A scalable platform for investigating the space-specific features of the temporal energy usage pattern and saving potential with real-time bigdata. (10th September 2021)

• Record Type: Journal Article
• Authors: Lee, Junsoo; Kim, Tae Wan; Lee, Chansik; Koo, Choongwan
• Is Part Of: Journal of cleaner production. Volume 314(2021)
• Publication Date: 2021-09-10
• Subjects: IoT-based smart energy meter -- Real-time bigdata -- Scalable analysis -- Energy usage pattern -- Energy saving potential -- Economic feasibility.; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2021.128028
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: The Korean government has initiated a "Green New Deal" policy, in which a smart energy platform was proposed for more efficient building energy management that could monitor energy consumption in real time and control electrical installation and appliance in a timely manner. With the energy bigdata collected via IoT-based smart energy meter, this study aimed to develop a scalable platform for investigating the space-specific features of the temporal energy usage pattern and the relevant energy saving potential by electrical installation (i.e., lighting, electrical appliances, heating & cooling systems) in a building. This study was conducted in four stages: (i) real-time bigdata collection; (ii) development of dashboard; (iii) scalable analysis of energy usage pattern; and (iv) scalable analysis of energy saving potential. Main finding can be summarized as follow. First, more than 50% of the energy usage in main spaces (i.e., classrooms) was consumed by the heating & cooling systems. Second, the total energy saving potential was estimated at 11.50% when applying the developed actuator to the standby power and electrical radiator. Third, the annual cost saving potential as economic feasibility was estimated at 11.13%. The proposed scalable platform can contribute to investigating the energy usage pattern by electrical installation from a spatio-temporal perspective and to changing the occupants' behaviors for energy savings by considering space-specific features and occupancy patterns. The proposed novel approach can be extended to various types of buildings. Highlights: A scalable platform was developed with real-time bigdata via IoT-based smart meter. The space-specific features of the temporal energy usage pattern was investigated. The energy saving potential by electrical installation and appliance was analyzed. Energy saving potential was estimated at 11.50% by blocking the standby power. It is expected to change occupants' behaviors for energy efficiency improvement.