On the importance of wind predictions in wake steering optimization

Elie Kadoche, Pascal Bianchi, Florence Carton, Philippe Ciblat, Damien Ernst
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Abstract

Abstract. Wake steering is a technique that optimizes the energy production of a wind farm by employing yaw control to misalign upstream turbines with the incoming wind direction. This work highlights the important dependence between wind direction variations and wake steering optimization. The problem is formalized over time as the succession of multiple steady-state yaw control problems interconnected by the rotational constraints of the turbines and the evolution of the wind. Then, this work proposes a reformulation of the yaw optimization problem of each time step by augmenting the objective function by a new heuristic based on a wind prediction. The heuristic acts as a penalization for the optimization, encouraging solutions that will guarantee future energy production. Finally, a synthetic sensitivity analysis of the wind direction variations and wake steering optimization is conducted. Because of the rotational constraints of the turbines, as the magnitude of the wind direction fluctuations increases, the importance of considering wind prediction in a steady-state optimization is empirically demonstrated. The heuristic proposed in this work greatly improves the performance of controllers and significantly reduces the complexity of the original sequential decision problem by decreasing the number of decision variables.
风力预测在尾流转向优化中的重要性
摘要风浪转向是一种通过偏航控制使上游涡轮机与风向错位来优化风电场发电量的技术。这项研究强调了风向变化与风场转向优化之间的重要关系。随着时间的推移,该问题被形式化为多个稳态偏航控制问题的连续过程,这些问题通过涡轮机的旋转约束和风的演变相互关联。然后,这项工作通过基于风力预测的新启发式来增强目标函数,从而对每个时间步骤的偏航优化问题进行重新表述。启发式对优化起到惩罚作用,鼓励能保证未来能源生产的解决方案。最后,对风向变化和尾流转向优化进行了合成敏感性分析。由于涡轮机的旋转限制,随着风向波动幅度的增加,在稳态优化中考虑风向预测的重要性得到了验证。本研究提出的启发式方法大大提高了控制器的性能,并通过减少决策变量的数量显著降低了原始顺序决策问题的复杂性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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