Extreme-learning-machine-based architecture to assess the reliability of the integrated energy systems-Reference-Cited by-同舟云学术

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Extreme-learning-machine-based architecture to assess the reliability of the integrated energy systems

Published:2023-04-21 Issue: Volume: Page:
ISSN:
Container-title:2023 8th International Conference on Intelligent Computing and Signal Processing (ICSP)
language:
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Author:

Huo Xianxu¹,Wang Qingbiao²,Zhao Chenyang³,Ding Yi¹,Zhang Bingchen⁴

Affiliation:

1. Electric Power Research Institute of State Grid Tianjin Electric Power Company,Tianjin,China,300384

2. State Grid Tianjin Electric Power Company,Baodi Power Supply Branch,Tianjin,China,301800

3. State Grid Tianjin Electric Power Company,Tianjin,China,300010

4. Tianjin University,Key Laboratory of Smart Grid of Ministry of Education,Tianjin,China,300072

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10248366/10248210/10248451.pdf?arnumber=10248451

Reference26 articles.

1. Bi-level Heat-Electricity Energy Sharing for Integrated Energy Systems with Energy Hubs and Prosumers

2. Reliability Evaluation for Integrated Power-Gas Systems With Power-to-Gas and Gas Storages

3. Risk assessment of integrated electricity and heat system with independent energy operators based on Stackelberg game

4. Day-Ahead Energy Trading Strategy of Regional Integrated Energy System Considering Energy Cascade Utilization

5. Optimal planning of stand-alone microgrids incorporating reliability

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