Virtual Cooling Control: Efficiency increase of refrigeration and cooling systems with intelligent control systems based on virtual data
Abstract
Energy consumption of cooling systems in Austria is estimated to account for approximately 10 to 14% of the total electrical energy use in the sectors ‘services’ and ‘material goods production’. Due to non-invasive, optimized control measures this cooling energy demand could be reduced effectively by up to 40%. The main goal of the research project ViCC is therefore to increase the energy efficiency of compression chiller based systems by means of coupling the BACS (Building Automation and Control System) with innovative control strategies through a holistic and systemic approach. ViCC deals with the question of how to generate virtual data/control points and implement them in an overall control strategy of specific cooling systems. A cooling system’s complexity lies within the coupling and control of multiple components and sub-systems, each of it frequently needing its own control strategy. The optimum in energy consumption, and therefore the goal of all intelligent overall cooling control strategies, lies within the optimized integration of all units and sub-systems’ controls in an efficient overall control algorithm. Basically, effectiveness of all control strategies in a cooling system has to be increased, mainly in part load operation, either through adaptation of temperature (hubs) and/or mass flows. Experience from real operations indicates, that neither temperature values nor important fluid mass flows are being varied significantly, thus producing low system efficiencies of compression chiller based cooling systems in part load operation. Literature review as well as calculations based on monitoring and analyses of cooling systems’ operational data suggest, that by implementing an optimized overall control algorithm based on the results gained from the ViCC project, the system’s overall energy efficiency can be increased by 25 %, leading to CO2-emission reductions of 25.885 t/a. Additionally, the integration of detailed operational data into the visual BACS leads to new possibilities concerning automated fault detection and predicted maintenance. Thus, reduction of operational-, service- and maintenance costs is achieved. The ‘control solution’ gained within the ViCC project is being experimentally validated and evaluated in terms of a preparation for a commercial launch. Further needed subsequent R&D actions are being automatically investigated and determined.
Publikationen
Project staff
Magdalena Wolf
Dipl.-Ing. Dr. Magdalena Wolf Bakk.techn.
magdalena.wolf@boku.ac.at
Tel: +43 1 47654-89315
BOKU Project Leader
01.10.2018 - 30.09.2022
Thomas Keller
Dipl.-Ing. Thomas Keller
thomas.keller@boku.ac.at
Tel: +43 1 47654-89314
Project Staff
01.10.2018 - 30.09.2022
Jan Kotik
Dipl.-Ing. Dr. Jan Kotik
jan.kotik@boku.ac.at
Tel: +43 1 47654-89312
Project Staff
01.10.2018 - 30.09.2022
Thomas Märzinger
Dipl.-Ing. Thomas Märzinger
thomas.maerzinger@boku.ac.at
Project Staff
01.10.2018 - 19.04.2021
Tobias Pröll
Univ.Prof. Dipl.-Ing. Dr.techn. Tobias Pröll
tobias.proell@boku.ac.at
Tel: +43 1 47654-89311
Project Staff
01.10.2018 - 30.09.2022