research-article

On the impact of PMU placement on observability and cross-validation

Authors:

Daniel Gyllstrom,

Elisha Rosensweig,

Jim KuroseAuthors Info & Claims

e-Energy '12: Proceedings of the 3rd International Conference on Future Energy Systems: Where Energy, Computing and Communication Meet

Article No.: 20, Pages 1 - 10

https://doi.org/10.1145/2208828.2208848

Published: 09 May 2012 Publication History

Abstract

Significant investments have been made into deploying phasor measurement units (PMUs) on electric power grids worldwide. PMUs allow the state of the power system -- the voltage phasor of system buses and current phasors of all incident transmission lines -- to be directly measured. In some cases, it is also possible to infer the voltage and current phasors at neighboring buses and lines. Because PMUs are expensive, it is typically not possible to deploy enough PMUs to observe all phasors in a grid network [3, 6].

In this paper, we prove the NP-Completeness of four problems relating to PMU placements at a subset of system buses to achieve different goals: FullObserve, MaxObserve, FullObserve-XV, and MaxObserve-XV. FullObserve considers the minimum number of PMUs needed to observe all nodes, while MaxObserve considers the maximum number of buses that can be observed with a given number of PMUs. While the first of these two has been considered in the past, our formulation here generalizes the systems being considered. Next, FullObserve-XV and MaxObserve-XV consider these two problems under the constraints that PMUs must be placed "close" to each other so their measurements can be cross-validated. FullObserve-XV considers observing the entire network, while MaxObserve-XV considers maximizing the number of observed buses under this new constraint.

Motivated by their high complexity, for each problem we investigate the performance of a suitable greedy approximation algorithm for PMU placement. Through simulations, we compare the performance of these algorithms with the optimal placement of PMUs over several IEEE bus systems as well as over synthetic graphs. In our simulations these algorithms yield results that are close to optimal - for all four placement problems, the greedy algorithms yield, on average, a PMU placement that is within 97% of optimal.

References

[1]

Synchro-Phasor Data Validation. Technical report, North-American Synchro-Phasor Initative, October 2010.

[2]

A. Aazami and M. D. Stilp. Approximation Algorithms and Hardness for Domination with Propagation. CoRR, abs/0710.2139, 2007.

[3]

T.L. Baldwin, L. Mili, Jr. Boisen, M. B., and R. Adapa. Power System Observability with Minimal Phasor Measurement Placement. Power Systems, IEEE Transactions on, 8(2):707--715, May 1993.

[4]

D. J. Brueni and L. S. Heath. The PMU Placement Problem. SIAM Journal on Discrete Mathematics, 19(3):744--761, 2005.

Digital Library

[5]

J. Chen and A. Abur. Placement of PMUs to Enable Bad Data Detection in State Estimation. Power Systems, IEEE Transactions on, 21(4):1608--1615, 2006.

[6]

J. De La Ree, V. Centeno, J. S. Thorp, and A. G. Phadke. Synchronized Phasor Measurement Applications in Power Systems. Smart Grid, IEEE Transactions on, 1(1):20--27, 2010.

[7]

M.R. Garey and D. S. Johnson. Computers and Intractability: A Guide to the Theory of NP-Completeness. W. H. Freeman & Co., New York, NY, USA, 1979.

Digital Library

[8]

D. Gyllstrom, E. Rosensweig, and J. Kurose. Max Observability PMU Placement with Cross-Validation. Technical Report UM-CS-2011-014.

[9]

D. Gyllstrom, E. Rosensweig, and J. Kurose. On the Impact of PMU Placement on Observability and Cross-Validation. Technical Report UM-CS-2012-001.

[10]

T. W. Haynes, S. M. Hedetniemi, S. T. Hedetniemi, and M. A. Henning. Domination in Graphs Applied to Electric Power Networks. SIAM J. Discret. Math., 15:519--529, April 2002.

Digital Library

[11]

D. Lichtenstein. Planar Formulae and Their Uses. SIAM J. Comput., 11(2):329--343, 1982.

Digital Library

[12]

L. Mili, T. Baldwin, and R. Adapa. Phasor Measurement Placement for Voltage Stability Analysis of Power Systems. In Decision and Control, 1990., Proceedings of the 29th IEEE Conference on, pages 3033--3038 vol.6, December 1990.

[13]

L. Vanfretti. Phasor Measurement-Based State-Estimation of Electrical Power Systems and Linearized Analysis of Power System Network Oscillations. PhD thesis, Rensselaer Polytechnic Institute, December 2009.

[14]

L. Vanfretti, J. H. Chow, S. Sarawgi, and B. (B.). Fardanesh. A Phasor-Data-Based State Estimator Incorporating Phase Bias Correction. Power Systems, IEEE Transactions on, 26(1):111--119, Feb 2011.

[15]

B. Xu and A. Abur. Observability Analysis and Measurement Placement for Systems with PMUs. In Proceedings of 2004 IEEE PES Conference and Exposition, vol.2, pages 943--946, 2004.

[16]

B. Xu and A. Abur. Optimal Placement of Phasor Measurement Units for State Estimation. Technical Report PSERC Publication 05--58, October 2005.

