A multi-objective scheduling method for hybrid integrated energy systems via Q-learning-based multi-population dung beetle optimizers-Reference-Cited by-同舟云学术

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A multi-objective scheduling method for hybrid integrated energy systems via Q-learning-based multi-population dung beetle optimizers

Published:2024-07 Issue: Volume:117 Page:109223
ISSN:0045-7906
Container-title:Computers and Electrical Engineering
language:en
Short-container-title:Computers and Electrical Engineering

Author:

Tu Naiwei,Fan Zuhao^ORCID,Pang Xinfu^ORCID,Yan Xin,Wang Yibao,Liu Yucheng,Yang Dong

Publisher

Elsevier BV

Reference57 articles.

1. Strategies to save energy in the context of the energy crisis: a review;Farghali;Environ Chem Lett,2023

2. Next frontiers in energy system modelling: A review on challenges and the state of the art;Fodstad;Renew Sustain Energy Rev,2022

3. Compressed air energy storage in integrated energy systems: A review;Bazdar;Renew Sustain Energy Rev,2022

4. Application of energy storage in integrated energy systems—A solution to fluctuation and uncertainty of renewable energy;Wang;J Energy Storage,2022

5. Thermodynamic analysis of a CCHP system integrated with a regenerative organic flash cycle;Ai;Appl Therm Eng,2022

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