Article

Data-driven planning of distributed energy resources amidst socio-technical complexities

  • Nature Energy 2, Article number: 17112 (2017)
  • doi:10.1038/nenergy.2017.112
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Abstract

New distributed energy resources (DER) are rapidly replacing centralized power generation due to their environmental, economic and resiliency benefits. Previous analyses of DER systems have been limited in their ability to account for socio-technical complexities, such as intermittent supply, heterogeneous demand and balance-of-system cost dynamics. Here we develop ReMatch, an interdisciplinary modelling framework, spanning engineering, consumer behaviour and data science, and apply it to 10,000 consumers in California, USA. Our results show that deploying DER would yield nearly a 50% reduction in the levelized cost of electricity (LCOE) over the status quo even after accounting for socio-technical complexities. We abstract a detailed matching of consumers to DER infrastructure from our results and discuss how this matching can facilitate the development of smart and targeted renewable energy policies, programmes and incentives. Our findings point to the large-scale economic and technical feasibility of DER and underscore the pertinent role DER can play in achieving sustainable energy goals.

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Acknowledgements

This material is based upon the work supported in part by the Stanford Precourt Institute for Energy, a Terman Faculty Fellowship (R.K.J.), a Powell Foundation Fellowship (R.R.) and the US National Science Foundation under a SEES Fellows award (1461549) and a CAREER award (1554178). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

Author information

Affiliations

  1. Department of Civil & Environmental Engineering, Jerry Yang and Akiko Yamazaki Environment and Energy Building (Y2E2), Room 269A, 473 Via Ortega, Stanford, California 94305, USA

    • Rishee K. Jain
  2. Institute for Computational and Mathematical Engineering, Jerry Yang and Akiko Yamazaki Environment and Energy Building (Y2E2), Room 268, 473 Via Ortega, Stanford, California 94305, USA

    • Junjie Qin
  3. Department of Civil & Environmental Engineering, Department of Electrical Engineering, Jerry Yang and Akiko Yamazaki Environment and Energy Building (Y2E2), Room 295, 473 Via Ortega, Stanford, California 94305, USA

    • Ram Rajagopal

Authors

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Contributions

R.K.J., J.Q. and R.R. conceived and designed the research and modelling framework. R.K.J. and J.Q. implemented the framework and analysed the results. R.K.J., J.Q. and R.R. prepared the manuscript. R.R. provided institutional and material support for the research.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Rishee K. Jain or Ram Rajagopal.

Supplementary information

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    Supplementary Information

    Supplementary Notes 1–2, Supplementary Figures 1–5, Supplementary Tables 1–7 and Supplementary References.