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Reviewing energy system modelling of decentralized energy autonomy

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  • Jann Michael Weinand
  • Fabian Scheller
  • Russell McKenna

Abstract

Research attention on decentralized autonomous energy systems has increased exponentially in the past three decades, as demonstrated by the absolute number of publications and the share of these studies in the corpus of energy system modelling literature. This paper shows the status quo and future modelling needs for research on local autonomous energy systems. A total of 359 studies are roughly investigated, of which a subset of 123 in detail. The studies are assessed with respect to the characteristics of their methodology and applications, in order to derive common trends and insights. Most case studies apply to middle-income countries and only focus on the supply of electricity in the residential sector. Furthermore, many of the studies are comparable regarding objectives and applied methods. Local energy autonomy is associated with high costs, leading to levelized costs of electricity of 0.41 $/kWh on average. By analysing the studies, many improvements for future studies could be identified: the studies lack an analysis of the impact of autonomous energy systems on surrounding energy systems. In addition, the robust design of autonomous energy systems requires higher time resolutions and extreme conditions. Future research should also develop methodologies to consider local stakeholders and their preferences for energy systems.

Suggested Citation

  • Jann Michael Weinand & Fabian Scheller & Russell McKenna, 2020. "Reviewing energy system modelling of decentralized energy autonomy," Papers 2011.05915, arXiv.org.
    • Handle: RePEc:arx:papers:2011.05915
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    1. Byrne, John & Shen, Bo & Wallace, William, 1998. "The economics of sustainable energy for rural development: A study of renewable energy in rural China," Energy Policy, Elsevier, vol. 26(1), pages 45-54, January.
    2. McKenna, R. & Bertsch, V. & Mainzer, K. & Fichtner, W., 2018. "Combining local preferences with multi-criteria decision analysis and linear optimization to develop feasible energy concepts in small communities," European Journal of Operational Research, Elsevier, vol. 268(3), pages 1092-1110.
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