Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Siddharth Bhela"'
Autor:
Bruno P. Leao, Jagannadh Vempati, Ulrich Muenz, Shashank Shekhar, Amit Pandey, David Hingos, Siddharth Bhela, Jing Wang, Chris Bilby
Publikováno v:
2022 IEEE Conference on Communications and Network Security (CNS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::81cd5cacaa158dccca1237e8888d6b34
https://doi.org/10.1109/cns56114.2022.9947256
https://doi.org/10.1109/cns56114.2022.9947256
Publikováno v:
2022 IEEE Power & Energy Society General Meeting (PESGM).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5d57a35a0355dabe14d8edb4164c4f7a
https://doi.org/10.1109/pesgm48719.2022.9916762
https://doi.org/10.1109/pesgm48719.2022.9916762
Synchronized data provide unprecedented opportunities for inferring voltage frequencies and rates of change of frequencies (ROCOFs) across the buses of a power system. Aligned to this goal, this work puts forth a novel framework for learning dynamics
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::00e16722c4857f82934ffc6ac6311923
https://hdl.handle.net/10919/108756
https://hdl.handle.net/10919/108756
Publikováno v:
IEEE Transactions on Power Systems. 34:3537-3546
This two-part work puts forth the idea of engaging power electronics to probe an electric grid to infer non-metered loads. Probing can be accomplished by commanding inverters to perturb their power injections and record the induced voltage response.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e2110d18da16a1084b1fa6a06867e07e
https://doi.org/10.1109/tpwrs.2019.2906306
https://doi.org/10.1109/tpwrs.2019.2906306
Synchrophasor data provide unprecedented opportunities for inferring power system dynamics, such as estimating voltage angles, frequencies, and accelerations along with power injection at all buses. Aligned to this goal, this work puts forth a novel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::800e40943de07d4b2699c20d61cca7b2
http://arxiv.org/abs/2105.12608
http://arxiv.org/abs/2105.12608
The dynamic response of power grids to small disturbances influences their overall stability. This paper examines the effect of network topology on the linearized time-invariant dynamics of electric power systems. The proposed framework utilizes ${\c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c2a2dcbd051acef76782a12bd61992ad
Publikováno v:
ACC
The dynamic response of power grids to small transient events or persistent stochastic disturbances influences their stable operation. This paper studies the effect of topology on the linear time-invariant dynamics of power networks. For a variety of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::783ca95c4f2906aebd37b1062cea3d65
Autor:
Lampros Svolos, Morgan E. Gorris, Kayla Diann Davie, Jacob Paul Tavenner, Levi Lystrom, D. L. Danielson, Luke Clyde Adams, Katherine Candice Kempfert, Kristin Nicole Mackowski, Brendan Alan Smith, Michael Sakano, Kaitlyn Scheib, Phuong Nguyen Uyen Chau, Jessica Conrad, Siddharth Bhela, Jeannie Marie Leesman, Kenneth C. Sockwell, Sina G. Lewis, Marilyn Leann Ramsey, Barton Jed Brown, Roman I. Zubatyuk, Kaitlyn Martinez, Sabine Silvia Zentgraf, Biswas Rijal, Michael John Gonzales, Bowen Li, Colin Mackenzie Adams, Jamil Gafur, Lewis R. Baker
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5164589819c2d28f47959859a32416ae
https://doi.org/10.2172/1481962
https://doi.org/10.2172/1481962
Distribution grids currently lack comprehensive real-time metering. Nevertheless, grid operators require precise knowledge of loads and renewable generation to accomplish any feeder optimization task. At the same time, new grid technologies, such as
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3d18894513cfa910a2521dd2d2266775
Publikováno v:
2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f41b302e6d5a1cc4a12146cc056f815a
https://doi.org/10.1109/camsap.2017.8313220
https://doi.org/10.1109/camsap.2017.8313220