State Evaluation of Electrical Equipment in Pumped Storage Power Station Based on Divisible Cloud Model

Considering the complexity of assessment indicators for electrical apparatus in pumped storage power plants and the limitations of scope of conventional evaluation methodologies, a joint evaluation method of primary and secondary equipment status of pumped storage power stations with subjective and objective coupling weights and two-dimensional divisible cloud model is proposed. This methodology is grounded in the empirical inspection data and flaw reports from a representative Chinese pumped storage power plant to establish a systematic evaluation system covering generator motor, main transformer, high-voltage electrical equipment and its related secondary auxiliary equipment. The improved self-adjusting analytic hierarchy process and the objective weighting method of CRITIC are utilized to calculate the coupling weights of indicators. Subsequently the two-dimensional cloud model parameter matrix of each evaluation indicator is calculated. The input cloud model generator visually presents the health state of the core electrical equipment of the power station. Finally, by establishing the segmentation plane, the high risk index can be quickly identified to reflect the status of parts. In the light of the constructed evaluation system and evaluation method, the risk of the main electrical equipment of the power station can be evaluated in the coming future, and the results show that the method can rapidly and effectively pinpoint the high-risk equipment. The presented study demonstrates the simplicity, feasibility, and efficacy of the methodology in assessing the operational status of both the core primary machinery and the auxiliary secondary infrastructure within a pumped-storage power plant, which offers valuable guidance for maintenance and decision-making of the power plants.