Assessment of Exogenous Variables on Intra-Day Solar Irradiance Forecasting Models
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- @InProceedings{dePaiva:2018:ieeeEEEIC,
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author = "Gabriel Mendonca {de Paiva} and
Sergio Pires Pimentel and Sonia Leva and Marco Mussetta",
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booktitle = "2018 IEEE International Conference on Environment and
Electrical Engineering and 2018 IEEE Industrial and
Commercial Power Systems Europe (EEEIC / I CPS
Europe)",
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title = "Assessment of Exogenous Variables on Intra-Day Solar
Irradiance Forecasting Models",
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year = "2018",
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abstract = "Accurate and practical forecasting models are very
important as tools for optimal integration of the solar
energy source in smart grids. This work presents a
comparison of four models of intra-day radiance
forecasting based on genetic programming. These models
are evaluated at two distinct locations, with
completely different climate characteristics, with data
structured in 10-minute averages to forecast irradiance
up to 180 minutes ahead. The models differ in the
addition of exogenous weather variables or exogenous
deterministic irradiance components. With the use of
genetic programming, and at these specific locations,
the addition of exogenous weather variables did not
result in permanent accuracy improvement, while
addition of the deterministic irradiance component
did.",
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keywords = "genetic algorithms, genetic programming",
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DOI = "doi:10.1109/EEEIC.2018.8493938",
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month = jun,
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notes = "Also known as \cite{8493938}",
- }
Genetic Programming entries for
Gabriel Mendonca de Paiva
Sergio Pires Pimentel
Sonia Leva
Marco Mussetta
Citations