基于新鲜度函数和预测有效度的模糊自适应变权重中长期电力负荷组合预测

针对传统电力负荷组合预测模型中出现的负权重、没有区别对待不同历史时段的误差对权重的影响以及变权重计算方法较为复杂等问题，文中提出一种基于新鲜度函数和预测有效度的模糊自适应变权重组合预测模型，并应用到中长期电力负荷组合预测中。利用预测有效度进行模型筛选，利用新鲜度函数体现预测中的“近大远小”原则，利用滚动时间域窗口的方法实现变权。算例表明，文中提出的组合预测模型预测精度较高，实用性强。

Combination Forecast of Mediumand Long-Term Load Using Fuzzy Adaptive Variable Weight Based on Fresh Degree Function and Forecasting Availability

In view of the negative weights and not making different treatment on the influence of errors in different historical time periods on weights in traditional load combination forecasting models as well as the complexity of calculating variable weights, the authors propose a combination forecasting model using fuzzy adaptive variable weight based on fresh degree function and forecasting availability and apply it in the medium- and long-term load forecasting. The model is screened by forecasting availability and the fresh degree function is adopted to embody the impact extent of historical data in different time periods as well as the rolling time-domain window is used to vary weights. Results of calculation examples show that the forecasting results by the proposed model is accurate and the proposed method is practicable.