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METHOD FOR FORECASTING RESIDENTIAL QUARTER SHORT-TERM LOAD

机译:住宅季度短期负荷的预测方法

摘要

Disclosed is a method for forecasting residential quarter short-term load, characterized by comprising: step 1: reading history sample data, and performing data screening on the history sample data; step 2: obtaining a load influencing factor coefficient set; step 3: constructing a training sample set and a forecasting sample set for neural network load forecasting; step 4: performing influencing factor separating processing on the training sample set to obtain a trained neural network; step 5: performing influencing factor separating processing on the forecasting sample set, and using a result obtained after processing as input of the trained neural network, to obtain a corresponding output resu and step 6: performing influencing factor adding processing on the output result to obtain load forecasting data of a week in the future. The present invention solves problems that residential quarter load data is small, has large fluctuation, and has lots of influencing factors, and improves the accuracy and operation speed of residential quarter load forecasting.
机译:公开了一种预测住宅小区短期负荷的方法,其特征在于,包括:步骤1:读取历史样本数据,并对历史样本数据进行数据筛选;步骤2:获得负荷影响因子系数集;步骤3:构造用于神经网络负荷预测的训练样本集和预测样本集;步骤4:对训练样本集进行影响因素分离处理,得到训练神经网络。步骤5:对预测样本集进行影响因素分离处理,并将处理后得到的结果作为训练后的神经网络的输入,得到相应的输出结果;步骤6:对输出结果进行影响因素加法处理,得到未来一周的负荷预测数据。本发明解决了住宅小区负荷数据小,波动大,影响因素多的问题,提高了住宅小区负荷预测的准确性和运行速度。

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