4.6 Article

Optimal PMU placement approach for power systems considering non-Gaussian measurement noise statistics

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.ijepes.2020.106577

Keywords

Optimal PMU placement; Robust estimator; Non-Gaussian noise; Influence function; State estimation

Funding

  1. National Natural Science Foundation of China [61903314]
  2. Basic Research Program of Science and Technology of Shenzhen, China [JCYJ20190809162807421]
  3. Natural Science Foundation of Fujian Province [2019J05020, 2018J01098]

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This study proposes a new optimal PMU placement approach considering different types of measurement noise and robust estimators, utilizing D-optimal and E-optimal experiment criterions, and evaluates the performance of the proposed method through simulations on IEEE 57-bus system and Polish 2383-bus system.
This paper investigates how to add a limited number of Phasor Measurement Units (PMUs) to the existing monitoring system so as to improve the estimation accuracy further. The existing methods are usually based on Gaussian noise assumption and the weighted least squares (WLS) estimator is taken into account. However, the Gaussian noise assumption is not always true in reality and the WLS is non-robust in this case. This paper proposes a new optimal PMU placement approach where the distribution of measurement noise can be non Gaussian or Gaussian and many robust estimators such as the maximum likelihood estimator, Multiple Segment, Quadratic-Linear, Square-Root and Schweppe-Huber Generalized-M estimator are considered. Based on the new Gain matrix obtained from the influence function approximation, the D-optimal and E-optimal experiment criterions are exploited in the optimal PMU placement problem. A convex relaxation in conjunction with an optimization improvement method based on the Fedorov exchange algorithm is utilized to solve the optimizing problem. Simulations on the IEEE 57-bus system and the Polish 2383-bus system are carried out to evaluate the effective performance of the proposed approach.

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