In this chapter, a distributed model predictive control (D-MPC) approach for optising active power of a wind farm is proposed. The control scheme is based on the fast gradient method via dual decomposition. The developed D-MPC approach is implemented using the clustering-based piecewise affine (PWA) wind turbine model, as described in Chapter 6.
The modern wind farm is required to operate much more like a conventional power plant and should ultimately replace conventional power plants. Specifically, for active power control, the wind farm must be capable of tracking the power references issued by the system operator.
Wind farm control can be implemented either by the utilization of a separate energy storage device or through derated operation of the wind turbines . In the latter case, the additional capital investment and maintenance cost of the energy storage system would be saved. Since the wind farm is required to produce less than the maximum possible power, the wind turbines must limit their power production. As long as the total power production of the farm meets demand, the wind turbines can vary their power production in response to wind speed fluctuations.
Conventionally, the dispatch function of each turbine is based on either the available power  or the actual output power . The conventional method focuses only ...