Improving Energy Efficiency and Thermal Comfort of Smart Buildings with HVAC Systems in the Presence of Sensor Faults
Yazarlar (3)
Öğr. Gör. Volkan GÜNEŞ
Samueli School Of Engineering, Amerika Birleşik Devletleri
Samueli School Of Engineering, Amerika Birleşik Devletleri
Samueli School Of Engineering, Amerika Birleşik Devletleri
| Bildiri Türü | Tebliğ/Bildiri |
| Bildiri Alt Türü | Tam Metin Olarak Yayınlanan Tebliğ (Uluslararası Kongre/Sempozyum) |
| Bildiri Niteliği | Web of Science Kapsamındaki Kongre/Sempozyum |
| DOI Numarası | 10.1109/HPCC-CSS-ICESS.2015.154 |
| Bildiri Dili | İngilizce |
| Kongre Adı | 12th IEEE International Conference on Embedded Software and Systems (ICESS) |
| Kongre Tarihi | 24-08-2015 / 26-08-2015 |
| Basıldığı Ülke | Amerika Birleşik Devletleri |
| Basıldığı Şehir | New York |
| Bildiri Linki | https://doi.org/10.1109/HPCC-CSS-ICESS.2015.154 |
| Özet |
| The smart building, as an application of the cyber-physical systems (CPSs), plays an important role in everyday lives of people. Thermal comfort and energy efficiency are primary goals for HVAC systems in smart buildings. Since the controllers of the HVACs heavily rely on data of sensors that are deployed in the buildings, temporary or permanent sensor faults may lead to increased energy consumption or decreased thermal comfort far below expectations. In this paper, we examine sensor data faults observed in the real-world sensor deployments, and their effects on thermal comfort and energy efficiency in multi-room buildings. The read-back and nearest neighbor monitoring approaches are proposed considering temporal and spatial correlations between data of sensors to mitigate the faults of interest. We adopt a model-based design methodology for the multi-room building as a CPS application and develop reusable system models in the MATLAB/Simulink environment. We conclude that the aforementioned faults may significantly reduce energy efficiency and thermal comfort unless mitigated. The proposed approaches improved thermal comfort by up to 75% for the room where the faulty sensor was deployed and reduced total energy consumption by up to 38%. |
| Anahtar Kelimeler |
| Atmospheric modeling | Heating | Mathematical model | Semantics | Smart buildings | Temperature sensors |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| WoS | 16 |
| SCOPUS | 20 |
| Google Scholar | 26 |