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作 者:宋关羽 于川航 冀浩然 赵金利[1] 徐晶 李鹏[1] SONG Guanyu;YU Chuanhang;JI Haoran;ZHAO Jinli;XU Jing;LI Peng(Key Laboratory of the Ministry of Education on Smart Power Grids(Tianjin University),Tianjin 300072,China;State Grid Tianjin Economic and Technological Research Institute,Tianjin 300160,China)
机构地区:[1]智能电网教育部重点实验室(天津大学),天津市300072 [2]国网天津市电力公司经济技术研究院,天津市300160
出 处:《电力系统自动化》2023年第6期90-100,共11页Automation of Electric Power Systems
基 金:国家自然科学基金资助项目(52007131);天津市应用基础研究项目(21JCQNJC00430)。
摘 要:分布式电源的高比例接入使配电网电压控制问题日益显著。与配电网中传统电压调控设备相比,集成储能智能软开关(ESOP)等新型电力电子设备具有更加灵活、快速的电压调节能力。实际配电网参数难以获取,运行场景复杂多变,基于物理模型的控制方法往往难以适应系统运行状态变化。为此,提出一种考虑量测数据质量的ESOP数据驱动电压控制方法。首先,基于无模型自适应预测控制方法,建立ESOP的数据驱动控制模型。然后,考虑数据驱动过程中实际量测数据存在量测误差的问题,采用坏数据辨识和量测扰动抑制方法对量测数据进行处理,提出考虑量测数据质量的ESOP数据驱动电压控制方法,以降低量测误差对数据驱动控制过程的影响。最后,在含四端ESOP的实际配电网算例中进行验证分析。结果表明,所提ESOP数据驱动电压控制方法可以有效解决配电网参数难以准确获取的问题,显著降低量测误差带来的不良影响,全面提升配电网电压控制水平。The high proportion of the access of distributed generators makes the voltage control problem of the distribution network more and more urgent. Compared with the traditional voltage regulation devices in distribution networks, the new power electronic devices represented by the energy storage integrated soft open point(ESOP) have more flexible and rapid voltage regulation capability. The actual distribution network parameters are difficult to obtain;the operation scenario is complex and changeable;and the control method based on the physical model is often difficult to adapt to the change of system operation state. Therefore, a datadriven voltage control method of ESOP considering the measured data quality is proposed. First, a data-driven control model of ESOP is established based on the model-free adaptive predictive control method. Then, considering the measurement error of actual measurement data in the data-driven process, the bad data identification and measurement disturbance suppression method are used to process the measurement data. A data-driven voltage control method of ESOP considering the measurement data quality is proposed to reduce the impact of measurement error on the data-driven control process. Finally, a practical distribution network example with a four-terminal ESOP is used for verification analysis. The results show that the proposed data-driven voltage control method of ESOP can effectively solve the problem that distribution network parameters are difficult to obtain accurately, significantly reduce the adverse effects caused by measurement errors, and comprehensively improve the voltage control level of distribution networks.
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