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Energy transition: user behaviour and sustainability

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Danie Nilsson

Postdoctoral Research Fellow


Presentation title: Applying behavioural science and reality TV to transition Australians towards sustainable housing.


Abstract: Shifting Australia’s residential housing market towards greater sustainability and energy efficiency is critical to reducing carbon emissions, as well as helping millions of people nationwide achieve more comfortable, healthy and affordable lives. Achieving these goals requires change at scale, yet it is often difficult to find practical and cost-effective ways to do so. Reality television is a powerful tool to reach large audiences en masse and has been shown to influence viewers’ behaviour, including purchasing decisions and actions. In light of this, a new 8-episode lifestyle reality TV series –‘Renovate or Rebuild’ – was created with the overarching goal of stimulating Australia’s sustainable housing market by encouraging greater uptake of energy efficient home designs, features and products.
To achieve optimal impact, ‘Renovate or Rebuild’ took an innovative approach that incorporated a range of behavioural science strategies in its design and delivery. A primary aim was to improve the communication and audience uptake of key sustainability messages and themes conveyed throughout the show.
To evaluate the success of applying this approach, a mixed-method study involving three longitudinal online surveys (n=5,142) and online focus groups (n=23) was conducted to collect both quantitative and qualitative data. Statistical analyses were subsequently collected to compare the survey data for real-world viewers and non-viewers of the show. Results revealed that after watching the TV series, viewers of the show were significantly more likely to consider having a ‘home energy star rating above the minimum standards for Australia’ as a ‘must have feature’. Furthermore, as the amount of TV series content watched by viewers increased, there was a significant increase in viewers’ self-reported desire for home energy star ratings above the minimum standard. Compared to non-viewers, viewers of the show were also significantly more likely to report seeking out information and intending to purchase and/or install products featured in the show.
Overall, the results of this study provide preliminary support for the positive impact of ‘Renovate or Rebuild’ on shifting viewers towards greater energy efficiency and more sustainable housing options. With a total reach of over 3.2 million views, the show’s innovative and strategic communications approach has demonstrated significant potential to positively drive and expand Australia’s sustainable housing market.

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Murad Tayebjee

Senior Lecturer

University of New South Wales

Presentation title: PlayEnergy: a massive multiplayer online game for teaching sustainable energy


Abstract: Sustainability is a complex concept. The UN divides sustainable development into three distinct but inextricably linked dimensions: environmental, economic, and social. Environmental sustainability focuses on the stability of biological and physical systems and preserving access to a healthy environment. Economic sustainability encompasses a strong and durable economic growth without exhausting natural or human resources and negatively impacting social, environmental, and cultural aspects of the community. Social sustainability emphasizes the importance of strong labour markets; adaptability to major demographic changes; stability in social and cultural systems; and democratic decision-making.
As we transition to renewable energy, we must consider the interaction between these three dimensions. If people employed in the fossil fuel sector become unemployed, how will that affect social sustainability? Continuing with the status quo will affect environmental sustainability but how long will it take for economic and social sustainability to also become compromised? Communicating these complexities is important to guide the public through the transition to renewables. We have developed a videogame that explores these concepts called PlayEnergy.
PlayEnergy is powered and delivered by Playconomics -- a massive multiplayer online strategy game (MMO) developed by LionsHeart Studios (a UNSW spin off company) and incorporating all dimensions of sustainable development. PlayEnergy was born from a close and exciting collaboration between LionsHeart and UNSW’s School of Photovoltaic and Renewable Energy Engineering.
Players organize a team of characters who interact with other players’ teams to gain ‘happiness’ points. The Entrepreneur character starts businesses, trades goods (including food, building materials, solar panels, electricity), hires Workers and pays them for their labour. Consumers and Architects purchase these goods. Consumers ‘produce’ happiness upon consuming goods. Architects manage a player’s house and purchase energy efficient appliances, solar panels, and air-conditioners so players can gain happiness from these additions. Entrepreneurs and Architects consume electricity to power their businesses and homes, respectively. If fossil fuels are used to generate electricity, carbon dioxide is produced, reducing the happiness for all, and increasing the chance of natural disasters! All energy generation is underpinned by calculations using weather data and thermodynamics. The result is a MMO with a full economy that captures the key considerations of transitioning to renewables.
Initially PlayEnergy was envisioned as a teaching aid for undergraduate university students. The project has evolved to serve a broader scope and educate high school students and the public. In this presentation we will report on the educational results and future implementation plans.

