Gis renewable resources assessment and optimization for the electrification of autonomous regions

Resumen

Abstract As part of this dissertation project, thorough literature review is carried out in the second chapter. Where, several findings published by researchers are investigated. Being the principal assignment, on recently published state of the art GIS methodologies applied to the area of renewable resource assessment. This project mainly deals, with GIS approaches and assessment of renewable resources to electrify isolated regions. Digital Elevation Model is the backbone of this procedure, where the mejor task on this research is to apply existing techniques for geo-spatial assessment of different renewable energy resources, with limitations in resource data. As a result of this study, methodologies for the evaluation of wind, solar and hydro resources are devised, for the electrification of isolated region. Since, the data scarcity is the major threat; we used remote sensed data from SWERA project, to make assesment of regional resources for the study region and validate the results against benchmark sites. It is given a high priority to indirect resource assessment methods, because of the shortage on direct resource measurement practices in most of the sub-saharan African region. Due to, a huge requirement of data pre-treatment for each type of resource, in order to be implemented on GIS platform, it urged us to use a combination of different tools and methods. In the first instance, for wind assessment WAsP is the basic instrument, meanwhile for the solar resource we used regional extrapolation based on ANFIS technique. The hydro regional resource assessment methodology is proposed on HEC-HMS platform, but due to time constraints and further detailed Geo-phisical data requirements, we were unable to do hydrological simulations. As a final results of this assessment, wind and solar resource maps are generated for the region considered. Finally, we proposed a Multi-Agent based methodology to analyze grass root electrification options for isolated regions, instead of the usual approach based on scenario comparison or numerical optimization. In this case, it is introduced a dynamic GIS approach for the integration of different resources for the electrification modeling. This method presents, more of interactive and flexible approach to analyze electrfication options, as well as to boost local grid formation and follow its evolution at regional scale. Key Words: Resource assessment; spatial extrapolation; modeling; remote sensed data