论文标题
估计电力系统中资产类健康指数
Estimating Asset Class Health Indices in Power Systems
论文作者
论文摘要
电力系统已广泛采用健康指数的概念来描述资产健康状况并选择适当的资产管理措施。现有的应用程序和研究工作集中在基于当前状况数据的基于当前或近乎未来的资产健康指数。对于预防资产管理，非常需要估计资产健康指数，尤其是对于资产具有相似的电气和/或机械特性的资产类别。这个重要的问题尚未得到充分解决。本文提出了一种基于序列学习的方法，以估算电力资产类别的健康指数。提出了基于序列学习的全面数据驱动方法，并根据实际效用数据进行实体测试。所提出的方法揭示了与其他估计方法相比的卓越性能。
Power systems have widely adopted the concept of health index to describe asset health statuses and choose proper asset management actions. The existing application and research works have been focused on determining the current or near-future asset health index based on the current condition data. For preventative asset management, it is highly desirable to estimate asset health indices, especially for asset classes in which the assets share similar electrical and/or mechanical characteristics. This important problem has not been sufficiently addressed. This paper proposes a sequence learning based method to estimate health indices for power asset classes. A comprehensive data-driven method based on sequence learning is presented and solid tests are conducted based on real utility data. The proposed method revealed superior performance with comparison to other Estimation methods.
