PL EN


2013 | 14 | 2 | 289-297
Article title

FORECASTING OF INDIVIDUAL ELECTRICITY USAGE USING SMART METER DATA

Content
Title variants
Languages of publication
EN
Abstracts
EN
Forecasting electricity usage is an important task to provide intelligence to the smart gird. The customers will benefit from metering solutions through greater understanding of their own energy consumption and future projections, allowing them to better manage costs of their usage. In this proof of concept paper, we show the approach for short term electricity load forecasting for 24 hours ahead, calculated on the individual household level. In this context authors will develop an approach to the analysis and prediction using Multivariate Adaptive Regression Splines (MARSplines).
Year
Volume
14
Issue
2
Pages
289-297
Physical description
Dates
published
2013
Contributors
References
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  • Song K.B., Baek Y.S., Hong D.H., Jang G. (2005) Short-term load forecasting for the holidays using fuzzy linear regression method, IEEE Transactions on Power Systems, vol. 20, 96–101.
  • Weron R. (2006) Modeling and forecasting electricity loads and prices: A statistical approach, Wiley, Chichester.
Document Type
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.desklight-364aa1e9-103c-4fbd-8b9e-2ea3bfd6794c
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