiveness of the proposed method is validated in an unbalanced distribution system considering nonlinear loads, where not only the rapid and self-adaptive voltage regulation is realized, but also system-wide optimization is achieved.

Keywords: Data-driven, distribution networks, Volt/VAr control, partial observation

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Received: 28 November 2020
Revised: 23 January 2021
Accepted: 28 April 2021
Published: 25 June 2021
Issue date: March 2023

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