Optimization of district heating production with thermal storage using mixed-integer nonlinear programming with a new initialization approach

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Abstract

Non-convex scheduling of energy production allows for more complex models that better describe the physical nature of the energy production system. Solutions to non-convex optimization problems can only be guaranteed to be local optima. For this reason, there is a need for methodologies that consistently provide low-cost solutions to the non-convex optimal scheduling problem. In this study, a novel Monte Carlo Tree Search initialization method for branch and bound solvers is proposed for the production planning of a combined heat and power unit with thermal heat storage in a district heating system. The optimization problem is formulated as a non-convex mixed-integer program, which is incorporated in a sliding time window framework. Here, the proposed initialization method offers lower-cost production planning compared to random initialization for larger time windows. For the test case, the proposed method lowers the yearly operational cost by more than 2,000,000 DKK per year. The method is one step in the direction of more reliable non-convex optimization that allows for more complex models of energy systems.
Original languageEnglish
Article number34
JournalEnergy Informatics
Volume4
Issue numberSuppl. 2
ISSN2520-8942
DOIs
Publication statusPublished - 24. Sep 2021
Event1st Energy Informatics.Academy Conference Asia - Sino-Danish Center Sustainable Energy, Beijing, China
Duration: 29. May 202130. May 2021
Conference number: 1
https://www.energyinformatics.academy/eia-asia-2021-conference

Conference

Conference1st Energy Informatics.Academy Conference Asia
Number1
LocationSino-Danish Center Sustainable Energy
Country/TerritoryChina
CityBeijing
Period29/05/202130/05/2021
Internet address

Keywords

  • Mixed integer non-linear optimization
  • MINLP
  • District heating Scheduling
  • Modeling
  • Tree Search
  • Initialization
  • Non-convex optimization

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