Multi-nodal short-term energy forecasting using smart meter data
Hayes, Barry P. Gruber, Jorn K. Prodanovic, Milan
Hayes, Barry P.
Gruber, Jorn K.
Prodanovic, Milan
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Repository DOI
Publication Date
2018-06-10
Keywords
Distributed power generation, Load forecasting, Smart meters, Electrical energy demand modelling, Transactive energy, AMI, Multinodal demand forecasting, Distributed energy system, Smart meter data, Advanced metering infrastructure, European country, Microgrid, Multinodal short-term energy forecasting
Type
Article
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Citation
Hayes, Barry P., Gruber, Jorn K., & Prodanovic, Milan. (2018). Multi-nodal short-term energy forecasting using smart meter data. IET Generation, Transmission and Distribution, 12(12), 2988-2994, Doi:10.1049/iet-gtd.2017.1599
Abstract
This paper deals with the short-term forecasting of electrical energy demands at the local level, incorporating advanced metering infrastructure (AMI), or ‘smart meter’ data. It provides a study of the effects of aggregation on electrical energy demand modelling and multi-nodal demand forecasting. This paper then presents a detailed assessment of the variables which affect electrical energy demand, and how these effects vary at different levels of demand aggregation. Finally, this study outlines an approach for incorporating AMI data in short-term forecasting at the local level, in order to improve forecasting accuracy for applications in distributed energy systems, microgrids and transactive energy. The analysis presented in this study is carried out using large AMI data sets comprised of recorded demand and local weather data from test sites in two European countries.
Publisher
Institution of Engineering and Technology (IET)
Publisher DOI
10.1049/iet-gtd.2017.1599
Rights
Attribution-NonCommercial-NoDerivs 3.0 Ireland