[17]

J. Zhang, G. Welch, and G. Bishop. Observability and Estimation Uncertainty Analysis for PMU Placement Alternatives. In North American Power Symposium (NAPS), 2010, pages 1--8, 2010.

Cited By

Agarwal ARamamritham K(2022)A Novel Approach for Deploying Minimum Sensors in Smart BuildingsACM Transactions on Cyber-Physical Systems10.1145/34779296:1(1-29)Online publication date: 31-Jan-2022
https://dl.acm.org/doi/10.1145/3477929
Agarwal A(2022)A Novel Polynomial Time Heuristic Algorithm for Minimal PMU Allocation in the GridSoft Computing: Theories and Applications10.1007/978-981-19-0707-4_60(661-671)Online publication date: 2-Jun-2022
https://doi.org/10.1007/978-981-19-0707-4_60
Agarwal ARamamritham K(2020)Tackling Issues Related to PMU Deployment in the Grid using a Novel Algorithm2020 IEEE First International Conference on Smart Technologies for Power, Energy and Control (STPEC)10.1109/STPEC49749.2020.9297698(1-6)Online publication date: 25-Sep-2020
https://doi.org/10.1109/STPEC49749.2020.9297698
Show More Cited By

Index Terms

On the impact of PMU placement on observability and cross-validation
1. Security and privacy
  1. Network security

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cover image ACM Other conferences

e-Energy '12: Proceedings of the 3rd International Conference on Future Energy Systems: Where Energy, Computing and Communication Meet

May 2012

250 pages

ISBN:9781450310550

DOI:10.1145/2208828

General Chairs:
Marco Ajmone Marsan
Politecnico di Torino, Italy, and Institute IMDEA Networks, Spain
,
Suresh Goyal
Alcatel-Lucent Bell Labs
,
Shugong Xu
Huawei Technologies, China
,
Program Chairs:
Antonio Fernández
Anta Institute IMDEA Networks, Spain
,
Milan Prodanovic
Institute IMDEA Energy, Spain
,
Ken Christensen
University of South Florida

Copyright © 2012 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 09 May 2012

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e-Energy'12

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e-Energy'12: 3rd International Conference on Energy-Efficient Computing and Networking

May 9 - 11, 2012

Madrid, Spain

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Overall Acceptance Rate 160 of 446 submissions, 36%

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Cited By

Agarwal ARamamritham K(2022)A Novel Approach for Deploying Minimum Sensors in Smart BuildingsACM Transactions on Cyber-Physical Systems10.1145/34779296:1(1-29)Online publication date: 31-Jan-2022
https://dl.acm.org/doi/10.1145/3477929
Agarwal A(2022)A Novel Polynomial Time Heuristic Algorithm for Minimal PMU Allocation in the GridSoft Computing: Theories and Applications10.1007/978-981-19-0707-4_60(661-671)Online publication date: 2-Jun-2022
https://doi.org/10.1007/978-981-19-0707-4_60
Agarwal ARamamritham K(2020)Tackling Issues Related to PMU Deployment in the Grid using a Novel Algorithm2020 IEEE First International Conference on Smart Technologies for Power, Energy and Control (STPEC)10.1109/STPEC49749.2020.9297698(1-6)Online publication date: 25-Sep-2020
https://doi.org/10.1109/STPEC49749.2020.9297698
Agarwal ARamamritham K(2020)A comparison of novel optimization model and algorithm for solving PMU deployment issues in the gridSādhanā10.1007/s12046-020-01522-y45:1Online publication date: 18-Nov-2020
https://doi.org/10.1007/s12046-020-01522-y
Ogawa SMori H(2018)Application of Moment Matching Method to Optimal Allocation of PMUs in State EstimationIEEJ Transactions on Power and Energy10.1541/ieejpes.138.124138:2(124-130)Online publication date: 2018
https://doi.org/10.1541/ieejpes.138.124
Tesfay TLe Boudec JSvensson O(2018)Optimal Software Patching Plan for PMUsIEEE Transactions on Smart Grid10.1109/TSG.2017.27142049:6(6500-6510)Online publication date: Nov-2018
https://doi.org/10.1109/TSG.2017.2714204
Mohamed Mohamud AWu JLong CLi S(2016)Minimum Phasor measurement unit placement for partial observability of power system2016 35th Chinese Control Conference (CCC)10.1109/ChiCC.2016.7554952(10085-10089)Online publication date: Jul-2016
https://doi.org/10.1109/ChiCC.2016.7554952
Li WVanfretti L(2015)A PMU-based state estimator considering classic HVDC links under different control modesSustainable Energy, Grids and Networks10.1016/j.segan.2015.04.0042(69-82)Online publication date: Jun-2015
https://doi.org/10.1016/j.segan.2015.04.004
Abood HSreeram V(2014)A review on phasor measurement units placement for state estimation studies2014 Australasian Universities Power Engineering Conference (AUPEC)10.1109/AUPEC.2014.6966493(1-6)Online publication date: Sep-2014
https://doi.org/10.1109/AUPEC.2014.6966493

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