基于人工神经网络的短期负荷预测,并对周末和季节变化进行特殊调整

N. Moharari, A. Debs
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引用次数: 11

摘要

利用作者提出的反向传播算法,将人工神经网络技术应用于电力负荷预测。这项工作的主要贡献是能够在相对较小的训练集上预测周末和节假日以及工作日的电力负荷。此外,还可以追踪季节变化对负荷模式的影响。他们的方法是向人工神经网络引入三组不同的输入,以遵循负荷模式、天气模式、季节因素,并考虑周末和假期等特殊事件。
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An artificial neural network based short term load forecasting with special tuning for weekends and seasonal changes
The artificial neural network (ANN) technique is utilized for power electric load forecasting using the backpropagation algorithm developed by the authors. The major contribution of this work is the ability to forecast the power electric load for weekends and holidays as well as weekdays with a relatively small training set. In addition the effect of seasonal change in load pattern can be tracked down. Their approach is to introduce three different sets of inputs to the ANN in order to follow the load pattern, weather pattern, seasonal factors and to consider special events like weekends and holidays.<>
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