Analysis of leading edge protection application on wind turbine performance through energy and power decomposition approaches
Analysis of leading edge protection application on wind turbine performance through energy and power decomposition approaches
复制标题
通过能量和功率分解方法分析风力涡轮机性能的前沿保护应用
DOI：
10.1002/we.2722
复制
发表时间：
2022
期刊：
影响因子：
4.1
通讯作者：
Rodgers, Marianne
中科院分区：
文献类型：
--
作者：
Latiffianti, Effi;Ding, Yu;Sheng, Shawn;Williams, Lindy;Morshedizadeh, Majid;Rodgers, Marianne
风力发电由随机但不可控的风和环境输入驱动，并随其变化。为了比较风力涡轮机的性能，功率输出的直接比较总是被天气输入的随机效应所混淆。因此，控制天气和环境影响至关重要。为了实现这一目标，我们的研究提出了一种能量分解方法。我们从比较总能量生产的变化开始，并将总能量的变化称为Δ能量。在这个增量能量上，我们应用我们的分解方法，该方法是将由于天气影响的能量变化部分与由于涡轮机本身的能量变化部分分开。我们推导出一组数学关系，使我们能够执行这种分解，并通过广泛的交叉验证和案例研究来检查所提出的分解方法的可信度和鲁棒性。然后，我们将分解方法应用于与几个风力涡轮机相关的监控和数据采集数据，这些风力涡轮机进行了前缘保护。我们的研究表明，应用于刀片的前沿保护可能会在短期内导致发电效率的小幅下降，尽管我们预计前沿保护将有利于刀片的长期可靠性。
Wind power production is driven by, and varies with, the stochastic yet uncontrollable wind and environmental inputs. To compare a wind turbine's performance, a direct comparison on power outputs is always confounded by the stochastic effect of weather inputs. It is therefore crucial to control for the weather and environmental influence. Toward that objective, our study proposes an energy decomposition approach. We start with comparing the change in the total energy production and refer to the change in total energy as delta energy. On this delta energy, we apply our decomposition method, which is to separate the portion of energy change due to weather effects from that due to the turbine itself. We derive a set of mathematical relationships allowing us to perform this decomposition and examine the credibility and robustness of the proposed decomposition approach through extensive cross‐validation and case studies. We then apply the decomposition approach to Supervisory Control and Data Acquisition data associated with several wind turbines to which leading‐edge protection was carried out. Our study shows that the leading‐edge protection applied on blades may cause a small decline to the power production efficiency in the short term, although we expect the leading‐edge protection to benefit the blade's reliability in the long term.
登录
查看更多内容
风能数据科学
DOI：
--
发表时间：
2019
期刊：
影响因子：
--
作者：
Yu Ding
通讯作者：
Yu Ding
影响因子：
8.7
作者：
Tinghui Ouyang;A. Kusiak;Yusen He
通讯作者：
Tinghui Ouyang;A. Kusiak;Yusen He
影响因子：
8.7
作者：
Ding, Yu;Kumar, Nitesh;Li, Qingchang
通讯作者：
Li, Qingchang
使用 AEP 损失法检测风力涡轮机结冰：案例研究
影响因子：
1.5
作者：
J. Jin;Timo Karlsson;M. Virk
通讯作者：
M. Virk