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Load forecasting using nonlinear modelling
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DOI：10.1016/j.conengprac.2004.07.006.png)
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Abstract
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The best-possible prediction of the gas consumption represents highly valuable information for gas producers. Using an appropriate model of the time-dependent and nonlinear gas consumption process, a prediction scheme can be set up for all the nodes in a gas network. In this paper, a nonlinear model with several inputs using noisy observations is built up as a combination of a prespecified dynamical term and an unknown static nonlinear component realized by region-wise base point driven interpolation. Also, the details of the practical application for a real gas network are shown. (c) 2004 Published by Elsevier Ltd.
Keywords:
system identification
nonlinear systems
errors-in-variables estimation
approximation methods
load forecasting
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