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Tuesday, 11 March 2014
16:30 - 18:00 Wind turbine noise: How to avoid disturbing the neighbours
Resource Assessment  

Room: Ponent
Session description

With a new version of IEC 61400-11 published this year, it may be thought that wind turbine noise emission is well understood. However, wind farm developers still receive complaints from residents about 'amplitude modulation' (AM) noise, a subject not covered by the IEC standard. Amplitude modulation will therefore be one of the main topics in this session. This session will also explore different sound propagation models and the impact of environmental conditions on propagation. Another topic for this session is how to optimise wind turbines and wind farms for sites with noise restrictions.

Learning objectives

  • Understand why it is important to consider noise for resource assessment
  • Understand how a wind farm as a whole can be optimised to maximise performance with noise constraints
  • Understand what amplitude modulation is and why it is a concern for residents near wind farms
  • Understand the role that propagation modelling plays in the prediction of far field noise
Lead Session Chair:
Saskia Honhoff, GE Energy, Germany
Benoit Petitjean GE Global Research, Germany
Benoit Petitjean (1) F P Akshay Ambekar (4) Roger Drobietz (2) Kevin Kinzie (3)
(1) GE Global Research, Garching bei München, Germany (2) GE Wind Energy, Salzbergen, Germany (3) GE Wind Energy, Greenville, SC, United States of America (4) GE Global Research, Bangalore, India

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Presenter's biography

Biographies are supplied directly by presenters at EWEA 2014 and are published here unedited

Dr. Benoit Petitjean has been working in the wind industry for 7 years. He is currently a Research Engineer with GE Global Research in Germany.
He holds a Diplôme d’Ingénieur from Ecole Centrale de Lyon, France (2002). He received his graduate degrees (M.S. and Ph.D.) from the Pennsylvania State University, USA where he investigated nonlinear effects in the noise radiated from high-speed model jets.
In 2007 he joined GE Wind Energy, where his activities focused essentially on achieving wind turbine blade noise reduction both by modifying blade shape and optimizing turbine operation.


Concepts for noise optimized wind farm operation


This paper intends to provide an overview of recent studies on technology elements and operating schemes to maximize farm-level annual energy production in noise constrained environments. First, a general methodology is presented at the single turbine level to design series of noise reduced operation modes (NRO) with specific noise targets and optimum energy yield. Second, strategies are described to best combine these modes in the context of a wind farm. Such a farm-level approach is critical for wind turbine installation in noise sensitive areas, especially in regions where the allowable noise levels are defined based on pre-existing background conditions.


At the turbine level, it is generally true that most operating parameters that drive towards higher power also drive towards higher noise. The challenge is thus to operate the turbine in a way that satisfies noise constraints with the highest possible power output. For this purpose, NRO modes are built using optimization procedures that combine both noise and power response surfaces. Nevertheless, because NRO’s are designed for a single turbine and based on near-field noise data, they do not provide a direct solution to meet far-field noise limits; it is their adequate combination that will help achieve this goal.

Main body of abstract

Once the individual turbine sound characteristics have been designed by the manufacturer, it is up to the farm operator to provide a site layout and operation that meet the local noise regulations. By judiciously selecting the right turbine configuration and operating modes, it is possible to optimize sound and power outputs without incurring unnecessary energy losses.
Typically, turbine configuration and operating modes are selected based on the worst case situation. A single noise propagation simulation is carried out using the maximum noise emission of all turbines within a farm as input. Following this approach, a single (fixed) NRO mode is attributed to each turbine across the farm. The modes can differ from turbine to turbine, but they are independent from any time-varying parameters influencing the overall farm noise emission, such as wind speed, wind direction, or air density. Obviously, this results in unnecessary conservatism for situations outside this worst case.
More sophisticated wind farm operation schemes are possible, with higher energy yield. Repeated optimization runs performed with a large variety of inputs representative of the different conditions experienced within a given site (and not only worst-case conditions) can be used to determine the most appropriate distribution of NRO modes across the farm. Combining an appropriate control architecture with real-time inputs allows to continuously adjust the farm operation in a manner that both satisfies all noise constraints and maximizes AEP. Results from field test measurements performed with both ‘worst-case’ and ‘optimized’ approaches will be presented in the paper.


Strategies have been presented to design and appropriately combine noise reduced operation modes in a wind farm in a way that optimizes both sound and power outputs, and avoids unnecessary energy losses. Such sophisticated farm-level operation schemes represent an important progress towards better-performing, better-accepted, and quieter wind parks. Additionally, these technology elements constitute the first steps towards a “smart wind farm,” which would automatically adjust operation to meet desired noise constraints as a response to changes in site ambient conditions.

Learning objectives
1. Upon completion, participants will be able to list the main mechanisms of wind turbine noise.
2. Participants will be able to describe how individual turbine operation can be adjusted to optimize energy yield when reduced noise levels are necessary.
3. Participants will be able to define strategies to optimize wind park-level energy production in noise constrained environments.