电力系统可靠性原始参数的分析与确定是可靠性评估的基础。针对电力系统可靠性原始参数的缺乏和开发电力系统可靠性原始参数小样本系统增加数据量的重要性 ,在对灰色预测模型进行深入研究的基础上 ,建立了一种改进 B矩阵的加权均值迭代生成和预测算法的改进灰色预测方法。改进灰色预测方法在建模和预测时充分利用最新的 4个信息 ,通过引入加权值对新旧信息做出不同的补偿 ,并采用加入新信息、去掉旧信息的新陈代谢灰色预测算法 ,大大减少了计算量 ,增强了新信息的作用和提高了预测的精度。通过对新投入的线路元件无故障工作时间预测 ,并进行传统模型和改进模型的结果精度比较 ,表明了改进的模型和预测算法预测电力系统可靠性原始参数的准确性、有效性和实用性 The analysis and determination of the original parameters of power system reliability are the basis of reliability assessment. Aiming at the lack of original parameters of power system reliability and the importance of developing original parameters of power system reliability small sample system to increase the amount of data, a weighted average iteration of improved B matrix is ​​established based on the gray prediction model Improved Gray Prediction Method for Generating and Predicting Algorithms. The improved gray forecasting method makes full use of the latest four information in the modeling and forecasting, compensates the old and new information differently by introducing the weighted value, and uses the new information to remove the old metabolic gray forecasting algorithm, which greatly reduces the computation This has enhanced the role of new information and improved the accuracy of forecasts. By predicting the working hours of newly input line components and comparing the accuracy of the results of the traditional model and the improved model, it is shown that the improved model and prediction algorithm can predict the accuracy, validity and practicability of the original parameters of the power system reliability