Toward a Survey-Based Assessment of Wind Turbine Noise: The Impacts on Wellbeing of Local Residents

Lida Liao, Yuliang Ling, Bin Huang, Xu Zhou, Hongbo Luo, Peiling Xie, Ying Wu and Jialiang Huang
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Lida Liao: School of Energy and Power Engineering, Changsha University of Science and Technology, Changsha 410114, China
Yuliang Ling: School of Energy and Power Engineering, Changsha University of Science and Technology, Changsha 410114, China
Bin Huang: School of Energy and Power Engineering, Changsha University of Science and Technology, Changsha 410114, China
Xu Zhou: College of Mechanical Engineering, Hubei University of Automotive Technology, Shiyan 442002, China
Hongbo Luo: School of Electrical & Information Engineering, Changsha University of Science and Technology, Changsha 410114, China
Peiling Xie: School of Energy and Power Engineering, Changsha University of Science and Technology, Changsha 410114, China
Ying Wu: College of Mechanical Engineering, Hubei University of Automotive Technology, Shiyan 442002, China
Jialiang Huang: School of Energy and Power Engineering, Changsha University of Science and Technology, Changsha 410114, China

Energies, 2020, vol. 13, issue 21, 1-16

Abstract: As a renewable energy source, wind energy harvesting provides a desirable solution to address the environmental concerns associated with energy production to satisfy the increasingly global demand. Over the years, the penetration of wind turbines has experienced a rapid growth, however, the impacts of turbine noise correspondingly become a major concern in wind energy harvesting. Recent studies indicate that the noise emitted by turbine operating could increase the risk of nuisance, which might further affect the well-being of local residents. However, the main factors affecting turbine noise assessment and to what extent they contribute to the assessment are still unclear. In this study, a survey-based approach is developed to identify these major factors and to explore the interactions between the factors and assessment results. Principal component analysis method was adapted to extract key factors; followed by reliability assessment, validity analysis, descriptive assessment, and correlation analysis were conducted to test the robust of the proposed methodology, as well as to examine the interactions between variables. Regression analysis was finally employed to measure the impacts on results contributed by the key factors. Findings of this study indicate that key factors including physical conditions, control capacity, and subjective opinions are of significant impact on residents’ response to wind turbine noise, while the factor of subjective opinions contributes predominately to the assessment results. Further validations also indicate that the proposed approach is robust and can be extensively applied in survey-based assessments for other fields.

Keywords: wind turbines noise; subjective opinions; physical condition; control capacity; noise assessment (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
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