Short-term load forecast using support vector regression and feature learning
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United States of America Patent
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Apr 28, 2015
Grant Date -
May 2, 2013
app pub date -
Oct 26, 2012
filing date -
Oct 31, 2011
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Abstract
In a support vector regression approach to forecasting power load in an electrical grid, a feature learning scheme weights each feature in the input data with its correlation with the predicted load, increasing the prediction accuracy. The kernel matrix for the input training data is computed such that features that align better with the target variable are given greater weight. The resulting load forecast may be used to compute commands sent to demand response modules.
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