This proposal will develop a comprehensive methodology aimed at integrating available big data sets (especially those related to cross-cutting dimensions such as social quality, wealthy issues and buildings energy performance) from different sources and applying a data processing for mapping the EP risk in any district located in Spain or Portugal. It is expected that at least three main data sets will be required: data related to energy costs, to household incomes and to household energy consumption. All these data obtained from different public and available databases will be integrated into this methodology. This methodology will integrate all these data sets and will be implemented in a GIS-based tool which, based on different EP indicators, will allow mapping easily the EP risk level of buildings and districts.

The second stage of the project is to identify cost-effective solutions to be implemented at the district level in the most affected areas, providing an estimation of the required investment and expected improvements (energy and economic savings and/or indoor temperatures). Moreover, the potential of rooftop solar installations for reducing energy consumption from the grid will be also assessed. This will be evaluated using LIDAR data and solar radiation models to determine the physical potential, and once the physical potential has been obtained, in the case of PV installations, the values will be compared to the real electricity consumption of the evaluated area. This comparison will allow quantifying the share of electricity demand that can be supplied from renewable energy sources (environmental issue), and an estimation of which part of the electricity consumption is self-consumed and which part is exported to the grid, to obtain a more adjusted value of the real operating costs of the systems and other related indicators. A schematic view of the methodology and the expected outcomes are presented in next figure:

This comprehensive methodology will be demonstrated in the framework of the project by means of applying it into different areas located in Spain and Portugal.