基于贝叶斯信息准则的非侵入式负荷事件检测算法

Non-intrusive load event detection algorithm based on Bayesian information criterion

用户负荷数据监测是实现需求侧管理的基础,非侵入式负荷监测技术是负荷监测的重要发展方向,而事件检测是非侵入式负荷监测中的一个关键环节。对适用于模型选取问题的贝叶斯信息准则进行建模,将贝叶斯信息准则首次运用到事件检测当中,利用快速事件检测算法降低贝叶斯信息准则检测算法的误检率,并能解决CUSUM算法中产生的漏检问题。最后采用真实数据集进行测试。实验结果表明,相比于CUSUM算法,基于贝叶斯信息准则的事件检测算法能达到更好的检测准确性,并且能明显提高计算运行的速度。

User load data monitoring is the basis of demand side management.Non-Intrusive Load Monitoring(NILM)is an important development direction of load monitoring,and event detection is a key point in NILM.In this paper,the Bayesian information criterion which is suitable for the model selection problem is modeled and applied to event detection for the first time.Fast event detection algorithm is used to reduce the false alarm rate of event detection algorithm based on Bayesian information criterion,which can solve the problem of missing detection point in CUSUM algorithm.Finally,a real data set is used for testing.The experimental results show that compared with CUSUM algorithm,the event detection algorithm based on Bayesian information criterion can achieve better detection accuracy and can significantly improve the speed of computation.