Deterministic and Probabilistic Wind Power Forecasts by Considering Various Atmospheric Models and Feature Engineering Approaches
Author:
Affiliation:
1. National Chung-Cheng University, Chiayi, Taiwan
2. Meteorological Information Center, Central Weather Bureau, Taipei, Taiwan
Funder
Ministry of Science and Technology, Taiwan
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Control and Systems Engineering
Link
http://xplorestaging.ieee.org/ielx7/28/10021929/09928779.pdf?arnumber=9928779
Reference52 articles.
1. Numerical weather prediction enhanced wind power forecasting: Rank ensemble and probabilistic fluctuation awareness
2. Combined Approach for Short-Term Wind Power Forecasting Based on Wave Division and Seq2Seq Model Using Deep Learning
3. A Nonparametric Probability Distribution Model for Short-Term Wind Power Prediction Error
4. ELM-QR-Based Nonparametric Probabilistic Prediction Method for Wind Power
5. Short-Term Forecasting and Uncertainty Analysis of Wind Power
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