RT journal article
T1 More robust offshore wind energy planning through model ensembling
A1 Depellegrin, Daniel
A1 Ambrosino, Maurizio
A1 Roy, Sanjoy
A1 García Sanabria, Javier
A1 Martí Llambrich, Carolina
A2 HistoriaGeografía y Filosofía
AB This research performs an ex-ante assessment of the 19 high potential areas for offshore wind energy(HPA-OWE) allocated in four maritime spatial planning subdivisions of Spain. A 39 geo-statisticalcriteria pool was developed and categorized into five planning tiers (coexistence, socio-ecological,spatial-efficiency, energy-equity, technical/technological). An ensemble of three multi-criteriadecision analysis (MCDA) techniques coupled with a Monte Carlo method based on a large, uniformnumber of randomly distributed criteria weights is applied for more robust priority rankings of HPAOWE. The co-existence tier indicates that HPA-OWE should be prioritized in the North Atlantic and inthe Levantine–Balearic planning subdivision. The application of machine learning on the MCDA resultsidentified criteria that most influence the rank of each HPA-OWE at planning subdivision. Theoutcomes highlight the need to include place-based data to better take into account spatialinequalities in coastal regions and re-balance them with socio-economic and energetically privilegedcoastal territories.
PB Springer Nature
SN 2731-426X
YR 2024
FD 2024-12-05
LK http://hdl.handle.net/10498/35818
UL http://hdl.handle.net/10498/35818
LA eng
DS Repositorio Institucional de la Universidad de Cádiz
RD 10-nov-2026