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Short-term wind power prediction and error analysis

机译:短期风电预测和误差分析

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摘要

The prediction accuracy of wind power is important to the power system operation. Based on BP neural network used to forecast directly and time-series method used to forecast indirectly, the output wind power prediction of 4 hours in advance was studied in this paper. Simulation results showed that the performance of direct prediction is better, and the reason for that was analyzed in the paper. Finally, error analysis of prediction was researched. Comprehensive evaluation of prediction error which contains horizontal and longitudinal error evaluation was proposed.
机译:风电的预测精度对电力系统操作非常重要。 基于用于直接预测和间接预测的时间序列方法的BP神经网络,本文研究了4小时的输出风电预测。 仿真结果表明,直接预测的性能更好,并在纸上分析了原因。 最后,研究了预测的误差分析。 提出了含有水平和纵向误差评估的预测误差的综合评价。

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