Analyzing the implementation of predictive control systems and application of stored data in non-residential buildings
In non-residential buildings, building energy management systems (BEMS) and the application of data hold significant promise in reducing energy consumption. Nevertheless, BEMS have different levels of complexity, benefit, and limitation. Despite the advanced technologies and improvements in building...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/413929 |
| Acceso en línea: | https://hdl.handle.net/2117/413929 https://dx.doi.org/10.1007/s12053-024-10249-2 |
| Access Level: | acceso abierto |
| Palabra clave: | Energy conservation Architecture and energy conservation Building energy management system Energy efficiency Control system Data storage Non-residential buildings Energia--Estalvi Arquitectura i estalvi d'energia Àrees temàtiques de la UPC::Energies Àrees temàtiques de la UPC::Edificació |
| Sumario: | In non-residential buildings, building energy management systems (BEMS) and the application of data hold significant promise in reducing energy consumption. Nevertheless, BEMS have different levels of complexity, benefit, and limitation. Despite the advanced technologies and improvements in building operation, there is a clear gap in the actual performance of buildings that has been attributed to the adoption of advanced technologies. Consequently, there is an increasing need for researchers and practitioners to study current practices in order to identify and address the challenges that compromise the core objectives of BEMS. For this reason, this paper aims to validate three research questions: (i) to examine the current state of BEMS and its functionalities; (ii) to analyze the type of control used; (iii) and to determine the availability of historical data compiled by BEMS and its application in non-residential buildings. A survey of 676 buildings and interviews with building professionals were conducted. The findings confirmed that most of the buildings applied BEMS with scheduled control. In addition, a lack of digitized data for analysis and predictions was detected. Indeed, only 0.60% of the investigated buildings implemented predictive control. Finally, using hierarchical clustering analysis, responses were grouped to analyze similarities between them. The study findings help to develop targeted actions for implementing predictive control in non-residential buildings. |
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