Journal article
Short-term residential load forecasting: Impact of calendar effects and forecast granularity
P Lusis, KR Khalilpour, L Andrew, A Liebman
Applied Energy | ELSEVIER SCI LTD | Published : 2017
Abstract
Literature is rich in methodologies for “aggregated” load forecasting which has helped electricity network operators and retailers in optimal planning and scheduling. The recent increase in the uptake of distributed generation and storage systems has generated new demand for “disaggregated” load forecasting for a single-customer or even down at an appliance level. Access to high resolution data from smart meters has enabled the research community to assess conventional load forecasting techniques and develop new forecasting strategies suitable for demand-side disaggregated loads. This paper studies how calendar effects, forecasting granularity and the length of the training set affect the ac..
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Funding Acknowledgements
Special thanks go to Pierre Pinson from the Technical University of Denmark and Souhaib Ben Taieb from Monash University for reviewing the paper and providing feedback. Dr. Khalilpour and Dr. Liebman would like to acknowledge the partial support of this project through a funding from the Australia-Indonesia Centre.