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A Matlab/Simulink based tool for developing fast simulation wind farm models has been proposed. The wind farm development tool accepts user defined parameters such as mean wind speed, turbulent intensity wind farm layout and etc. to develop a wind farm model. The wind farm model contains the 5MW Supergen wind turbine dynamics suitable for controller design, a wind-field model based on the Veers algorithm for generating turbulent wind-field, and wake models based on the Frandsen analytical wake modelling technique for representing the wake propagation through the wind farm. The developed wind farm model is suitable for active power control and developing control algorithms for primary frequency response.

Failure of offshore wind turbine components is one of the main contributors to the O&M cost and in turn the cost of energy from offshore wind. In order to try and reduce the O&M costs a clear understanding of what drives these failures must be obtained. This paper aims to find a correlation between weather conditions and turbine failures. Site conditions examined include, amongst others, wind speed, turbulence intensity and turbine positioning in the wind farm. Exact turbine and wind farm numbers, rated power and blade size cannot be provided for confidentiality reasons. The findings of this analysis show that, weather conditions are a key factor to offshore turbine failures.

Collective control of a small cluster of wind turbines using a single controller is investigated to enable simplification of the turbines. For simplicity, reduced cost, and possibly improved reliability, each turbine is constant speed stall regulated. In return, each turbine experiences reduced energy capture and increased loads, and these disadvantages become greater as the number of wind turbines in the cluster increases. In this paper, a cluster consisting of 5 turbines is assessed in comparison to the situation with each turbine having its own converter and controller. A new collective control strategy that acts in response to the poorest control is proposed as opposed to acting in response to the average control. The control strategy is applied to a cluster model, which is also developed in this paper by modifying a Matlab/SIMULINK® simulation model of the SUPERGEN 5MW exemplar wind turbine, and simulation results demonstrate that the control strategy could be more cost effective than each turbine having its own converter and controller, especially with optimal design of rotors.

A coordinated power system stabiliser (PSS) design for wind turbine equipped with doubly-fed induction generator (DFIG) is presented in this paper. It is shown that the proposed control scheme enables the optimal performance for both the wind turbine structural loads damping and the power system damping. The interaction between wind turbine controller and PSS is studied by simulation. A holistic model including both the wind turbine and the electric network dynamics is employed for the assessment of controller performance. The influence of PSS control on wind turbine drive-train and tower are demonstrated. A generic network model is used to test the contribution that wind farm can make to the power system damping. It is shown that wind turbine is capable of providing similar damping response as synchronous generator do with acceptable increase of structural loads.