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Mixed-integer nonlinear optimization for district heating network expansion

Mixed-integer nonlinear optimization for district heating network expansion AbstractWe present a mixed-integer nonlinear optimization model for computing the optimal expansion of an existing tree-shaped district heating network given a number of potential new consumers. To this end, we state a stationary and nonlinear model of all hydraulic and thermal effects in the pipeline network as well as nonlinear models for consumers and the network’s depot. For the former, we consider the Euler momentum and the thermal energy equation. The thermal aspects are especially challenging. Here, we develop a novel polynomial approximation that we use in the optimization model. The expansion decisions are modeled by binary variables for which we derive additional valid inequalities that greatly help to solve the highly challenging problem. Finally, we present a case study in which we identify three major aspects that strongly influence investment decisions: the estimated average power demand of potentially new consumers, the distance between the existing network and the new consumers, and thermal losses in the network. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png at - Automatisierungstechnik de Gruyter

Mixed-integer nonlinear optimization for district heating network expansion

Roland, Marius; Schmidt, Martin
at - Automatisierungstechnik , Volume 68 (12): 16 – Nov 18, 2020
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Publisher
de Gruyter
Copyright
© 2020 Walter de Gruyter GmbH, Berlin/Boston
ISSN
2196-677X
eISSN
2196-677X
DOI
10.1515/auto-2020-0063
Publisher site
See Article on Publisher Site

Abstract

AbstractWe present a mixed-integer nonlinear optimization model for computing the optimal expansion of an existing tree-shaped district heating network given a number of potential new consumers. To this end, we state a stationary and nonlinear model of all hydraulic and thermal effects in the pipeline network as well as nonlinear models for consumers and the network’s depot. For the former, we consider the Euler momentum and the thermal energy equation. The thermal aspects are especially challenging. Here, we develop a novel polynomial approximation that we use in the optimization model. The expansion decisions are modeled by binary variables for which we derive additional valid inequalities that greatly help to solve the highly challenging problem. Finally, we present a case study in which we identify three major aspects that strongly influence investment decisions: the estimated average power demand of potentially new consumers, the distance between the existing network and the new consumers, and thermal losses in the network.

Journal

at - Automatisierungstechnik – de Gruyter

Published: Nov 18, 2020

References

  • An optimization approach for district heating strategic network design
  • Bottom-up and top-down heat demand mapping methods for small municipalities, case Gllogoc
  • High detail stationary optimization models for gas networks
  • Distributed energy resource system optimisation using mixed integer linear programming
  • A MINLP optimization of the configuration and the design of a district heating network: study case on an existing site
  • Optimisation of structure and operation of district cooling networks in urban regions