An Optimization Method of Energy Demand Forecasting Method Based on Neural Network-Reference-Cited by-同舟云学术

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An Optimization Method of Energy Demand Forecasting Method Based on Neural Network

Published:2023-12-01 Issue: Volume:180 Page:111-114
ISSN:
Container-title:2023 5th International Conference on Smart Power & Internet Energy Systems (SPIES)
language:
Short-container-title:

Author:

Zhao Yufan¹,Song Ruizhuo¹,Li Chengfeng²

Affiliation:

1. School of Automation and Electrical Engineering University of Science and Technology Beijing,Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education,Beijing,China,100083

2. Clean Energy Branch of CNOOC Energy Technology & Services Limited, Tianjin,Tianjin,China,300452

Funder

National Natural Science Foundation of China

Fundamental Research funds for the Central Universities

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10474594/10474601/10474617.pdf?arnumber=10474617

Reference17 articles.

1. The role of regulatory reforms, market changes, and technology development to make demand response a viable resource in meeting energy challenges

2. Estimating the benefits of cooperation in a residential microgrid: A data driven approach;Rieger;Applied Energy,2016

3. Assessing the benefits of residential demand response in a real time distribution energy market;Siano,2016

4. Dual battery management for renewable energy integration in EV charging stations

5. Short-term load forecast of integrated energy system based on wavelet packet decomposition and recurrent neural network;Zhu;Electric Power Construction,2020

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