Game theory-based optimal deloading control of wind turbines under scalable structures of wind farm

This study addresses the problem of how to harvest as much kinetic energy as possible during deloading control of variable speed wind turbines (VSWTs) by distributedly adjusting rotor speeds under scalable wind farm topology. To that end, a game theory-based distributed control framework is investigated to enable the optimal rotor speed setting of VSWTs such that maximal kinetic energy can be stored in rotating masses of VSWTs for further system support, and meanwhile, the power dispatch objective for VSWTs can be fulfilled. It is shown that through distributedly detecting the changing network topologies within wind farm, the proposed methodology enables individual VSWT to adaptively increase its stored kinetic energy while requiring only local information sharing. It is important both theoretically and practically that the design has autonomously guaranteed maximal kinetic energy storing for all VSWTs in wind farm of time varying topologies and provides robustness, scalability and efficiency in the absence of global information sharing. Simulation results and case studies are included to demonstrate the effectiveness of the proposed controls both in Matlab and DIgSILENT/PowerFactory.