冗余保护配置的变电站故障诊断方法研究

发布时间：2019-01-23 18:55

【摘要】：西北750kV联网工程，是西北电网发展史上工程规模最大、电压等级最高、线路最长和最为复杂的一项超高压输变电工程，是西北地区的水火风电外送的大通道。750kV变电站作为750kV电网的枢纽，其包含750kV、330kV和66kV三个电压等级，保护采用双重化配置，这使得750kV变电站的网络拓扑结构更加复杂，保护配置增多。当变电站发生故障时，故障信息量增多，且更复杂，需运行人员能够快速准确地判断出故障，并对其进行故障定位和恢复。因此，研究变电站故障诊断系统，对于保证电网安全稳定运行具有重要的意义。本文以750kV变电站为研究对象，针对保护装置及断路器存在误动和拒动等不确定性，以及传统故障诊断中诊断信息源不全面和异常时报警信息量庞大等特点，采用FPN(Fuzzy Petri Net,模糊Petri网)、RS(Rough Sets,粗糙集)和信息融合的三种诊断方法对其进行了研究，并通过仿真验证了该方法的有效性。首先针对保护装置及断路器存在误动和拒动等不确定性情况，以及750kV变电站的双网双重保护配置特性，提出具有冗余保护配置的变电站FPN故障诊断方法。在该方法中利用双重保护装置的信息，研究了元件诊断模型的冗余知识表示方法，建立了故障元件的FPN冗余诊断模型，根据750kV变电站的双网特性，将冗余诊断模型分为主网和冗余网两个子网模型。在模型中采用联合信息熵确定了初始信息的可信度，通过模糊推理获得最小故障诊断结果集。仿真结果表明该方法的有效性。其次针对750kV变电站线路的复杂性、双重化保护配置、以及异常时报警信息量庞大和传统故障诊断中诊断信息源不全面等特点，提出了基于RS的冗余保护配置的分层变电站故障诊断方法。在该方法中根据750kV变电站的电压等级特性，将750kV变电站划分为3个区域，根据每个区域的接线特点，进行分区处理。之后，利用故障录波信息和已有的故障信息，基于粗糙集的知识获取方法，构建诊断决策表，通过简化决策表，获得最小属性约简表。在此基础上建立比较序列与参考序列，采用灰关联分析确定约简表中属性的灰关联度和决策属性中可疑故障元件的关联可信度，获得明确的诊断结果。仿真结果表明该方法精度更高、有效性更好。最后利用融合互补的思想，，引入DS信息融合技术，建立DS证据理论的融合诊断模型，将FPN和RS两种诊断方法获得的诊断结果在DS证据理论决策级进行融合，通过DS决策规则，获得精确的诊断结果。仿真结果表明该方法的精确性和准确性。
[Abstract]:The Northwest 750kV interconnection project is an ultra-high voltage transmission and transformation project with the largest scale, the highest voltage grade, the longest line and the most complex transmission and transformation in the history of Northwest Power Grid. The 750kV substation, as the hub of the 750kV power network, consists of three voltage levels of 750 kV or 330 kV and 66kV. The protection adopts a dual configuration, which makes the network topology of the 750kV substation more complex. Protection configuration increased. When substation fault occurs, the amount of fault information increases and the fault information is more complex. The operator should be able to judge the fault quickly and accurately, and to locate and recover the fault. Therefore, the study of substation fault diagnosis system is of great significance to ensure the safe and stable operation of power network. In this paper, 750kV substation is taken as the research object. Aiming at the uncertainty of maloperation and rejection of protective devices and circuit breakers, as well as the characteristics of incomplete diagnostic information source in traditional fault diagnosis and large amount of alarm information when abnormal, FPN (Fuzzy Petri Net, is adopted in this paper. Fuzzy Petri net), RS (Rough Sets, rough set) and three diagnostic methods of information fusion are studied, and the effectiveness of the method is verified by simulation. Firstly, aiming at the uncertainty of maloperation and rejection of protection device and circuit breaker, and the dual-network dual protection configuration of 750kV substation, a fault diagnosis method for substation FPN with redundant protection configuration is proposed. In this method, the redundant knowledge representation method of the component diagnosis model is studied, and the FPN redundancy diagnosis model of the fault element is established. According to the characteristics of the double network of the 750kV substation, the method uses the information of the dual protection device to study the redundant knowledge representation method of the component diagnosis model. The redundancy diagnosis model is divided into two subnet models: main network and redundant network. In the model, the reliability of initial information is determined by joint information entropy, and the minimum fault diagnosis result set is obtained by fuzzy reasoning. Simulation results show the effectiveness of the method. Secondly, aiming at the complexity of 750kV substation line, the double protection configuration, the huge amount of alarm information when abnormal and the incomplete diagnosis information source in traditional fault diagnosis, etc. A fault diagnosis method for hierarchical substation based on RS redundancy protection configuration is proposed. In this method, according to the voltage grade characteristics of 750kV substation, the 750kV substation is divided into three regions. According to the connection characteristics of each area, the 750kV substation is partitioned. Then, using fault recording information and existing fault information, a diagnosis decision table is constructed based on rough set knowledge acquisition method, and the minimum attribute reduction table is obtained by simplifying the decision table. On this basis, the comparison sequence and the reference sequence are established, and the grey correlation degree of attributes in the reduction table and the correlation reliability of suspicious fault elements in the decision attribute are determined by grey correlation analysis, and the definite diagnosis results are obtained. Simulation results show that the method is more accurate and effective. Finally, using the idea of fusion and complementation and introducing DS information fusion technology, the fusion diagnosis model of DS evidence theory is established. The diagnostic results obtained by FPN and RS are fused at the DS evidence theory decision level, and the DS decision rules are adopted. Obtain accurate diagnostic results. Simulation results show that the method is accurate and accurate.
【学位授予单位】：兰州交通大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM63

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