A Theory for Power Extraction from Passive Accelerators and Confined Flows
A Theory for Power Extraction from Passive Accelerators and Confined Flows
复制标题
从无源加速器和受限流中提取功率的理论
DOI：
10.3390/en13184854
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发表时间：
2020
期刊：
影响因子：
3.2
通讯作者：
Siddharth Pannir
中科院分区：
文献类型：
--
作者：
Robert Freda;Bradford G. Knight;Siddharth Pannir
没有公认的流体理论存在的功率提取从无压的约束流。缺乏一个有效的模型来确定基线均匀功率提取受限流造成的困难，在表征功率系数。目前，研究的主要主体仅限于扩散器增强风力涡轮机（DAWT）和被动流体加速器。流体动力与速度的立方成正比;因此，被动加速是一条通往有效可再生能源的有前途的道路。被动加速器的假设模型和实验分别产生较低的理想功率极限和较差的性能。我们发现，这些结果来自于误用的贝茨定律和缺乏一个通用的理论，限制流提取。实验性能是由于低效率的DAWT和先验假设表现出较高的预测误差和连续性的侵犯。一个流体模型，准确地预测现有的数据和新的实验数据，显示磁盘特定的最大CP的限制通道在38%的可用磁盘的功率。当面积比等于1时，这明显低于假设模型得出的59%的贝茨自由膨胀极限。实验和他们的结果与非DAWT加速器，新的实验结果超过CP的限制以前预测和建议的预测模型相关。
No accepted fluid theory exists for power extraction from unpressurized confined flow. The absence of a valid model to determine baseline uniform power extraction in confined flows creates difficulties in characterizing the coefficient of power. Currently, the primary body of research has been limited to Diffuser Augmented Wind Turbines (DAWTs) and passive fluid accelerators. Fluid power is proportional to the cube of velocity; therefore, passive acceleration is a promising path to effective renewable energy. Hypothetical models and experiments for passive accelerators yield low ideal power limits and poor performance, respectively. We show that these results derive from the misapplication of Betz’s Law and lack of a general theory for confined flow extraction. Experimental performance is due to the low efficiency of DAWTs and prior hypotheses exhibit high predictive error and continuity violations. A fluid model that accurately predicts available data and new experimental data, showing disk specific maximum CP for the confined channel at 38% of power available to disk, is presented. This is significantly lower than the 59% Betz freestream limit yielded by hypothetical models when the area ratio equals one. Experiments and their results are presented with non-DAWT accelerators, where new experimental results exceed CP limits predicted previously and correlate with the proposed predictive model.