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Comparison of very short-term load forecasting techniques

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7 Author(s)
Liu, K. ; Autom. & Robotics Res. Inst., Texas Univ., Arlington, TX, USA ; Subbarayan, S. ; Shoults, R.R. ; Manry, M.T.
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Three practical techniques-fuzzy logic (FL), neural networks (NN), and autoregressive models-for very short-term power system load forecasting are proposed and discussed in this paper. Their performances are evaluated through a computer simulation study. The preliminary study shows that it is feasible to design a simple, satisfactory dynamic forecaster to predict very short-term power system load trends online. FL and NN can be good candidates for this application

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Power Systems, IEEE Transactions on  (Volume:11 ,  Issue: 2 )