Optimization of the Capacity Value of Wind Farms using Windfarm Cluster Control
U. Fechner (TU Delft - Aerospace Engineering)
S. J. Watson (TU Delft - Aerospace Engineering)
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Abstract
Integrating larger amounts of wind energy into the grid would be easier if the grid operator could control the amount of wind power to match demand. Can the kinetic energy stored in the wind field be used to shift any high wind power peaks towards the demand peaks? To answer this question, FLORIDyn.jl was developed, a low-computational-cost dynamic wind farm model, and an innovative model-predictive control algorithm was used for controlling a wind farm cluster. By controlling not only one wind farm, but a wind farm cluster, it was possible to achieve time shifts in the energy delivered. The results show that by controlling the induction factor of nine turbine groups in three wind farms, it was possible to increase the power output during high demand by more than 2 % for about 30 minutes. This is a promising result, considering that no additional hardware would be required. Further research is needed to integrate a mesoscale model using more representative test case inflow conditions.
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