scholarly journals Comparative Environmental Assessment of Wind Energy Projects: Acoustic Load

2018 ◽  
Keyword(s):  
Wind Energy ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Environmental Assessment ◽  
Noise Level ◽  
Background Noise ◽  
Comfort Level ◽  
Background Noise Level ◽  
Energy Projects ◽  
Acoustic Load

Purpose. Comparative environmental assessment of wind energy projects from the perspective of the potential acoustic load on the environment: compliance with permissible values, specificity of propagation and optimization of siting. Methods. Analysis and synthesis of information, field research, cartographic and mathematical modelling. Results. In the most part of the study area, the background noise level reached rather high values, higher than the «comfort» level of 45 dB. The simulation of sound propagation from the wind turbine showed an attenuation to a value of less than 20 dB at a distance of 2 kilometers. The resulting acoustic load was calculated for the points referring to the buildings of the nearest settlements (for the case of installing the Enercon E-40 and Enercon E-115 wind turbines). The calculations of the resulting sound levels make it possible to state that the acoustic effect of the wind turbines in both siting strategies is 15-20 dB lower compared to the background noise level, the main component of which is wind noise. The excess of noise level was 5 dB for Enercon E-115, and 8-9 dB for Enercon E-40. Conclusions. According to the type of wind turbine, the noise level may overlap with the background level and produce a relatively less acoustic impact on the local population. Even in case of the extensive wind energy development strategy, the total noise levels will not exceed the background levels within the model site.

SHAPING OF AN AUTONOMOUS POWER SYSTEM FOR GUARANTEED POWER SUPPLY WITH THE PREDOMINANCE WIND ENERGY

2018 ◽  
pp. 28-50
Author(s):  
S. G. Ignatiev ◽  
S. V. Kiseleva
Keyword(s):  
Energy Storage ◽  
Wind Speed ◽  
Wind Energy ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Energy Demand ◽  
Diesel Generator ◽  
Average Wind Speed ◽  
Wind Speeds ◽  
Average Wind

Optimization of the autonomous wind-diesel plants composition and of their power for guaranteed energy supply, despite the long history of research, the diversity of approaches and methods, is an urgent problem. In this paper, a detailed analysis of the wind energy characteristics is proposed to shape an autonomous power system for a guaranteed power supply with predominance wind energy. The analysis was carried out on the basis of wind speed measurements in the south of the European part of Russia during 8 months at different heights with a discreteness of 10 minutes. As a result, we have obtained a sequence of average daily wind speeds and the sequences constructed by arbitrary variations in the distribution of average daily wind speeds in this interval. These sequences have been used to calculate energy balances in systems (wind turbines + diesel generator + consumer with constant and limited daily energy demand) and (wind turbines + diesel generator + consumer with constant and limited daily energy demand + energy storage). In order to maximize the use of wind energy, the wind turbine integrally for the period in question is assumed to produce the required amount of energy. For the generality of consideration, we have introduced the relative values of the required energy, relative energy produced by the wind turbine and the diesel generator and relative storage capacity by normalizing them to the swept area of the wind wheel. The paper shows the effect of the average wind speed over the period on the energy characteristics of the system (wind turbine + diesel generator + consumer). It was found that the wind turbine energy produced, wind turbine energy used by the consumer, fuel consumption, and fuel economy depend (close to cubic dependence) upon the specified average wind speed. It was found that, for the same system with a limited amount of required energy and high average wind speed over the period, the wind turbines with lower generator power and smaller wind wheel radius use wind energy more efficiently than the wind turbines with higher generator power and larger wind wheel radius at less average wind speed. For the system (wind turbine + diesel generator + energy storage + consumer) with increasing average speed for a given amount of energy required, which in general is covered by the energy production of wind turbines for the period, the maximum size capacity of the storage device decreases. With decreasing the energy storage capacity, the influence of the random nature of the change in wind speed decreases, and at some values of the relative capacity, it can be neglected.

