BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//ESIG - ECPv6.16.3//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://www.esig.energy
X-WR-CALDESC:Events for ESIG
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/New_York
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20240310T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20241103T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20250309T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20251102T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20260308T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20261101T060000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250226T160000
DTEND;TZID=America/New_York:20250226T170000
DTSTAMP:20260607T003949
CREATED:20250204T215830Z
LAST-MODIFIED:20260116T185102Z
UID:16026-1740585600-1740589200@www.esig.energy
SUMMARY:G-PST/ESIG Webinar Series: Reliable Energy Forecasting for Power System Operations
DESCRIPTION:Download Presentation \nView Webinar Recording \n\n \nFeatured Speakers: Akylas Stratigakos\, Research Associate\, Imperial College London; Wangkun Xu\, Research Associate\, Imperial College London \nAbout the Webinar: Short-term energy forecasting\, from a few minutes to a few days ahead\, is critical for the near real-time operations of low-carbon power systems\, enabling operators to better cope with variable and uncertain renewable production. Energy forecasting tools deployed in operational processes are increasingly based on machine learning methods\, aggregating heterogeneous data from various sources\, such as production measurements and weather forecasts. The resultant forecasts are subsequently used as input in decision-making tasks\, such as market-clearing or scheduling processes. This talk will present novel ideas to improve the reliability of energy forecasts and operational decisions concerning two critical aspects: (i) dealing with missing data after model deployment\, and (ii) tailoring energy forecasts to downstream decision-making tasks. \nIn the first part\, we consider the problem of missing data after a model has been deployed in production\, which could result from an equipment failure or cyberattack\, and we will present novel forecasting methods that seamlessly handle missing data operationally by adapting to the available information. In the second part\, we consider the issue of tailoring energy forecasts to the downstream decision tasks. Instead of solely focusing on statistical accuracy\, we will present a smart predict-and-optimize (SPO) approach that embeds knowledge about the downstream decision task during model training\, leading to more economical and robust decisions. \nAbout the Speakers: Akylas Stratigakos received a Diploma in Electrical and Computer Engineering from the University of Patras\, Greece\, and a Ph.D. in Energy and Process Engineering from Mines Paris\, PSL University\, France. He is currently a Research Associate within the Department of Electrical and Electronic Engineering at Imperial College London. His research interests include energy forecasting\, decision-making under uncertainty\, and machine learning applications in power systems. \nDr. Wangkun Xu received a Ph.D. in Electrical Engineering from the Control and Power Research group at Imperial College London\, in 2024. He is currently a research associate in the same group. His research interests include a broad range of machine learning\, optimization\, and control applications for secure and robust power system operations. \nModerator: Charlie Smith\, Principal  Consultant\, ESIG \nRegistration Cost: FREE \nQ&A Session: We will be using the slido platform for Q&A. Please submit your questions and follow-along during the event at this link.
URL:https://www.esig.energy/event/reliable-energy-forecasting/
CATEGORIES:Webinars
END:VEVENT
END:VCALENDAR