TY - JOUR
T1 - The Grid Event Signature Library
T2 - An Open-Access Repository of Power System Measurement Signatures
AU - Wilson, Aaron J.
AU - Riza Ekti, Ali
AU - Follum, Jim
AU - Biswas, Shuchismita
AU - Annalicia, Christabella
AU - Joo, Jhi Young
AU - Aziz, Omer
AU - Lian, Jamie
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2024
Y1 - 2024
N2 - The power grid is undergoing massive changes, driven by the need to improve both reliability and resiliency, as well as meeting goals intended to combat climate change. Many solutions to such problems will require vast amounts of data. Almost all measurement, control - and in the future, artificial intelligence (AI) - systems utilize sensing mechanisms designed to capture, transmit, or even act on voltage and/or current measurement parsing and characterization. In this paper, a free, open-access online repository of such grid signatures is presented with the intent of encouraging open sharing of power grid data for the development of artificial intelligence and data-driven applications to meet the goals of tomorrow's grid. Known as the Grid Event Signature Library, or GESL, this Department of Energy-funded endeavour has seen a growth of over 200 users worldwide since its inception.
AB - The power grid is undergoing massive changes, driven by the need to improve both reliability and resiliency, as well as meeting goals intended to combat climate change. Many solutions to such problems will require vast amounts of data. Almost all measurement, control - and in the future, artificial intelligence (AI) - systems utilize sensing mechanisms designed to capture, transmit, or even act on voltage and/or current measurement parsing and characterization. In this paper, a free, open-access online repository of such grid signatures is presented with the intent of encouraging open sharing of power grid data for the development of artificial intelligence and data-driven applications to meet the goals of tomorrow's grid. Known as the Grid Event Signature Library, or GESL, this Department of Energy-funded endeavour has seen a growth of over 200 users worldwide since its inception.
KW - Artificial intelligence
KW - data-driven applications
KW - power systems
KW - signatures
UR - http://www.scopus.com/inward/record.url?scp=85194086461&partnerID=8YFLogxK
U2 - 10.1109/ACCESS.2024.3404886
DO - 10.1109/ACCESS.2024.3404886
M3 - Article
AN - SCOPUS:85194086461
SN - 2169-3536
VL - 12
SP - 76207
EP - 76218
JO - IEEE Access
JF - IEEE Access
ER -