Open AccessModeling of meteorological variables in localities without meteorological data, from the data recorded in neighboring locations that have topomesoclimatically similar conditions for the installation of renewable energy projects
Author(s) -
Eduardo Mera,
Patrício Pacheco,
Carolina Parodi,
L Gutiérrez
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1723/1/012040
Subject(s) - renewable energy , wind speed , meteorology , variable renewable energy , environmental science , variable (mathematics) , correlation coefficient , wind power , data archive , variables , computer science , statistics , engineering , geography , mathematics , database , electrical engineering , mathematical analysis , power (physics) , physics , quantum mechanics , energy storage
The present study models meteorological variables for a sector with nonexistent data through the technique of data imputation [2,3] for the installation of renewable energy projects, which in a first step seek for data generated under similar conditions, and in a second step applies a ratio [2] to these data based on an expert consultation. To validate the methodology, a meteorological station representative of the sector under study was installed and the modeled and real values were contrasted, registering that the lowest correlation coefficient is in the variable of Wind Speed (0.246) and high in the variable Temperature (0.657).