Managing uncertainties is a key driver in reducing costs and improving the production, reliability, and thereby the value of offshore wind. Uncertainties translate into higher safety margins adding materials to components, shorter maintenance cycles, and increases in the cost of financing wind farms.
The HIPERWIND project aims at achieving a 9% reduction in the Levelized Cost of Energy of offshore wind farms, through advancements of basic wind energy science which will lead to reductions in risk and uncertainty. The outcome is cost efficient offshore wind through a reduction in unnecessary use of materials, less unscheduled maintenance, and optimized operating strategy tailored at delivering power with high market value.
The core challenge addressed in the project is the advancement of the entire modelling chain spanning basic atmospheric physics to advanced engineering design in order to lower uncertainty and risk for large offshore wind farms. The five specific objectives of the HIPERWIND project are to:
1) improve the accuracy and spatial resolution of met-ocean models;
2) develop novel load assessment methods tailored to the dynamics of large offshore fixed bottom and floating wind turbines;
3) develop an efficient reliability computation framework;
4) develop and validate the modelling framework for degradation of offshore wind turbine components due to loads and environment; and
5) prioritize concrete, quantified measures that result in LCOE reduction of at least 9% and market value improvement of 1% for offshore wind energy.
HIPERWIND employed multi-scale atmospheric flow and ocean modelling, creating a seamless connection between models of phenomena on mesoscale level and those on wind farm level, with the aim of reducing uncertainty in load predictions, and broadening the range of scenarios for which adequate load predictions are possible. Improved modelling of environmental conditions, improved load predictions, better reliability assessment and lower uncertainty, cost efficient design and operating strategies, and lower O&M costs are expected to yield a projected 9% decrease in the Levelized Cost of Energy (LCOE) and 1% increase in the market value of offshore wind by the conclusion of the project.
The project activities took place from December 2020 to September 2024, and concluded with full completion of the above scientific objectives. The methodologies and the tool for computing Levelized Cost of Energy (LCOE) developed as part of the project were applied on the Hiperwind use cases with a “before” and “after” calculation, in order to assess the impact of innovations developed in Hiperwind. The outcomes of these studies showed an overall LCOE reduction in the range of 5-10%, where the 10% is based on the calculations with present-day assumptions about interest rates and turbine size.
The outcomes of the project (outlined in the "Key Highlights" graphic) include advanced new scientific methods, software tools and models, which altogether led to significant cost reduction and improved approaches to offshore wind turbine design.
The primary conclusions from Hiperwind are:
- Practical examples of design under uncertainty were shown
- Along the way to delivering the design under uncertainty, a number of other useful scientific results were obtained, as well as model chain improvements and software tools
- We saw that understanding uncertainties lead to design improvements
- Integrated design approach is critical for the efficient design of offshore wind turbines
- A significant LCOE reduction was achieved - but besides the engineering, the cost of capital was a major external factor driving the LCOE.
