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Designing residential energy systems considering prospective costs and life cycle GHG emissions

Author

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  • Terlouw, Tom
  • AlSkaif, Tarek
  • Bauer, Christian
  • Mazzotti, Marco
  • McKenna, Russell

Abstract

Novel energy technologies are typically associated with large investments and environmental impacts generated in the construction phase. In this work, we present a systematic approach to optimally design residential energy systems, considering (prospective) costs and life cycle greenhouse gas (GHG) emissions of a large set of low-carbon energy technologies and sources. To achieve this, an optimization problem has been formulated and is tested on several scenarios considering climate-specific heat and electricity demand as well as scenario-specific conditions, such as the flexibility of grid electricity tariffs and associated GHG intensities. With GHG-intensive grid electricity supply and flexible energy tariffs, we recommend to implement policy measures to encourage the investment in residential solar PV-coupled batteries and heat pumps, especially in the near future. The inclusion of environmental impacts generated from the production of energy technologies cannot be neglected; they should be considered during the design phase of residential energy systems. Current high electricity and natural gas prices result in the installation of low-carbon energy system components. This implies that battery systems are already an effective option to reduce the reliance on carbon-intensive and expensive energy supply. And lastly, the large-scale deployment of residential lithium-ion batteries might be limited by global lithium production. This implies that energy system designers should consider alternative electricity storage technologies in their energy technology portfolio.

Suggested Citation

  • Terlouw, Tom & AlSkaif, Tarek & Bauer, Christian & Mazzotti, Marco & McKenna, Russell, 2023. "Designing residential energy systems considering prospective costs and life cycle GHG emissions," Applied Energy, Elsevier, vol. 331(C).
    • Handle: RePEc:eee:appene:v:331:y:2023:i:c:s0306261922016191
    DOI: 10.1016/j.apenergy.2022.120362
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    References listed on IDEAS

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    1. Matthias Ehrgott, 2005. "Multicriteria Optimization," Springer Books, Springer, edition 0, number 978-3-540-27659-3, June.
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    1. Zhou, Yuan & Wang, Jiangjiang & Yang, Mingxu & Xu, Hangwei, 2023. "Hybrid active and passive strategies for chance-constrained bilevel scheduling of community multi-energy system considering demand-side management and consumer psychology," Applied Energy, Elsevier, vol. 349(C).

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