Share

Recommended by the IIR

Investigation of model predictive control for fifth generation district heating and cooling (5GDHC) substations.

Number: No 281

Author(s) : BUFFA S., SOPPELSA A., PIPICIELLO M., HENZE G. P., FEDRIZZI R.

Summary

This work investigates the performance of a model predictive controller for customer-sited energy transfer substations, installed in fifth generation district heating and cooling networks (5GDHC) that include electrically driven heat pumps and thermal energy storage systems. Using heat pumps effectively couples the thermal and electrical distribution networks at the individual building level, which opens the door to new scenarios in terms of smart management of urban energy systems. The model predictive controller (MPC) implemented includes two key elements based on artificial intelligence: a composite model of the 5GDHC substation based on several artificial neural networks (ANN) and a constrained optimization solver based on particle swarm optimization (PSO). This study focuses on the analysis performed to test the predictive controller and to un-derstand how it affects the substation energy performance and the building owner’s energy bill under different boundary conditions. Moreover, the capacity of the MPC in providing demand flexibility to the power grid has been evaluated through a load shifting strategy obtainedby exploiting the capacity of the substation’s thermal energy storage.

Available documents

Format PDF

Pages: 11 p.

Available

Free

Download

Details

  • Original title: Investigation of model predictive control for fifth generation district heating and cooling (5GDHC) substations.
  • Record ID : 30030078
  • Languages: English
  • Subject: Technology
  • Source: 13th IEA Heat Pump Conference 2021: Heat Pumps – Mission for the Green World. Conference proceedings [full papers]
  • Publication date: 2021/08/31

Links


See other articles from the proceedings (198)
See the conference proceedings

Indexing