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Optimum Placement of Phasor Measurement Units in Power Systems.

, , , , , , and . IEEE Trans. Instrumentation and Measurement, 68 (2): 421-429 (2019)

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A Distributed Robust Power System State Estimation Approach Using $t$-Distribution Noise Model., , , , and . IEEE Syst. J., 15 (1): 1066-1076 (2021)An Agent-Based Distributed State Estimation Approach for Interconnected Power Systems., , , , and . IEEE Syst. J., 17 (2): 3016-3025 (June 2023)Optimum Placement of Phasor Measurement Units in Power Systems., , , , , , and . IEEE Trans. Instrumentation and Measurement, 68 (2): 421-429 (2019)Distributed State Estimation Using a Modified Partitioned Moving Horizon Strategy for Power Systems., , , and . Sensors, 17 (10): 2310 (2017)A Distributed Maximum-Likelihood-Based State Estimation Approach for Power Systems., , , , , and . IEEE Trans. Instrum. Meas., (2021)Dissipativity constraint for distributed power system state estimation., and . ICCAIS, page 360-365. IEEE, (2015)Robust Power System State Estimation Using t-Distribution Noise Model., , , and . IEEE Syst. J., 14 (1): 771-781 (2020)NSGA-III integrating eliminating strategy and dynamic constraint relaxation mechanism to solve many-objective optimal power flow problem., , , and . Appl. Soft Comput., (October 2023)Recursive maximum likelihood estimation with t-distribution noise model., , , , and . Autom., (2021)Iterated moving horizon estimation for power systems., , , , and . ICCAIS, page 81-86. IEEE, (2014)