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

Abstract

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

Data‐driven weather forecasting models performance comparison for improving offshore wind turbine availability and maintenance

“…For example, [8] presents operational wave height limits for various forms of transportation, including helicopters and sea vessels to improve the ability to schedule maintenance, reducing costs related to vessel dispatch and recall due to unexpected wave patterns. Catterson et al (2016), [9], proposed an economic forecasting metric (EFM) which considers the economic impact of an incorrect forecast above or below critical wave height boundaries. In this study, a methodology is described for formulating criterion where the connection between forecasting error and economic consequences are amplified in terms of opportunity cost.…”

“…Significant economic benefits (of at least £55,350 per annum) resulted from applying RMSE instead of EFM for the 8 hr ahead case study. Taylor and Jeon (2018), [10], extended the work of [9] by incorporating probabilistic forecasting and examined whether a probabilistic approach to decision making is more effective than the deterministic approach used in [9]. They concluded that the wave height forecast by the probabilistic approach is the most accurate and should be included in the decisionmaking process of whether or not to launch service vehicles for offshore turbines.…”

Towards Improved Understanding of the Applicability of Uncertainty Forecasts in the Electric Power Industry

“…In this case the forecast representation can be discrete, e.g., probability of having wind speed below 4 m/s during an X hours window. The economic cost for deterministic forecast errors is therefore dependent on whether the forecasts and realizations fall on the same side of the threshold or not which makes forecast evaluation challenging [155] and is a strong argument for taking a probabilistic approach.…”

A Data-driven Vessel Motion Model for Offshore Access Forecasting

“…In practice, this This work is supported by the EPSRC Supergen Wind Hub project ORACLES, EP/L014106/1. 978-1-7281-1450-7/19/$31.00 ©2019 IEEE currently translates as single-valued deterministic forecasts of significant wave height obtained via Numerical Weather Prediction (NWP) models for horizons of over approximately 6 hours [2], [3]. This information is assimilated along with information flows from assets, other important weather variables (lightning risk, visibility, etc), and live point measurements by the marine coordination team who then use this information, the current schedule, and site expertise to execute operation and maintenance each day.…”