This work presents a distributed method for control centers to monitor the operating condition of a power network. Specifically we consider (static) state estimation problems, in which the state vector consists of the voltage magnitude and angle at all network buses. We consider the state to be linearly related to network measurements, which include power flows, current injections, and voltages phasors at some buses. We admit the presence of several cooperating control centers, and we design two distributed methods for them to compute the minimum variance estimate of the state given the network measurements. The two distributed methods rely on different modes of cooperation among control centers: in the first method an incremental mode of cooperation is assumed, whereas, in the second method, a diffusive interaction is implemented. These estimation methods, which are proved to converge in finite time, are further exploited to develop a distributed algorithm to detect corrupted data among network measurements.

A distributed method for state estimation and false data detection in power networks

CARLI, RUGGERO;
2011

Abstract

This work presents a distributed method for control centers to monitor the operating condition of a power network. Specifically we consider (static) state estimation problems, in which the state vector consists of the voltage magnitude and angle at all network buses. We consider the state to be linearly related to network measurements, which include power flows, current injections, and voltages phasors at some buses. We admit the presence of several cooperating control centers, and we design two distributed methods for them to compute the minimum variance estimate of the state given the network measurements. The two distributed methods rely on different modes of cooperation among control centers: in the first method an incremental mode of cooperation is assumed, whereas, in the second method, a diffusive interaction is implemented. These estimation methods, which are proved to converge in finite time, are further exploited to develop a distributed algorithm to detect corrupted data among network measurements.
2011
Proceedings of the IEEE International Conference on Smart Grid Communications (SmartGridComm), 2011
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/2532273
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