输变电系统可靠性评估中设备故障率预测方法研究

由于输变电设备在地域分布上的复杂性、运行状态的随机多样性,使得输变电设备故障率具有时变性、随机性等特点。同时由于反映设备故障的信息获取困难,故难以应用常规的回归分析法、分解分析法等时间序列分析法建立准确的故障率预测模型。文中以全网输变电设备故障率为研究对象,提出了一种基于自回归-移动平均混合模型(ARMA模型)的输变电设备故障率预测方法,克服了常规解析法进行输变电设施可靠性评估信息获取困难的缺点,能有效提高全网输变电设施可靠性评估的合理性和准确性。最后,对220k V输电线路故障率进行了预测,结果表明,所提预测模型具有较高的精度,能够满足实际工程的应用要求。

A prediction method for failure rate of equipments in reliability evaluation of power transmission system

Accurate predicting of failure rate of power transmission equipments can enhance credibility of reliability assessment for transmission systems and its prediction results, so as to improve the reliability management level of power transmission system. However, due to the complexity of power transmission equipments distributed geographically, and randomness and diversity of operation states, the failure rate of power transmission equipments have characteristics of time-varying and stochastic. As it is difficult to obtain the information reflecting equipment faults, conventional methods of regression analysis and decomposition analysis and time series analysis could not be used to establish accurate prediction model of failure rate. This paper presents a predicting method of transmission failure rate based on autoregressive-moving average(ARMA) model in order to adapt to time variation and randomness of equipment failure rate of power transmission system. The method is focused on equipment failure rate of whole power transmission system without the difficulty of obtaining information for reliability evaluation in conventional analytic methods, and less information is needed. So the validity and accuracy of reliability evaluation for equipments in whole transmission system are improved effectively. Finally, the method is used to predict the failure rate of a provincial 220kV power transmission system. The results have shown that the method has high accuracy, and can be applied to engineering practice to improve stability of power systems .