A Topology Identification Method to Enhance the Linear Estimation of Generator Rotor Speeds

This paper proposes a methodology to avoid biased estimations of generator rotor speeds under network topology changes. The algorithm is based on deep neural networks and executes topology processing considering the relevant branches for rotor speed estimations. The proposed technique uses the measurements from the same phasor measurement units (PMUs) needed to carry out generator rotor speed estimations; thus, it does not imply an additional cost for the transmission system operator. The proposed methodology is demonstrated with a centralized and distributed approach, using a modified version of the New England test system and the IEEE 118-bus test system, respectively. The numerical results on both test systems demonstrate the reliability and the low computational burden of the proposed algorithm.