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湖南大学电气与信息工程学院,湖南省长沙市 470082
Received:17 February 2025,
Revised:2025-05-21,
Online First:11 July 2025,
Published:25 November 2025
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申亚涛,王子鉴,谷紫文等.数据驱动的低压有源配电网电压在线调控策略[J].电力系统自动化,2025,49(22):135-144.
SHEN Yatao,WANG Zijian,GU Ziwen,et al.Data-driven Online Voltage Regulation Strategy for Low-voltage Active Distribution Networks[J].Automation of Electric Power Systems,2025,49(22):135-144.
申亚涛,王子鉴,谷紫文等.数据驱动的低压有源配电网电压在线调控策略[J].电力系统自动化,2025,49(22):135-144. DOI: 10.7500/AEPS20250217003.
SHEN Yatao,WANG Zijian,GU Ziwen,et al.Data-driven Online Voltage Regulation Strategy for Low-voltage Active Distribution Networks[J].Automation of Electric Power Systems,2025,49(22):135-144. DOI: 10.7500/AEPS20250217003.
含高比例户用光伏的低压有源配电网面临严重的过电压问题。同时,拓扑结构和线路参数的缺失,进一步增加了电压优化调控难度。为此,提出一种数据驱动的电压在线调控策略。首先,通过数据驱动的方法,在线辨识与更新系统节点电压-功率方程中的参数,为动态估计节点电压提供基础。然后,建立以最大化光伏消纳为目标的电压优化调控模型,并根据模型求解结果,在控制光伏逆变器跟踪无功指令的同时,对有功输出进行动态限幅,从而实现电压的有效调控。算例结果表明,该策略不仅在无电气模型的条件下解决了节点电压估计问题,而且可以按照无功优先的原则有效治理过电压,实现光伏最大化消纳,验证了所提策略的有效性。
Low-voltage active distribution networks with a high proportion of rooftop photovoltaic face severe overvoltage issues. Simultaneously
the lack of topological structure and line parameters further complicates voltage optimization and regulation. To address this
a data-driven online voltage regulation strategy is proposed. First
a data-driven method is employed to online identify and update the parameters in the system node voltage-power equation
providing a foundation for dynamically estimating node voltages. Then
a voltage optimization and regulation model aimed at maximizing photovoltaic accommodation is established. Based on the model solution results
while controlling the photovoltaic inverters to track reactive power commands
dynamic limiting of active power output is implemented to achieve effective voltage regulation. Case results demonstrate that this strategy not only resolves the issue of node voltage estimation without an electrical model but also effectively achieves overvoltage mitigation following the principle of reactive power priority
maximizing photovoltaic accommodation and validating the effectiveness of the proposed strategy.
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