Prediction of Threshold Sand Rates from Acoustic Monitors Using Artificial Intelligence

2021 ◽  
Author(s):  
Ronald E. Vieira ◽  
Bohan Xu ◽  
Asad Nadeem ◽  
Ahmed Nadeem ◽  
Siamack A. Shirazi
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Noise Level ◽  
Background Noise ◽  
Pipe Wall ◽  
Flow Patterns ◽  
Operating Conditions ◽  
Flow Conditions ◽  
Background Noise Level ◽  
Input Parameters

Abstract Solids production from oil and gas wells can cause excessive damage resulting in safety hazards and expensive repairs. To prevent the problems associated with sand influx, ultrasonic devices can be used to provide a warning when sand is being produced in pipelines. One of the most used methods for sand detection is utilizing commercially available acoustic sand monitors that clamp to the outside of pipe wall and measures the acoustic energy generated by sand grain impacts on the inner side of a pipe wall. Although the transducer used by acoustic monitors is especially sensitive to acoustic emissions due to particle impact, it also reacts to flow induced noise as well (background noise). The acoustic monitor output does not exceed the background noise level until a sufficient sand rate is entrained in the flow that causes a signal output that is higher than the background noise level. This sand rate is referred to as the threshold sand rate or TSR. A significant amount of data has been compiled over the years for TSR at the Tulsa University Sand Management Projects (TUSMP) for various flow conditions with stainless steel pipe material. However, to use this data to develop a model for different flow patterns, fluid properties, pipe, and sand sizes is challenging. The purpose of this work is to develop an artificial intelligence (AI) methodology using machine learning (ML) models to determine TSR for a broad range of operating conditions. More than 250 cases from previous literature as well as ongoing research have been used to train and test the ML models. The data utilized in this work has been generated mostly in a large-scale multiphase flow loop for sand sizes ranging from 25 to 300 μm varying sand concentrations and pipe diameters from 25.4 mm to 101.6 mm ID in vertical and horizontal directions downstream of elbows. The ML algorithms including elastic net, random forest, support vector machine and gradient boosting, are optimized using nested cross-validation and the model performance is evaluated by R-squared score. The machine learning models were used to predict TSR for various velocity combinations under different flow patterns with sand. The sensitivity to changes of input parameters on predicted TSR was also investigated. The method for TSR prediction based on ML algorithms trained on lab data is also validated on actual field conditions available in the literature. The AI method results reveal a good training performance and prediction for a variety of flow conditions and pipe sizes not tested before. This work provides a framework describing a novel methodology with an expanded database to utilize Artificial Intelligence to correlate the TSR with the most common production input parameters.

Simulation of Flow Field on a Large Scale Wind Turbine

2008 ◽  
Author(s):  
I. Janajreh ◽  
C. Ghenai
Keyword(s):  
Flow Field ◽  
Wind Energy ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Cross Sections ◽  
Large Scale ◽  
Wind Farms ◽  
Operating Characteristics ◽  
Cross Sectional ◽  
Capital Costs

Large scale wind turbines and wind farms continue to evolve mounting 94.1GW of the electrical grid capacity in 2007 and expected to reach 160.0GW in 2010 according to World Wind Energy Association. They commence to play a vital role in the quest for renewable and sustainable energy. They are impressive structures of human responsiveness to, and awareness of, the depleting fossil fuel resources. Early generation wind turbines (windmills) were used as kinetic energy transformers and today generate 1/5 of the Denmark’s electricity and planned to double the current German grid capacity by reaching 12.5% by year 2010. Wind energy is plentiful (72 TW is estimated to be commercially viable) and clean while their intensive capital costs and maintenance fees still bar their widespread deployment in the developing world. Additionally, there are technological challenges in the rotor operating characteristics, fatigue load, and noise in meeting reliability and safety standards. Newer inventions, e.g., downstream wind turbines and flapping rotor blades, are sought to absorb a larger portion of the cost attributable to unrestrained lower cost yaw mechanisms, reduction in the moving parts, and noise reduction thereby reducing maintenance. In this work, numerical analysis of the downstream wind turbine blade is conducted. In particular, the interaction between the tower and the rotor passage is investigated. Circular cross sectional tower and aerofoil shapes are considered in a staggered configuration and under cross-stream motion. The resulting blade static pressure and aerodynamic forces are investigated at different incident wind angles and wind speeds. Comparison of the flow field results against the conventional upstream wind turbine is also conducted. The wind flow is considered to be transient, incompressible, viscous Navier-Stokes and turbulent. The k-ε model is utilized as the turbulence closure. The passage of the rotor blade is governed by ALE and is represented numerically as a sliding mesh against the upstream fixed tower domain. Both the blade and tower cross sections are padded with a boundary layer mesh to accurately capture the viscous forces while several levels of refinement were implemented throughout the domain to assess and avoid the mesh dependence.

