A cross-European efficiency assessment of offshore wind farms: A DEA approach
Negar Akbari,
Dylan Jones and
Richard Treloar
Renewable Energy, 2020, vol. 151, issue C, 1186-1195
Abstract:
Offshore wind energy is recognized as an important source of renewable energy and has experienced rapid growth in recent years especially in north-western European countries. In this paper, the efficiency of 71 offshore wind farms across five north-western European countries is assessed using the Data Envelopment Analysis (DEA) Method. The number of turbines, cost, distance to shore, and area of the wind farms are selected as the inputs and the connectivity to population centres, the produced electricity and the water depth are considered as the outputs. The results show that the average CCR efficiency score of all offshore wind farms considered in this study is 87%, and the relative median efficiency of offshore wind farms in different countries is not statistically different. This study offers a practical and holistic performance assessment to the offshore wind stakeholders and policy makers via including economic, environmental, technical and social inputs and outputs in the analysis.
Keywords: Renewable energy; Decision making; Offshore wind farms; Data envelopment analysis; Efficiency assessment (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960148119318245
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:151:y:2020:i:c:p:1186-1195
DOI: 10.1016/j.renene.2019.11.130
Access Statistics for this article
Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides
More articles in Renewable Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().