A fuzzy analytic network process model to mitigate the risks associated with offshore wind farms
- Submitting institution
-
The University of Kent
- Unit of assessment
- 12 - Engineering
- Output identifier
- 18998
- Type
- D - Journal article
- DOI
-
10.1016/j.eswa.2014.10.019
- Title of journal
- Expert Systems with Applications
- Article number
- -
- First page
- 2143
- Volume
- 42
- Issue
- 4
- ISSN
- 0957-4174
- Open access status
- Out of scope for open access requirements
- Month of publication
- March
- Year of publication
- 2015
- URL
-
https://kar.kent.ac.uk/79819/
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
0
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper is the first time to solve the problem of fuzzy multi-criteria risk mitigation in offshore renewable wind energy projects under the risks of system failures (e.g. structural damage) as well as natural hazards. We propose an improved fuzzy analytic network process (FANP) approach to determine the most appropriate risk mitigation strategy according to four performance measures: safety, added value, cost and feasibility. Through a European project, the tool was adopted in a 30×2MW offshore wind farm and the results showed significant improvements in catastrophic accident prevention compared to when the classical AHP and ANP models were applied.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
