Ziyuan Wang, Dain Yap Liffman, et al.
CIKM 2018
Industrial buildings are demonstrating increasing rates of energy consumption, with heating, ventilation, and air conditioning (HVAC) typically constituting over 50% of this consumption. However, these energy requirements are heavily influenced by weather conditions based on the season, the time of day, and different in-building activities. These activities take place in industrial setup over 24 h and have different HVAC energy requirements. In this paper, we propose a binary (0,1) integer linear programming approach to efficiently schedule activities based on weather forecasting, thus minimizing the energy required by HVAC. Experimental results show that energy consumption can be reduced by up to 30%.
Ziyuan Wang, Dain Yap Liffman, et al.
CIKM 2018
Hoang Tam Vo, Ziyuan Wang, et al.
iThings/GreenCom/CPSCom/SmartData/Blockchain/CIT 2018
Kashif Hesham Khan, Caspar Ryan, et al.
IEEE Access
Wei Emma Zhang, Ermyas Abebe, et al.
ISWC-Posters-Demos-Industry 2016