In a significant stride towards enhancing wind turbine modeling and integration into hybrid renewable energy systems, researchers have developed a novel nonlinear extended model that promises to bridge the gap between theoretical benchmarks and real-world engineering scenarios. This advancement, led by Shifeng Jia from the Research Centre for Digitalization and Intelligent Diagnosis to New Energies at Northeast Petroleum University in China, is set to revolutionize the energy sector by improving the robustness and efficiency of wind power systems.
The existing models often simplify generators as first-order inertia models, which fail to capture the complexities of practical engineering environments. “Fluctuations in machine parameters are inevitable in complex engineering settings, and these have not been fully considered in the existing models,” Jia explains. To address this, Jia and his team have proposed a comprehensive nonlinear extended model that incorporates ultra-local models to redesign control strategies for both machine side and grid side.
One of the standout features of this new model is the integration of a super-helical integral sliding-mode-observer. This innovative component is designed to estimate rotational speed and electrical angle, even in the presence of machine parameter mismatches and disturbances. “This enhances the robustness of the model, making it more reliable and adaptable to real-world conditions,” Jia adds.
The practical implications of this research are substantial. The wind turbine model has been successfully applied to a hybrid energy storage and hydrogen production system, serving as the supply side. This ensures stable power delivery based on advanced control strategies for both machine side and grid side. The effectiveness of these methods has been demonstrated through co-simulation studies using MATLAB/SIMULINK and FAST, as well as hardware-in-loop experimental platforms.
This research, published in the English-language journal *Engineering Science and Technology: An International Journal*, is poised to shape future developments in the field of renewable energy. By providing a more accurate and robust model for wind turbines, it paves the way for more efficient and reliable integration of wind power into hybrid energy systems. This could have significant commercial impacts, particularly in the energy sector, where the demand for stable and sustainable power sources is ever-increasing.
As the world continues to shift towards renewable energy, advancements like these are crucial. They not only improve the performance of existing technologies but also open up new possibilities for innovation and development. With the work of researchers like Shifeng Jia, the future of wind energy looks brighter and more promising than ever.