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Benefits of spatiotemporal modeling for short‐term wind power forecasting at both individual and aggregated levels.
- Published in:
- Environmetrics, 2018, v. 29, n. 3, p. 1, doi. 10.1002/env.2493
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Analysis of aggregated functional data from mixed populations with application to energy consumption.
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- Environmetrics, 2017, v. 28, n. 2, p. n/a, doi. 10.1002/env.2414
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- Article
Power grid frequency prediction using spatiotemporal modeling.
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- Statistical Analysis & Data Mining, 2021, v. 14, n. 6, p. 662, doi. 10.1002/sam.11535
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- Article
Very short-term spatio-temporal wind power prediction using a censored Gaussian field.
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- Stochastic Environmental Research & Risk Assessment, 2018, v. 32, n. 4, p. 931, doi. 10.1007/s00477-017-1435-7
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- Article
Spatial models for probabilistic prediction of wind power with application to annual-average and high temporal resolution data.
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- Stochastic Environmental Research & Risk Assessment, 2017, v. 31, n. 7, p. 1615, doi. 10.1007/s00477-016-1329-0
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- Article