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Saman Halgamuge


The University of Melbourne

Presentation title: Deep learning and optimisation-based approaches to forecast distributed solar generation


Abstract: Small-scale distributed solar PV systems installed on the rooftops of residential and commercial buildings (i.e., behind-the-meter PV systems) have seen exponential growth in the past decade due to the high demand for solar energy as a clean and renewable energy source. However, the variable and non-dispatchable nature of PV power generation have caused multiple issues in integrating high amounts of distributed solar PV systems into existing electricity networks. The ability to control, estimate and forecast the power generation of distributed PV systems is becoming essential to overcome these issues and effectively integrate PV systems into existing distribution networks and energy markets. In particular, accurate PV power forecasts can reduce the uncertainty associated with integrating PV power, allowing energy stakeholders to better plan and manage the energy supply. In this work, we discuss and address three important challenges associated with accurately forecasting distributed solar generation using novel optimisation and deep learning-based approaches.
The forecast horizon and resolution (i.e., frequency of the forecast) requirements of distributed solar forecasts can differ significantly based on the application of interest. However, many forecasting methods have varying performances across different horizons and resolutions. Such variations make it challenging for a solar forecasting practitioner to determine which forecasting method to use for the task at hand. Therefore, in this work, we first introduce an optimisation-based forecast combination method to accurately forecast solar generation regardless of the resolution and horizon of interest. During short-time horizons, the variability of solar generation is primarily caused by cloud movement. Therefore, a promising solution to improve forecasts is to use images of clouds, which reflect the second-to-second changes in cloud cover affecting solar generation. Recently, attention-based deep neural networks have shown pre-eminent success in many computer vision tasks, including spatiotemporal applications. However, the impact of such networks on similar cloud prediction tasks and the subsequent impact on solar forecasting is yet to be well known. To this end, we next introduce and discuss how attention-based deep neural networks can be adapted to cloud movement prediction and their impact towards distributed solar forecasting. Finally, in this work, we discuss challenges in forecasting regional solar generation (i.e., aggregated solar generation from all distributed PV systems) and propose novel deep learning-based approaches to improve regional solar forecasts addressing these challenges.


Hannah Korsmeyer

Research Fellow

Monash University

Presentation title: Digital energy futures: forecasting everyday life


Abstract: Digital Energy Futures is a landmark four-year project funded by the Australian Research Council, in partnership with Monash University, Ausgrid, AusNet Services and Energy Consumers Australia. As the project concludes in 2023, it has delivered new resources and methodologies to help understand and plan for residential energy futures from the perspective of people’s everyday lives.


In this presentation, we reflect on the outcomes of the project and its benefits for the energy sector, across six stages of research, which involved over 100 people and households in ethnographic research, and survey responses from more than 5000 Australians. In Stage 1, which involved a review of industry reports from the digital technology and energy sector, we identify how industry assumptions about future everyday life misalign with each other and also with the expectations of household energy consumers. In Stage 2, we present highlights from our 45 trends in changing everyday practices, drawn from interviews, home tours and research activities with 72 households. These include new trends in household comfort, such as the emerging focus on healthy, safe, and comfortable air; and the link between the charging of digital devices and electric vehicles. In Stage 3, we share highlights from Energy Consumers Australia’s Energy Consumer Behaviour Survey, which longitudinal tracks trends in digital energy futures informed by our research. Stage 4 involved 10 design ethnography workshops with 43 households to explore people’s future visions in relation to electric vehicles and battery charging in local neighbourhoods, the rise of emerging air technologies, and the reconfiguration of routines and load shifting in response to more frequent extreme weather.


From this stage, we identify key foresights to guide residential forecasting, and reframe key foresighting concepts about how consumers are expected to act and respond in current and future scenarios. For instance, the research highlights the need to reframe the concept of “set and forget” to “set and notify”, where consumers continually adapt and modify their use of smart and automated devices through access to notifications about changing circumstances (e.g. weather, allergens, air quality, service delivery, appointments and energy). In Stage 5, we provide an overview of our scenarios for future living, which modify established industry scenarios to provide plausible energy visions grounded in the experiences and future expectations of people who participated in our research. Finally, we share our principles for demand management and opportunities for supporting or intervening in digital energy futures as they unfold.

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