Learning exact topology of a loopy power grid from ambient dynamics

Saurav Talukdar; Deepjyoti Deka; Blake Lundstrom; Misha Chertkov; Murti V. Salapaka

doi:10.1145/3077839.3077851

Learning exact topology of a loopy power grid from ambient dynamics

Saurav Talukdar, Deepjyoti Deka, Blake Lundstrom, Misha Chertkov, Murti V. Salapaka

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

11 Scopus citations

Abstract

Estimation of the operational topology of the power grid is necessary for optimal market settlement and reliable dynamic operation of the grid. This paper presents a novel framework for topology estimation for general power grids (loopy or radial) using time-series measurements of nodal voltage phase angles that arise from the swing dynamics. Our learning framework utilizes multivariate Wiener filtering to unravel the interaction between fluctuations in voltage angles at different nodes and identifies operational edges by considering the phase response of the elements of the multivariate Wiener filter. The performance of our learning framework is demonstrated through simulations on standard IEEE test cases.

Original language	English (US)
Title of host publication	e-Energy 2017 - Proceedings of the 8th International Conference on Future Energy Systems
Publisher	Association for Computing Machinery, Inc
Pages	222-227
Number of pages	6
ISBN (Electronic)	9781450350365
DOIs	https://doi.org/10.1145/3077839.3077851
State	Published - May 16 2017
Event	8th ACM International Conference on Future Energy Systems, e-Energy 2017 - Shatin, Hong Kong Duration: May 16 2017 → May 19 2017

Publication series

Name	e-Energy 2017 - Proceedings of the 8th International Conference on Future Energy Systems

Other

Other	8th ACM International Conference on Future Energy Systems, e-Energy 2017
Country/Territory	Hong Kong
City	Shatin
Period	5/16/17 → 5/19/17

Bibliographical note

Publisher Copyright:
© 2017 ACM.

Keywords

Dynamics
Loopy graphs
Power grid
Structure learning
Swing equations
Wiener filltering

Access

10.1145/3077839.3077851

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Full text

Cite this

Talukdar, S., Deka, D., Lundstrom, B., Chertkov, M., & Salapaka, M. V. (2017). Learning exact topology of a loopy power grid from ambient dynamics. In e-Energy 2017 - Proceedings of the 8th International Conference on Future Energy Systems (pp. 222-227). (e-Energy 2017 - Proceedings of the 8th International Conference on Future Energy Systems). Association for Computing Machinery, Inc. https://doi.org/10.1145/3077839.3077851

Learning exact topology of a loopy power grid from ambient dynamics. / Talukdar, Saurav; Deka, Deepjyoti; Lundstrom, Blake et al.
e-Energy 2017 - Proceedings of the 8th International Conference on Future Energy Systems. Association for Computing Machinery, Inc, 2017. p. 222-227 (e-Energy 2017 - Proceedings of the 8th International Conference on Future Energy Systems).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Talukdar, S, Deka, D, Lundstrom, B, Chertkov, M & Salapaka, MV 2017, Learning exact topology of a loopy power grid from ambient dynamics. in e-Energy 2017 - Proceedings of the 8th International Conference on Future Energy Systems. e-Energy 2017 - Proceedings of the 8th International Conference on Future Energy Systems, Association for Computing Machinery, Inc, pp. 222-227, 8th ACM International Conference on Future Energy Systems, e-Energy 2017, Shatin, Hong Kong, 5/16/17. https://doi.org/10.1145/3077839.3077851

Talukdar S, Deka D, Lundstrom B, Chertkov M, Salapaka MV. Learning exact topology of a loopy power grid from ambient dynamics. In e-Energy 2017 - Proceedings of the 8th International Conference on Future Energy Systems. Association for Computing Machinery, Inc. 2017. p. 222-227. (e-Energy 2017 - Proceedings of the 8th International Conference on Future Energy Systems). doi: 10.1145/3077839.3077851

Talukdar, Saurav ; Deka, Deepjyoti ; Lundstrom, Blake et al. / Learning exact topology of a loopy power grid from ambient dynamics. e-Energy 2017 - Proceedings of the 8th International Conference on Future Energy Systems. Association for Computing Machinery, Inc, 2017. pp. 222-227 (e-Energy 2017 - Proceedings of the 8th International Conference on Future Energy Systems).

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Learning exact topology of a loopy power grid from ambient dynamics

Abstract

Publication series

Other

Bibliographical note

Keywords

Access

OpenUrl availability

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