scholarly journals Tourist Viewshed Externalities and Wind Energy Production

2017 ◽  
Vol 46 (2) ◽  
pp. 224-241 ◽  
Author(s):  
Jacob R. Fooks ◽  
Kent D. Messer ◽  
Joshua M. Duke ◽  
Janet B. Johnson ◽  
Tongzhe Li ◽  
...  
Keyword(s):  
Wind Energy ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Energy Production ◽  
Hotel Room ◽  
Negative Effect ◽  
The Impact ◽  
Large Wind

This study uses an experiment where ferry passengers are sold hotel room “views” to evaluate the impact of wind turbines views on tourists’ vacation experience. Participants purchase a chance for a weekend hotel stay. Information about the hotel rooms was limited to the quality of the hotel and its distance from a large wind turbine, as well as whether or not a particular room would have a view of the turbine. While there was generally a negative effect of turbine views, this did not hold across all participants, and did not seem to be effected by distance or hotel quality.

Optimized Small Vertical Axis Wind Turbine (VAWT), Phase I

2021 ◽  
Author(s):  
Moshe Zilberman ◽  
Abdelaziz Abu Sbaih ◽  
Ibrahim Hadad
Keyword(s):  
Wind Energy ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Cost Effective ◽  
Clean Energy ◽  
Vertical Axis ◽  
Low Noise ◽  
Power Coefficient ◽  
Vertical Axis Wind Turbine ◽  
Different Types

Abstract Wind energy has become an important resource for the growing demand for clean energy. In 2020 wind energy provided more than 6% of the global electricity demand. It is expected to reach 7% at the end of 2021. The installation growth rate of small wind turbines, though, is relatively slow. The reasons we are interested in the small vertical axis wind turbines are their low noise, environmentally friendly, low installation cost, and capable of being rooftop-mounted. The main goal of the present study is an optimization process towards achieving the optimal cost-effective vertical wind turbine. Thirty wind turbine models were tested under the same conditions in an Azrieli 30 × 30 × 90 cm low-speed wind tunnel at 107,000 Reynolds number. The different types of models were obtained by parametric variations of five basic models, maintaining the same aspect ratio but varying the number of bucket phases, the orientation angles, and the gaps between the vanes. The best performing turbine model was made of one phase with two vanes of non-symmetric bipolynomial profiles that exhibited 0.2 power coefficient, relative to 0.16 and 0.13 that were obtained for symmetrical polynomial and the original Savonius type turbines, respectively. Free rotation, static forces and moments, and dynamic moments and power were measured for the sake of comparison and explanation for the variations in performances of different types of turbines. CFD calculations were used to understand the forces and moment behaviors of the optimized turbine.

Effect of Slotted Angle on Savonius Wind Turbine Performance

2021 ◽  
Vol 104 ◽  
pp. 83-88
Author(s):  
Rahmat Wahyudi ◽  
Diniar Mungil Kurniawati ◽  
Alfian Djafar
Keyword(s):  
Wind Energy ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Electrical Energy ◽  
Speed Ratio ◽  
Angle Variation ◽  
Wind Speeds ◽  
Turbine Performance ◽  
Savonius Wind Turbine ◽  
Low Wind Speeds

The potential of wind energy is very abundant but its utilization is still low. The effort to utilize wind energy is to utilize wind energy into electrical energy using wind turbines. Savonius wind turbines have a very simple shape and construction, are inexpensive, and can be used at low wind speeds. This research aims to determine the effect of the slot angle on the slotted blades configuration on the performance produced by Savonius wind turbines. Slot angle variations used are 5o ,10o , and 15o with slotted blades 30% at wind speeds of 2,23 m/s to 4,7 m/s using wind tunnel. The result showed that a small slot angle variation of 5o produced better wind turbine performance compared to a standard blade at low wind speeds and a low tip speed ratio.

