基于不确定性推理的变电站拓扑错误辨识

采用基于确定因子的不确定性推理方法,文中提出一种变电站拓扑错误辨识方法。在规则法的基础上,根据规则采用的数据类型和关系的不同,将规则分为四大类进行阐述。然后根据不确定性推理方法,对各类拓扑错误辨识规则建立了不精确模型,利用不确定性推理的传播算法和合成算法,计算出每个断路器和刀闸的综合可信度,从而判断断路器和刀闸的开合状态。该方法利用变电站内三相多源数据,冗余度高,提高了对刀闸的辨识能力,解决了规则冲突的问题。算例结果表明,该算法能够对多个不良数据和拓扑错误同时存在的情况进行有效辨识。

Substation Topology Error Identification Based on Uncertainty Reasoning

A substation topology error identification method based on uncertainty reasoning is proposed. Topology error identification rules are divided into four categories according to different data types and relationships used by each rule. An inaccurate model for each of the data in substation and topology error identification rules is developed. The integrated certainty factor value of each circuit breaker and switch is calculated by using the transfer algorithm and synthetic algorithm of uncertainty reasoning. The results are used to determine the status of each circuit breaker and switch. This substation topology error identification method has high redundancy using the three-phase multi-source data in substation and has improved the ability of identifying the switch status and solved the problem of conflicts between rules. Simulation for the multiple topology errors with multiple bad data has validated its effectiveness and high reliability.