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Trading Energy Yield for Frequency Regulation: Optimal Control of Kinetic Energy in Wind Farms

机译:交易能量产量以进行频率调节:风电场中动能的最佳控制

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The burden on conventional units to regulate the system frequency increases if they are replaced due to wind farms. This paper explores up to which time scales the rotating kinetic energy in wind turbines can smooth frequency variations and assist with the regulation task. To this end, a comparison is made between a standard wind turbine controller and optimal control of wind turbines, respectively derived from causal time-domain simulations and an optimization algorithm that allows predicting. The latter algorithm is used to give a benchmark for the smoothing potential, shown by plotting the Pareto efficiency of the normalized standard deviation of frequency variability versus a normalized measure of the energy yield. Results indicate that smoothing comes with an energy loss that is determined by the energy content of power imbalances. It is shown that a wind share of 20%, within the instantaneous generation mix, can absorb frequency variations on timescales up to 100 sec while the energy loss is limited to only 2%. A higher share of wind power aggravates frequency variability. Nevertheless, in such circumstances the potential of rotating kinetic energy in wind farms increases.
机译:如果由于风电场而更换了常规机组,则调节系统频率的负担就会增加。本文探讨了风轮机中的旋转动能可以在多大程度上缩放频率变化并协助调节任务。为此,在分别从因果时域模拟和允许预测的优化算法中得出的标准风力涡轮机控制器和风力涡轮机的最佳控制之间进行了比较。后一种算法用于提供平滑潜力的基准,通过绘制频率可变性的标准化标准差的Pareto效率对能量产量的标准化度量来绘制。结果表明,平滑带来的能量损耗取决于功率不平衡的能量含量。结果表明,在瞬时发电混合中,风能份额为20%,可以吸收高达100秒的时标上的频率变化,而能量损失仅限制为2%。更高比例的风能加剧了频率可变性。然而,在这种情况下,风电场中旋转动能的潜力增加了。

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