Requirements for the design of wind turbines advance facing the challenges of a high content of renewable energy sources in the public grid. A high percentage of renewable energy weaken the grid and grid faults become more likely, which add additional loads on the wind turbine. Load calculations with aero-elastic models are standard for the design of wind turbines. Components of the electric system are usually roughly modeled in aero-elastic models and therefore the effect of detailed electrical models on the load calculations is unclear. A holistic wind turbine model is obtained, by combining an aero-elastic model and detailed electrical model into one co-simulation. The holistic model, representing a DFIG turbine is compared to a standard aero-elastic model for load calculations. It is shown that a detailed modelling of the electrical components e.g., generator, converter, and grid, have an influence on the results of load calculations. An analysis of low-voltage-ride-trough events during turbulent wind shows massive increase of loads on the drive train and effects the tower loads. Furthermore, the presented holistic model could be used to investigate different control approaches on the wind turbine dynamics and loads. This approach is applicable to the modelling of a holistic wind park to investigate interaction on the electrical level and simultaneously evaluate the loads on the wind turbine.
Digital twins enable the observation, prediction, and optimization of a physical system and thus allow to realize their full potential. However, their functionality is mainly based on simulation models of the entire system behavior. For modular multi-domain systems, this requires the extensive use of dynamically composed models that are made up of individual component models. The FMI-Standard forms a solid foundation for this problem and is very well known in the automotive engineering fields. However, composed system models using FMI are not widely adapted in renewable energy and wind energy yet. So far, the coupling of simulation models is limited. This paper discusses the strategy of building digital twins from individual FMUs with predefined model interfaces based on an ontology for renewable energy systems. An accelerated development is enabled by the exchange of sub-models in the digital twin without adjustments of interface. An example for the proposed process is given by the composed simulation model of a hydrogen generation process based on wind energy.
Controller design is always accompanied by an evaluation of control performance. However, for wind turbines, there is only a diffuse consensus on what a good controller constitutes, and no clear method to evaluate overall controller performance. Most evaluations, which can be found in wind turbine control literature, follow similar approaches. However, details, such as the models used, the scope of simulation or the result evaluation metric, can change the validity of results greatly. We sort these different evaluation approaches and align them with the V-Model for system design. This yields a structured process which defines requirements within three major domains: Stable automated operation, energy production and structural loads and limits. By following our proposed process, an impartial control evaluation scheme can be setup. Doing so, the complexity of evaluation and validation is handled in a systematic way. We give a clear indication which requirements need to be specified and show which difficulties arise when setting up an evaluating method. Furthermore, the influence of different evaluation parameters on the resulting controller quality measures is shown by evaluating results in slightly different ways. Thereby, the importance of the careful selection of quality measures is emphasized considering the high complexity of the task.
Wind turbines are a major source of renewable energy. Load monitoring is considered to improve reliability of the systems and to reduce the cost of operation. We propose a load monitoring system which consists of inertial measurement units. These track the movement of rotor blade, hub and tower top. In addition, wind turbine states, e.g. yaw angle, pitch angle and rotation speed, are recorded. By solving a navigation algorithm with a Kalman Filter approach, the raw sensor data is combined with an error model to reduce the tracking error. In total, five inertial measurement units are installed on the research wind energy converter AD 8–180 on the test site in Bremerhaven. Results show that tracking the blade movement in full operation is possible and that loads can be estimated with a model-based approach. In comparison to simulations, the blade deflections can be approximated by an aeroelastic model. The presented approach can be used as basis for comprehensive load monitoring and observer system with additional increase of system robustness by measurement redundancy.
The development and simulation of engineering systems, especially wind turbines, is becoming increasingly complex and elaborate. At the Fraunhofer Institute for Wind Energy Systems (IWES), the in-house tool MoWiT (Modelica library for Wind Turbines) is being developed for load simulation. MoWiT is based on the modeling language Modelica and is constantly evolving. It is, thus, also becoming more and more enhanced. This results in an increased need for automation for the complex simulation setups and a need for quality assurance of simulation code used. Test automation is used to always ensure the quality of the code. The automation of various simulations and the test automation for the load simulation code are provided by PyWiT (Python Framework for Wind Turbines), which will be presented here in more detail.
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