Energy optimization for HVAC systems in multi-VAV open offices: A deep reinforcement learning approach

Hao Wang, Xiwen Chen, Natan Vital, Edward Duffy and Abolfazl Razi

Applied Energy, 2024, vol. 356, issue C, No S030626192301718X

Abstract: With global warming intensifying and resource conflicts escalating, the world is undergoing a transformative shift toward sustainable practices and energy-efficient solutions. With more than 32% of the global energy used by commercial and residential buildings, there is an urgent need to revisit traditional approaches to Building Energy Management (BEM). Within a BEMSplatform, regulating the operation of Heating, Ventilation, and Air Conditioning (HVAC) systems is more important, noting that HVAC systems account for about 40% of the total energy cost in the commercial sector.

Keywords: Smart buildings; Building energy management; Energy simulation; Energy optimization; Open-plan office; Deep reinforcement learning; HVAC system (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (4)

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DOI: 10.1016/j.apenergy.2023.122354

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