GLOW-Energy nested bio system flows:from the home to the hub

ee66a2b5-a664-4981-9aae-c56cc6c665b4

Active

EPSRC
EPSRC
EPSRC
EPSRC
EPSRC

£2,329,325

May 31, 2022

Nov. 30, 2024

The aim of this project is to provide an innovative dynamic approach to transform how people manage energy in homes inspired by bees' social organization and communication. A new computational system is developed to identify and communicate inefficiencies found between individual household energy use and community energy demand. Bees have evolved an efficient mechanism to communicate collective needs at an individual level in responsive and targeted ways that humans have not. The new system draws on behavioural patterns found in bees as a way to communicate an optimised approach to managing energy behaviour in homes in a responsive, targeted and effective way.

Currently, energy in homes is managed through technologies that are designed to alert users to reduce their use when passing a designed threshold. These thresholds are derived mostly from technical data rather than evidence that takes into account the social values and approaches to community, ways of living and home character. It is well established that despite being alerted to change how they use energy, most users do not alter their behaviour in the longer term. This lack of responsiveness is seen to occur mainly through not taking into account users' values, their homes' social and spatial character and ways of living. Energy demand in housing is growing and diversifying with predicted carbon emissions from homes significantly impacting on health and wellbeing of society as a whole. Without a significant step change in the status quo, the long-term impacts of managing energy demand unsustainably in housing are critical.

Working closely with three housing communities and industry partners, the research will use mixed methods to study how energy is used in homes and how this varies between different communities. The existing behavioural patterns across the three housing communities will be studied and identified inefficiencies will be computationally optimised using learning found in bees' communication protocols. The developed computational system prototype will be tested initially through a web-based app, through which potential users could engage in a selection of behaviour change scenarios based on their inputs related to their self-identified behavioural patterns. Engagement and responses from the app will be studied and presented at two separate citizen juries in order to develop a holistic understanding into potential prototype service applications across a range of communities and sectors.

The project extends current work in EPSRC Energy and Digital Economy themes and provides multiple benefits not just through the developed prototype but also in evidencing use of innovative mixed methods that may be applied in future technology innovation studies in a range of sectors including energy. Findings will benefit a range of stakeholders including residents, housing developers, energy policymakers, energy technology developers, architects and housing associations. The project will benefit residents through enabling a user-focused and evidence-based approach to managing energy in homes, whilst housing developers can gain a better holistic understanding of how energy is used in homes and how its spatial and social configuration supports net-zero carbon design and development. Energy policymakers will benefit from gaining new insights and an evidence base that offer social and spatial knowledge, household behavioural patterns, and social responses that will better inform future sustainable energy demand management.

Building on a growing interest in sustainable energy transitions and energy democracy, this project offers an accelerated approach for both communities and individuals to forge a new relationship with energy. Though the focus is on the energy sector and housing, findings from this project have wider implications and potential benefits in the food supply chain for instance where collective needs necessitate an optimised individual response.