EESS talk - Student presentation on "Closing the survey-modelling loop: an analysis of consumer preferences for load-shifting via a model-driven adaptive survey design"
Abstract:
To foster the transition toward a user-centred energy system based on renewable energy sources, effective policy-making requires a comprehensive understanding of individual and household energy behaviour. However, soliciting information from consumers regarding hypothetical and unfamiliar scenarios, such as those presented by dynamic energy systems, poses inherent challenges that conventional survey, featuring fixed standardised questions, struggle to effectively address.In response to these challenges, we propose a pioneering approach: the model-driven adaptive survey. This method enhances conventional survey design by establishing a dynamic feedback loop between survey responses and an energy demand model. Through this mechanism, consumers can iteratively evaluate the potential effect of their behavioural adjustments via tailored feedback. Employing this approach, we conducted a survey across Germany and German-speaking cantons of Switzerland (N=1,594) investigating load-shifting preferences for laundry and dishwashing in response to four Demand-Side Management (DSM) scenarios.Our empirical findings reveal that households exhibit a willingness to engage in load-shifting behaviours, even in the absence of direct economic incentives. Notably, motivations such as supporting grid stability under the risk of congestion and contributing to increased utilisation of renewable energy sources can stimulate such behavioural shifts. Methodologically, our results underscore the efficacy of integrating energy demand models into survey designs to facilitate households in making complex energy-related decisions in a tailored manner. Lastly, we reflect on the broader implications of our findings, suggesting that energy models hold promise in regularly assisting consumers in navigating the intricacies of future dynamic energy scenarios.
Short Biography:
Matteo Barsanti holds an MSc in energy engineering from the Politecnico di Milano and is currently a fourth-year PhD student at Human-Environment Relationship in Urban Systems (HERUS) laboratory at EPFL, under the supervision of Dr Claudia Binder and Dr Selin Yilmaz. His research delves into the complexities of residential energy consumption, aiming to anticipate and address the challenges of managing an increasingly decarbonised and electrified energy system. Specifically, he focuses on enhancing existing methodologies for modelling residential energy demand and flexibility, drawing insights from social sciences to transcend the limitations of purely engineering and techno-economic perspectives.
To foster the transition toward a user-centred energy system based on renewable energy sources, effective policy-making requires a comprehensive understanding of individual and household energy behaviour. However, soliciting information from consumers regarding hypothetical and unfamiliar scenarios, such as those presented by dynamic energy systems, poses inherent challenges that conventional survey, featuring fixed standardised questions, struggle to effectively address.In response to these challenges, we propose a pioneering approach: the model-driven adaptive survey. This method enhances conventional survey design by establishing a dynamic feedback loop between survey responses and an energy demand model. Through this mechanism, consumers can iteratively evaluate the potential effect of their behavioural adjustments via tailored feedback. Employing this approach, we conducted a survey across Germany and German-speaking cantons of Switzerland (N=1,594) investigating load-shifting preferences for laundry and dishwashing in response to four Demand-Side Management (DSM) scenarios.Our empirical findings reveal that households exhibit a willingness to engage in load-shifting behaviours, even in the absence of direct economic incentives. Notably, motivations such as supporting grid stability under the risk of congestion and contributing to increased utilisation of renewable energy sources can stimulate such behavioural shifts. Methodologically, our results underscore the efficacy of integrating energy demand models into survey designs to facilitate households in making complex energy-related decisions in a tailored manner. Lastly, we reflect on the broader implications of our findings, suggesting that energy models hold promise in regularly assisting consumers in navigating the intricacies of future dynamic energy scenarios.
Short Biography:
Matteo Barsanti holds an MSc in energy engineering from the Politecnico di Milano and is currently a fourth-year PhD student at Human-Environment Relationship in Urban Systems (HERUS) laboratory at EPFL, under the supervision of Dr Claudia Binder and Dr Selin Yilmaz. His research delves into the complexities of residential energy consumption, aiming to anticipate and address the challenges of managing an increasingly decarbonised and electrified energy system. Specifically, he focuses on enhancing existing methodologies for modelling residential energy demand and flexibility, drawing insights from social sciences to transcend the limitations of purely engineering and techno-economic perspectives.
Practical information
- General public
- Free
- This event is internal
Organizer
- EESS - IIE
Contact
- Prof. Claudia Binder, HERUS