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Leith, Douglas J., Heidl, Martin and Ringwood, John (2004) Gaussian Process Prior Models for Electrical Load Forecasting. Probabilistic Methods Applied to Power Systems. pp. 112-117.
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Abstract
This paper examines models based on Gaussian Process (GP) priors for electrical load forecasting. This methodology is seen to encompass a number of popular forecasting methods, such as Basic Structural Models (BSMs) and Seasonal Auto-Regressive Intergrated (SARI) as special cases. The GP forecasting models are shown to have some desirable properties and their performance is examined on weekly and
yearly Irish load data.
| Item Type: | Article |
|---|---|
| Keywords: | Gaussian process; basic structural models; electrical load forecasting; electricity demand; seasonal auto-regressive intergrated; |
| Academic Unit: | Faculty of Science and Engineering > Electronic Engineering |
| Item ID: | 1938 |
| Depositing User: | Professor John Ringwood |
| Date Deposited: | 19 May 2010 15:57 |
| Journal or Publication Title: | Probabilistic Methods Applied to Power Systems |
| Publisher: | IEEE |
| Refereed: | Yes |
| Related URLs: | |
| Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
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