An economic impact metric for evaluating wave height forecasters for offshore wind maintenance access

Catterson, V.M., McMillan, D., Dinwoodie, I., Revie, M., Dowell, J. , Quigley, J. and Wilson, K. (2016) An economic impact metric for evaluating wave height forecasters for offshore wind maintenance access. Wind Energy, 19(2), pp. 199-212. (doi: 10.1002/we.1826)

Abstract

This paper demonstrates that wave height forecasters chosen on statistical quality metrics result in sub-optimal decisionsupport for offshore wind farm maintenance. Offshore access is constrained by wave height, but the majority of approachesto evaluating the effectiveness of a wave height forecaster utilize overall accuracy or error rates. This paper introduces anew metric more appropriate to the wind industry, which considers the economic impact of an incorrect forecast above orbelow critical wave height boundaries. The paper describes a process for constructing a value criterion where the impli-cations between forecasting error and economic consequences are explicated in terms of opportunity costs and realizedmaintenance costs. A comparison between nine forecasting techniques for modeling and predicting wave heights basedon historical data, including an ensemble aggregator, is described demonstrating that the performance ranking of fore-casters is sensitive to the evaluation criteria. The results highlight the importance of appropriate metrics for wave heightprediction specific to the wind industry and the limitations of current models that minimize a metric that does not supportdecision-making. With improved ability to forecast weather windows, maintenance scheduling is subject to less uncer-tainty, hence reducing costs related to vessel dispatch, and lost energy because of downtime.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Browell, Dr Jethro
• Authors: Catterson, V.M., McMillan, D., Dinwoodie, I., Revie, M., Dowell, J., Quigley, J., and Wilson, K.
• College/School: College of Science and Engineering > School of Mathematics and Statistics > Statistics
• Journal Name: Wind Energy
• Publisher: Wiley
• ISSN: 1095-4244
• ISSN (Online): 1099-1824
• Published Online: 06 January 2015