A Scalable Ensemble Approach to Forecast the Electricity Consumption of Households-Reference-Cited by-同舟云学术

A Scalable Ensemble Approach to Forecast the Electricity Consumption of Households

Published:2023-01 Issue:1 Volume:14 Page:757-768
ISSN:1949-3053
Container-title:IEEE Transactions on Smart Grid
language:
Short-container-title:IEEE Trans. Smart Grid

Author:

Botman Lola¹^ORCID,Soenen Jonas²^ORCID,Theodorakos Konstantinos³^ORCID,Yurtman Aras²^ORCID,Bekker Jessa²,Vanthournout Koen³^ORCID,Blockeel Hendrik²^ORCID,De Moor Bart¹^ORCID,Lago Jesus⁴^ORCID

Affiliation:

1. Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing, and Data Analytics, KU Leuven, Leuven, Belgium

2. Department of Computer Science, DTAI Declarative Languages and Artificial Intelligence, KU Leuven, Leuven, Belgium

3. Energietechnologie (ETE), VITO/EnergyVille, Genk, Belgium

4. International Technologies, Amazon, Amsterdam, The Netherlands

Funder

Flemish Government under the “Onderzoeksprogramma Artificiële Intelligentie (AI) Vlaanderen” Program

KU Leuven Research Fund

European Research Council under the European Union’s Horizon 2020 Research and Innovation Programme

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/5165411/9997165/09830758.pdf?arnumber=9830758

Reference31 articles.

1. A method of formulating energy load profile for domestic buildings in the UK

2. Regression analysis for prediction of residential energy consumption

3. Using regression analysis to predict the future energy consumption of a supermarket in the UK

4. A new error measure for forecasts of household-level, high resolution electrical energy consumption

5. The Probable Error of a Mean

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