Short-term prediction of electric demand in building sector via hybrid support vector regression-Reference-Cited by-同舟云学术

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Short-term prediction of electric demand in building sector via hybrid support vector regression

Published:2017-10 Issue: Volume:204 Page:1363-1374
ISSN:0306-2619
Container-title:Applied Energy
language:en
Short-container-title:Applied Energy

Author:

Chen Yibo,Tan Hongwei

Funder

Zhejiang Zhengling New Energy Technology Co. Ltd

China Intelligent Urbanization Co-creation for High Density Region

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Mechanical Engineering,General Energy,Building and Construction

Reference36 articles.

1. UNEP. Cities and Climate Change, ; 2015.

2. Demand flexibility versus physical network expansions in distribution grids;Spiliotis;Appl Energy,2016

3. Demand-side management and optimal operation of industrial electricity consumers: an example of an energy-intensive chemical plant;Xenos;Appl Energy,2016

4. Energy flow modeling and optimal operation analysis of the micro energy grid based on energy hub;Ma;Energy Convers Manage,2017

5. Artificial neural network model for forecasting sub-hourly electricity usage in commercial buildings;Chae;Energy Build,2016

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