Identification of a dynamic system model for a building and heating system including heat pump and thermal energy storage

Christian Finck*, Rongling Li, Wim Zeiler

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

Controllers employing optimal control strategies will path the way to enable flexible operations in future power grids. As buildings will increasingly act as prosumers in future power grids, optimal control of buildings’ energy consumption will play a major role in providing flexible operations. Optimal controllers such as model predictive controller are able to manage buildings’ operations and to optimize their energy consumption. For online optimization, model predictive controller require a model of the energy system. The more accurate the system model represents the system dynamics, the more accurate the model predictive controller predicts the future states of the energy system while optimizing its energy consumption. In this article, we present a system model that can be used in online MPC, including dynamic programming as optimization strategy. The system model is validated using a building and heating system, including heat pump and thermal energy storage.

The following bullet points summarize the main requirements for the configuration of the system model:

• The system model performs fast with low computational effort in less than 1s

• The system model can be implemented in online MPC

• The system model accurately represents the dynamic behaviour
Original languageEnglish
Article number100866
JournalMethodsX
Volume7
Number of pages12
DOIs
Publication statusPublished - 2020

Keywords

  • Optimal control
  • Model predictive control
  • ANN
  • Black box modelling
  • Grey box modelling

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