Petri, Ioan ORCID: https://orcid.org/0000-0002-1625-8247, Rana, Omer ORCID: https://orcid.org/0000-0003-3597-2646, Rezgui, Yacine ORCID: https://orcid.org/0000-0002-5711-8400 and Fadli, Fodil 2021. Edge HVAC analytics. Energies 14 (17) , 5464. 10.3390/en14175464 |
PDF
- Published Version
Available under License Creative Commons Attribution. Download (398kB) |
Abstract
Integrating data analytics, optimisation and dynamic control to support energy services has seen significant interest in recent years. Larger appliances used in an industry context are now provided with Internet of Things (IoT)-based interfaces that can be remotely monitored, with some also provided with actuation interfaces. The combined use of IoT and edge computing enables connectivity between energy systems and infrastructure, providing the means to implement both energy efficiency/optimisation and cost reduction strategies. We investigate the economic implications of harnessing IoT and edge/cloud technologies to support energy management for HVAC (Heating, Ventilation and Air Conditioning) systems in buildings. In particular, we evaluate the cost savings for building operations through energy optimisation. We use a real use case for energy optimisation as identified in the EU “Sporte2” project (focusing on the energy optimisation of sports facilities) and explore several scenarios in relation to costs and energy optimisation.
Item Type: | Article |
---|---|
Date Type: | Publication |
Status: | Published |
Schools: | Engineering |
Additional Information: | This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
Publisher: | MDPI |
ISSN: | 1996-1073 |
Funders: | Sporte.3Q NPRP grant No. NPRP12S-0222-190128 from the Qatar National Research Fund (a member of Qatar Foundation) |
Related URLs: | |
Date of First Compliant Deposit: | 2 September 2021 |
Date of Acceptance: | 24 August 2021 |
Last Modified: | 03 May 2023 11:28 |
URI: | https://orca.cardiff.ac.uk/id/eprint/143830 |
Citation Data
Cited 3 times in Scopus. View in Scopus. Powered By Scopus® Data
Actions (repository staff only)
Edit Item |