This paper describes the results of a pilot energy efficiency application, which is a part of the European project Esmartcity. The pilot refers to a real building of Politecnico di Milano composed of 14 classrooms over 4 floors. A quite complex centralized thermal network composed of different delivery devices (fan coils and radiators) and generation devices (water-to-water and air-to-water heat pumps, air handling unit with heat recovery) is used to control each room temperature, humidity and CO2 levels. In spite of its complexity, the overall system is unable to sufficiently compensate disturbances, which are mainly due to people occupancy. The installation of smart multi sensors in a mesh network over the building allows data collection sufficient to build realistic physical models, design innovative and non-intrusive control strategies for disturbance compensations, and evaluate performance. In particular, the paper designs and compares an innovative rule-based feedback-feedforward control scheme integrating and estimation of people counting algorithms and a water temperature tracking algorithm based on a short recirculation circuit. Results show energy efficiency enforcement of about 12.6% and 10.7% respectively, without the need of structural retrofitting of the building and with a small, though measureable, comfort increase.

Digital Techniques for Energy Optimization in a University Building: A case study

Ferrarini L.;Babini R.
2020-01-01

Abstract

This paper describes the results of a pilot energy efficiency application, which is a part of the European project Esmartcity. The pilot refers to a real building of Politecnico di Milano composed of 14 classrooms over 4 floors. A quite complex centralized thermal network composed of different delivery devices (fan coils and radiators) and generation devices (water-to-water and air-to-water heat pumps, air handling unit with heat recovery) is used to control each room temperature, humidity and CO2 levels. In spite of its complexity, the overall system is unable to sufficiently compensate disturbances, which are mainly due to people occupancy. The installation of smart multi sensors in a mesh network over the building allows data collection sufficient to build realistic physical models, design innovative and non-intrusive control strategies for disturbance compensations, and evaluate performance. In particular, the paper designs and compares an innovative rule-based feedback-feedforward control scheme integrating and estimation of people counting algorithms and a water temperature tracking algorithm based on a short recirculation circuit. Results show energy efficiency enforcement of about 12.6% and 10.7% respectively, without the need of structural retrofitting of the building and with a small, though measureable, comfort increase.
2020
IEEE International Conference on Emerging Technologies and Factory Automation, ETFA
978-1-7281-8956-7
building energy efficiency
CO2 control
multi-sensor network
temperature control
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1149677
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