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文章摘要
基于非参数估计的电压暂降下敏感设备故障率评估
Fault rate assessment of voltage sag sensitive equipment based on nonparametric assessment
Received:February 28, 2020  Revised:February 28, 2020
DOI:10.19753/j.issn1001-1390.2023.06.013
中文关键词: 电能质量  电压暂降  设备故障率评估  概率密度  电压耐受曲线
英文关键词: power quality, voltage sag, equipment fault rate assessment, probability density, voltage tolerance curve
基金项目:中国南方电网有限责任公司科技项目(GDKJXM20172957)
Author NameAffiliationE-mail
Lin Zhichao* Huizhou Power Supply Bureau of Guangdong Power Grid Co. Lid. lsoulss@163.com 
Luo Busheng Huizhou Power Supply Bureau of Guangdong Power Grid Co. Lid. lsoulss@163.com 
Song Zhijian Huizhou Power Supply Bureau of Guangdong Power Grid Co. Lid. lsoulss@163.com 
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中文摘要:
      电压暂降下敏感设备的故障率是电网侧和用户侧开展电压暂降治理的重要参考信息。文中提出一种基于非参数估计的敏感设备故障率评估方法。针对电压暂降的幅值、持续时间和波形点等特征具有独立性,基于非参数估计方法,提出电压暂降特征量的概率密度函数评估方法,从而构建不确定区域内电压耐受曲线拐点位置分布的联合概率密度函数。将不确定性区域受影响情况分为三个区域进行分析,提出基于U-T联合概率密度函数的电压暂降下敏感设备故障率评估模型。搭建PC机的电压耐受能力测试平台,基于测试数据验证所提算法。构建理论仿真模型并接入IEEE标准测试系统仿真,以仿真数据验证所提方法。基于实测数据与仿真数据,与现有算法进行对比,证明了所提方法的正确性和实用性。
英文摘要:
      The fault rate of voltage sag sensitive equipment is important reference information for power grid side and user side to carry out voltage sag mitigation measure. This paper presents a nonparametric estimation method for fault rate assessment of sensitive equipment. In view of the independence of the magnitude, duration and point on wave of the voltage sag, a method for evaluating the probability density function of the characteristic quantity of voltage sag is proposed based on the non-parametric estimation method, so as to construct the joint probability density function of the position distribution of the infection point of the voltage tolerance curve in the uncertain area. The affected conditions of the uncertainty region are divided into three regions for analysis, and the fault rate evaluation model of the sensitive device based on the U-T joint probability density function is proposed. A PC voltage tolerance test platform is built, and the proposed method is verified based on the test data. A theoretical simulation model is built and connected to IEEE standard test system to verify the proposed method with simulation data. Based on the measured data and the simulated data, the correctness and practicability of the proposed method are proved by comparing with the existing method.
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