Abstract
State estimation aims to estimate the optimal state variables that can represent the current state of a system based on the measurement set in the power system. The PMU (phasor measurement unit) is a key technology that can directly improve the performance of the monitoring, control and state estimation in the power system. The PMU enables the direct measurement of state variables such as voltage magnitude and phase angle. It also makes it possible to synchronize the measurement set using the GPS time stamp. To improve the performance of state estimation, it is not economical to place PMUs on all buses in the power system, so the PMU optimal placement must be determined. PMU optimal placement can be expressed as a limited optimization problem that secures the observability of the system with the placement of minimal PMUs by identifying the locations at which the PMUs should be installed. In this paper, we present the development of a PMU optimal placement algorithm that can determine the observability by searching the spanning tree of the graph, by which a topological connection relationship is created by measurement set.
Similar content being viewed by others
References
Abur A, Exposito AG (2004) Power system state estimation: theory and implementation. Marcel Dekker, Inc.
Clements KA, Krumpholz GR, Davis PW (1982) Power system state estimation with measurement deficiency: an algorithm that determines the maximal observable subnetwork. IEEE Trans Power Apparat Syst 101:3044–3052
Mori H, Tsuzuki S (1991) A fast method for topological observability analysis using a minimum spanning tree technique. IEEE Trans Power Systems 6:491–498
Nucera RR, Gilles ML (1991) Observability analysis: a new topological algorithm. IEEE Trans Power Syst 6:466–475
Kennedy J, Eberhart E (1997) A discrete binary version of particle swarm algorithm. In: IEEE computational cybernetics and simulation conference 5: 4104–4109
Hajain M, Ranjbar AM, Amraee T, Shirani AR (2007) Optimal placement of phasor measurement units: Particle swarm optimization approach. In: International conference intelligent systems and applications in power systems
Nuqui RF, Phadke AG (2005) Phasor measurement unit placement techniques for complete and incomplete observability. IEEE Trans Power Syst 20(4):2381–2388
Peng J, Sun Y, Wang HF (2006) Optimal PMU placement for full network observability using Tabu search algorithm. Elec Power Syst Res 28(4):223–231
Baldwin TL, Mili L, Boisen MB Jr, Adapa R (1993) Power system observability with minimal phasor measurement placement. IEEE Trans Power Syst 8(2):707–715
Rakpenthai C, Premrudeepreechacharn S, Uatrongjit S, Watson NR (2007) An optimal PMU placement method against measurement loss and branch outage. IEEE Trans Power Del 22(1):101–107
Gou B (2008) Generalized integer linear programming formulation for optimal PMU placement. IEEE Trans Power Syst 23(3):1099–1104
Gou B (2008) Optimal placement of PMUs by integer linear programming. IEEE Trans Power Syst 23(3):1525–1526
Xu B, Abur A (2004) Observability analysis and measurement placement for system with PMUs. In IEEE PES power systems conference and exposition 2:943–946
Dua D, Dambhare S, Gajbhiye RK, Soman SA (2008) Optimal multistage scheduling of PMU placement: an ILP approach. IEEE Trans Power Del 23(4):1812–1820
Aminifar F, Khodaei A, Fotuhi-Firuzabad M, Shahidehpour M (2010) Contingency-constrained PMU placement in power networks. IEEE Trans Power Syst 25(1):516–523
Asprou M, Kyriakides E (2011) Optimal PMU placement for improving hybrid state estimator accuracy, IEEE Power Tech 2011, Trondheim, Norway, p 1–7
Manousakis N, Korres G (2013) A weighted least squares algorithm for optimal PMU placement. Power Eng Lett 28(3):3499–3500
Chandrasekhar Y, Reddy KN, Masheswarapu S (2015) Optimal placement of PMU’s considering sensitivity analysis. In: International conference on TAP energy. Kollam, India
Akhlaghi S (2016) Optimal PMU placement considering contingency-constraints for power system observability and measurement redundancy. In: 2016 IEEE power and energy conference at Illinois, p 1–7
Wang H, Cheng C, Zong X (2016) Optimal PMU placement for the system observability based on system topology model. In: 2016 third international conf. on TSA. Wuhan, China
Lu C, Wang Z, Shen R, Yang Y (2018) An optimal PMU placement with reliable zero injection observation. IEEE Access 6:54417–54426
Acknowledgments
This work was supported by the Soonchunhyang University Research Fund (No. 20120669).
Funding
This research was supported by the Korea Electric Power Corporation (Grant number: R18XA06-76).
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Kim, BH., Kim, H. PMU Optimal Placement Algorithm Using Topological Observability Analysis. J. Electr. Eng. Technol. 16, 2909–2916 (2021). https://doi.org/10.1007/s42835-021-00822-5
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s42835-021-00822-5