Equation-based modelling for dynamic optimization of district scale energy systems- A scalability study

Gerald Schweiger, Filip Jorissen, Hakan Runvik, Lieve Helsen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The optimal operation of energy systems is essential for future sustainable energy systems. While previous studies have shown the potential for equation-based modelling languages for the dynamic optimization of various systems, there is a lack of scalability studies. We investigated the scalability of two different Modelica-based tools for dynamic optimization using two use cases. The first case represents a dynamic optimization of the heating system of a multi-zone building. The second case represents a dynamic optimization of a small-scale district heating system. We show that linear scaling is possible for the tested range.

Original languageEnglish
Title of host publicationSEST 2019 - 2nd International Conference on Smart Energy Systems and Technologies
PublisherInstitute of Electrical and Electronics Engineers
ISBN (Electronic)9781728111568
DOIs
Publication statusPublished - 1 Sep 2019
Event2nd International Conference on Smart Energy Systems and Technologies, SEST 2019 - Porto, Portugal
Duration: 9 Sep 201911 Sep 2019

Publication series

NameSEST 2019 - 2nd International Conference on Smart Energy Systems and Technologies

Conference

Conference2nd International Conference on Smart Energy Systems and Technologies, SEST 2019
CountryPortugal
CityPorto
Period9/09/1911/09/19

Keywords

  • district energy system
  • dynamic optimization
  • equation-based modelling
  • scalability

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment
  • Electrical and Electronic Engineering
  • Control and Optimization

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