Research on intelligent analysis method for dynamic response of onshore wind turbines

Researchers have developed a high-fidelity 13-degree-of-freedom nonlinear model and an intelligent algorithm for wind turbine dynamic analysis. This framework accurately captures complex tower-blade interactions, including often-neglected torsional effects, achieving a remarkable agreement with high-fidelity benchmarks. Published in Smart Construction, this work provides a powerful and efficient tool for structural assessment and future optimization of large-scale wind energy systems.

The global push for sustainable energy has cemented wind power's role in the renewable transition. However, designing safe and cost-effective onshore wind turbines requires a deep understanding of their dynamic behavior under complex environmental loads. Traditional modeling approaches often struggle to balance computational efficiency with simulation accuracy, particularly in capturing the full coupled dynamics of the entire system.

Addressing this challenge, a research team led by Professor Xuhong Zhou from Chongqing University has developed an innovative nonlinear dynamic modeling and intelligent analysis framework for onshore wind turbines. Their study introduces a comprehensive 13-degree-of-freedom (13-DOF) multibody model derived using Euler-Lagrange formalism.

"This model provides a holistic view of wind turbine dynamics," explains Professor Guoqing Huang. "A key advancement is the explicit incorporation of the tower's torsional degree of freedom, an aspect often simplified in conventional models but critical for accurate load assessment in the upper tower sections."

The tower and blades are modeled as Euler-Bernoulli beams capable of capturing both bending and torsional deformations, with aerodynamic loads computed via an enhanced Blade Element Momentum theory. To tackle the critical challenge of selecting optimal vibration mode functions—which significantly impact computational cost and result accuracy—the team proposed an intelligent mode selection algorithm. This algorithm automatically identifies the most suitable mode shapes based on structural response convergence.

"A major hurdle in efficient simulation is choosing the right modal representations without sacrificing physical accuracy," says Professor Jiepeng Liu. "Our intelligent algorithm systematically optimizes this selection, striking a balance that avoids the prohibitive computational cost of high-fidelity commercial tools while maintaining high accuracy."

The numerical simulations, implemented symbolically in MATLAB®, were rigorously validated against OpenFAST, a widely recognized high-fidelity simulation tool from the National Renewable Energy Laboratory (NREL), using the NREL 5-MW reference turbine as a benchmark. The results demonstrated that the proposed model effectively captures nonlinear and coupled dynamic behavior.

"The validation showed a close agreement with OpenFAST outputs, with relative errors in key response metrics, such as tower-top and blade-tip displacements, maintained within 3.5%," notes Doctor Maolin Dai from Chongqing University. "This level of accuracy, achieved at a fraction of the computational expense, is highly promising for engineering applications."

This modeling framework offers a reliable tool for the structural dynamic assessment of existing turbines and establishes a solid foundation for future applications in optimization and control of large-scale wind energy systems. By enabling more accurate and efficient simulations, it can contribute to the design of lighter, safer, and more economically competitive wind turbine towers, which account for a significant portion of project costs.

"The framework is particularly suitable for preliminary design, parameter sensitivity studies, and dynamic response analysis," concludes Associate Professor Liang Cao from Hunan University. "It charts a clear path for developing next-generation, performance-driven design tools for the wind energy industry."

The team acknowledges future directions, including further theoretical refinement to capture more complex dynamic couplings and expansion of the model's validation under non-steady-state conditions like turbulent inflow.

This paper "Research on intelligent analysis method for dynamic response of onshore wind turbines" was published in Smart Construction (ISSN: 2960-2033), a peer-reviewed open access journal dedicated to original research articles, communications, reviews, perspectives, reports, and commentaries across all areas of intelligent construction, operation, and maintenance, covering both fundamental research and engineering applications. The journal is now indexed in Scopus, and article submission is completely free of charge until 2026.

Citation:

Dai M, Cao L, Huang G, Zhou X, Liu J. Research on intelligent analysis method for dynamic response of onshore wind turbines. Smart Constr. 2025; 20250028. https://doi.org/10.55092/sc20250028