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Equipment maintenance decision is a very critical technology in power grid asset management. The traditional maintenance decision focuses on the analysis of the operation performance of the equipment itself, but lacks the analysis and description of the fuzziness of power equipment outage parameters. Therefore, this paper establishes the reliability assessment model based on equipment health condition monitoring, which makes the maintenance decision transition from equipment level to system level, and the fuzzy mathematics theory is introduced to establish a model describing the fuzziness of equipment failure rate parameter to make system reliability assessment and equipment maintenance decision scheme. Firstly, this paper proposes a fuzzy failure rate model of power transformer based on condition monitoring. Then the fuzzy parameters are combined with the conventional probabilistic reliability assessment method to establish the fuzzy probability hybrid reliability assessment model of the transmission system, and the fuzzy maintenance reliability benefit index is defined and deduced. Finally, a maintenance strategy of transformer based on fuzzy probability hybrid reliability assessment and fuzzy set theory is proposed, and the case study is carried out on a regional power grid in East China. The results show that the proposed model provides an improved maintenance strategy of power equipment. [ABSTRACT FROM AUTHOR]

This paper presents a maintenance strategy for overhead lines based on condition monitoring and system reliability assessment. A quantitative relationship between the condition monitoring data and failure rate of overhead lines is established. The system reliability is evaluated using monitoring data; the reliability benefit due to the maintenance of each line is quantified; and the maintenance ranking order is created using the benefit/cost ratio index. The proposed strategy can provide the largest reliability improvement at the lowest maintenance cost and within budget. Case studies were performed on a 182-bus, 5474-MW transmission system located in southwest China. [ABSTRACT FROM PUBLISHER]

This article presents a quantified method to evaluate an overall condition index of power equipment and its probability density distribution using monitored data. A special transformation is developed to normalize the monitored data of different parameters. The overall condition index can be easily calculated using the normalized parameters. To capture the uncertainty and randomness of the monitored data, the kernel density evaluation method is used to assess the probability distribution of the condition index. With the probability density function, the probability of power equipment operating in the normal condition can be assessed. The monitored data of two breakers for five monitored parameters are used in the case study. The results indicate that the proposed method can straightforwardly identify which breaker has a worse performance and, therefore, should be considered for maintenance first. [ABSTRACT FROM AUTHOR]