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SUMMARY:MechE Seminar: Embracing Uncertainties in Systems Modeling to Unlo
 ck the Energy Transition
DTSTART:20250211T151500
DTEND:20250211T161500
DTSTAMP:20260525T190815Z
UID:d3b2e3cd2fea37b7a2be8526baa2151c9b41446a82f57868e3fde8c1
CATEGORIES:Conferences - Seminars
DESCRIPTION:Dr. Stefano Moret\, Department of Mechanical and Process Engin
 eering\, ETH Zurich\nAbstract: The energy transition is put at stake by un
 precedented uncertainties in energy prices\, technological developments\, 
 geopolitics\, and social acceptance. Due to fundamental methodological\, c
 omputational\, and data challenges\, this uncertainty is at best rarely co
 nsidered in energy planning models. This neglect increases the risk of mis
 sing our urgent climate targets.\n\nIn this seminar\, we show how these ba
 rriers can be overcome to enable a systematic consideration of uncertainty
  in energy planning. We first introduce a robust optimization framework th
 at can consider hundreds of sources of uncertainties typically found in en
 ergy models. Then\, we demonstrate computational breakthroughs in existing
  uncertainty quantification methods by exploiting the properties of convex
  optimization problems. Finally\, we show how machine learning can help st
 reamline the complex outputs of uncertainty studies into interpretable opt
 ions for decision-makers. Applications to a new energy system model\, Ener
 gyScope\, highlight the impact of these developments on real-world case st
 udies. The presented findings unlock new exciting frontiers\, such as fact
 oring in uncertainties in large-scale models and in multi-stage planning p
 rocesses\, and the potential to narrow the gap between quantitative models
  and real-world decision-making for a faster energy transition.\n\nReferen
 ces:\n[1] S. Moret\, F. Babonneau\, M. Bierlaire\, and F. Maréchal\, “
 Decision support for strategic energy planning: A robust optimization fram
 ework\,” European Journal of Operational Research\, vol. 280\, no. 2\, p
 p. 539–554\, Jan. 2020\, doi: 10.1016/j.ejor.2019.06.015.\n[2] M. Borasi
 o and S. Moret . Deep decarbonisation of regional energy systems: a novel 
 modelling approach and its application to the Italian energy transition. R
 enewable & Sustainable Energy Reviews\, 2022. Vol. 153\, p. 111730. DOI: 1
 0.1016/j.rser.2021.111730\n[3] F. Baader\, S. Moret \, W. Wiesemann\, I. S
 taffell and A. Bardow. Streamlining Energy Transition Scenarios to Key Pol
 icy Decisions. Pre-print: https://arxiv.org/pdf/2311.06625\n\n\nBiography:
  Stefano Moret is a Principal investigator\, Group Leader and Lecturer at 
 ETH Zurich\, where his research is funded by an Ambizione Grant awarded by
  the Swiss National Science Foundation (SNSF). His research interests are 
 in energy systems modeling and the consideration of uncertainty in energy 
 planning and strategic decision-making. Stefano has an Industrial and Mech
 anical Engineering background from the University of Padova (Italy) and ho
 lds a PhD in Energy from EPFL. Before joining ETH Zurich\, he was a SNSF E
 arly Postdoc Mobility Fellow and Research Associate at Imperial College Lo
 ndon.
LOCATION:BM 5202 https://plan.epfl.ch/?room==BM%205202 https://epfl.zoom.u
 s/j/66189803108
STATUS:CONFIRMED
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