首页> 外文会议>IEEE Conference on Industrial Electronics and Applications; 20070523-25; Harbin(CN) >Taboo Search Algorithm Based ANN Model for Wind Speed Prediction
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Taboo Search Algorithm Based ANN Model for Wind Speed Prediction

机译:基于禁忌搜索算法的风速预测神经网络模型

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摘要

Wind power is fluctuate, intermittent and stochastic. The large capacity wind power connected with power grids will bring austere challenge to the safety and stabilization of power system operation. Wind speed prediction is an effective approach for this problem. ANN (Artificial Neural Network) has been used extensively in wind speed prediction. But ANN is apt to getting into local minima and its convergence rate is slow. Tabu search is a kind of intelligent algorithm, which can achieve the global optimizations. This paper put forward a wind speed prediction model of neural network based on tabu search algorithm. How to decide the input of a neural network is a difficult issue. This paper put forward a simple linear correlation analysis method for the input selection. The result shows that with appropriate input parameters, the wind speed prediction model of neural network based on tabu search algorithm can improve the prediction precision.
机译:风能波动,间歇性和随机性。与电网连接的大容量风电将给电力系统的安全和稳定带来严峻的挑战。风速预测是解决此问题的有效方法。 ANN(人工神经网络)已广泛用于风速预测中。但是人工神经网络很容易陷入局部极小,其收敛速度很慢。禁忌搜索是一种智能算法,可以实现全局优化。提出了基于禁忌搜索算法的神经网络风速预测模型。如何确定神经网络的输入是一个难题。提出了一种简单的线性相关分析方法用于输入选择。结果表明,在适当的输入参数的基础上,基于禁忌搜索算法的神经网络风速预测模型可以提高预测精度。

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