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Design and Development of BP Neural Network-based Wind Power Prediction System of Dechang Wind Farm

机译:甲板风电场BP神经网络风电预测系统的设计与开发

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In this paper, Sichuan Dechang Wind Farm is taken as the research object. A wind power prediction model is established based on the BP neural network, the weight and the threshold of the BP neural network are optimized with FOA algorithm, and the wind power in the next 24h is predicted based on the numerical weather prediction and historical operation data. A wind power prediction system of Dechang Wind Farm is designed and developed based on the actual business requirements of the power plant. Based on the tests, this system operates stably and reliably, which can provide reference for wind power prediction of other wind farms.
机译:本文称,四川德邦风电场被视为研究对象。 基于BP神经网络建立了风力预测模型,通过FOA算法优化了BP神经网络的权重和阈值,并且基于数字天气预报和历史操作数据来预测接下来的24H中的风力 。 基于电厂的实际业务要求,设计和开发了Dechang风电场的风电预测系统。 基于测试,该系统稳定可靠地运行,可以为其他风电场的风力预测提供参考。

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