Experimental validation of a Kalman observer using linearized OpenFAST and a fully instrumented 1:70 model
[1];
- Department of Mechanical Engineering University of Maine Orono Maine USA, Alfond Offshore Ocean Engineering Wind and Wave Lab Advanced Structures and Composites Center Orono Maine USA
- Alfond Offshore Ocean Engineering Wind and Wave Lab Advanced Structures and Composites Center Orono Maine USA, Department of Civil &, Environmental Engineering University of Maine Orono Maine USA
- Department of Mechanical Engineering University of Maine Orono Maine USA, Biorobotics and Biomechanics Laboratory University of Maine Orono Maine USA
Abstract To enable real‐time monitoring and control strategies for floating offshore wind turbines, accurate information about the state of the system is needed. This paper details the application of a Kalman filter to the UMaine VolturnUS‐S floating wind platform to provide accurate state estimates in real time using minimal system measurements. The midfidelity nonlinear simulation tool OpenFAST was used to generate the underlying linear state‐space model for the Kalman filter. This linear model and its limitations are demonstrated through comparison with experimental data collected on a 1:70 froude‐scaled model of the floating platform and tower. Using a selection of five measurements from the real system, a Kalman filter was developed to provide estimates for the remaining system states and measurements. These estimates were then validated against the experimental values collected from testing of the scale model. Validation of the Kalman filter produced accurate estimates of surge, heave, and tower base bending moment, measurements of which were not available to the Kalman filter. Performance of the Kalman filter was tested and validated over a range of sea conditions from rated wind speed to storm events and demonstrated robustness in the Kalman filter to maintain accuracy across all operating conditions despite significant error in the underlying linear model for extreme conditions.
- Sponsoring Organization:
- USDOE
- Grant/Contract Number:
- SC0022103
- OSTI ID:
- 2352358
- Alternate ID(s):
- OSTI ID: 2440508; OSTI ID: 2532396
- Journal Information:
- Wind Energy, Journal Name: Wind Energy Journal Issue: 8 Vol. 27; ISSN 1095-4244
- Publisher:
- Wiley Blackwell (John Wiley & Sons)Copyright Statement
- Country of Publication:
- United Kingdom
- Language:
- English
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