基于无模型自适应控制的配电网电压控制方案
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TM73

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国家自然科学基金资助项目(52077035)


Distribution network voltage control scheme based on model-free adaptive control
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the Open Project Program of the National Key Laboratory for Smart Grid Protection and Operation Control

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    摘要:

    新型电力系统下分布式新能源、分布式发电、电动汽车等新型元素大规模发展,配电网电压控制将面临控制对象特性异构、模型复杂、场景多变等挑战。在此背景下,文中提出一种基于无模型自适应控制的配电网电压控制方案。该方案在配电网电压控制分区及主导节点选取的基础上,利用主导节点电压、分布式电源以及储能装置出力等数据建立实时动态线性化数据滚动池,基于特征模型理论和数据驱动,将复杂系统电压控制特性通过控制器特征参数进行时变修正,在不损失系统模型信息的基础上降低了控制模型复杂程度。最后,通过改进的IEEE 33节点配电网系统算例进行仿真分析和对比,结果证明了所提控制方案的有效性。相较于传统的基于模型的控制方法,所提控制方案能够更快速地响应扰动带来的电压波动问题,应用前景良好。

    Abstract:

    With the large-scale development of new elements such as distributed new energy,distributed generation and electric vehicles under the new power system,the distribution network voltage control is faced with challenges such as heterogeneous control object characteristics,complex models and variable scenarios. In this context,a distribution network voltage control strategy based on model-free adaptive control is proposed. The data from dominant node voltages,distributed generation,and energy storage device output are used by this strategy to establish a real-time dynamic linearized data rolling pool based on the distribution network voltage control partitioning and dominant node selection. Based on the characteristic model theory and data drive,the complex system voltage control characteristics are time-varyingly modified by the controller characteristic parameters,and the control model complexity is reduced without losing system model information. Finally,the effectiveness of the proposed control strategy is shown in the results by simulating and comparing in the modified IEEE 33-node distribution network system arithmetic. The response of the proposed control strategy is quicker than that of traditional model-based control method,thus reducing the voltage fluctuation caused by disturbances. The proposed control strategy has good application prospects.

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潘俊迪,陈中,倪纯奕,万玲玲,王毅.基于无模型自适应控制的配电网电压控制方案[J].电力工程技术,2023,42(5):128-137

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  • 收稿日期:2023-03-20
  • 最后修改日期:2023-05-22
  • 录用日期:2023-03-21
  • 在线发布日期: 2023-10-10
  • 出版日期: 2023-09-28
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