Uncertain wind power forecasting using LSTM‐based prediction interval
Estimating prediction intervals (PIs) is an efficient and reliable way of capturing the
uncertainties associated with wind power forecasting. In this study, a state of the art recurrent
neural network (RNN) known as long short‐term memory (LSTM) is used to produce reliable
PIs for one‐hour ahead wind power uncertainty forecast using the non‐parametric lower
upper bound estimation framework. Two realistic hourly stamped wind power data sets are
obtained and by using mutual information and false nearest neighbours techniques, the data …
uncertainties associated with wind power forecasting. In this study, a state of the art recurrent
neural network (RNN) known as long short‐term memory (LSTM) is used to produce reliable
PIs for one‐hour ahead wind power uncertainty forecast using the non‐parametric lower
upper bound estimation framework. Two realistic hourly stamped wind power data sets are
obtained and by using mutual information and false nearest neighbours techniques, the data …
[引用][C] Uncertain wind power forecasting using LSTM-based prediction interval [J]
B Abhishek, B Chinmaya, TV Sarathkumar - IET Renewable Power Generation, 2020
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