dc.contributor |
Universitat Politècnica de Catalunya. Departament d'Enginyeria Elèctrica |
dc.contributor |
Everis |
dc.contributor |
Sumper, Andreas |
dc.contributor |
Anguera Jordà, Adriana |
dc.contributor.author |
Farinoni, Matteo |
dc.coverage.spatial |
east=-3.7037901999999576; north=40.4167754; name=Sol, 28013 Madrid, Espanya |
dc.date |
2016-07 |
dc.identifier.uri |
http://hdl.handle.net/2117/104141 |
dc.language.iso |
eng |
dc.publisher |
Universitat Politècnica de Catalunya |
dc.rights |
Attribution-NonCommercial-NoDerivs 3.0 Spain |
dc.rights |
info:eu-repo/semantics/openAccess |
dc.rights |
http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
dc.subject |
Àrees temàtiques de la UPC::Desenvolupament humà i sostenible |
dc.subject |
Poverty -- Prevention |
dc.subject |
Electric power distribution -- Spain |
dc.subject |
Pobresa -- Prevenció |
dc.subject |
Energia elèctrica -- Distribució -- Espanya |
dc.title |
Energy Poverty: Measurement Strategies and Solutions |
dc.type |
info:eu-repo/semantics/masterThesis |
dc.description.abstract |
This work wants to propose measurement methodologies and solutions for tackling the energy poverty and affordability issue in developed countries, focusing on the European Union and in particular on Spain and Catalonia.
The research is carried out as a support tool for policy makers and public authorities, providing an objective and scientific evaluation of a problem which is currently at the centre of both the political and economic debate. Two are the aims of this project.
First aim is to analyse and test, on a real database, all the indicators used throughout Europe so far. This will lead to the choice of a suitable indicator that could be applied to Spain for assessing and estimating the energy poverty extension and impact over Spanish society.
Second aim, based on previous step, is to model the phenomenon in an innovative manner using machine learning instruments. This will allow to understand what are the variables that increase the risk for a single households of facing an energy vulnerability situation. As a core added value, the analysis will not take into account information that are commonly owned by private utility companies.
In the final part of the project the results obtained from the trained model are applied and tuned to a specific study case: the city of Barcelona. An energy vulnerability ranking will order all city neighbourhoods according to their probability of hosting families in energy deprivation conditions. Moreover, it will be possible to evaluate the drivers of the problem case by case.
This outcomes can set the base for the implementation of effective policies following a specific and demonstrated framework and order of action, optimizing and controlling the use of public financial resources. |