DECISION SUPPORT FOR OFFSHORE WIND TURBINE INSTALLATION

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DECISION SUPPORT FOR OFFSHORE WIND TURBINE INSTALLATION TOMAS GINTAUTAS*, AAU (tg@civil.aau.dk) PROFESSOR JOHN DALSGAARD SØRENSEN, AAU Science meets industry 2016 April 6 th, Stavanger

About the DECOFF project KPN project supported by Research Council of Norway (MAROFF) and Statoil. 3 years. Started in 2013, end December 31st 2015. Project management by Christian Michelsen Research. Research partners: MARINTEK- Couple weather forecast models to an advanced dynamical model (SIMO) to obtain response parameters. Uni Research, University of Bergen, Meteorologisk Institutt - Improve local ensemble weather forecasts by utilizing local measurements. Aalborg University - Use statistical models to capture uncertainty of response characteristics. Christian Michelsen Research - Integrate the above into an online risk based decision support system. DEPARTMENT OF CIVIL ENGINEERING SCIENCE MEETS INDUSTRY 2016, STAVANGER

Agenda Research Motivation Description of the software tool in question. Short term verification input. Weather and vessel model. Position Input variables Hywind Rotor-Lift installation phases Acceptance limits under consideration Types of acceptance limits Procedure for estimating Probabilities of Failed Operations Proof of concept. DEMO Risk Based Decision Making Probability based Decision Making. Acceptance limit Probabilities of Failure Operation Failure rate Weather window estimation Long(er) term verification for summer 2014. Conclusions and discussion DEPARTMENT OF CIVIL ENGINEERING SCIENCE MEETS INDUSTRY 2016, STAVANGER

Motivation State-of-the-art in assessing if a weather sensitive offshore operation is safe to commence is only based on significant wave height Hs and wind speed at the location in question. The actual limitations of installation are mostly physical: strength of the installation equipment used - crane cable loads, tug wire tensions, etc. Limits on the equipment being installed maximum acceleration limits on wind turbine nacelle/rotor components. safe working environment conditions motions and accelerations at the height/location of the installation limiting or prohibiting the installation crews work. Transition from limits on weather conditions to limits on physical response criteria in decision making would improve the predictions of weather windows for installation and potentially reduce the cost of energy. DEPARTMENT OF CIVIL ENGINEERING SCIENCE MEETS INDUSTRY 2016, STAVANGER

DECOFF method Topology Forecasted met-ocean conditions Hydrodynamic multibody motion simulator Operation input (cranes, vessels, lifting equipment, etc.). Time series of relevant responses (equipment loads, motions) Operational Acceptance limits (maximum crane loads, allowable motions). STATISTICAL MODEL Estimates of statistical parameters of extreme responses Estimates of Probability of Operation Failure Decision making based on combination of Probabilities and/or Costs of failed operations

DECOFF Example test case Hywind Rotor-Lift Operation Phase 1 Phase 2 Phase 3 Phase 4 Phase 5 Phase 6 Transition to field 8 hours Preparation for lift 3 hours Rotor lift up 0.2 hours Rotate rotor 0.2 hours Lift-up close to nacelle 0.4 hours Connecting rotor to nacelle 0.3 hours Total duration 12.1 hours Test case: Phases 3-6 barge is at the installation position, rotor is lifted up and bolted to the nacelle.

Limiting operational parameters Hywind Rotor-Lift Operation Phase 1 Phase 2 Phase 3 Phase 4 Phase 5 Phase 6 6-7Transition to field 8 hours Preparation for lift 3 hours Rotor lift up 0.2 hours Rotate rotor 0.2 hours Lift-up close to nacelle 0.4 hours Connecting rotor to nacelle 0.3 hours Phase 3 Operation Limits Crane Load Lift Wire Tension Tug Wire Tension Airgap between blades and waves Rotor acceleration Rotor rotational acceleration Rotor Sway motion Rotor Surge motion Phase 6 Operation Limits Relative yaw angle between rotor and special tool Relative tiltangle between rotor and special tool Relative axial velocity Relative radial velocity Airgal between blade 3 and tower DEPARTAMENT OF CIVIL ENGINEERING SCIENCE MEETS INDUSTRY 2016, STAVANGER

