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

ISCSIC '18 [online] : Proceedings of the 2nd International Symposium on Computer Science and Intelligent Control. ACM International Conference Proceeding Series 2018
Nikolajs Bogdanovs, Aleksandrs Ipatovs, Romualds Beļinskis, Viktors Jeralovičs, Andris Krūmiņš, Viktors Afoņičevs

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.

Keywords
Building management systemEnergy saving HVAC Weather forecast
DOI
10.1145/3284557.3284720
Hyperlink
https://dl.acm.org/citation.cfm?doid=3284557.3284720

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

Publication language
English (en)