Proportional dispatch and fairness in wind farm power tracking

Abstract

Controlling the power output of a wind farm to track a target signal enables contributing to the power grid stability. This can be achieved by dividing the target signal into individual turbine power setpoints, which are then tracked by the corresponding turbine controllers. In this work, we address the problem of finding power allocations that fairly spread the power reserves (i.e. the unused fraction of available powers) among turbines, thereby improving robustness to uncertainties and varying wind conditions. Specifically, we investigate the fairness properties of proportional dispatch, the most widely used power allocation strategy. We show that, because of wake interactions within the wind farm, proportional dispatch must be applied iteratively to achieve fair distribution of power reserves. We study the convergence of the iterative proportional dispatch (IPD) process to equalized reserves, and then illustrate it using both steady-state and dynamic wind farm simulators. The numerical results show that IPD closely approximates max-min fairness, a related fairness criterion, while requiring significantly less computational effort than black-box optimization. Finally, we show that IPD also reduces the complexity of the problem of fair power dispatch combined with yaw wake steering optimization.