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Solar Power Generation Forecast Based on LSTM

机译:基于LSTM的太阳能发电预测

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摘要

Photovoltaic power generation is an effective way to use solar energy, which is a recognized ideal renewable energy source. However, photovoltaic that is susceptible to weather conditions is unstable, and will adversely affect the power grid. Therefore, it is necessary to improve the accuracy of solar power generation. This paper uses the LSTM model to predict solar power generation. At the same time, the data is reduced by using PCA to reduce the training duration of the model and improve the generalization ability of the model. Compared with other models, simulation experiment shows that the LSTM model is better.
机译:光伏发电是使用太阳能的有效方法,这是一个公认的理想可再生能源。然而,易受天气条件的光伏是不稳定的,并且会对电网产生不利影响。因此,有必要提高太阳能发电的准确性。本文使用LSTM模型来预测太阳能发电。同时,通过使用PCA来减少数据来降低模型的训练持续时间并提高模型的泛化能力。与其他模型相比,仿真实验表明,LSTM模型更好。

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