Load Identification and Prediction Based on Feature Fusion and Lightweight Neural Network-Reference-Cited by-同舟云学术

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Load Identification and Prediction Based on Feature Fusion and Lightweight Neural Network

Published:2024-05-10 Issue: Volume:20 Page:4565-4570
ISSN:
Container-title:2024 IEEE 7th International Electrical and Energy Conference (CIEEC)
language:
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Author:

Zhang Junwei¹,Tan Zhukui¹,Zhang Ruiqi²,Li Keke³,Zhang Jianfeng³

Affiliation:

1. Electric Power Research Institute of Guizhou Power Grid Co., Ltd.,Guiyang,China

2. Tianjin University,Key Laboratory of Smart Grid of Ministry of Education,Tianjin,China

3. School of Electrical and Information Engineering, Tianjin University,Tianjin,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10582916/10582978/10583060.pdf?arnumber=10583060

Reference21 articles.

1. Credibility evaluation of topology identification results in low-voltage distribution network based on quality of measured data;Li;Power Demand Side Management,2018

2. Review of power system load forecasting and its deveoment;Chongqing;Automation of Electric Power Systems,2004

3. Ultra short-term power load forecasting based on combined LSTM-XG Boost model;Zhenyu;Power System Technology,2020

4. An explainable framework for load forecasting of a regional integrated energy system based on coupled features and multi-task learning

5. Application of SPSS in characteristic of short load and its forecasting;Dongsheng;Power System Protection and Control,2009

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