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International Conference on Economics, Engineering, Applied Computational Science (EECAS)



    An Integrated Spatial Model for Selecting Regional Clusters of Photovoltaic Distributed Generation

    Author(s): Anibal E. Fernandes, Paulo F. Ribeiro, Carlos A. Felgueiras

    Abstract: This paper presents a methodology that integrates spatial methods for decisionmaking support based on technical criteria to expand participation of Photovoltaic Distributed Generation (PVDG) in electric power systems of a geographical region. The methodology starts with punctual environmental information, for example from a set of Data Collection Platforms (DCP), that were used as Decision Making Units (DMU) in a Data Envelopment Analysis (DEA) for ranking their efficiency. The DEA makes use of meteorological data such as temperature, wind speed, and cloudiness, as input, and solar irradiation, elevation, and insulation as output data. For the better-ranked, the Fuzzy TOPSIS multi-criteria method was applied to refine the DEA results. Then, for the best DMU, a classified Photovoltaic Power Potential (PPP) map was generated by the integration of the Normalized Difference Vegetation Index (NDVI) with slope and aspect maps using a Geographical Information System (GIS). Subsequently, utilizing the Analytic Hierarchy Process (AHP), the best of 8 sectors of a circular region centered of chosen DMU was selected, using the following criteria: distance to electric transmission lines and substations, solar irradiation of the region, and the PPP map. Within this sector, the PPP map was reclassified keeping only micro-regions with excellent and good classes. One of the main contributions of the research is related to the innovation in the use and integration of the Voronoi diagram and the Delaunay triangulation for identification and connection of clusters of micro-regions with the potential for PVDG. Moreover, production values of these grouped regions were estimated using a production ratio value of the worst-case scenario of a set of solar plants currently in operation. The methodology of this work is illustrated by a case study in Brazil is considered useful for better cost-effective investment decision makings and can be applied in any region where there is potential for using solar energy.

    Keywords: Renewable energy, Solar energy, Fuzzy TOPSIS, Geographic Information System, Photovoltaic Distributed Generation, Multicriteria decision-making

    Pages: 130-150