【作者】 徐兵；

【导师】 文福拴；

【作者基本信息】 浙江大学 ， 电气工程， 2017， 硕士

【摘要】 快速识别电力系统中的故障元件和分析引起故障的原因,有助于尽快恢复系统的正常运行和减少停电损失。气象等要素是导致电力系统故障的主要原因之一,但如何在故障诊断中适当计及这些要素的影响是一个有待深入研究的问题。在此背景下,比较系统地考虑了气象等要素对电力系统故障的影响,在现有故障诊断方法的基础上利用故障发生时刻的气象等外部要素情况分析导致故障的原因。首先,根据发生故障前后的电力系统拓扑结构,识别停电区域,确定候选故障元件;在此基础上,以继电保护和断路器状态为信息源,构建了电力系统故障诊断的一种简化模型,从候选的故障元件中确定故障元件。之后,以从污秽监测系统、雷电监测系统、气象预警系统等外部环境监测设备获得的信息与数据以及所确定的故障元件为故障影响要素分析的信息源,分析导致故障的外部影响因素,以帮助系统运行人员快速定位和排除故障,尽快恢复系统正常运行。针对传统后备保护整定困难、动作延时长、配合关系复杂等问题,提出了一种利用有限相量测量单元的故障识别与广域后备保护策略。首先,根据相量测量单元的安装位置划分后备保护区域;在发生故障时,利用电气量信息确定故障设备所在的后备保护区域,以期快速缩小可疑故障设备范围。接着,提出一种基于解析模型的故障识别方法和广域后备保护策略。当主保护未能成功切除故障时,这种解析模型可综合利用主保护动作警报、断路器动作警报、后备保护启动信息和功率方向继电器指向信息,利用禁忌算法(Tabu Search,TS)求解最优故障假说,并通过解析保护和断路器的动作逻辑判断拒动装置。之后,根据不同的拒动情况提出相应的后备保护策略以防止故障扩大。最后,以IEEE 39节点系统为例,对所提出的方法做了验证。仿真结果表明,所提出的方法是可行的,具有较强的容错能力。针对我国配电网分布式发电、电动汽车以及可控负荷接入量的大规模增多的发展趋势,分析其对传统配电网保护装置配置的影响,以及固有配电网故障诊断及定位方法的不足,建立基于微型同步相量测量装置(Micro Phasor Measurement Unit,μPMU)的智能配电网故障诊断框架。联合μPMU采集的高精度电气量量测信息和馈线终端系统(Feeder Terminal Unit,FTU)监测的节点过电流信息等,提出了适用于具有高渗透率分布式电源的智能配电网故障诊断及定位方法。在故障发生时,根据停电区域确定可疑故障设备的备选范围;其次,综合利用配电系统中控制主站收集到的μPMU和FTU警报信息,建立基于多源信息的配电系统故障诊断解析模型;接着,通过优化算法求解最优解,寻找故障元件;最后,对故障诊断结果进行评价。最后对全文做了总结,并对本文所述的研究内容进行了展望。更多还原

【Abstract】 Prompt fault diagnosis can help restore the power system concerned quickly,and thus reduce outage costs.Meteorological factors,as well as other impacting factors,represent some of the main causes of power system faults,and how to appropriately take into account of the influences of these impacting factors in power system fault diagnosis is a challenge task.Given this background,the influences of meteorological and other impacting factors are systematically investigated,and based on an existing fault diagnosis method the meteorological and other impacting factors at the fault occurrence period are employed to analyze the fault cause.First,the outage area is identified so as to attain the suspected fault sections using a network topology analysis method.Then,a simplified fault diagnosis model is presented to identify the fault section(s)from suspected ones by utilizing the state information of protective relays and circuit breakers.Finally,data from the concerned contamination monitoring system,lightning monitoring system,weather pre-warning system,and monitoring equipments for other external environmental factors,together with the estimated fault section(s),are used for analyzing those factors having impacts on fault occurrence,so as to assist the operators to locate and clear the fault(s),and ultimately speed the system restoration procedure.The traditional backup protection has some drawbacks,including difficult protection setting,long time delay and complicated coordination.Given this background,a fault section identification and wide-area backup protection strategy is proposed based on limited phasor measurement units(PMUs).First,the whole power network is divided into several backup protection zones(BPZs)based on the placement of PMUs.Once a fault occurs,the electrical quantities are utilized to identify the faulted BPZ,so as to quickly narrow down the scope of suspected fault sections.Then,an analytic model based fault section identification method and a wide-area backup protection strategy are presented using alarm information of main and backup protective relays,power direction relays,and circuit breakers.The proposed strategy will be activated only if the main protection relay fails to clear the fault.The well-established Tabu Search(TS)algorithm is utilized to seek the optimal fault hypothesis,and determine the malfunctioned protective relays and/or circuit breakers.Based on the identified malfunctions,the corresponding backup protection scheme is initiated to prevent the fault from spreading.Finally,several test cases are carried out on the IEEE 39-bus power system,and it is demonstrated that the proposed method is feasible and fault-tolerated.Aiming at the problem of large-scale increasement of distributed power generation,electric vehicles and controllable load in Chinese distribution network,this thesis points out the shortcomings of protection device and fault diagnosis method in traditional distribution network,and presents an intelligent fault diagnosis framework based on micro synchronous phasor measurement units(μPMUs).Using the high-precision electrical data information collected byμPMUs and the node over-current information monitored by feeder terminal units(FTUs),this thesis propose an intelligent fault diagnosis and localization method for active distribution networks.After a fault occurs,the area of suspected faulty devices is determined based on the power failure area.Secondly,the fault diagnosis model of power distribution system based on multi-source information is established by using the information of μMUs and FTUs collected by the control station in the distribution system.Secondly,combining the alarm information from μPMUs and FTUs received by the control master station,the fault diagnosis method.of the distribution system based on analytical model is established.Then,the optimization algorithm is used to solve the optimal solution and find the faulty component.Finally,the fault diagnosis results are evaluated.The last part of this thesis summarizes the whole text,and makes a prospect for the future research in this thesis.更多还原