Modeling 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. Issue 1 (January 2021) - Mera, E; Pacheco, P; Parodi, C; Gutiérrez, L
Abstract: 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).