A state assessment method for intelligent substation secondary equipment based on grey theory and cloud model

For the complex diversity of the secondary fault mechanism of the smart substation, the traditional single-factor assessment is difficult to effectively mine potential safety hazards. A hierarchical evaluation model and index system for the secondary equipment state assessment is established based on the corresponding research. And grey clustering in grey theory is used to establish a grey clustering model for the state assessment of secondary equipment. In order to save manpower and take into account the objectivity of the state assessment, the grey prediction GM (1,1) model is used to discretely model the expert scores to obtain enough evaluation samples. At the same time, taking into account the uncertainty of the evaluation index, a grey model is used to construct a grey white weight function, and combined with the analytic hierarchy process to calculate the combined weight of the state indicators. The actual case simulation results show that the method supposed in this paper is small in computation and simple in operation, and can provide scientific guidance for the state-repairing work of secondary equipment and systems in smart substations accurately and in a timely manner. © 2019, Power System Protection and Control Press. All right reserved.