Machine learning-based digital district heating/cooling with renewable integrations and advanced low-carbon transition

Y Zhou, S Zheng, JLM Hensen - Renewable and Sustainable Energy …, 2024 - Elsevier
Intermittent power production with hybrid storages, dynamic grids' interactions for synergistic
complementation, advanced energy management, optimal design and robust operation are …

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

Y Zhou - Energy and AI, 2022 - Elsevier
Energy paradigm transition towards the carbon neutrality requires combined and continuous
efforts in cleaner power production, advanced energy storages, flexible district energy …

Performance prediction, optimal design and operational control of thermal energy storage using artificial intelligence methods

Z He, W Guo, P Zhang - Renewable and Sustainable Energy Reviews, 2022 - Elsevier
Capable of storing and redistributing energy, thermal energy storage (TES) shows a
promising applicability in energy systems. Recently, artificial intelligence (AI) technique is …

A model predictive control strategy to optimize the performance of radiant floor heating and cooling systems in office buildings

J Joe, P Karava - Applied Energy, 2019 - Elsevier
This paper introduces a smart operation strategy based on model predictive control (MPC) to
optimize the performance of hydronic radiant floor systems in office buildings and presents …

Integration of an energy management tool and digital twin for coordination and control of multi-vector smart energy systems

E O'Dwyer, I Pan, R Charlesworth, S Butler… - Sustainable Cities and …, 2020 - Elsevier
Abstract As Internet of Things (IoT) technologies enable greater communication between
energy assets in smart cities, the operational coordination of various energy networks in a …

A hybrid deep learning-based method for short-term building energy load prediction combined with an interpretation process

C Zhang, J Li, Y Zhao, T Li, Q Chen, X Zhang - Energy and Buildings, 2020 - Elsevier
Data driven-based building energy load prediction is of great value for building energy
management tasks such as fault diagnosis and optimal control. However, there are two …

A data-driven rolling optimization control approach for building energy systems that integrate virtual energy storage systems

Y Mu, Y Xu, J Zhang, Z Wu, H Jia, X **, Y Qi - Applied Energy, 2023 - Elsevier
The virtual energy storage system (VESS) is an innovative and cost-effective technique for
coupling building envelope thermal storage and release abilities with the electric and heat …