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A probabilistic framework for forecasting household energy demand profiles

Abstract:

Recent work introduced a novel time-permuting error measure for forecasts of half-hourly, household-level energy demand, designed to reward forecasts which predict extremes (spikes) in demand at approximately the right times, albeit perhaps slightly early or late. In many applications such as smart storage control, such forecasts are preferable to those that predict no spikes at all. Building on that idea, we make three contributions. First we introduce a probabilistic framework to estimate e...

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Publication status:
Submitted
Peer review status:
Not peer reviewed
Version:
Author's Original

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Institution:
CountingLab Ltd.
Role:
Author, Contributor
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Institution:
University of Oxford
Department:
Mathematical,Physical & Life Sciences Division - Mathematical Institute
Role:
Author
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Institution:
University of Oxford
Department:
Mathematical,Physical & Life Sciences Division - Mathematical Institute
Role:
Author
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Institution:
University of Reading
Role:
Author
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Institution:
CountingLab Ltd.
Role:
Author
Publication date:
2014-03-06
URN:
uuid:68b6552b-4b96-4384-a7c6-9c8cd55b6c8d
Local pid:
ora:8211

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