发电机组非计划停机事件的贝叶斯网络分析

Bayesian network analysis of unplanned shutdown of generating units

为保障发电机组安全稳定运行,需要对机组产生故障的原因进行深入分析。利用发电厂非计划停机事件的分析报告,对非计划停机事件的影响因素进行归纳总结,最终形成预测电厂非计划停机的贝叶斯网络图。通过发电厂非计划停机的贝叶斯网络分析,对各种影响因素对于非计划停机的影响程度进行因果推断分析。结果表明,当对设备老化评估不足时,由于设备发生故障而导致停机事件发生的概率会大幅提升。当设备长期处于恶劣环境中时,老化故障的概率会迅速增大。通过贝叶斯网络分析,明确各种影响因素对非计划停机事件的影响概率情况,为发电企业的能源大数据分析提供参考,提高机组设备安全运行的可靠性。

To ensure the safe and stable operation of generator sets,it is necessary to analyze the causes of their failures intensively.Based on the analysis report on unplanned shutdowns of a power plant,the influencing factors of the unplanned outage events are summarized,and the Bayesian network diagram for predicting the unplanned outages is made.According to Bayesian network analysis on the unplanned shutdowns of the power plant,the causal inference analysis on the impacts of various factors on unplanned shutdowns is carried out.The results show that when the aging status evaluation of equipment is insufficient,the probability of outage events caused by equipment failure will be significantly increased.Placing equipment in an unfavorable environment for a long time will boost the probability of aging faults.Through Bayesian network analysis,the impact probabilities of various influencing factors on unplanned outage events are clarified,which provides reference for energy big data analysis of power generation enterprises and will improve the operation reliability and safety of units.