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A Versatile Mixture Distribution and Its Application in Economic Dispatch with Multiple Wind Farms

机译:多种混合气分布及其在多风电场经济调度中的应用

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摘要

An improved versatile distribution for wind power is proposed, with higher representation accuracy and more suitable applications in economic dispatch (ED) compared with Versatile distribution. Further, versatile mixture distribution (VMD) is proposed to represent all possible wind power distribution with customized arbitrary errors. Compared with Gaussian Mixture distribution (GMD), it has more flexible forms and can represent wind power more accurately. Its cumulative distribution function has analytical forms with higher computational efficiency. Then, real-time dynamic ED model and algorithm based on VMD with multiple wind farms (WFs) is proposed. Based on the VMD model, the probability distributions of wind power of each WF and the summation of all WFs are modeled. The ED model and algorithm solve the problem of the correlation of multiple renewable energy random variables with high computation efficiency for real-time ED. The results show that compared with GMD or unimodal distributions, VMD can represent wind power more accurately and can greatly simplify and speed up the ED model and algorithm. Compared with other methods for multiple renewable energy random variables, the proposed model and algorithm can improve economy significantly.
机译:与通用分布相比,提出了一种改进的风能通用分布,具有更高的表示精度和更适合在经济调度(ED)中的应用。此外,提出了通用混合分布(VMD)来代表具有定制的任意误差的所有可能的风力发电分布。与高斯混合分布(GMD)相比,它具有更灵活的形式并且可以更精确地表示风能。其累积分布函数具有解析形式,具有较高的计算效率。然后,提出了基于VMD的多风场(WFs)实时动态ED模型和算法。基于VMD模型,对每个WF的风能概率分布和所有WF的总和进行建模。 ED模型和算法解决了多个可再生能源随机变量之间的相关性问题,实时ED计算效率高。结果表明,与GMD或单峰分布相比,VMD可以更准确地表示风能,并且可以大大简化和加速ED模型和算法。与其他针对多个可再生能源随机变量的方法相比,该模型和算法可以显着提高经济性。

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