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

EasyChair Preprint 1554

Abstract

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 (DER) using explorative spatial data mining techniques. Results show clustering of DER that are all in early adoption stage. Furthermore, spatial adoption patterns are simulated over a 20 year horizon, analyzing technology concentration changes over time and comparing three different energy policy designs. Outcomes provide useful indication for both electrical network planning and energy policy design.

Keyphrases: Diffusion of Innovation, Spatial Data Mining, renewable energy

@booklet{EasyChair:1554,
  author    = {Fabian Heymann and Filipe Joel Soares and Pablo Duenas and Vladimiro Miranda},
  title     = {Explorative Spatial Data Mining for Energy Technology Adoption and Policy Design Analysis},
  howpublished = {EasyChair Preprint 1554},
  year      = {EasyChair, 2019}}