Modeling Speech Level as a Function of Background Noise Level and Talker-to-Listener Distance for Talkers Wearing Hearing Protection Devices

2017 ◽  
Vol 60 (12) ◽  
pp. 3393-3403 ◽  
Author(s):  
Rachel E. Bouserhal ◽  
Annelies Bockstael ◽  
Ewen MacDonald ◽  
Tiago H. Falk ◽  
Jérémie Voix
Keyword(s):  
Noise Level ◽  
Background Noise ◽  
Speech Sound ◽  
Sound Level ◽  
Hearing Protection ◽  
Background Noise Level ◽  
Vocal Effort ◽  
Protection Devices ◽  
The Difference ◽  
The Relationship

Purpose Studying the variations in speech levels with changing background noise level and talker-to-listener distance for talkers wearing hearing protection devices (HPDs) can aid in understanding communication in background noise. Method Speech was recorded using an intra-aural HPD from 12 different talkers at 5 different distances in 3 different noise conditions and 2 quiet conditions. Results This article proposes models that can predict the difference in speech level as a function of background noise level and talker-to-listener distance for occluded talkers. The proposed model complements the existing model presented by Pelegrín-García, Smits, Brunskog, and Jeong (2011) and expands on it by taking into account the effects of occlusion and background noise level on changes in speech sound level. Conclusions Three models of the relationship between vocal effort, background noise level, and talker-to-listener distance for talkers wearing HPDs are presented. The model with the best prediction intervals is a talker-dependent model that requires the users' unoccluded speech level at 10 m as a reference. A model describing the relationship between speech level, talker-to-listener distance, and background noise level for occluded talkers could eventually be incorporated with radio protocols to transmit verbal communication only to an intended set of listeners within a given spatial range—this range being dependent on the changes in speech level and background noise level.

Sound environment quality in nursing units in Chinese nursing homes: A pilot study

2020 ◽  
Vol 27 (4) ◽  
pp. 283-298
Author(s):  
Hui Xie ◽  
Bingzhi Zhong ◽  
Chang Liu
Keyword(s):  
Nursing Homes ◽  
Nursing Staff ◽  
Noise Level ◽  
Background Noise ◽  
Subjective Evaluation ◽  
Reverberation Time ◽  
Staff Members ◽  
Background Noise Level ◽  
Sound Environment ◽  
Nursing Station

Recent studies have investigated sound environment in nursing homes. However, there has been little research on the sound environment of nursing units. This research sought to address this gap. Subjective evaluations were gathered using questionnaire surveys of 75 elderly residents and 30 nursing staff members in five nursing units of five nursing homes in Chongqing, China. Background noise level and reverberation time were measured in five empty bedrooms, five occupied bedrooms and five occupied nursing station areas, in five nursing units. The subjective evaluation results indicate that the residents stay in the nursing units for most of their waking hours. The residents and nursing staff had strong preferences for natural sounds, with the lowest perceptions of these in the nursing units. The background noise level in all the occupied bedrooms exceeded Chinese standards for waking and sleeping hours. Only 20% of the occupied nursing station areas were below the allowable noise level for recreation and fitness room during sleeping hours. The nursing station area was identified as the main source of noise in the unit during waking hours. The average background noise level of the occupied bedrooms was 3–12 dBA higher than that of the empty bedrooms during sleeping hours. Attention should be given to the implementation of noise specifications for sleeping hours. The reverberation time of the bedrooms was within the range of 0.44–0.68 s, and in the nursing station areas it was 0.63–1.54 s.

Sign in / Sign up

Export Citation Format

Share Document