Health status assessment of smart meters based on variable weight and index cloud matter‐element model

Abstract

Abstract Smart meters are one of the crucial terminals in the construction of smart grids, and it is necessary to assess their health status to prevent failures. Based on a hierarchical evaluation index system, this study improved the entropy method and adopted a combined weighting method to integrate subjective and objective weights. The authors constructed an index cloud matter‐element model to develop the extensibility of the matter element and used the correlation between the level and index clouds to evaluate the health status of smart meters. Here, the level cloud model and the index cloud model reflected the fuzziness of the boundary of the health level and the uncertainty of the sampling data of indexes, respectively. Based on the theory of constant weight decision and variable weight, the weight was adjusted dynamically by combining the real‐time operation data of the entropy method, and the evaluation results were corrected in real time to elucidate the effect of extreme changes and unhealthy conditions on smart meters. Verification of the calculation example demonstrated accurate evaluation using the method in this study, and the maintenance schedule could be adjusted reasonably.

Keywords

• planning (Artificial Intelligence)
• uncertainty handling