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Dynamic state estimation in power systems is based on the extended Kalman filter (EKF) scheme. The EKF system uses a linearised measurement equation, neglecting the nonlinearities of the measurement function. Under certain circumstances (e.g. large load changes) this leads to degradation in the filter performance. Two algorithms are proposed for dynamic state estimation which incorporate the measurement function nonlinearities in the EKF scheme. The performance of the schemes are compared with the standard linear EKF scheme under various conditions and comparative results are presented.