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Almeida, Marcelo Pinho and Muñoz, Mikel and Parra, Iñigo de la and Perpiñan Lamigueiro, Oscar (2017). Comparative study of PV power forecast using parametric and nonparametric PV models. "Solar Energy", v. 155 ; pp. 854-866. ISSN 0038-092X. https://doi.org/10.1016/j.solener.2017.07.032.
Title: | Comparative study of PV power forecast using parametric and nonparametric PV models |
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Author/s: |
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Item Type: | Article |
Título de Revista/Publicación: | Solar Energy |
Date: | October 2017 |
ISSN: | 0038-092X |
Volume: | 155 |
Subjects: | |
Freetext Keywords: | PV plant; PV power forecast; Quantile Regression Forests; PV system modeling |
Faculty: | E.T.S.I. Diseño Industrial (UPM) |
Department: | Ingeniería Eléctrica, Electrónica Automática y Física Aplicada |
Creative Commons Licenses: | Recognition - No derivative works - Non commercial |
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Forecast procedures for large ground mounted PV plants or smaller BIPV or BAPV systems may use a parametric or a nonparametric model of the PV system. In this paper, both approaches are used independently to calculate the energy delivered to the grid on an hourly basis in forecast procedures that use meteorological variables from a Numerical Weather Prediction model as inputs, and their performances against real generation data from six PV plants are analyzed. The parametric approach relies on mathematical models with several parameters that describe the PV systems and it was implemented in MATLAB whereas the nonparametric approach is based on Quantile Regression Forests with training and forecast stages and its code was built in R. The parametric approach presented more significant bias on its results, mostly due to the input data and the transposition model of irradiance from a horizontal surface to the plane of the PV array.
Type | Code | Acronym | Leader | Title |
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FP7 | 308468 | PVCROPS | UNIVERSIDAD POLITECNICA DE MADRID | PhotoVoltaic Cost reduction, Reliability, Operational performance, Prediction and Simulation |
Item ID: | 49898 |
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DC Identifier: | https://oa.upm.es/49898/ |
OAI Identifier: | oai:oa.upm.es:49898 |
DOI: | 10.1016/j.solener.2017.07.032 |
Official URL: | https://www.sciencedirect.com/science/article/pii/S0038092X17306175 |
Deposited by: | Memoria Investigacion |
Deposited on: | 02 Apr 2018 09:07 |
Last Modified: | 31 Oct 2019 23:30 |