The distribution of wind power from a dispersed array of wind turbine generators and its reliability based applications

IF 2.6 2区数学 Q1 MATHEMATICS, APPLIED

Journal of Computational and Applied Mathematics Pub Date : 2025-07-14 DOI:10.1016/j.cam.2025.116908

Serkan Eryilmaz , Cihangir Kan , Yilser Devrim

引用次数: 0

Abstract

In this paper, the probability distribution of wind power from a dispersed array of wind turbine sites is studied considering forced outage rates of wind turbines. The wind speeds at distinct sites are assumed to be dependent and the dependence is modeled by copulas. In particular, the probability distribution of the aggregate power from two sites is exactly derived. The probability distribution of the aggregate power is also derived under the particular case when site 1 consists of

n_{1}

identical wind turbines of type 1 and site 2 consists of

n_{2}

identical wind turbines of type 2. Numerical results are presented to illustrate the theoretical findings for a chosen copula function.

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风力发电机分散阵列的风力分布及其可靠性应用

本文考虑风力机的强制停运率，研究了分散风力机场址的风力发电的概率分布。假设不同地点的风速是相互依赖的，这种依赖关系用copulas来模拟。特别地，精确地推导了两个站点的总功率的概率分布。还推导了站点1由n1台相同的1型风力机组成，站点2由n2台相同的2型风力机组成的特殊情况下，总功率的概率分布。给出了数值结果来说明所选联结函数的理论结果。

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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来源期刊

Journal of Computational and Applied Mathematics 数学-应用数学

CiteScore

5.40

自引率

4.20%

发文量

437

审稿时长

3.0 months

期刊介绍： The Journal of Computational and Applied Mathematics publishes original papers of high scientific value in all areas of computational and applied mathematics. The main interest of the Journal is in papers that describe and analyze new computational techniques for solving scientific or engineering problems. Also the improved analysis, including the effectiveness and applicability, of existing methods and algorithms is of importance. The computational efficiency (e.g. the convergence, stability, accuracy, ...) should be proved and illustrated by nontrivial numerical examples. Papers describing only variants of existing methods, without adding significant new computational properties are not of interest. The audience consists of: applied mathematicians, numerical analysts, computational scientists and engineers.