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SUMMARY:EESS talk - Student presentation on "Closing the survey-modelling 
 loop: an analysis of consumer preferences for load-shifting via a model-dr
 iven adaptive survey design"
DTSTART:20240409T121500
DTEND:20240409T124500
DTSTAMP:20260509T161130Z
UID:f263807011a8faf16d4ecdb4c7afec7e89186dc31d8d58c4c34ec9a4
CATEGORIES:Conferences - Seminars
DESCRIPTION:Matteo Barsanti\, HERUS\nAbstract:\nTo foster the transition t
 oward a user-centred energy system based on renewable energy sources\, eff
 ective policy-making requires a comprehensive understanding of individual 
 and household energy behaviour. However\, soliciting information from cons
 umers regarding hypothetical and unfamiliar scenarios\, such as those pres
 ented by dynamic energy systems\, poses inherent challenges that conventio
 nal survey\, featuring fixed standardised questions\, struggle to effectiv
 ely address.In response to these challenges\, we propose a pioneering appr
 oach: the model-driven adaptive survey. This method enhances conventional 
 survey design by establishing a dynamic feedback loop between survey respo
 nses and an energy demand model. Through this mechanism\, consumers can it
 eratively evaluate the potential effect of their behavioural adjustments v
 ia tailored feedback. Employing this approach\, we conducted a survey acro
 ss Germany and German-speaking cantons of Switzerland (N=1\,594) investiga
 ting 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 behaviour
 s\, even in the absence of direct economic incentives. Notably\, motivatio
 ns such as supporting grid stability under the risk of congestion and cont
 ributing to increased utilisation of renewable energy sources can stimulat
 e such behavioural shifts. Methodologically\, our results underscore the e
 fficacy of integrating energy demand models into survey designs to facilit
 ate households in making complex energy-related decisions in a tailored ma
 nner. Lastly\, we reflect on the broader implications of our findings\, su
 ggesting that energy models hold promise in regularly assisting consumers 
 in navigating the intricacies of future dynamic energy scenarios.\n\nShort
  Biography:\nMatteo Barsanti holds an MSc in energy engineering from the P
 olitecnico di Milano and is currently a fourth-year PhD student at Human-E
 nvironment Relationship in Urban Systems (HERUS) laboratory at EPFL\, unde
 r the supervision of Dr Claudia Binder and Dr Selin Yilmaz. His research d
 elves into the complexities of residential energy consumption\, aiming to 
 anticipate and address the challenges of managing an increasingly decarbon
 ised and electrified energy system. Specifically\, he focuses on enhancing
  existing methodologies for modelling residential energy demand and flexib
 ility\, drawing insights from social sciences to transcend the limitations
  of purely engineering and techno-economic perspectives.\n\n 
LOCATION:GC B1 10 https://plan.epfl.ch/?room==GC%20B1%2010 https://epfl.zo
 om.us/j/69011077410
STATUS:CONFIRMED
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