Automatic regionalization algorithm for distributed state estimation in power systems

Dexin Wang; Liuqing Yang; Anthony Florita; S. M.Shafiul Alam; Tarek Elgindy; Bri Mathias Hodge

doi:10.1109/GlobalSIP.2016.7905950

Automatic regionalization algorithm for distributed state estimation in power systems

Dexin Wang, Liuqing Yang, Anthony Florita, S. M.Shafiul Alam, Tarek Elgindy, Bri Mathias Hodge

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

3 Scopus citations

Abstract

The deregulation of the power system and the incorporation of generation from renewable energy sources recessitates faster state estimation in the smart grid. Distributed state estimation (DSE) has become a promising and scalable solution to this urgent demand. In this paper, we investigate the regionalization algorithms for the power system, a necessary step before distributed state estimation can be performed. To the best of the authors' knowledge, this is the first investigation on automatic regionalization (AR). We propose three spectral clustering based AR algorithms. Simulations show that our proposed algorithms outperform the two investigated manual regionalization cases. With the help of AR algorithms, we also show how the number of regions impacts the accuracy and convergence speed of the DSE and conclude that the number of regions needs to be chosen carefully to improve the convergence speed of DSEs.

Original language	English (US)
Title of host publication	2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	787-790
Number of pages	4
ISBN (Electronic)	9781509045457
DOIs	https://doi.org/10.1109/GlobalSIP.2016.7905950
State	Published - Apr 19 2017
Externally published	Yes
Event	2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Washington, United States Duration: Dec 7 2016 → Dec 9 2016

Publication series

Name	2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings

Other

Other	2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016
Country/Territory	United States
City	Washington
Period	12/7/16 → 12/9/16

Bibliographical note

Funding Information:
This work was supported in part by the National Science Foundation under grant number ECCS-1232305 and the U.S. Department of Energy under Contract No. DE-AC36-08-GO28308 with the National Renewable Energy Laboratory as part of the project work performed under the SunShot National Laboratory Multiyear Partnership.

Publisher Copyright:
© 2016 IEEE.

Keywords

Automatic regionalization
Distributed state estimation
Partitioning
Power system operations
Spectral clustering

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Publisher link

10.1109/GlobalSIP.2016.7905950

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Wang, D., Yang, L., Florita, A., Alam, S. M. S., Elgindy, T., & Hodge, B. M. (2017). Automatic regionalization algorithm for distributed state estimation in power systems. In 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings (pp. 787-790). Article 7905950 (2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GlobalSIP.2016.7905950

Automatic regionalization algorithm for distributed state estimation in power systems. / Wang, Dexin; Yang, Liuqing; Florita, Anthony et al.
2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. p. 787-790 7905950 (2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings).

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

Wang, D, Yang, L, Florita, A, Alam, SMS, Elgindy, T & Hodge, BM 2017, Automatic regionalization algorithm for distributed state estimation in power systems. in 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings., 7905950, 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 787-790, 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016, Washington, United States, 12/7/16. https://doi.org/10.1109/GlobalSIP.2016.7905950

Wang D, Yang L, Florita A, Alam SMS, Elgindy T, Hodge BM. Automatic regionalization algorithm for distributed state estimation in power systems. In 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2017. p. 787-790. 7905950. (2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings). doi: 10.1109/GlobalSIP.2016.7905950

Wang, Dexin ; Yang, Liuqing ; Florita, Anthony et al. / Automatic regionalization algorithm for distributed state estimation in power systems. 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 787-790 (2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings).

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abstract = "The deregulation of the power system and the incorporation of generation from renewable energy sources recessitates faster state estimation in the smart grid. Distributed state estimation (DSE) has become a promising and scalable solution to this urgent demand. In this paper, we investigate the regionalization algorithms for the power system, a necessary step before distributed state estimation can be performed. To the best of the authors' knowledge, this is the first investigation on automatic regionalization (AR). We propose three spectral clustering based AR algorithms. Simulations show that our proposed algorithms outperform the two investigated manual regionalization cases. With the help of AR algorithms, we also show how the number of regions impacts the accuracy and convergence speed of the DSE and conclude that the number of regions needs to be chosen carefully to improve the convergence speed of DSEs.",

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N2 - The deregulation of the power system and the incorporation of generation from renewable energy sources recessitates faster state estimation in the smart grid. Distributed state estimation (DSE) has become a promising and scalable solution to this urgent demand. In this paper, we investigate the regionalization algorithms for the power system, a necessary step before distributed state estimation can be performed. To the best of the authors' knowledge, this is the first investigation on automatic regionalization (AR). We propose three spectral clustering based AR algorithms. Simulations show that our proposed algorithms outperform the two investigated manual regionalization cases. With the help of AR algorithms, we also show how the number of regions impacts the accuracy and convergence speed of the DSE and conclude that the number of regions needs to be chosen carefully to improve the convergence speed of DSEs.

AB - The deregulation of the power system and the incorporation of generation from renewable energy sources recessitates faster state estimation in the smart grid. Distributed state estimation (DSE) has become a promising and scalable solution to this urgent demand. In this paper, we investigate the regionalization algorithms for the power system, a necessary step before distributed state estimation can be performed. To the best of the authors' knowledge, this is the first investigation on automatic regionalization (AR). We propose three spectral clustering based AR algorithms. Simulations show that our proposed algorithms outperform the two investigated manual regionalization cases. With the help of AR algorithms, we also show how the number of regions impacts the accuracy and convergence speed of the DSE and conclude that the number of regions needs to be chosen carefully to improve the convergence speed of DSEs.

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Automatic regionalization algorithm for distributed state estimation in power systems

Abstract

Publication series

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Bibliographical note

Keywords

UN SDGs

Publisher link

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