Periodic Reporting for period 2 - HIPERWIND (HIghly advanced Probabilistic design and Enhanced Reliability methods for high-value, cost-efficient offshore WIND)
Berichtszeitraum: 2022-06-01 bis 2023-05-31
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 employs 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 will 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 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 employs 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 will 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.
At the end of the second reporting period (RP2), all remaining deliverables within WP2 and WP3 were completed, meaning that WP1, WP2 and WP3 have now concluded.
The following concrete activities took place within RP2:
- WP2: Completion of the activities on uncertainty quantification of wave modelling, studying differences between different wave modelling fidelity approaches.
- WP3: Completion of the activities related to uncertainty quantification of wind farm flow and load models, specifically focusing on comparison of engineering wake modelling solutions to LES simulations, as well as the effect of floating turbine motion on wakes.
- WP4: Developing, testing and prioritizing methods for efficient reliability assessment with respect to Ultimate Limit State and Fatigue Limit State. Developing a design evaluation procedure that evaluates floating wind turbine design against Serviceability Limit States.
- WP5: Developing and implementing a life model for main bearings, including the effect of lubricant temperature and quality.
- WP6: The activities have started with collecting inputs and preparing simulation tools.
The following technical deliverables were completed during Reporting Period 2:
D2.2: Realistic representation of nonlinear wave conditions applicable for offshore wind turbine design
D3.2: Turbine loading and wake model uncertainty
D5.1: Offshore wind turbine drivetrain component degradation and lifing models
D5.2: Quantification of the impact of electrical events on drivetrain mechanical component degradation
This adds to the technical deliverables already completed during Reporting Period 1:
D1.1: Supply of measurement data to the necessary parties from the appropriate platform
D1.2: Design brief for the use cases and models in engineering tools
D1.3: Baseline FLS and ULS simulation results from the use cases
D2.1: Atmospheric-wave multi-scale flow modelling that will resolve the flow fields from mesoscale to farm/turbine scale
D2.3: Environmental joint probability distributions and uncertainties
D3.1: Wind farm parameterization and turbulent wind box generation
D3.3: Aero-servo-hydroelastic model uncertainty
D4.1: Novel surrogate modelling approaches for wind turbine reliability assessment
All technical deliverables from WPs 2, 3 and 4 have been made publicly available on the project website www.hiperwind.eu.
The following concrete activities took place within RP2:
- WP2: Completion of the activities on uncertainty quantification of wave modelling, studying differences between different wave modelling fidelity approaches.
- WP3: Completion of the activities related to uncertainty quantification of wind farm flow and load models, specifically focusing on comparison of engineering wake modelling solutions to LES simulations, as well as the effect of floating turbine motion on wakes.
- WP4: Developing, testing and prioritizing methods for efficient reliability assessment with respect to Ultimate Limit State and Fatigue Limit State. Developing a design evaluation procedure that evaluates floating wind turbine design against Serviceability Limit States.
- WP5: Developing and implementing a life model for main bearings, including the effect of lubricant temperature and quality.
- WP6: The activities have started with collecting inputs and preparing simulation tools.
The following technical deliverables were completed during Reporting Period 2:
D2.2: Realistic representation of nonlinear wave conditions applicable for offshore wind turbine design
D3.2: Turbine loading and wake model uncertainty
D5.1: Offshore wind turbine drivetrain component degradation and lifing models
D5.2: Quantification of the impact of electrical events on drivetrain mechanical component degradation
This adds to the technical deliverables already completed during Reporting Period 1:
D1.1: Supply of measurement data to the necessary parties from the appropriate platform
D1.2: Design brief for the use cases and models in engineering tools
D1.3: Baseline FLS and ULS simulation results from the use cases
D2.1: Atmospheric-wave multi-scale flow modelling that will resolve the flow fields from mesoscale to farm/turbine scale
D2.3: Environmental joint probability distributions and uncertainties
D3.1: Wind farm parameterization and turbulent wind box generation
D3.3: Aero-servo-hydroelastic model uncertainty
D4.1: Novel surrogate modelling approaches for wind turbine reliability assessment
All technical deliverables from WPs 2, 3 and 4 have been made publicly available on the project website www.hiperwind.eu.
The Hiperwind project has already provided several types of exploitable results that have potential for directly impacting users. These include:
- Aeroelastic code benchmarks that serve as reference and a public demonstration of the adequacy of the codes;
- A range of software scripts and tools for preparation of enhanced, modular CFD simulations on multiple scales;
- Methods to extract extreme transient wind events from wind time series and include the measured time series directly in wind turbine load simulations;
- An open-access tool for generation of synthetic turbulence fields that can be used as inputs to load simulations - and allow embedding of measured time series as well as producing non-Gaussian turbulence fields;
- Improved methods for load surrogate modeling that take into account wake effects in an arbitrary wind farm by parameterizing the layout;
- An approach for computing the uncertainty of an engineering model with respect to a more advanced high-fidelity model - applied both on hydrodynamic and on aerodynamic load uncertainty assessment.
- A time series surrogate model capable of producing an output similar to aeroelastic load simulations with several orders of magnitude better efficiency
- A public wind turbine drive train description
- An integrated electrical-mechanical simulation framework capable of (1) simulating diverse power grid disturbances and (2) analyzing the impact of power grid disturbances on the mechanical degradation of offshore wind turbine components.
In addition, the project actively uses the available dissemination channels and has as of the time of completion of this report resulted in the following public outputs:
- Eleven open-access journal papers (including conference papers) have been published
- More than ten conference presentations and posters
- Nine technical deliverables are published on the Hiperwind website
- A webinar was held in November 2019
- A LinkedIn page has been established and regularly updated with new posts and features
- Four short feature videos have been published and linked with the LinkedIn page.
- Aeroelastic code benchmarks that serve as reference and a public demonstration of the adequacy of the codes;
- A range of software scripts and tools for preparation of enhanced, modular CFD simulations on multiple scales;
- Methods to extract extreme transient wind events from wind time series and include the measured time series directly in wind turbine load simulations;
- An open-access tool for generation of synthetic turbulence fields that can be used as inputs to load simulations - and allow embedding of measured time series as well as producing non-Gaussian turbulence fields;
- Improved methods for load surrogate modeling that take into account wake effects in an arbitrary wind farm by parameterizing the layout;
- An approach for computing the uncertainty of an engineering model with respect to a more advanced high-fidelity model - applied both on hydrodynamic and on aerodynamic load uncertainty assessment.
- A time series surrogate model capable of producing an output similar to aeroelastic load simulations with several orders of magnitude better efficiency
- A public wind turbine drive train description
- An integrated electrical-mechanical simulation framework capable of (1) simulating diverse power grid disturbances and (2) analyzing the impact of power grid disturbances on the mechanical degradation of offshore wind turbine components.
In addition, the project actively uses the available dissemination channels and has as of the time of completion of this report resulted in the following public outputs:
- Eleven open-access journal papers (including conference papers) have been published
- More than ten conference presentations and posters
- Nine technical deliverables are published on the Hiperwind website
- A webinar was held in November 2019
- A LinkedIn page has been established and regularly updated with new posts and features
- Four short feature videos have been published and linked with the LinkedIn page.