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Applying responsible algorithm design to neighbourhood-scale batteries in Australia

Abstract

The digital energy era presents at least three systemic concerns to the design and operation of algorithms: bias of considerations towards the easily quantifiable; inhibition of explainability; and undermining of trust and inclusion, as well as energy users’ autonomy and control. Here we examine these tensions through an interdisciplinary study that reveals the diversity of possible algorithms and their accompanying material effects, focused on neighbourhood-scale batteries (NSBs) in Australia. We conducted qualitative research with energy sector professionals and citizens to understand the range of perceived benefits and risks of NSBs and the algorithms that drive their behaviour. Issues raised by stakeholders were integrated into NSB optimization algorithms whose effects on NSB owners and customers were quantified through techno-economic modelling. Our results show the allocation of benefits and risks vary considerably between different algorithm designs. This indicates a need to improve energy algorithm governance, enabling accountability and responsiveness across the design and use of algorithms so that the digitization of energy technology does not lead to adverse public outcomes.

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Fig. 1: Risks and benefits of NSB.
Fig. 2: Layout of neighbourhood energy system and neighbourhood net load.
Fig. 3: Simulation of NSB operating under financial optimization.
Fig. 4: Simulation of NSB operating under carbon emission reduction optimization and cooptimization.
Fig. 5: Simulation of NSB operating under self-sufficiency optimization and timer function.
Fig. 6: Comparison of the performance of the six algorithms against five metrics.

Data availability

The NextGen electricity data used in this study are available from the ACT Government through the website www.energydata.act.gov.au/pubhome. The qualitative data are not available due to abiding by ethics requirements to ensure anonymity of participants.

Code availability

We carried out quantitative analysis using our open-source software packages available at https://github.com/bsgip/c3x-data and https://github.com/bsgip/c3x-enomo. The script used to calculate presented results is available at https://github.com/bsgip/2021-responsible_algorithm_NSB.

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Acknowledgements

We thank K. Lucas-Healey, H. Temby, A. Mackenzie and J. Davis for thoughtful discussions, as well as for C. Tidemann, K. Golson and A. Dwyer as facilitators for the social research. We are grateful for the generosity of the participants who contributed to the qualitative research activity. We also thank the ANU Battery Storage and Grid Integration Program software development team for their support. All authors received funding from the Australian Renewable Energy Agency under the Distributed Energy Resources Program.

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Contributions

H.R.-C. conceived the study, collected the qualitative data, performed the social science analysis and wrote the article. B.C.P.S. conceived the study, wrote the quantitative analysis software, performed the quantitative analysis and wrote the article. M.S. conceived the study and edited the article. L.B. conceived the study, wrote the quantitative analysis software and edited the article.

Corresponding authors

Correspondence to Hedda Ransan-Cooper or Björn C. P. Sturmberg.

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Ethics statement

All the research conducted in this paper complies with Australian ethical regulations. The quantitative household energy data were provided by the Australian Capital Territory government, made available for the purposes of research by participating households as a requirement of their program participation (data have been anonymized). The social research activity was approved by the Australian National University’s human ethics committee (approval number 2019/241). As part of this process, all participants provided informed written consent. Only the citizen participants in the research (not the energy sector professionals) were provided with a AU$50 voucher for their participation as a way to mitigate the risk of only topic enthusiasts volunteering their time.

Competing interests

The authors declare no competing interests.

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Peer review information Nature Energy thanks Tarek AlSkaif, Christine Milchram and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary Notes, Methods, Table 1 and Figs. 1–4.

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Ransan-Cooper, H., Sturmberg, B.C.P., Shaw, M.E. et al. Applying responsible algorithm design to neighbourhood-scale batteries in Australia. Nat Energy 6, 815–823 (2021). https://doi.org/10.1038/s41560-021-00868-9

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