BEGIN:VCALENDAR
VERSION:2.0
PRODID:IEEE vTools.Events//EN
CALSCALE:GREGORIAN
BEGIN:VTIMEZONE
TZID:America/New_York
BEGIN:DAYLIGHT
DTSTART:20260308T030000
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3
TZNAME:EDT
END:DAYLIGHT
BEGIN:STANDARD
DTSTART:20261101T010000
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11
TZNAME:EST
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20260420T121739Z
UID:1129E905-1CA7-4627-9060-E0D5E342522F
DTSTART;TZID=America/New_York:20260512T140000
DTEND;TZID=America/New_York:20260512T150000
DESCRIPTION:Virtual power contracts - financial instruments that settle aga
 inst electricity-market outcomes - are increasingly being used by corporat
 e buyers and governments to hedge electricity price risk and support effic
 ient investments in new energy technologies. Because electricity sellers a
 re subject to production and congestion uncertainty in the underlying comm
 odity network\, settlement losses can exceed spot-revenues. Under limited 
 liability\, this creates counterparty default risk for the buyer. We study
  the optimal design of virtual power contracts when a buyer procures from 
 privately informed sellers subject to quantity and price-separation risk. 
 The optimal contract conditions payments on generation and transmission ou
 tcomes\, providing production and locational insurance. Common designs\, s
 uch as fixed-price contracts-for-differences\, provide price-stability but
  may expose the buyer to seller default risk. More flexible designs\, such
  as adaptive-price contracts with a floor\, improve the buyer's ability to
  screen generators with heterogeneous default risk but introduce greater p
 rice volatility. Our results highlight a trade-off between screening count
 erparty risk and price stability\, and provide guidance for the design of 
 long-term electricity procurement auctions.\n\nSpeaker(s): Felipe Verasteg
 ui\n\nRoom: 202\, Bldg: ECE\, 141 Warren St\, New Jersey Institute of Tech
 nology\, Newark\, New Jersey\, United States\, 07103
LOCATION:Room: 202\, Bldg: ECE\, 141 Warren St\, New Jersey Institute of Te
 chnology\, Newark\, New Jersey\, United States\, 07103
ORGANIZER:marcos.netto@njit.edu
SEQUENCE:20
SUMMARY:Virtual Power Contracts and Seller Default Risk
URL;VALUE=URI:https://events.vtools.ieee.org/m/555645
X-ALT-DESC:Description: <br /><p>Virtual power contracts - financial instru
 ments that settle against electricity-market outcomes - are increasingly b
 eing used by corporate buyers and governments to hedge electricity price r
 isk and support efficient investments in new energy technologies. Because 
 electricity sellers are subject to production and congestion uncertainty i
 n the underlying commodity network\, settlement losses can exceed spot-rev
 enues. Under limited liability\, this creates counterparty default risk fo
 r the buyer. We study the optimal design of virtual power contracts when a
  buyer procures from privately informed sellers subject to quantity and pr
 ice-separation risk. The optimal contract conditions payments on generatio
 n and transmission outcomes\, providing production and locational insuranc
 e. Common designs\, such as fixed-price contracts-for-differences\, provid
 e price-stability but may expose the buyer to seller default risk. More fl
 exible designs\, such as adaptive-price contracts with a floor\, improve t
 he buyer's ability to screen generators with heterogeneous default risk bu
 t introduce greater price volatility. Our results highlight a trade-off be
 tween screening counterparty risk and price stability\, and provide guidan
 ce for the design of long-term electricity procurement auctions.</p>
END:VEVENT
END:VCALENDAR