ML4Heat - Tools for optimized operation of existing district heating networks based on machine learning methods

This thermographic image shows a district in Berlin; the district heating pipes are clearly visible. The ML4Heat project is investigating how energy distribution can be optimized at the transfer stations and throughout the district heating network.

Project goals

The global objective of the ML4Heat project is the development of methods and software tools for the optimization of the operation of existing district heating networks under energetic and economic aspects. For this purpose, sensor and operating data of the district heating transfer stations as well as the heat supply shall be collected to a large extent and evaluated by means of machine learning methods.

Project result

Tools are to be realized on three levels:

1. Optimized operation of the district heating stations through performance and condition monitoring: the aim is to achieve the most automatic possible performance monitoring and optimization of the control in the district heating stations.

2. String optimization: Methods are developed which, based on the measurement data of the district heating transfer stations, can quickly recognize or ideally already predict the utilization of sections (strings). For this purpose machine learning methods in combination with basic physical equations are used.

3. Network optimization: First of all, methods are developed to predict the energy demand for the entire district heating network more accurately than before. For this purpose, the findings on local capacity planning gained during the string optimization will be combined with external data (especially weather forecasts). Taking into account the use of renewable energy sources (e.g. solar energy), the demand for fossil fuels can be significantly reduced through more accurate real-time forecasts.

Project partners

  • Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB  (Koordination)
  • KT-Elektronik GmbH


Associated partners:

  • Vattenfall Wärme Berlin AG
  • Fernheizwerk Neukölln

Systems for Measurement, Control and Diagnosis department

The Systems for Measurement, Control and Diagnosis (MRD) department at Fraunhofer IOSB is responsible for the project..

Project profile

Project duration: July 2019 - December 2022, supervised by the Project Management Jülich

The ML4Heat project is funded by the Federal Ministry for Economic Affairs and Energy (BMWi) as part of the 7th energy research program of the federal government

Funding Number: 03ET1668

Research topic

Would you like to learn more about this topic area? Then visit the research topic page “Energy-optimized operation of buildings and district heating networks“ and find out more.