基于BP神经网络的风电功率预测模型研究
Research on Wind Power Prediction Model Based on BP Neural Network
摘要: 为了保证风电系统可靠运行，本文提出了基于声雷达数据的BP神经网络风电功率预测方法。试验结果表明，使用声雷达设备预测风电功率效果明显优于普通的测风设备，误差可减少4%左右，总体误差也满足先行工业标准，对风力发电厂的并网及检修有指导意义。
Abstract: In order to ensure the reliable operation of wind power system, a wind power prediction method based on BP neural network based on acoustic radar data is proposed in this paper. The test results show that the wind power prediction effect of acoustic radar equipment is obviously better than that of ordinary wind measuring equipment, and the error can be reduced by about 4%. The overall error also meets the advance industrial standard, which has a guiding significance for the grid-connection and maintenance of wind power plants.
文章引用：掌旭, 高阳, 刘文超, 修唯, 李一鸣, 邹邦柱, 吴昊. 基于BP神经网络的风电功率预测模型研究[J]. 电力与能源进展, 2023, 11(1): 22-29. https://doi.org/10.12677/AEPE.2023.111003

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