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Identification of key performance indicators and complimentary load profiles for 5th generation district energy networks

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  • Millar, Michael-Allan
  • Yu, Zhibin
  • Burnside, Neil
  • Jones, Greg
  • Elrick, Bruce

Abstract

Mass adoption of renewable heating is essential for achieving Net Zero 2050 emission targets. Rapid decarbonisation of heating could be delivered by 5th generation district heating networks, which share heating and cooling and offer energy, cost and carbon savings. We present an assessment framework for determining the economic, operational, and carbon benefits of heat pump driven energy sharing networks for an urban centre. Our analysis of complementary heating and cooling loads enabled novel identification of the building types which are best suited to thermal energy sharing. An urban street was modelled using Integrated Energy System Virtual Environment software, which produced heating, cooling, and hot water loads. These were implemented into a linear programming cost and carbon optimisation problem, producing operating curves for a pool of de-localised heat pumps under either cost or emission minimalization scenarios. Results show that energy sharing networks may reduce the Levelised Cost of Energy by 69% and carbon emissions by 13% when compared to an electrified non-shared energy system. Based on these findings, a load matrix was constructed to identify which energy loads from different building types can be suitably used for energy sharing. Despite promising cost-savings results, we conclude that low temperature district heating networks have much greater financial benefit when utilising appropriately sized thermal storage and time of use tariffs, rather than energy sharing. However, carbon savings can be made over alternatives, such as natural gas boilers. For developers undertaking a heat network project, the primary goal should be clearly defined as either carbon saving or money-making objective, as these are difficult to achieve synergistically.

Suggested Citation

  • Millar, Michael-Allan & Yu, Zhibin & Burnside, Neil & Jones, Greg & Elrick, Bruce, 2021. "Identification of key performance indicators and complimentary load profiles for 5th generation district energy networks," Applied Energy, Elsevier, vol. 291(C).
  • Handle: RePEc:eee:appene:v:291:y:2021:i:c:s0306261921002014
    DOI: 10.1016/j.apenergy.2021.116672
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    6. Abugabbara, Marwan & Javed, Saqib & Johansson, Dennis, 2022. "A simulation model for the design and analysis of district systems with simultaneous heating and cooling demands," Energy, Elsevier, vol. 261(PA).
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