基于多状态信息修正优化组合的电力设备故障率计算方法

Calculation Method for Fault Rate of Electric Power Equipment Based on Multi-state Information Amendment Optimization Combination

采用多状态修正优化组合预测方法,建立天气因素、材料绝缘老化和设备检修影响的3种状态修正优化组合预测电力设备故障率模型。针对各随机影响因素的特点,依据可拓性原理预测3种天气状态模型的故障率,由3种参数威布尔分布-Copula函数的联合失效概率密度法计算绝缘老化引起的设备故障率,基于Holt-Winters模型来预估设备检修造成的故障率,再采用果蝇算法加权组合优化所求得的各子模型的故障率,算出具有高准确度的预测值。以某地区的电力系统为实例进行分析,所得结果表明所述模型可有效提高设备故障率的预测精度,同时也验证了果蝇优化算法在求解多状态修正优化组合预测问题时的有效性。

Forecasting method for multi-state information amendment optimization combination is used to establish three kinds of models of state amendment optimization combination for forecasting fault rates of electric power equipments, which are respectively affected by weather, insulation aging of materials and equipment overhaul. In allusion to characteristics of various stochastic influencing factors, extensible principle is applied in forecasting fault rates of three kinds of weather state models. Joint failure probability density method based on three parameters Weibull distribution-Copula function is used for calculating fault rate caused by insulation aging and Holt-Winters model is used to estimate fault rate due to equipment over- haul. Predicted value with high degree of accuracy is worked out by using fruit flies optimization algorithm to weight and op- timize the fault rate of each subrnodel. Taking one power system in some region for an example, the analysis results indicate that these models can effectively improve forecasting precision of fault rates, meanwhile the fruit flies optimization algo-rithm is efficient to solve the forecasting problem of multi-state information amendment optimization combination.