A practical account of what onboard wind generation delivered in the first year -- and what the data revealed about optimisation opportunities in year two.
The first year of any onboard wind installation is a calibration period. Generation data accumulates, the vessel's routing patterns become visible in the yield figures, and the gap between projected and actual performance either closes or reveals the assumptions that need revising. This account draws on operational data from a bulk carrier installation to show what year one looked like.
The vessel is a handymax bulk carrier operating primarily on North Atlantic and Baltic routes, with seasonal South American charter rotations. The installation comprises two turbines mounted on the main deck amidships, positioned to capture the acceleration corridor identified in the pre-installation site survey. Battery storage is included as standard; the storage system manages the relationship between generation and the vessel's hotel load.
Routes were not modified for the installation. The vessel's trading pattern was taken as given, and the yield projections were built on that pattern.
The North Atlantic and Baltic routes produced the highest generation density, as expected from the wind climate. The South American rotations produced lower generation due to the trade wind pattern on those headings -- light following winds for extended periods, with strong beam-wind generation on the transoceanic leg.
Annual generation across both turbines came in approximately 8% above the projection. The projection had been built conservatively, using ambient forecast wind data. The actual yield reflected the venturi acceleration that the forecast model had not captured. This is a consistent finding across maritime installations where the projection was not site-modelled: ambient forecast data understates actual yield.
Three optimisation opportunities emerged from the first year's data.
First: battery dispatch timing. The vessel's hotel load follows a predictable 24-hour pattern tied to crew activity. The battery management system's default strategy had not fully adapted to this pattern in the first months; by month eight it had learned the load curve and the dispatch efficiency improved measurably.
Second: heading optimisation on one regular route. Analysis of the generation data showed that a minor variation in departure heading on one specific Baltic passage -- approximately 15 degrees -- would increase average beam-wind exposure by an estimated 20% over that leg with no meaningful increase in passage time. This was flagged to the vessel's routing team for assessment.
Third: redundancy confirmation. The separation between the two turbines meant that when one unit was offline for its annual service, the other continued generating. Single-turbine installations do not have this redundancy; for operators with a strong self-consumption case, two-turbine installations provide both more generation and operational resilience.
Year one data from any installation is primarily useful for model validation and optimisation identification -- not for judging whether the system is performing. The yield curve improves as the AI layer learns the vessel's load pattern. Route analysis takes a full trading year to complete. Year two and year three are where the projections and the actuals converge.
See also: ROI for maritime wind · Fuel savings overview · Full FAQ