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An internet of things upgrade for smart and scalable heating, ventilation and air-conditioning control in commercial buildings

Png, Ethan, Srinivasan, Seshadhri, Bekiroglu, Korkut, Chaoyang, Jiang, Su, Rong, Poolla, Kameshwar
Applied energy 2019 v.239 pp. 408-424
Internet, air conditioning, algorithms, automation, buildings, computer software, energy, energy conservation, heating systems, models, prediction, prototypes, sensation, ventilation systems, Singapore
Scalability of control algorithms used for savings energy in commercial building Heating, Ventilation and Air-Conditioning (HVAC) system and their implementation on low cost resource constrained hardware is a challenging problem. This paper presents the Internet of Things (IoT) prototype which implements a smart and scalable control approach called the Smart-Token Based Scheduling Algorithm (Smart-TBSA) to minimize energy in commercial building HVAC systems. The IoT prototype is formalized with an architecture that encapsulates the different components (hardware, software, networking, and their integration) along with their interactions. A detailed description of the different components, hardware design, deployment issues, and their integration with legacy systems as well as cloud-connectivity is presented. In addition, simple modifications required for transforming the optimization models to an active control technique is also presented. While scalability is provided by the decentralized control, recursive zone thermal model identification, prediction occupant’s thermal sensation, and embedding them within the optimization models enhances the smartness. Consequently, due to the implementation of Smart-TBSA using IoT devices, an otherwise centralized control architecture of the legacy building automation system is transformed to a more scalable and smart decentralized one. The proposed Smart-TBSA and IoT prototype are illustrated on a pilot building in Nanyang Technological University, Singapore having 85 zones. Our results shows that by combining IoT with decentralized control, energy savings up to 20% can be derived. Moreover, we show that legacy building automation system can be transformed into a more smart, adaptable, scalable, and decentralized control by deploying IoT devices without incurring significant costs.