Wind energy is an important source of renewable energy with significant untapped potential around the world. However, the cost of wind energy production is high, and efforts to lower the cost of energy generation will help enable more widespread use of wind energy. Yaw error reduces the efficiency of turbines as well as lowers the reliability of key components in turbines. Light detection and ranging (LIDAR) devices can correct the yaw error; however, they are expensive, and there is a trade‐off between their costs and benefits. In this study, a stochastic discrete‐event simulation was developed that models the operation of a wind farm. We maximize the net present value (NPV) changes associated with using LIDAR devices in a wind farm and determine the optimum number of LIDAR devices and their associated turbine stay time as a function of number of turbines in the wind farm for specific turbine sizes. The outcome of this work will help wind farm owners and operators make informed decisions about purchasing LIDAR devices for their wind farms.

中文翻译：

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最大化风电场中LIDAR系统的偏航误差校正应用的回报

风能是可再生能源的重要来源，在世界范围内具有巨大的未开发潜力。但是，风能生产的成本很高，降低能源生产成本的努力将有助于使风能得到更广泛的利用。偏航误差降低了涡轮机的效率，并降低了涡轮机关键部件的可靠性。光检测和测距（LIDAR）设备可以纠正偏航误差；但是，它们很昂贵，并且成本和收益之间需要权衡。在这项研究中，开发了一种随机离散事件模拟，用于模拟风电场的运行。我们最大化与在风电场中使用LIDAR设备相关的净现值（NPV）变化，并针对特定的风机尺寸，确定LIDAR设备的最佳数量及其相关的风机停留时间，作为风电场中风机数量的函数。这项工作的结果将帮助风电场所有者和运营商做出有关为其风电场购买LIDAR设备的明智决定。