Artificial Neural Networks in Short Term load Forecasting
　　　　　　　　　　　　　　K.F. Reinschmidt, President B. Ling
　　　　Stone h Webster Advanced Systems Development Services, Inc.
　　　　       245 Summer Street Boston, U 0221 0
　　　　　　　　　　　　　　　　　Phone: 617-589-1 84 1
　　Abstract：
　　　We discuss the use of artificial neural networks to the short term forecasting of loads. In this system, there are two types of neural networks: non-linear and linear neural networks. The nonlinear neural network is used to capture the highly non-linear relation between the load and various input parameters. A neural networkbased ARMA model is mainly used to capture the load variation over a very short time period. Our system can achieve a good accuracy in short term load forecasting.

　　　Key words: short-term load forecasting, artificial neural network



人工神經(jīng)網(wǎng)絡在短期負荷預測中的應用
　　　摘要：
　　　在本文，我們將討論如何利用人工神經(jīng)網(wǎng)絡對短期負荷進行預測。在這類系統(tǒng)中，有兩種類型的神經(jīng)網(wǎng)絡：非線性和線性神經(jīng)網(wǎng)絡。非線性神經(jīng)網(wǎng)絡是用來捕獲負荷和各種輸入?yún)?shù)之間的高度非線性關系?；贏RMA模型的神經(jīng)網(wǎng)絡，主要用來捕捉很短的時間期限內(nèi)負載的變化。我們的系統(tǒng)可以實現(xiàn)準確性高的短期負荷預測。
　　　
　　　關鍵詞：短期負荷預測，人工神經(jīng)網(wǎng)絡