Neighbourhood batteries in Australia: Anticipating questions of value conflict and (in)justice

We have a new paper published today in Energy Research & Social Science.


  • Energy professionals and citizens hold diverse values on algorithm design, governance and the energy transition generally.
  • Differences in how values are interpreted and which values are emphasised suggest future points of conflict (and injustice).
  • Systemic issues raised both down and upstream of the technology suggest distributed responsability ill suited to centralised governance.
  • Our focus on responsibility and justice reorients the problem to re-design rather than accommodation.

Pre-print is freely available below and the published paper is available at

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Local network pricing and community storage a powerful combo: ANU

If networks could charge for localised use of their service, all customers in areas with high PV and community-scale batteries would pay lower bills … with no cost to the network, research shows.

Is rooftop solar a problem in the suburbs? Apparently so, with rising PV exports prompting falls in feed-in tariffs, plans for export charges in Adelaide and deployment of community-scale batteries in many cities.

As the grid transitions away from coal, it seems as though rooftop solar is part of the solution and part of the problem at the same time. Is there a simple solution that could see all that excess solar energy shared equitably and leave customers better off?

Yes, there is. Or there could be, if networks were allowed more flexibility in how they charge for their services.

Full story in ecogeneration

Obey your master … how algorithms can steer a neighbourhood battery

Ecogeneration interview about our Nature Energy paper on battery algorithms

Research shows that if energy professionals and customers agree on what they expect a community battery to do, engineers can write performance algorithms to suit those objectives.

Can you trust a battery to make the best decisions about when to charge and discharge? It depends who owns it, for a start, but most of all it depends who wrote the code that is its book of commands.

As community batteries are deployed to manage solar exports and calm grid disturbances, researchers at the Australian National University wanted to understand the degree to which these assets can be bent to serve their owners or the communities they are plonked in the middle of.

“How an electric vehicle or a battery operates in your home, these things are governed by algorithms coded up by humans,” says ANU battery storage and grid integration research leader Bjorn Sturmberg. “They are not governed by the physics of spinning machines, which is traditionally what we have built our energy system around.”

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Applying responsible algorithm design to neighbourhood-scale batteries in Australia

Our new paper in Nature Energy asks fundamental questions of what values and biases algorithms are encoding into our digital energy system.

Abstract below:
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.

Full text available here