Measuring the long run technical efficiency of offshore wind farms

Giacomo Benini and Gilles Cattani

Applied Energy, 2022, vol. 308, issue C, No S0306261921014835

Abstract: Offshore wind energy has emerged as an attractive alternative to conventional resources to meet the Paris agreement commitment. The present paper studies the long run capacity of offshore wind farms to transform kinetic energy into electricity. We start estimating the technical efficiency of twenty-six farms over a thirteen years interval using a fully parametric and a semiparametric stochastic frontier model. The latter allows the factors of production to impact non-linearly on the quantity of electricity produced, those reducing the possibility of committing a functional misspecification error. Our results suggest that fully parametric specifications fails to identify the non-linear effect of labour cost on volumes of electricity produced. Then, we regress the estimated technical efficiency over the farm age, while controlling for the technological change of the wind power industry, to single out the resilience of the technical efficiency to aging. According to our calculations, technical efficiency ranges from 83% to 98% and it does not decline with age. This result shades light on the capacity of offshore wind farms to be a long term solution of the energy transition.

Keywords: Wind; Power industry; Technical efficiency; Stochastic Frontier Analysis; Age (search for similar items in EconPapers)
JEL-codes: C14 C51 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261921014835
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:appene:v:308:y:2022:i:c:s0306261921014835

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic

DOI: 10.1016/j.apenergy.2021.118218

Access Statistics for this article

Applied Energy is currently edited by J. Yan

More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().