Institutional, social and individual behavioural effects of energy feedback in public buildings across eleven European cities

Ozawa-Meida, Leticia; Wilson, Caroline; Fleming, Paul; Stuart, Graeme; Holland, C.R.

doi:10.1016/j.enpol.2017.08.026

Cited by 8 publications

(2 citation statements)

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“…Formal and informal networks (communities of practice) can emerge introducing and diffusing new models, concepts and practices, so these can become part of the organisation's culture [34]. Social norms can be enhanced when users perceive competition of energy performance improvement between buildings [35]. Competitive approaches (energy reduction competitions) and incentivisation models (gamification) can help to intensify knowledge exchange and participation among building users as well as promoting cooperative behaviour [36].…”

Section: Energy Feedback and Visualisationmentioning

confidence: 99%

“…The modelling approach is described in detail in Stuart and Fleming [37] The core of the calculation is an inverse model and a unitless performance indicator. The algorithm [37] was originally developed from a prototype designed in the SmartSpaces EU project [35]. Data are continually imported into the system, cleaned and mapped against local weather data drawn from open sources [38].…”

Section: The Energy Data Innovation Networkmentioning

confidence: 99%

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Supporting Decentralised Energy Management through Smart Monitoring Systems in Public Authorities

Stuart

Ozawa-Meida

2020

Energies

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Energy infrastructure in large, multi-site organisations such as municipal authorities, is often heterogeneous in terms of factors such as age and complexity of the technology deployed. Responsibility for day-to-day operation and maintenance of this infrastructure is typically dispersed across large numbers of individuals and impacts on even larger numbers of building users. Yet, the diverse population of stakeholders with an interest in the operation and development of this dynamic infrastructure typically have little or no visibility of energy and water usage. This paper explores the integration of utility metering data into urban management processes via the deployment of an accessible “smart meter” monitoring system. The system is deployed in three public authorities and the impact of the system is investigated based on the triangulation of evidence from semi-structured interviews and case studies. The research is framed from three perspectives: the bottom-up micro-level (individual and local), the top-down macro-level (organisation-wide and strategic) and intermediate meso-level (community-focused and operation). Evidence shows that improved communication across these levels enables a decentralisation and joining-up of energy management. Evidence points to the importance of reducing the cognitive load associated with monitoring systems. Better access to information supports more local autonomy, easier communication and cooperation between stakeholders and fosters the conditions necessary for adaptive practices to emerge.

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Section: Energy Feedback and Visualisationmentioning

confidence: 99%

Section: The Energy Data Innovation Networkmentioning

confidence: 99%