University of Tasmania, Australia

Stochastic modelling of wind power and optimal stabilising control of wind turbines

Wind power is known to be a rich energy resource but very unstable. The effective use of such power is heavily depending on how we can cope with its instability. This is critical for the integration of wind turbine generators into electric power system due to the stability requirement of the later. This project aims to develop an effective control method for wind turbine generators to maximize its power generation and minimize the volatility of the ambient power system.

The research is based on the stochastic modelling of wind power system with possible meteorological information. Stochastic method is selected because of its suitable to model systems subject to random noises and uncertainties. The system model is updated according to meteorological predictions and corrected according to current and historical measurements. Wind turbine will be carefully modelled to reflect the particular performance of power generation associated with the stochastic wind model. The integrated system is then analysis in terms of its controllability and stabilizability. The stability requirement from power system is then carefully characterised for the wind turbine generator. Stochastic optimal control will be developed to meet such requirement. Based on that, efficient computation algorithm will be developed. A simulation system is to then be designed and developed to conduct simulation experiments and demonstrate the effectiveness of the proposed method.