Integrated Energy System Load Forecasting Based on GSO-LSTM and Feature Selection-Reference-Cited by-同舟云学术

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Integrated Energy System Load Forecasting Based on GSO-LSTM and Feature Selection

Published:2024-06-21 Issue: Volume:42 Page:288-297
ISSN:
Container-title:2024 6th International Conference on Energy Systems and Electrical Power (ICESEP)
language:
Short-container-title:

Author:

Hu Zeyan¹,Zheng Peng²,Cai Jiaxin²,Zhu Lingling²,Cai Yuqing¹,Fang Minghui¹

Affiliation:

1. Marketing Service Center of State Grid Fujian Electric Power, Company Limited,Fujian,China

2. State Grid Corporation of Fujian Province,Fujian,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10649893/10651613/10651922.pdf?arnumber=10651922

Reference25 articles.

1. Research on Optimal Operation Strategy of Park Integrated Energy System Considering Coupling Response Characteristics of Cooling, Heating and Power Demand;Haipeng

2. Multi-load Prediction of Integrated Energy System Based on LSTM and Multi-task Xi;Qingkai;Automation of Electric Power Systems,2021

3. Joint Prediction Method of Short-term Cooling, Heating and Electric Load Based on Weather Information;Deyin;Power System Technology,2021

4. A Survey of Data-Driven Load Forecasting of Integrated Energy Systems;Jizhong

5. Overview of novel swarm intelligence optimization algorithms;Yuelin,2022

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