Wind farm control including grid support and load minimisation and (re)distribution

Abstract

Considering the increasing number of wind farms and the increasing proportion of renewable energy in the energy grid, wind farms will be more and more likely to supply ancillary services to the grid for significant periods at a time. Also, there is a trend towards overplanting offshore wind farms. These trends offers two opportunities; on the one hand, the better the ancillary services can be predicted and delivered, the more valuable they will be. On the other hand, it is an opportunity to allow the most heavily loaded wind turbines in the wind farm to operate at lower loads for a while and even out the wear-and-tear across the wind farm. Wind farm control has, understandably, been largely focused on maximizing the total power output of the wind farm, by balancing which turbines should capture the energy from the wind, wake redirection and even sinusoidal loading of the first row of wind turbines. It is also possible to take loading of the wind turbines in the farm into account, for instance using model predictive control. However, it has also been shown that fairly basic feedback control systems can already improve tracking behavior significantly. Because wind turbine controllers are in a much better position to control detailed loads on a wind turbine than the, rather low frequency, wind farm controller, the role of the wind farm controller should be assign power production to those wind turbines that are in the best position to produce at minimal cost (i.e. loads). The work presented here investigates a basic feedback control system that achieves power tracking but also redistributes loading across the wind farm to reduce the rate of damage of the whole farm and to relieve loading from the wind turbines that have accumulated the heaviest loads. The controller uses an online rainflow counting algorithm to keep track of loading and load rate and redistributes accordingly. The performance of the controller is tested using FastFarm and the interaction between the wind farm controller and the way the wind turbine controller implements the power setpoint is also investigated.