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DTSTART:20260329T030000
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DTSTART:20261025T020000
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DTSTAMP:20261001T134609Z
UID:A3C5401C-7717-4679-B951-45241322436D
DTSTART;TZID=Europe/Zurich:20260928T160000
DTEND;TZID=Europe/Zurich:20260928T170000
DESCRIPTION:With society’s increasing dependence on electricity to suppor
 t essential services and daily activities (including transportation\, comm
 erce\, communications\, healthcare\, water systems\, and emergency respons
 e)\, the resilience of electric power infrastructure has become a critical
  national priority. Extreme weather events\, climate-driven hazards\, and 
 human-triggered disruptions are increasingly challenging the ability of po
 wer systems to deliver reliable and secure electricity. Among these threat
 s\, wildfires have emerged as one of the most destructive and complex risk
 s facing electric utilities\, creating a two-way interaction in which powe
 r infrastructure can both be impacted by and contribute to wildfire igniti
 on and propagation. In this talk\, I will discuss how risk-informed planni
 ng and operational strategies can be developed and implemented to improve 
 the survivability\, adaptability\, and resilience of electric power system
 s under high-impact\, low-probability events. Particular attention will be
  given to the growing wildfire threat and the need for proactive\, risk-in
 formed decision-making frameworks that account for both grid reliability a
 nd public safety considerations. The presentation will highlight results a
 nd findings from our past and ongoing research projects at the GW Smart Gr
 id Laboratory\, where we investigate the interactions between wildfires an
 d power systems through the development of advanced optimization\, simulat
 ion\, and decision-support tools.\n\nCo-sponsored by: Ali Razi-Kazemi\n\nS
 peaker(s): Payman\n\nVirtual: https://events.vtools.ieee.org/m/572294
LOCATION:Virtual: https://events.vtools.ieee.org/m/572294
ORGANIZER:ali.razi-kazemi@hitachienergy.com
SEQUENCE:31
SUMMARY:Enhancing Resilience of Modern Power Grids to Extreme Wildfire Even
 ts
URL;VALUE=URI:https://events.vtools.ieee.org/m/572294
X-ALT-DESC:Description: &lt;br /&gt;&lt;p class=&quot;MsoNormal&quot; style=&quot;margin-bottom: 0i
 n\; text-align: justify\; line-height: normal\; mso-layout-grid-align: non
 e\; text-autospace: none\;&quot;&gt;&lt;span style=&quot;mso-bidi-font-family: Calibri\; m
 so-bidi-theme-font: minor-latin\; color: #1f3864\; mso-themecolor: accent1
 \; mso-themeshade: 128\;&quot;&gt;With society&amp;rsquo\;s increasing dependence on e
 lectricity to support essential services and daily activities (including t
 ransportation\, commerce\, communications\, healthcare\, water systems\, a
 nd emergency response)\, the resilience of electric power infrastructure h
 as become a critical national priority. Extreme weather events\, climate-d
 riven hazards\, and human-triggered disruptions are increasingly challengi
 ng the ability of power systems to deliver reliable and secure electricity
 . Among these threats\, wildfires have emerged as one of the most destruct
 ive and complex risks facing electric utilities\, creating a two-way inter
 action in which power infrastructure can both be impacted by and contribut
 e to wildfire ignition and propagation. In this talk\, I will discuss how 
 risk-informed planning and operational strategies can be developed and imp
 lemented to improve the survivability\, adaptability\, and resilience of e
 lectric power systems under high-impact\, low-probability events. Particul
 ar attention will be given to the growing wildfire threat and the need for
  proactive\, risk-informed decision-making frameworks that account for bot
 h grid reliability and public safety considerations. The presentation will
  highlight results and findings from our past and ongoing research project
 s at the GW Smart Grid Laboratory\, where we investigate the interactions 
 between wildfires and power systems through the development of advanced op
 timization\, simulation\, and decision-support tools. &lt;/span&gt;&lt;/p&gt;
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