Assessment of Wind Power Generation

Khanittha Wannakam, S. Jiriwibhakorn
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引用次数: 2

Abstract

Wind power generation is an unstable source of renewable energy. Electricity depends on the weather at the installation location of the wind turbine. This paper presents the prediction of wind power by using the Weibull distribution and Adaptive Neuro-Fuzzy Inference System. The lowest error rates from the Adaptive Neuro-Fuzzy Inference System were 2.1912% and 4.5678%. This is the error value of the training data and the test data respectively.
风力发电评估
风力发电是一种不稳定的可再生能源。电力取决于风力涡轮机安装地点的天气。本文提出了利用威布尔分布和自适应神经模糊推理系统对风电进行预测的方法。自适应神经模糊推理系统的最低错误率分别为2.1912%和4.5678%。这是训练数据和测试数据的误差值。
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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