Explorative spatial data mining for energy technology adoption and policy design analysis

F. Heymann, F.J. Soares, P. Dueñas, V. Miranda

19th Conference on Artificial Intelligence - EPIA 2019, Vila Real (Portugal). 03-06 septiembre 2019

Resumen:

Spatial data mining aims at the discovery of unknown, useful patterns from large spatial datasets. This article presents a thorough analysis of the Portuguese adopters of distributed energy resources using explorative spatial data mining techniques. Results show clustering of distributed energy resources that currently passing the early adoption stage in Portugal. Furthermore, spatial adoption patterns are simulated over a 20 year horizon, analyzing technology concentration changes over time while comparing three different energy policy designs. Outcomes provide useful indication for both electrical network planning and energy policy design.

Palabras clave: Diffusion of Innovation, Renewable Energy, Spatial Data Mining

DOI: https://doi.org/10.1007/978-3-030-30241-2_36

Publicado en Progress in Artificial Intelligence, pp: 427-437, ISBN: 978-3-030-30240-5

Fecha de publicación: 2019-09-03.

Cita:
F. Heymann, F.J. Soares, P. Dueñas, V. Miranda, Explorative spatial data mining for energy technology adoption and policy design analysis, 19th Conference on Artificial Intelligence - EPIA 2019, Vila Real (Portugal). 03-06 septiembre 2019. En: Progress in Artificial Intelligence: Proceedings of the 19th EPIA Conference on Artificial Intelligence, EPIA 2019, vol. Part I, ISBN: 978-3-030-30240-5