Operational state assessment of cross-linked polyethylene power cable on the basis of an optimized cloud matter-element theory

Polyethylene power cables are likely to encounter high failure rates due to adverse operation conditions. In order to ensure a safe and reliable operation of the Polyethylene power cables, a state assessment approach should be conducted to evaluate the actual operation state of the Polyethylene power cables and determine the maintenance schedule. Several techniques which are used to preempt cable failure and schedule efficient maintenance in the past work have been reviewed, each of which is found with limitation. Taking a 10 kV - Polyethylene power cable as an example and considering the uncertainty of cloud model as well as the qualitative characteristics of matter-element theory, a cable operation state assessment method based on improved cloud matterelement theory with optimal entropy was proposed. Firstly, aiming at the randomness and fuzziness of operation condition level boundary, cloud matter-element theory was proposed to construct the index system of state evaluation. Secondly, based on a comprehensive consideration on the characteristics of clarity and fuzziness of grade division, the optimized cloud entropy calculation method suitable for fuzzy indices is proposed, and the traditional extension cloud theory is improved. Finally, according to the cloud matter-element model correlation degree assessment matrix and comprehensive weight, the operation condition grade of Polyethylene power cable is comprehensively evaluated. The method could effectively deal with the uncertainties in the state assessment according to the changes of the power cable operation condition, and the assessment results were more objective and reasonable. The proposed method in this paper conquers the drawbacks of the past work and can effectively deal with the uncertainty factors in transformer state assessment. The evaluation results are closer to the real state of the equipment and have wider application scenarios.