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DTSTAMP:20261112T205112Z
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DESCRIPTION:Title: Data-Driven Modeling of Inverter-Based Resources: Black-
 Box and White-Box Approaches\n\nAbstract:\n\nAs inverter-based resources (
 IBRs) play a growing role\, accurate dynamic models are increasingly criti
 cal for reliable planning and operation of power systems highly penetrated
  by renewables\, storage\, and data centers. In practice\, however\, IBR m
 odeling is challenging because some resources come with imperfect or outda
 ted engineering models\, while others appear as black boxes due to proprie
 tary controls and undocumented mode changes. This webinar introduces two c
 omplementary data-driven approaches to this problem: white-box methods tha
 t use measurements to validate and calibrate known models\, and black-box 
 methods that learn dynamic behavior directly from noisy data when internal
  model details are unavailable. The webinar emphasizes the practical value
  of combining both perspectives. White-box approaches offer interpretabili
 ty and support model validation when structure is known\, whereas black-bo
 x approaches enable faithful modeling when the resource is inaccessible fr
 om a modeling standpoint. Together\, they form a flexible foundation for i
 mproving IBR representation and strengthening grid stability studies in di
 verse practical settings.\n\nSpeaker(s): \, Yuzhang Lin\n\nVirtual: https:
 //events.vtools.ieee.org/m/590712
LOCATION:Virtual: https://events.vtools.ieee.org/m/590712
ORGANIZER:guoxian2012@gmail.com
SEQUENCE:12
SUMMARY:IEEE PES Schenectady Chapter Virtual Lecture “Data-Driven Modelin
 g of IBR: Black-Box and White-Box Approaches”
URL;VALUE=URI:https://events.vtools.ieee.org/m/590712
X-ALT-DESC:Description: <br /><p class="MsoNormal" style="text-align: justi
 fy\; text-justify: inter-ideograph\;"><strong>Title:</strong> Data-Driven 
 Modeling of Inverter-Based Resources: Black-Box and White-Box Approaches</
 p>\n<p class="MsoNormal" style="text-align: justify\; text-justify: inter-
 ideograph\;"><strong>Abstract: </strong></p>\n<p class="MsoNormal" style="
 text-align: justify\; text-justify: inter-ideograph\;">As inverter-based r
 esources (IBRs) play a growing role\, accurate dynamic models are increasi
 ngly critical for reliable planning and operation of power systems highly 
 penetrated by renewables\, storage\, and data centers. In practice\, howev
 er\, IBR modeling is challenging because some resources come with imperfec
 t or outdated engineering models\, while others appear as black boxes due 
 to proprietary controls and undocumented mode changes. This webinar introd
 uces two complementary data-driven approaches to this problem: white-box m
 ethods that use measurements to validate and calibrate known models\, and 
 black-box methods that learn dynamic behavior directly from noisy data whe
 n internal model details are unavailable. The webinar emphasizes the pract
 ical value of combining both perspectives. White-box approaches offer inte
 rpretability and support model validation when structure is known\, wherea
 s black-box approaches enable faithful modeling when the resource is inacc
 essible from a modeling standpoint. Together\, they form a flexible founda
 tion for improving IBR representation and strengthening grid stability stu
 dies in diverse practical settings.</p>
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