Advances of machine learning in multi-energy district communities‒ mechanisms, applications and perspectives-Reference-Cited by-同舟云学术

Advances of machine learning in multi-energy district communities‒ mechanisms, applications and perspectives

Published:2022-11 Issue: Volume:10 Page:100187
ISSN:2666-5468
Container-title:Energy and AI
language:en
Short-container-title:Energy and AI

Author:

Zhou Yuekuan

Publisher

Elsevier BV

Subject

Artificial Intelligence,General Energy,Engineering (miscellaneous)

Reference208 articles.

1. Low-carbon transition in smart city with sustainable airport energy ecosystems and hydrogen-based renewable-grid-storage-flexibility;Zhou;Energy Rev,2022

2. Transition towards carbon-neutral districts based on storage techniques and spatiotemporal energy sharing with electrification and hydrogenation;Zhou;Renew Sustain Energy Rev,2022

3. Y Zhou, S Zheng. Machine-learning based hybrid demand-side controller for high-rise office buildings with high energy flexibilities Appl Energy 2020. 10.1016/j.apenergy.2019.114416.

4. Machine-learning based study on the on-site renewable electrical performance of an optimal hybrid PCMs integrated renewable system with high-level parameters’ uncertainties;Zhou;Renew Energy,2020

5. Uncertainty study on thermal and energy performances of a deterministic parameters based optimal aerogel glazing system using machine-learning method;Zhou;Energy,2020

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