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Strong growth figures prove that wind is now a mainstream option for new power generation. All the successful megawatt-class wind technology developments to date are results of evolutionary design efforts based on the premise that control can significantly improve energy capture and reduce dynamic loads. The main challenge is wind stochasticity that impacts both power quality and drivetrain fatigue life for a wind generating system. In the proposed paradigm, control is exercised through a self-tuning regulator (STR) that incorporates a recursive least-squares algorithm to predict the process parameters and update the states. In above rated regimes, the control strategy incorporating a pitch regulatory system aims to regulate turbine power and maintain stable, closed-loop behavior in the presence of turbulent wind inflow. The control scheme is formulated based on a detailed performability model; the wind speed is generated by a stochastic model, while the drivetrain is modeled as a multiinertia system linked by a non- ideal (Ks ≠ ∞) shaft described by nonlinear equations. Computer simulations reveal that achieving the two objectives of maximizing energy extraction and load reduction by the STR becomes more attractive relative to the classical PID controller design. [ABSTRACT FROM AUTHOR]

Surge tests were performed to derive a generator model considering its frequency characteristics. Impulse voltages were applied to one terminal of the generators after placing a variable capacitor at the same terminal. The inductances and the core-loss resistances of a generator model can be determined from the measured oscillating voltages. This paper presents a generalization of the method aimed at deriving these generator parameters. The accuracy of the proposed method is confirmed to be satisfactory after comparing measured and simulated transfer voltages. [ABSTRACT FROM AUTHOR]