Data-driven Localization and Estimation of Disturbance in the Interconnected Power System
Author(s)Lee, Hyang-Won; Zhang, Jianan; Modiano, Eytan H.
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Identifying the location of a disturbance and its magnitude is an important component for stable operation of power systems. We study the problem of localizing and estimating a disturbance in the interconnected power system. We take a model-free approach to this problem by using frequency data from generators. Specifically, we develop a logistic regression based method for localization and a linear regression based method for estimation of the magnitude of disturbance. Our model-free approach does not require the knowledge of system parameters such as inertia constants and topology, and is shown to achieve highly accurate localization and estimation performance even in the presence of measurement noise and missing data. ©2018
DepartmentMassachusetts Institute of Technology. Department of Aeronautics and Astronautics; Massachusetts Institute of Technology. Laboratory for Information and Decision Systems
IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids
Institute of Electrical and Electronics Engineers (IEEE)
Lee, Hyang-Won, Jianan Zhang, and Eytan Modiano, "Data-driven Localization and Estimation of Disturbance in the Interconnected Power System." 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm 2018), Oct. 29-31, 2018, Aalborg, Denmark (Piscataway, N.J.: IEEE, 2018): p. 1-6 doi 10.1109/SMARTGRIDCOMM.2018.8587509 ©2018 Author(s)