Chaired by: Ervin Bossanyi (DNV GL)
Topic: CM. Control and Monitoring
Form of presentation: Oral
Duration: 90 minutes
Vasilis Pettas, Mohammad Salari, David Schlipf, Po Wen Cheng
In recent years the focus of wind energy industry is on reducing levelized cost of energy by rotor upscaling. Moreover, a current topic of interest to both industry and academia is the extension of lifetime to existing wind turbines approaching the end of initial design span. Thus, the need for load alleviation technologies integrated in the design process or for retrofit purposes is becoming more relevant. One of these is individual blade pitch control, a recurring topic in research, with known advantages and weaknesses namely the pitch actuator and bearing wear. The present work suggests such a system incorporating three independent controllers with input the root bending moments on the rotating frame. The linear system identification for controller design is based on black box identification and filters are used both at the input and output. Different setups of the independent blade control scheme are applied on a 10 MW reference turbine, with a large and highly flexible rotor representative of the current industrial status, in fully turbulent conditions. The investigation aims on evaluating the system’s performance based on the fatigue load alleviation potential for different components as well as identifying the tradeoffs for each design choice.
Marta Bertelè, Carlo Luigi Bottasso, Stefano Cacciola
In this paper, the turbine itself is used as anemometer to estimate the infow condition at the rotor disk. Indeed, given that any anisotropy in the wind will lead to periodic loads on the machine, by studying the machine response one could infer rotor effective wind conditions and exploit such information to maximize the performance of a single turbine or of a wind farm. Specifically, expanding the idea of , the case of an individual pitch controlled machine (IPC) is here considered: a non-linear implicit model is therefore formulated to relate the wind characteristic to the pitch and blade loads 1xRev harmonics and its performance will be tested in both turbulent and uniform wind conditions.
To reduce the cost of wind energy, it is essential to reduce loads on turbine blades to increase lifetime and decrease maintenance cost. To achieve this, Individual Pitch Control (IPC) received an increasing amount of attention recently. In this paper, a data-driven IPC algorithm called Subspace Predictive Repetitive Control (SPRC) is used to alleviate periodic loads on a scaled 2-bladed wind turbine in turbulent wind conditions. These wind conditions are created in an open-jet wind tunnel with an active grid, enabling unique reproducible high turbulent wind conditions. Signicant load reductions are achieved even under these high turbulent conditions.
Wind energy research groups from various disciplines generally use self-developed baseline wind turbine control implementations and tunings, which complicates the evaluation and comparison of new control algorithms. To solve this problem, the Delft Research Controller (DRC) aims to provide an open, modular and fully adaptable baseline wind turbine controller to the scientific community. New control implementations can be added to the existing baseline controller for public use, and in this way, convenient assessments of the proposed algorithms is possible. Like NREL’s high-fidelity wind turbine simulation software FAST, the DRC is being developed in Fortran and uses the Bladed-style DISCON controller interface. Because of the open character and modular set-up, scientists are able to collaborate and contribute in making continuous improvements to the code. The compiled controller is configured by a single control settings parameter file, and can work with any wind turbine model in FAST and Bladed. Baseline parameter files are supplied for the NREL 5-MW and DTU 10-MW reference wind turbines.