AI-big data analytics for building automation and management systems: a survey, actual challenges and future perspectives

Y Himeur, M Elnour, F Fadli, N Meskin, I Petri… - Artificial Intelligence …, 2023 - Springer
In theory, building automation and management systems (BAMSs) can provide all the
components and functionalities required for analyzing and operating buildings. However, in …

[HTML][HTML] An overview of machine learning applications for smart buildings

K Alanne, S Sierla - Sustainable Cities and Society, 2022 - Elsevier
The efficiency, flexibility, and resilience of building-integrated energy systems are
challenged by unpredicted changes in operational environments due to climate change and …

[HTML][HTML] Energy modelling and control of building heating and cooling systems with data-driven and hybrid models—A review

Y Balali, A Chong, A Busch, S O'Keefe - Renewable and Sustainable …, 2023 - Elsevier
Implementing an efficient control strategy for heating, ventilation, and air conditioning
(HVAC) systems can lead to improvements in both energy efficiency and thermal …

Application of machine learning in thermal comfort studies: A review of methods, performance and challenges

ZQ Fard, ZS Zomorodian, SS Korsavi - Energy and Buildings, 2022 - Elsevier
This paper provides a systematic review on the application of Machine Learning (ML) in
thermal comfort studies to highlight the latest methods and findings and provide an agenda …

[HTML][HTML] Market mechanisms for local electricity markets: A review of models, solution concepts and algorithmic techniques

G Tsaousoglou, JS Giraldo, NG Paterakis - Renewable and Sustainable …, 2022 - Elsevier
The rapidly increasing penetration of distributed energy resources (DERs) calls for a
hierarchical framework where aggregating entities handle the energy management …

Smart Home Energy Management Systems in Internet of Things networks for green cities demands and services

MS Aliero, KN Qureshi, MF Pasha, G Jeon - Environmental Technology & …, 2021 - Elsevier
Today, 44% of global energy has been derived from fossil fuel, which currently poses a
threat to inhabitants and well-being of the environment. In a recent investigation of the global …

Applications of reinforcement learning for building energy efficiency control: A review

Q Fu, Z Han, J Chen, Y Lu, H Wu, Y Wang - Journal of Building Engineering, 2022 - Elsevier
The wide variety of smart devices equipped in modern intelligent buildings and the
increasing comfort requirements of occupants for the environment make the control of …

Ten questions concerning reinforcement learning for building energy management

Z Nagy, G Henze, S Dey, J Arroyo, L Helsen… - Building and …, 2023 - Elsevier
As buildings account for approximately 40% of global energy consumption and associated
greenhouse gas emissions, their role in decarbonizing the power grid is crucial. The …

[HTML][HTML] Artificial intelligence for electricity supply chain automation

L Richter, M Lehna, S Marchand, C Scholz… - … and Sustainable Energy …, 2022 - Elsevier
Abstract The Electricity Supply Chain is a system of enabling procedures to optimize
processes ranging from production to transportation and consumption of electricity. The …

Multi-agent attention-based deep reinforcement learning for demand response in grid-responsive buildings

J **e, A Ajagekar, F You - Applied Energy, 2023 - Elsevier
Integrating renewable energy resources and deploying energy management devices offer
great opportunities to develop autonomous energy management systems in grid-responsive …