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Multi-horizon Scalable Wind Power Forecast System

机译:多水平可扩展风电预测系统

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Wind power is the Non-Conventional Renewable Energy that has become more relevant in recent years. Given the stochastic behavior of wind speed it is necessary to have efficient prediction models at different horizons. Several kind of models have been used to forecast wind power, but using the same kind of model to forecast at different horizons is not recommendable, therefore a multi-model system needs to be implemented. We propose an scalable wind power forecasting system for multiple horizons using open source software, focusing on the forecast model selection, validated with Chilean wind farms data. Showing that RNN models can make significantly better forecasts than traditional models and can scale easily.
机译:风力发电是近年来非常规的可再生能源。考虑到风速的随机行为,有必要在不同的视野下建立有效的预测模型。已经使用了几种模型来预测风能,但是不建议使用相同的模型在不同的水平进行预测,因此需要实现多模型系统。我们使用开源软件,针对智利的风电场数据进行了验证,提出了一种使用开源软件的可扩展风能预测系统,该系统可用于多个视野,重点是预测模型的选择。表明RNN模型可以比传统模型做出更好的预测,并且可以轻松扩展。

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