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...

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Detalhes bibliográficos
Autores: Savadkoohi, Marjan|||0000-0002-3707-2601, Macarulla Martí, Marcel|||0000-0002-5469-7291, Tejedor Herrán, Blanca|||0000-0002-2064-0617, Casals Casanova, Miquel|||0000-0001-5379-894X
Tipo de documento: artigo
Data de publicação:2024
País:España
Recursos:Universitat Politècnica de Catalunya (UPC)
Repositório:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglês
OAI Identifier:oai:upcommons.upc.edu:2117/413929
Acesso em linha:https://hdl.handle.net/2117/413929
https://dx.doi.org/10.1007/s12053-024-10249-2
Access Level:Acceso aberto
Palavra-chave: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
Descrição
Resumo: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.