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Publikācija: Impact of Intelligence System of Building Management System for Energy Efficiency in the Test Facility

Publication Type Full-text conference paper published in conference proceedings indexed in SCOPUS or WOS database
Funding for basic activity Contract research work
Defending: ,
Publication language English (en)
Title in original language Impact of Intelligence System of Building Management System for Energy Efficiency in the Test Facility
Field of research 2. Engineering and technology
Sub-field of research 2.2 Electrical engineering, Electronic engineering, Information and communication engineering
Research platform Energy and Environment
Authors Nikolajs Bogdanovs
Aleksandrs Ipatovs
Romualds Beļinskis
Viktors Jeralovičs
Andris Krūmiņš
Viktors Afoņičevs
Keywords Building management systemEnergy saving HVAC Weather forecast
Abstract Energy savings with building’s automation is related to the functionality of the system, equipment automation level, control algorithms and user-selected operating parameters. It is difficult and time-consuming process to customize each of these algorithms to a level, which would ensure the rational use of energy resources. To increase adjusting quality of the control system of building’s engineering system it is necessary to use and apply new advanced methods and technologies in buildings and control algorithms of automation system. This work presents the method of creating self-learning system, which is capable to inform about negative influence of different control algorithms. This self-learning system also provides error detection in engineering systems of the building. This system was designed in Matlab & Python programming language.
DOI: 10.1145/3284557.3284720
Hyperlink: https://dl.acm.org/citation.cfm?doid=3284557.3284720 
Reference Bogdanovs, N., Ipatovs, A., Beļinskis, R., Jeralovičs, V., Krūmiņš, A., Afoņičevs, V. Impact of Intelligence System of Building Management System for Energy Efficiency in the Test Facility. In: ISCSIC '18 [online] : Proceedings of the 2nd International Symposium on Computer Science and Intelligent Control. ACM International Conference Proceeding Series, Sweden, Stockholm, 21-23 September, 2018. New York: Association for Computing Machinery, 2018, pp.100-105. ISBN 978-145036628-1. Available from: doi:10.1145/3284557.3284720
Additional information Citation count:
  • Scopus  0
ID 28906