Aktuelle Forschungsprojekte

Image Testing of mobile leak detectors according to DIN EN 14624
Image Reducing the filling quantity
Image Development of test methods and test rigs for stationary integrated refrigeration units
Image Swirl-free on the move...
Image Testzentrum PLWP at ILK Dresden
Image Performance tests of refrigerant compressors
Image Low noise and non metallic liquid-helium cryostat
Image Test rigs for refrigeration and heat pump technology
Image Innovative cryogenic cooling system for the recondensation / liquefaction of technical gases up to 77 K
Image Software for technical building equipment
Image Calibration of Low Temperature Sensors
Image Computational fluid dynamics CFD
Image Multifunctional electronic modules for cryogenic applications
Image Electrochemical decontamination of electrically conducting surfaces „EDeKo II“
Image Non- invasive flow measurements
Image Characterisation of Superconductors in Hydrogen Atmosphere

You are here:  Home /  Research and Development


Optimizing HVAC operation with machine learning

BMWi Euronorm Innokom

01/2019–05/2021

Dr.-Ing. Thomas Oppelt

+49-351-4081-5321

in progress

Intelligent control of HVAC systems – high comfort with low energy demand

Motivation

During operation, the energy efficiency of many HVAC systems remains considerably below the value predicted when planning. One reason is that especially complex systems with multiple generators, storages and consumer locations frequently are not operated optimally.

Aim of the project

Development of a tool for optimizing the operation of HVAC systems which uses machine learning (ML) methods and data from the digital building model (Building Information Model, BIM):

  • Optimization goal: high energy efficiency with at the same time high comfort for users

  • Saving operating costs, energy and carbon dioxide emissions due to increased efficiency

  • Continuous autonomous improvement of the ML algorithm by learning from new measured data with auto-adaptive reaction to changing conditions (building, system, use, smart meter for real time billing of energy and media, etc.)

Approach

  • Reproduction of the real system’s thermal-energetic behaviour in the machine learning system, training with BIM data, measured data and a digital twin of the real system
  • Application of ML methods for load forecasting (weather, usage patterns)

  • Automatic classification of utilisation scenarios, fault detection

  • Integration of available tools for efficient simulation of indoor air flows and for calculating energy demands

  • Co-Validation of optimization tool, experimental studies and digital twin

Interested?

Please get in touch with us if you are interested in a cooperation: klima@ilkdresden.de

 


Your Request

Further Projects - Research and Development

Image

Brine (water)-water heat pump

Test according DIN EN 14511 and 14825

Image

Air-water heat pumps

Test according DIN EN 14511 and 14825

Image

High temperature heat pump

Using waste heat from industrial processes

Image

Micro heat exchangers in refrigeration

3D-printing of micro heat exchangers

Image

Electrochemical decontamination of electrically conducting surfaces „EDeKo II“

Improvement of sanitary prevention by electrochemical decontamination