The research addresses one of the key obstacles in the spatial planning of wind turbines: the perception of low-frequency pressure fluctuations and infrasound, along with their impact on humans and the environment. The main objective of the project is to prove that existing measurements of wind turbine infrasound are often distorted by pseudosound (pressure fluctuations caused by turbulent airflow over sensors and building structures), leading to an overestimation of measured infrasound levels. The project will provide clear scientific answers, advanced measurement methodologies, and a foundation for drafting new national legislation regarding wind turbine noise.
Scientific Background and Challenge
Sleep and well-being disturbances, which individuals living near wind turbines often attribute to infrasound, are the most common public argument against their installation. The perception of infrasound is more pronounced indoors than outdoors. However, wind movement over buildings creates strong turbulence and pressure fluctuations.
The key question answered by this project is:
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Do individuals indoors truly perceive real infrasound propagating from the wind turbine through windows, doors, and walls, or are they experiencing acoustic resonance effects (e.g., Helmholtz resonance or standing waves) excited within the room by locally generated pseudosound due to wind turbulence?
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Real infrasound has extremely long wavelengths (approximately 344 meters at 1 Hz). Conversely, the pressure pulses generated as wind turbine blades pass the tower (the so-called Blade Passage Frequency – BPF) last only a fraction of a second. Consequently, a question arises: Do spectral components arround 1 Hz and their harmonics represent actual acoustic wave propagation, or are rather the result of the frequency analysis of repeating pulses?
Project Objectives
The project pursues four main goals:
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Separation of Infrasound and Pseudosound: Prove that measured pressure fluctuations in the infrasonic range are a combination of real infrasound and pseudosound, and develop a methodology for their precise separation.
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Assessment of Background for Legislation: Develop a methodology for evaluating baseline ambient noise under wind turbine operating conditions (at wind speeds above 6.5 m/s) and incorporate the findings into guidelines for national legislation.
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Reduction of Indoor Pressure oscillation Levels: Demonstrate that pressure fluctuations inside rooms can be reduced through proper source identification and the adjustment of structural and ventilation parameters.
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Public Education and Restoring Public Trust: Educate the public using rigorous scientific evidence and noise mitigation methods to restore trust in objective measurements of wind turbine impacts.
Methodology and Work Packages
The research work is divided into several interconnected work packages that combine experimental measurements, advanced signal processing, and numerical simulations:
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Development of Measurement Algorithms and IoT Sensors (WP1 & WP2): Developing novel alignment algorithms and correlation matrices based on wave propagation velocity (speed of sound c ≈ 344 m/s vs. wind speed v ≈ 10 m/s. Detection and separation of infrasound from pseudosound will be conducted using a network of autonomous wireless IoT infrasound sensor arrays supported by processing on FPGA/ARM platforms.
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Turbulence Simulations (WP3): Utilizing supercomputing capacity at the Faculty of Mechanical Engineering in Ljubljana to perform Large Eddy Simulations (LES) to model turbulent wind flow around buildings in a real-world environment (the settlement of Dolenja vas).
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Interaction with Buildings and Enclosed Spaces (WP4): Investigating resonance phenomena in typical living spaces (Helmholtz resonance, standing waves) and the effect of structural element static stiffness on indoor infrasound excitation.
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Integration and Legislative Proposals (WP5): Synthesizing findings and, in cooperation with the Ministry of the Environment, Climate and Energy (MOPE), preparing expert technical foundations for new limit values and evaluation methodologies for wind turbine noise.
Partner Institutions and Collaboration
The project is led by the Laboratory for Power Engineering Machinery and Applied Acoustics (LEDSTA) at the Faculty of Mechanical Engineering, University of Ljubljana, in close collaboration with the Laboratory for Integrated Circuit Design (FE), the Laboratory for Fluid Dynamics and Thermodynamics (LFDT), and the Ministry of the Environment, Climate and Energy (MOPE). The project serves as an umbrella project for the project “Full spectrum characterization of wind turbines noise by measurements, modelling, objective and subjective assessment,” carried out at the Faculty of Electrical Engineering and Computing, University of Zagreb.
Research projects are (co)financed by the Slovenian Research and Innovation Agency
- Member of the University of Ljubljana: Faculty of Mechanical Engineering
- Project code: J1-70055
- Science: Natural sciences
- SICRIS: WIND TURBINE GENERATED INFRASOUND OR PSEUDOSOUND?
The project follows the standard procedure of the Laboratory for Power Engineering Machinery and Applied Acoustics (LEDSTA) for research data management, prepared in accordance with FAIR principles (Findable, Accessible, Interoperable, Reusable), the requirements of ARIS, the Regulation on Open Science, and the recommendations of Science Europe and Horizon Europe.
The project primarily generates experimental acoustic data, sound pressure and vibration measurements, data from various sensors, numerical simulations, and derived research data. Due to the large volumes of raw data (up to several TB per individual measurement campaign or simulation), these are retained only during the execution of the project, result analysis, and the preparation of scientific publications. Upon completion of the research, they are generally deleted, except where funding bodies or contractual conditions require longer retention.
Derived research data, metadata, calibration data, input models, software code, documentation, and results used in scientific publications are stored for the long term. This approach ensures traceability, research reproducibility, and long-term reusability of data, with significantly lower storage space requirements.
Research data is shared according to the principle “as open as possible, as closed as necessary.” Following the publication of results, derived data, software code, input models, and experimental protocols are made publicly accessible, provided this is permitted by requirements regarding personal data protection, intellectual property, and contractual obligations.
A more detailed description of the research data management procedures is available in the document on the LEDSTA laboratory website: LEDSTA Standard Operating Procedure – Research Data Management Plan (PDF).