Regression-based spatial GIS analysis for an accurate assessment of renewable energy potential

This work aims to evaluate technically and economically the performance of a large photovoltaic power plant, emphasizing the potential of the eastern region of Morocco for the production of electricity and hydrogen. We used weather data from about 24 cities and based on the simulation of a 110 MW power plant by the SAM (Sys-tem Advisor Module) software. The required data is collected and then implemented in a regression model to ob-tain a suitable energy production equation. This assessment method aims to provide high-resolution GIS maps and provide accurate data on the techno-economic potential of the plant in the region as well as the amounts of hydrogen that can be produced. The findings reveal that at the regional level, the simulation of the available power plant potential gives good results. The use of a regression model instead of the interpolation methods pro-vided by GIS software allows us to obtain a better cartographic resolution, this last one depends certainly on the resolution of the spatial data used in the prediction, as far as data resolution and quality are good, as far as the results are better too.(c) 2022 Published by Elsevier Inc. on behalf of International Energy Initiative.

Automated summary

This study aims to evaluate the technical and economic performance of a large photovoltaic power plant in the eastern region of Morocco, and emphasizes the potential for electricity and hydrogen production. The study uses weather data and the SAM software for simulation, and a regression model for energy production equation. The study provides high-resolution GIS maps and accurate techno-economic potential data.