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Short-Term Wind Speed Forecasting of Lelystad Wind Farm by Using ANN Algorithms

机译:利用ANN算法,lecystad风电场的短期风速预测

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摘要

The installation of wind energy based electricity systems is growing at a very fast pace all over the world because of the increased urge of using renewable energy resources and environmental concerns regarding electricity generation. Forecasting wind speed is found to be critical for wind energy systems since it greatly influences its large-scale integration. The intermittent nature of wind speed leads to further problems in its large-scale integration in the power systems. Wind speed forecasting is essential to operate wind energy based power systems in an efficient and secure way. In this paper, different ANN algorithms have been applied to forecast short-term wind speed of Lelystad Wind Farm, Nederland using MATLAB R1 pmb4a. The data used in the forecasting are hourly historical data of the wind direction & wind speed. The simulation results have shown accurate one hour ahead forecasts with small error in wind speed forecasting.
机译:由于利用可再生能源资源和有关发电的环境问题的推动,风能基电系统的安装在世界各地的一次非常快速地增长。由于它大大影响了其大规模集成,因此发现预测风速对风能系统至关重要。风速的间歇性质导致其在电力系统中的大规模集成中的进一步存在问题。风速预测以高效且安全的方式操作风能基于电力系统必不可少的。在本文中,应用了不同的ANN算法,用于使用Matlab R1 PMB4A预测奈良兰州莱美氏风电场的短期风速。预测中使用的数据是风向和风速的每小时历史数据。仿真结果表明,在风速预测中具有小错误的预测预测精确预测。

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