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Multi criteria dynamic design optimization of a small scale distributed energy system

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  • Rieder, Andreas
  • Christidis, Andreas
  • Tsatsaronis, George

Abstract

The aim of this paper is to analyze the mutual interdependencies and trade-offs between heat storage and district heating network considering economic and ecological aspects. Therefore, a MILP (mixed integer linear programming) problem of a distributed energy system is formulated with a weighted multi-criteria objective function including profit and operational CO2 emissions. The considered components include CHP (combined heat and power) units of three different types, a thermal storage facility, a boiler, and district heating pipelines. In a single optimization step placement, quantity and capacity of all components as well as their operation is determined. The computed designs as well as the operation of the energy system are compared under varying weightings and different technology scenarios. We also conduct a sensitivity analysis of the investment costs associated with heat storage and of the piping costs for the district heating network. The results favor the construction of heat storage devices over a district heating network. This applies to both environmental impact and cost of energy supply and can be well explained by the decoupling of heat demand and electricity production, which is shown in a correlation analysis.

Suggested Citation

  • Rieder, Andreas & Christidis, Andreas & Tsatsaronis, George, 2014. "Multi criteria dynamic design optimization of a small scale distributed energy system," Energy, Elsevier, vol. 74(C), pages 230-239.
  • Handle: RePEc:eee:energy:v:74:y:2014:i:c:p:230-239
    DOI: 10.1016/j.energy.2014.06.007
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    13. Sejkora, Christoph & Kühberger, Lisa & Radner, Fabian & Trattner, Alexander & Kienberger, Thomas, 2022. "Exergy as criteria for efficient energy systems – Maximising energy efficiency from resource to energy service, an Austrian case study," Energy, Elsevier, vol. 239(PC).
    14. Ying Zhu & Quanling Tong & Xueting Zeng & Xiaxia Yan & Yongping Li & Guohe Huang, 2019. "Optimal Design of a Distributed Energy System Using the Functional Interval Model That Allows Reduced Carbon Emissions in Guanzhong, a Rural Area of China," Sustainability, MDPI, vol. 11(7), pages 1-22, April.
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    16. Falke, Tobias & Krengel, Stefan & Meinerzhagen, Ann-Kathrin & Schnettler, Armin, 2016. "Multi-objective optimization and simulation model for the design of distributed energy systems," Applied Energy, Elsevier, vol. 184(C), pages 1508-1516.
    17. Stojiljković, Mirko M. & Ignjatović, Marko G. & Vučković, Goran D., 2015. "Greenhouse gases emission assessment in residential sector through buildings simulations and operation optimization," Energy, Elsevier, vol. 92(P3), pages 420-434.
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    19. Dorotić, Hrvoje & Pukšec, Tomislav & Duić, Neven, 2019. "Multi-objective optimization of district heating and cooling systems for a one-year time horizon," Energy, Elsevier, vol. 169(C), pages 319-328.
    20. Tan, Siah Hong & Barton, Paul I., 2015. "Optimal dynamic allocation of mobile plants to monetize associated or stranded natural gas, part I: Bakken shale play case study," Energy, Elsevier, vol. 93(P2), pages 1581-1594.
    21. Miao Li & Yiran Feng & Maojun Zhou & Hailin Mu & Longxi Li & Yajun Wang, 2019. "Economic and Environmental Optimization for Distributed Energy System Integrated with District Energy Network," Energies, MDPI, vol. 12(10), pages 1-19, May.
    22. Capone, Martina & Guelpa, Elisa & Verda, Vittorio, 2021. "Multi-objective optimization of district energy systems with demand response," Energy, Elsevier, vol. 227(C).
    23. Atabay, Dennis, 2017. "An open-source model for optimal design and operation of industrial energy systems," Energy, Elsevier, vol. 121(C), pages 803-821.
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