Optimal PMU placement for power system state estimation using population-based algorithms incorporating observability requirements

Khokhlov, M. V.; Pozdnyakova, O. A.; Obusevs, Artjoms

doi:10.1109/RTUCON51174.2020.9316476

Publication type:	Conference paper
Type of review:	Not specified
Title:	Optimal PMU placement for power system state estimation using population-based algorithms incorporating observability requirements
Authors:	Khokhlov, M. V. Pozdnyakova, O. A. Obusevs, Artjoms
et. al:	No
DOI:	10.1109/RTUCON51174.2020.9316476
Proceedings:	2020 IEEE 61th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON)
Conference details:	61st International Scientific Conference on Power and Electrical Engineering, Riga, Latvia, 5-7 November 2020
Issue Date:	Jan-2021
Publisher / Ed. Institution:	IEEE
Language:	English
Subjects:	Experimental design; Observability; Optimal PMU placement; State estimation; Optimality criteria; Population-based optimisation algorithms
Subject (DDC):	621.3: Electrical, communications, control engineering
Abstract:	This paper is devoted to the problem of the phasor measurement units (PMUs) placement for power system state estimation using optimality criteria proposed by the theory of optimal experimental design, such as A-, D-, M-, I-, G-optimality criteria. The high complexity of the task posed limits on the possibilities of solving it by exact mathematical methods only to small scale power systems. The paper studies the possibility to use population-based optimization algorithms (Genetic Algorithm, Differential Evolution, Particle Swarm Optimization, and Ant Colony Optimization). To meet the state observability requirements, the repair procedure is incorporated in the population-based algorithms. This allows to overcome the drawbacks in the existing methods based on the assumption of a priory observability of the power system and to take into account the system contingencies such as the phasor failures, the PMU losses, and the branch outages. We demonstrate the effectiveness of the proposed method in terms of the PMU placement design's efficiency and computation efforts through the numerical simulations on a standard IEEE 118-bus system.
URI:	https://digitalcollection.zhaw.ch/handle/11475/22168
Fulltext version:	Submitted version
License (according to publishing contract):	Licence according to publishing contract
Departement:	School of Engineering
Organisational Unit:	Institute of Energy Systems and Fluid Engineering (IEFE)
Appears in collections:	Publikationen School of Engineering

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Khokhlov, M. V., Pozdnyakova, O. A., & Obusevs, A. (2021, January). Optimal PMU placement for power system state estimation using population-based algorithms incorporating observability requirements. 2020 IEEE 61th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON). https://doi.org/10.1109/RTUCON51174.2020.9316476

Khokhlov, M.V., Pozdnyakova, O.A. and Obusevs, A. (2021) ‘Optimal PMU placement for power system state estimation using population-based algorithms incorporating observability requirements’, in 2020 IEEE 61th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON). IEEE. Available at: https://doi.org/10.1109/RTUCON51174.2020.9316476.

M. V. Khokhlov, O. A. Pozdnyakova, and A. Obusevs, “Optimal PMU placement for power system state estimation using population-based algorithms incorporating observability requirements,” in 2020 IEEE 61th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON), Jan. 2021. doi: 10.1109/RTUCON51174.2020.9316476.

KHOKHLOV, M. V., O. A. POZDNYAKOVA und Artjoms OBUSEVS, 2021. Optimal PMU placement for power system state estimation using population-based algorithms incorporating observability requirements. In: 2020 IEEE 61th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON). Conference paper. IEEE. Januar 2021

Khokhlov, M. V., O. A. Pozdnyakova, and Artjoms Obusevs. 2021. “Optimal PMU Placement for Power System State Estimation Using Population-Based Algorithms Incorporating Observability Requirements.” Conference paper. In 2020 IEEE 61th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON). IEEE. https://doi.org/10.1109/RTUCON51174.2020.9316476.

Khokhlov, M. V., et al. “Optimal PMU Placement for Power System State Estimation Using Population-Based Algorithms Incorporating Observability Requirements.” 2020 IEEE 61th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON), IEEE, 2021, https://doi.org/10.1109/RTUCON51174.2020.9316476.