基于模型预测和溯因推理网络的电网故障诊断方法

考虑电网出现故障时,仅依靠开关量状态信息进行诊断,诊断信息冗余度低,复杂故障情况下会影响诊断结果的准确性.引入电气量信息,提出了模型预测和数据清洗方法,建立电网故障诊断系统.利用模型预测得到准确的电气量信息,建立清洗规则和逻辑推理规则,分别对开关量进行数据清洗和验证故障信息.在此基础上,利用溯因推理网络(abductive reasoning network,ARN)对故障信息进行诊断,得出候选故障.仿真结果验证了该方法的有效性和准确性.

Method of Power Grid Fault Diagnosis Based on Model Prediction and Abductive Reasoning Network

Considering the power grid fault， the diagnostic information redundancy is low based only on protective relays and circuit breakers(switch) for diagnosis， and the accuracy of diagnosis will be affected under complex fault cases. The electric data information was introduced to propose the model prediction and data cleaning method， as well as to establish the power network fault diagnosis system. By using the model to predict the electric quantity information accurately， the cleaning rules and the logical inference rules were established， and the data cleaning and verification of the switch were carried out respectively. On this basis， the abductive reasoning network (ARN) was used to diagnose the fault information， and the candidate faults were obtained. The simulation results verified the validity and accuracy of this method.