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Profitability optimization of a wind power plant performed through parabolic RANS simulations and an economic model

机译：通过抛物线RANS模拟和经济模型对风电厂进行盈利能力优化

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This work focuses on the optimization of performance and profitability of a wind farm carried out by means of an economic model and Reynolds-Averaged Navier-Stokes (RANS) simulations of wind turbine wakes. Axisymmetric RANS simulations of isolated wind turbine wakes are leveraged with a quadratic super-positioning model to estimate wake interactions within wind farms. The resulting velocity field is used with an actuator disk model to predict power production from each turbine in the wind farm. Design optimization is performed by considering a site in North Texas, whose wind resource statistics are obtained from a meteorological tower. The RANS solver provides capabilities to simulate different incoming wind turbulence intensities and, hence, the wind farm optimization is performed by taking the daily cycle of the atmospheric stability into account. The objective functional of the optimization problem is the levelized cost of energy (LCoE) encompassing capital cost, operation and maintenance costs, land cost and annual power production. At the first level of the optimization problem, the wind farm gross capacity is determined by considering three potential turbine types with different rated power. Subsequently, the optimal wind farm layout is estimated by varying the uniform spacing between consecutive turbine rows. It is found that increasing turbine rated power, the wind farm profitability is enhanced. Substituting a wind farm of 24 turbines of 2.3-MW rated power with 18, 3-MW turbines could reduce the LCoE of about 1.56 $/MWh, while maintaining a similar gross capacity factor. The optimization of the spacing between turbine rows was found to be sensitive to the land cost. For a land cost of 0.05 $/m~2 , the layout could be designed with a spacing between 6 to 15 rotor diameters without any significant effect on the LCoE, while an increased land cost of 0.1 $/m~2 leads to an optimal spacing of about 6 rotor diameters.
机译：这项工作的重点是通过经济模型和雷诺平均Navier-Stokes（RANS）对风力涡轮机尾流的仿真来优化风电场的性能和盈利能力。隔离式风力涡轮机尾流的轴对称RANS仿真与二次叠加模型一起用于估算风电场内的尾流相互作用。生成的速度场与执行器盘模型一起使用，以预测风电场中每个涡轮机的发电量。通过考虑北德克萨斯州的一个站点进行设计优化，该站点的风能统计数据是从气象塔获得的。 RANS求解器提供了模拟不同传入风湍流强度的功能，因此，通过考虑大气稳定性的每日周期来进行风电场优化。优化问题的目标功能是能源的平均成本（LCoE），包括资本成本，运营和维护成本，土地成本和年发电量。在优化问题的第一级，通过考虑三种具有不同额定功率的潜在涡轮机类型来确定风电场的总容量。随后，通过改变连续的涡轮机排之间的均匀间隔来估计最佳风电场布局。发现增加涡轮机的额定功率后，风电场的盈利能力得到提高。用18台3兆瓦的风机代替24台额定功率为2.3兆瓦的风机的风电场，可以降低LCoE约1.56美元/兆瓦时，同时保持类似的总容量系数。发现涡轮机排之间的间隔的优化对土地成本敏感。对于土地成本为0.05 $ / m〜2的情况，可以将布局设计为6到15个转子直径之间的间距，而不会对LCoE产生任何重大影响，而增加的土地成本为0.1 $ / m〜2则可以实现最优约6个转子直径的间距。

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  • 来源
    《Wind energy symposium 2018》|2018年|644-653|共10页
  • 会议地点 Kissimmee(US)
  • 作者

    V. Santhanagopalan; L.Y. Al-Hamidi; S. Letizia; L. Zhan; G. V. Iungo;

  • 作者单位

    The. University of Texas at Dallas, Mechanical Engineering Department, 75080 Richardson. TX;

    The. University of Texas at Dallas, Mechanical Engineering Department, 75080 Richardson. TX;

    The. University of Texas at Dallas, Mechanical Engineering Department, 75080 Richardson. TX;

    The. University of Texas at Dallas, Mechanical Engineering Department, 75080 Richardson. TX;

    The. University of Texas at Dallas, Mechanical Engineering Department, 75080 Richardson. TX;

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