Short term Validation. Simulation input - weather Location: 7 ⁰ W 55.25 ⁰ N FINO 3 site Forecast: ECMWF 2013 2013-08-06 00:00:00 51 ensemble members Parameters used: Wind speed and direction. Sig wave height and peak and direction. Swell sig wave height and mean period and direction. DEPARTAMENT OF CIVIL ENGINEERING SCIENCE MEETS INDUSTRY 2016, STAVANGER

Types of acceptance limits Exceedance acceptance limit. The response has to be above the acceptance limit (no slack in lifting cables, tug wires, tower clearance etc.) Non-Exceedance acceptance limit. The response has to be below a certain acceptance limit (maximum motions, loads on lifting equipment etc.) Evaluation of non-exceedance function at accetpance limit R min.,, Evaluation of exceedance function at accetpance limit R max.,,

Procedure of Failure Probability estimation Weather forecasts are passed through hydrodynamic multibody motion simulator (SIMO) and response time series are analysed statistically in order to obtain Probabilities of Failed operations: 1. Peak Over Threshold method is applied to extract extreme values of relevant responses.

Procedure of Failure Probability estimation 2. Weibull or Normal distribution is fitted to the extremes using Maximum Likelihood parameter estimation. 3. Evaluate the extreme response distribution at acceptance limit. 4. Steps 1-3 are repeated for 51 forecast ensembles. 5. The Probability of Failure for one acceptance limit is an average over 51 ensembles (may also be any quantile required).,, 6. Combining all the acceptance limits gives Probability of failure for the whole operation., 1 1,, )

Proof of Concept. Short Term Verification DEPARTAMENT OF CIVIL ENGINEERING

Acceptance limit Probabilities of Failure DECOFF MEETING PAGE 13 - DATE DEPARTMENT OF CIVIL ENGINEERING

Combination of Probabilities of Failure Hywind Rotor-Lift Operation Phase 1 Phase 2 Phase 3 Phase 4 Phase 5 Phase 6-7 Transition to field 8 hours Preparation for lift 3 hours Rotor lift up 0.2 hours Rotate rotor 0.2 hours Lift-up close to nacelle 0.4 hours Connecting rotor to nacelle 0.3 hours P F, Air Gap Blade Water,Ph 2 + P F, Air Gap Blade Water,Ph 2 = P F, CraneLoad, Ph 3 + P F, CraneLoad,Ph 4 + P F, CraneLoad, Ph5 = P F, Rotor Sway, Ph 3 + P F, Rotor Sway, Ph 4 + P F, Rotor Sway, Ph 5 = P F, Acceleration, Ph 3 + P F, Acceleration, Ph 4 + P F, Acceleration, Ph 5 = P F, Crane Load + P F, Air Gap Blade Water + P F, Rotor Sway + P F, Acceleration +... =, 1 1,, ) P F, Operation

Operation Failure Probability, 1 1,, )

Extension to Risk based decision making C total C waiting C equipment N phases N AccLim i 1 j 1 P AccLim, i, j C AccLim, i, j Having Probabilities of Failure related to a particular acceptance limit or operation phase and combining those with monetary consequences of failure with particular failures, Risk Based decision making is possible. This allows relative comparison among different weather windows. What is needed: Cost in NOK ( ) related to Operation Failure with a particular acceptance limit. Cost in NOK ( ) of complete Operation Failure for less detailed analysis. DEPARTMENT OF CIVIL ENGINEERING SCIENCE MEETS INDUSTRY 2016, STAVANGER

Long(er) term verification. Input Location: 7 ⁰ W 55.25 ⁰ N FINO 3 site. Forecast: ECMWF May 1 st to August 1 st 2014. measurements @FINO3. Parameters used: Wind speed and direction. Significant wave height and peak and direction. Swell sig wave height and mean period and direction. Hydrodynamic model: Hywind Rotor Lift operation. Benchmarking: The proposed method is benchmarked against a standard Alpha-Factor from DNV-HS-101. Benchmarking cases: Tabulated Alpha-Factors from DNV-HS-10. Site specific Alpha-Factors for FINO3 site according to DNV-HS-10. DECOFF method with ECMWF forecasts @FINO3. DECOFF method with measurements @FINO3. DEPARTMENT OF CIVIL ENGINEERING SCIENCE MEETS INDUSTRY 2016, STAVANGER

