Analysis of ultrasonic non destructive evaluation data using singular value decomposition of the Hankel data matrix

A multi-machine power system excitation predictive control method using balanced reduced model is presented. First, the theory of empirical Gramians balanced reduction was used to reduce the orders of power system non-linear dynamic model to save the time-solving of open-loop optimisation in model predictive control. Then, it used the minimum deviation of system output(state) and control input as the control objective, using the non-linear reduced system sampling linearisation model as equivalent constraints and the change limits of system output and control input as unequivalent constraints to establish the excitation predictive control model based on reduced model. Next, the interior-point method was used to solve the optimal control problem. Finally, took advantage of a four-machine power system to verify the effectiveness of the predictive control method, and the simulating results show that excitation predictive control method using balanced reduced model for the multi-machine power systems can greatly shorten the optimisation time-calculating, meanwhile maintain the voltages of generator terminals within the set points and have a better control performance than traditional excitation control.

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“…S [ R n×n is the Hankel singular value matrix [19], and its singular values meet s 1 ≥ s 2 ≥ · · · ≥ s n .…”

Section: Empirical Gramians Matrixmentioning

confidence: 99%

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