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In this paper, the robust wake steering control concept for wind farms is presented based on the control functions of the neighboring wind turbines. In wind farms, to increase the total output power, the effects of wake on downstream wind turbines should be considered. Hence, in this research, for output power maximisation, a robust Adaptive Learning Game Theory (ALGT) optimisation method is developed. The proposed procedure is based on the game theory method, but that enables coordination via repeated interactions using control functions of the neighboring turbines in a wind farm for a squarely payoff-based scenario where the turbines have access only to measurements from their neighbors. This robust optimisation method in the presence of uncertainty enables an interaction framework that creates a set of joint control functions. In this method, each turbine makes an independent decision in every iteration based on the control laws of each localised areas.

Robust wake steering control design in a wind farm for power optimisation using adaptive learning game theory (ALGT) method