Bootstrapped Ensemble of Artificial Neural Networks Technique for Quantifying Uncertainty in Prediction of Wind Energy Production
نویسندگان
چکیده
The accurate prediction of wind energy production is crucial for an affordable and reliable power supply to consumers. Prediction models are used as decision-aid tools electric grid operators dynamically balance the provided by a pool diverse sources in mix. However, different uncertainty affect predictions, providing decision-makers with non-accurate possibly misleading information operation. In this regard, work aims quantify possible that predictions ensemble Artificial Neural Network (ANN) models. proposed Bootstrap (BS) technique quantification relies on estimating Intervals (PIs) predefined confidence level. capability BS verified, considering 34 MW plant located Italy. obtained results show provides more satisfactory than adopted owner Mean-Variance Estimation (MVE) literature. PIs also analyzed terms weather conditions experienced time horizons prediction.
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ژورنال
عنوان ژورنال: Sustainability
سال: 2021
ISSN: ['2071-1050']
DOI: https://doi.org/10.3390/su13116417