含分布式电源的配电网故障特征识别与诊断

Access of flexible loads like massive distributed generation and electric cars has posed challenges to the operating reliability of the power distribution networks, making it difficult for the traditional fault-diagnosing methods to meet the demands for safety operation of the power distribution networks with distributed generation. In light of new problems such as the ever-changing grid architecture and failure mode, this project focuses on overcoming the lack of integration mechanism knowledge and data information-related technical methods during the diagnosis of grid faults by proposing the extraction method of features of multi-mode complicated faults in the power distribution network with distributed generation in order to enhance the overall reliability of the distribution networks. Specifically, the method utilizes the features of power distribution network faults and properties of the grid to build the model of mechanisms related to the fault disturbance incidents as well as feature base of multi-mode complicated faults in the power distribution network, and adopts data like phasor measurement to track the evolution trajectory of faults and produces correct online diagnosis of faults in the power distribution networks through fault mechanisms and the inversion theory. In addition, it can reliably recognize minor faults of the power distribution network based on the mining of historical data information and feature-matching techniques. This project aims to collect the on-off action signal and fault recording data of the measurement and protection device, set up the diagnostic system of grid faults and conduct application research at the Regulation and Control Center of the State Grid Shandong Electric Power Company. And the research findings will provide references for the improvement of operating stability and reliability of the power distribution network, as well as the promotion of its overall automation level.

大规模分布式电源、电动汽车等柔性负荷的接入给配电网运行可靠性带来挑战，导致传统电网故障诊断方法难以满足含分布式电源配电网安全运行要求。本项目从提高配电网综合可靠性目标出发，根据含分布式电源配电网面临的电网架构、故障形式不断变化等新问题，针对电网故障诊断存在的缺乏融合机理知识和数据信息的技术手段，提出含分布式电源的配电网多形态复杂故障特征提取方法，利用配电网故障特征及电网特性，建立故障扰动事件相关机理模型，建立配电网多形态复杂故障特征库；利用同步相量测量等信息追踪故障演化轨迹，并通过故障机理、反演理论等实现配电网故障在线正确诊断；基于历史数据信息挖掘和特征匹配技术，实现配电网微弱故障的可靠识别。本项目拟在国网山东省电力公司调控中心采集测控保护装置开关动作信号及故障录波数据，搭建电网故障诊断系统，开展应用研究。研究成果为提高配电网运行稳定性、可靠性，及全面提升配电网自动化水平提供了参考依据。

本项目从提高配电网综合可靠性目标出发，根据含分布式电源配电网面临的电网架构、故障形式不断变化等新问题，针对电网故障诊断存在的缺乏融合机理知识和数据信息的技术手段，提出含分布式电源的配电网多形态复杂故障特征提取方法，利用配电网故障特征及电网特性，建立故障扰动事件相关机理模型，建立配电网多形态复杂故障特征库；利用同步相量测量等信息追踪故障演化轨迹，并通过故障机理、反演理论等实现配电网故障在线正确诊断；基于历史数据信息挖掘和特征匹配技术，实现配电网微弱故障的可靠识别。.项目取得的主要结果是：.1、提出了含分布式电源配电网故障分析方法，由分布式电源并网和孤岛模式下可测电流的正序、负序和零序分量表示故障特征，准确的对配电网的故障进行检测和分类。.2、提出了基于多源信息融合的配电网故障诊断方法，通过获取开关动作告警信号，并对获取的告警信号利用故障判定矩阵运算进行故障区域分析。.3、提出了基于电力扰动数据特征匹配的配网电缆早期故障识别方法，从多种异常状况中分类识别配电电缆早期故障，以及评估配电电缆的健康状况，依据态势感知预测即将发生的故障原因。.4、研发了基于附加电力电子电源的配电网故障主动定位装置，在实际配电网线路故障定位测试，能够快速确定故障类型及准确故障定位。.项目成果主要包括SCI论文9篇、中文EI期刊论文2篇、EI会议论文7篇、中文核心期刊论文2篇。申请发明专利13项、实用新型专利7项、软件著作权2项。协助培养博士生3人、硕士生17人。获得2020 IEEE亚洲工业与商业电力系统国际学术会议（I&CPS Asia 2020）最佳论文奖、2019 日本仪器与控制工程师学会会议海报论文奖等。