In attempting to control the power output of a wind farm, it is first necessary to smooth the power fluctuations due to wind turbulence. This is accomplished by spatial smoothing, whereby the high frequency power components of a single wind turbine generator (WTG) is reduced by a factor of N-1/2, where N is the number of WTGs in the farm. For this reason the first part of the thesis is concerned with developing a model of smoothing in a wind farm and justifying it mathematically.;After spatial smoothing, the wind farm output still contains low frequency fluctuations. The second part of the thesis makes use of a combination of: (i) pitch angle control of the turbine blades, (ii) power electronic control of the generators, (iii) spatial filtering and (iv) negative feedback control to remove the low frequency fluctuations. The wind farm output then has the quality to be sold as regulated power which fetches a better economic return than when sold as energy. This, of course, presumes that 1-hour ahead prediction of wind velocity at 1-hour long low variance is available.;The thesis also considers the case when the conditions for regulated power are not predicted. In this situation, the wind farm may opt to use the tracking mode which tracks the slowly time varying non-turbulent wind power. The thesis examines the possibility of diverting some of the wind farm power to implement dynamic performance enhancement strategies, for system damping for example.;The controllability of the wind farm is demonstrated by simulations of a wind farm made up of 24 wind turbine-generators (WTGs) using 1-hour long wind velocity data.
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