Forecast electricity demand in commercial building with machine learning models to enable demand response programs-Reference-Cited by-同舟云学术

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Forecast electricity demand in commercial building with machine learning models to enable demand response programs

Published:2022-01 Issue: Volume:7 Page:100121
ISSN:2666-5468
Container-title:Energy and AI
language:en
Short-container-title:Energy and AI

Author:

Pallonetto Fabiano^ORCID,Jin Changhong,Mangina Eleni^ORCID

Funder

Sustainable Energy Authority of Ireland

Ministero dell’Istruzione, dell’Università e della Ricerca

Publisher

Elsevier BV

Subject

Artificial Intelligence,General Energy,Engineering (miscellaneous)

Reference43 articles.

1. Global carbon budget 2018;Le Quéré;Earth Syst Sci Data,2018

2. Electricity information overview;International Energy Agency,2020

3. Introduction to electric load forecasting methods;Alkhathami;J Adv Electr Comput Eng,2015

4. Review of building energy modeling for control and operation;Li;Renew. Sustain. Energy Rev.,2014

5. Effort Sharing among EU Member States: Green Deal Emission Reduction Targets for 2030;Steininger,2020

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