Long term verification. Alpha-Factor method Alpha-Factor method in a nutshell: Determine the maximum allowable wave height/wind speed for operation in question (or a part of operation). Use a reduction factor (alpha-factor) to reduce the allowable met-ocean conditions to take uncertainties of weather forecasts into consideration. DEPARTMENT OF CIVIL ENGINEERING SCIENCE MEETS INDUSTRY 2016, STAVANGER

Long term verification. Alpha-Factor method Weather limits for Hywind Rotor Lift operation: H s =1.5m, T p =5s, W s =7m/s. Case α Hs for α Tp for α Ws for Quantile H s =1.5m T p =5s W s =7m/s T4-1.WFQ=C 0.705 inf 0.79 1 0.8 mean T4-2.WFQ=B 0.740 inf 0.79 1 0.8 maximum T4-3.WFQ=A+M 0.780 inf 0.79 1 0.8 maximum T4-4.WFQ=A+C 0.925 inf 0.79 1 0.8 maximum T 4-5. WFQ = A+M+C 0.925 inf 0.79 1 0.8 maximum FINO3 measurements 0.810 inf 0.79 1 0.8 maximum T x-y table indicator for reference in DNV-HS-10; WFQ weather forecast quality class A, B or C. +M meteorologist on site, +C calibrated based on measurement data. DEPARTMENT OF CIVIL ENGINEERING SCIENCE MEETS INDUSTRY 2016, STAVANGER

Long term verification. Alpha-Factor method DEPARTMENT OF CIVIL ENGINEERING SCIENCE MEETS INDUSTRY 2016, STAVANGER

Long term verification. Results Alpha-Factor method DECOFF method with ECMWF DEPARTMENT OF CIVIL ENGINEERING

Long term verification. Results Alpha-Factor method DECOFF method with FINO3 measurements DEPARTMENT OF CIVIL ENGINEERING

Long term verification. Results Number of weather windows Length of weather windows [Number X Length] of weather windows

Conclusions and discussion After extensive testing it can be concluded that the procedure for estimation of Probability of Failed Operations produces consistent results and could be used to assist in decision making for Offshore Wind Turbine installation. The proposed new DECOFF method performs better or at least as good as the standard Alpha-factor method (when number of windows X total window length measure is used). Weather forecast uncertainty plays a central role when predicting weather windows. With increasing uncertainty the length and number of weather windows decreases. This is on par with the standard Alpha-factor method. Using better, less uncertain, weather forecasts (calibrated weather forecasts, downscaling etc.) would be very beneficial in performance of DECOFF method. Easy extension to Oil and Gas an other relevant industries. DEPARTMENT OF CIVIL ENGINEERING SCIENCE MEETS INDUSTRY 2016, STAVANGER

Future work Possible future work would include but should not be limited to: Updating the model with Structural Reliability techniques in order to reduce the demand on a lot of simulations necessary to obtain reliable results. Splitting the limit states in Serviceability and Ultimate with a possibility to use separate maximum allowable Probabilities of Failure for different types of Limit States. Including Costs of Failure to produce a Risk-Based aspect allowing to evaluate different weather windows in terms of expected Risk rather than just Probability of Failure. Improving the accuracy of weather forecasts. Extending the methodology to more general Offshore Operations (Oil and Gas, Wind turbine installation on monopoles/jackets etc). DEPARTMENT OF CIVIL ENGINEERING SCIENCE MEETS INDUSTRY 2016, STAVANGER

THANK YOU FOR YOUR ATTENTION! ANY QUESTIONS? COMMENTS? TOMAS GINTAUTAS*, AAU tg@civil.aau.dk JOHN DALSGAARD SØRENSEN, AAU jds@civil.aau.dk