Explorative Spatial Data Mining for Energy Technology Adoption and Policy Design Analysis

• Type: Article in International Conference Proceedings Book
• Date: 2019

Authors

Heymann, F (Author) Other; Soares, FJ (Author) Other; Duenas, P (Author) Other; Vladimiro Miranda (Author) FEUP

Conference proceedings International

Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Pages: 427-437

19th EPIA Conference on Artificial Intelligence, EPIA 2019

3 September 2019 through 6 September 2019

Indexing

Scopus - 1 Citation

Other information

Authenticus ID: P-00R-4KC

DOI: 10.1007/978-3-030-30241-2_36

Abstract (EN): 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. These resources are currently passing the early adoption stage in the study area. Results show adopter clustering during the current stage. 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. © Springer Nature Switzerland AG 2019.

Language: English

Type (Professor's evaluation): Scientific