A combined deep learning load forecasting model of single household resident user considering multi-time scale electricity consumption behavior-Reference-Cited by-同舟云学术

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A combined deep learning load forecasting model of single household resident user considering multi-time scale electricity consumption behavior

Published:2022-02 Issue: Volume:307 Page:118197
ISSN:0306-2619
Container-title:Applied Energy
language:en
Short-container-title:Applied Energy

Author:

Yang Wangwang,Shi Jing,Li Shujian,Song Zhaofang,Zhang Zitong,Chen Zexu

Publisher

Elsevier BV

Subject

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

Reference46 articles.

1. A hybrid model for building energy consumption forecasting using long short term memory networks;Somu;Appl Energy,2020

2. Energy consumption prediction of office buildings based on echo state networks;Shi;Neurocomputing,2016

3. Fuzzy-based heat and power hub models for cost-emission operation of an industrial consumer using compromise programming;Khodaei;Appl Therm Eng,2018

4. Assessing the benefits of residential demand response in a real time distribution energy market;Siano;Appl Energy 2016;161,2016

5. An analytical methodology for reliability assessment and failure analysis in distributed power system;Ghiasi;SN Applied Sciences,2019

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