【摘要】 大型调相机作为高压直流输电工程中的重要设备，其健康状态对于电网安全运行具有重要意义。为此，本文提出一种基于趋势预测的大型调相机健康状态评价方法。首先，针对调相机的设备构成，基于多层次模糊综合评价法构建了调相机健康状态评估体系；其次，提出基于层次分析法与熵权法的组合赋权法进行指标权重赋值，应用模糊隶属度进行逐层评价；最后，提出了基于小波包-长短期记忆神经网络预测模型的劣化度改进方法，以实现实时状态评估。算例结果表明所提方法较于传统评估方法，更具合理性，有助于实现设备的故障预警，为换流站的调度运行与设备检修提供参考意见。更多还原

【Abstract】 As an important equipment in UHVDC transmission projects, the state of health of the synchronous condenser is of great significance to the safe operation of the power grid. To this end, a method for evaluating the health status of the large-scale synchronous condenser based on trend prediction is proposed. First of all, aiming at the equipment composition of the synchronous condenser, based on the multi-level fuzzy comprehensive evaluation method, the health status evaluation system of the camera is constructed. Secondly, a combination weighting method based on analytic hierarchy process and entropy weight method is proposed for index weight assignment, and fuzzy membership degree is used for layer-by-layer evaluation. Finally, a degradation improvement method is proposed based on wavelet packet and long-short term memory neural network prediction model to achieve real-time state evaluation. The results of the calculation examples show that the proposed method is more reasonable than the traditional evaluation method, which is helpful to realize the early warning of equipment failure, and provides reference opinions for the dispatching operation and equipment maintenance of the converter station.更多还原