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SUMMARY:SolarFit: A Successive Refinement Approach for Sizing of PV and St
 orage Systems in EV-Enabled Homes - Julia Gschwind ETH Zurich\, University
  of Cambridge
DTSTART:20250717T120000Z
DTEND:20250717T130000Z
UID:TALK232144@talks.cam.ac.uk
CONTACT:114742
DESCRIPTION:*Abstract*\n\nThe growing accessibility of solar photovoltaic 
 (PV) systems offers a promising pathway for homeowners to decarbonize thei
 r buildings. However\, determining the appropriate size of a PV system and
  battery storage remains a complex task\, influenced by household energy d
 emand\, daily activity patterns\, and local solar potential. This decision
  becomes more complex with the increasing adoption of electric vehicles (E
 Vs)\, as commute patterns and charging strategies\, including bidirectiona
 l charging\, significantly influence electricity demand profiles.\nConvent
 ional approaches to sizing PV and battery systems rely on detailed simulat
 ions that\, while accurate\, are computationally intensive and often take 
 several minutes to hours to complete. This latency reduces interactivity a
 nd limits users' ability to explore different scenarios\, such as varying 
 EV charging policies or desired levels of energy self-sufficiency. \nIn th
 is work\, we introduce SolarFit\, an application that delivers instant\, h
 igh-accuracy sizing recommendations based on simple user-provided inputs. 
 SolarFit leverages a neural network-based surrogate model\, which generate
 s results within milliseconds. By drastically reducing computation time\, 
 our approach enables users to efficiently evaluate a range of scenarios an
 d identify system configurations that best match their needs. \n\n*Bio*\n\
 nJulia Gschwind is a visiting Master's student at the University of Cambri
 dge from ETH Zurich. She is supervised by Prof. Srinivasan Keshav and her 
 research focuses on using neural networks to predict the optimal sizing of
  photovoltaic systems.
LOCATION:Room GS15 at the William Gates Building and on Zoom: https://cl-c
 am-ac-uk.zoom.us/j/4361570789?pwd=Nkl2T3ZLaTZwRm05bzRTOUUxY3Q4QT09&amp\;fr
 om=addon 
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