Short-term Load Forecasting Method Based on Artificial Intelligence Highway Neural Network-Reference-Cited by-同舟云学术

Short-term Load Forecasting Method Based on Artificial Intelligence Highway Neural Network

Published:2021-10-22 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE 5th Conference on Energy Internet and Energy System Integration (EI2)
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Author:

Zhang Jinjin¹,Wang Tao²,Wu Junyong¹,Zhu Hainan²,Lan Dong¹,Li Fengshuo²

Affiliation:

1. Electrical Engineering College Beijing Jiaotong University,Beijing,China

2. State Grid Shandong Electric Power Company Weifang Power Supply Company,Planning and Development Department,Weifang,China

Funder

Science and Technology Project of State Grid Shandong Electric Power Company

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9712847/9712848/09713655.pdf?arnumber=9713655

Reference18 articles.

1. Research on Short-term Load Forecasting Based on Data Mining;sun;Tsinghua University,2004

2. Weather sensitive short-term load forecasting using artificial neural networks and time series;karaki;International Journal of Power and Energy Systems,2019

3. RBF-NN short-term load forecasting model considering the comprehensive influence factors of demand response;zhang;Proceedings of the CSEE,0

4. Short-term load forecasting method based on load characteristic clustering and Elastic Net analysis;jin;Electric Power,2020

5. User classification and power consumption behavior analysis based on cluster analysis;xu;Shanxi Electric Power,2016

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