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Evaluation and optimization of district energy network performance: Present and future

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  • Wang, Yang
  • Zhang, Shanhong
  • Chow, David
  • Kuckelkorn, Jens M.

Abstract

The building sector accounts for the largest portion of total final energy consumption in most countries, and is responsible for around one third of carbon emissions, which have been regarded as the cause for global warming and climate changes. District energy network, which can supply consumers with heating/cooling and electricity, is an effective and proven approach to enhance energy efficiency and reduce carbon emissions. Currently, the approach of integrated energy systems (including renewable energy) tends to be increasingly necessary and significant for the district energy network. This article presents a comprehensive review of energy performance of district energy networks, focusing on optimization and evaluation of district heating network combining with other relevant energy systems and renewable technologies. This review consists of the concept of district energy network, typical applications of district energy network, and significant literatures of energy performance of various energy networks based on theoretical modelling and analysis, physical experimental studies and numerical simulations. Furthermore, over 30 factors affecting energy performance have been substantially investigated and assessed. This review has demonstrated that main effects on energy network performance are significantly linked to configurations and capacities of system, climate conditions (locations and time), and the interaction between various factors. An optimal overall performance of district energy network would need to integrate several advanced energy systems, e.g. a balanced energy network.

Suggested Citation

  • Wang, Yang & Zhang, Shanhong & Chow, David & Kuckelkorn, Jens M., 2021. "Evaluation and optimization of district energy network performance: Present and future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).
    • Handle: RePEc:eee:rensus:v:139:y:2021:i:c:s1364032120308613
    DOI: 10.1016/j.rser.2020.110577
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    5. Calise, Francesco & Cappiello, Francesco Liberato & Cimmino, Luca & Dentice d’Accadia, Massimo & Vicidomini, Maria, 2023. "A comparative thermoeconomic analysis of fourth generation and fifth generation district heating and cooling networks," Energy, Elsevier, vol. 284(C).
    6. Alabi, Tobi Michael & Aghimien, Emmanuel I. & Agbajor, Favour D. & Yang, Zaiyue & Lu, Lin & Adeoye, Adebusola R. & Gopaluni, Bhushan, 2022. "A review on the integrated optimization techniques and machine learning approaches for modeling, prediction, and decision making on integrated energy systems," Renewable Energy, Elsevier, vol. 194(C), pages 822-849.
    7. Régis Delubac & Sylvain Serra & Sabine Sochard & Jean-Michel Reneaume, 2021. "A Dynamic Optimization Tool to Size and Operate Solar Thermal District Heating Networks Production Plants," Energies, MDPI, vol. 14(23), pages 1-27, November.

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