A quantitative analysis of the impact of wind turbines on operational Doppler weather radar data

Abstract. In many countries wind turbines are rapidly growing in numbers as the demand for energy from renewable sources increases. The continued deployment of wind turbines can, however, be problematic for many radar systems, which are easily disturbed by turbines located in the radar line of sight. Wind turbines situated in the vicinity of Doppler weather radars can lead to erroneous precipitation estimates as well as to inaccurate wind and turbulence measurements. This paper presents a quantitative analysis of the impact of a wind farm, located in southeastern Sweden, on measurements from a nearby Doppler weather radar. The analysis is based on 6 years of operational radar data. In order to evaluate the impact of the wind farm, average values of all three spectral moments (the radar reflectivity factor, absolute radial velocity, and spectrum width) of the nearby Doppler weather radar were calculated, using data before and after the construction of the wind farm. It is shown that all spectral moments, from a large area at and downrange from the wind farm, were impacted by the wind turbines. It was also found that data from radar cells far above the wind farm (near 3 km altitude) were affected by the wind farm. It is shown that this in part can be explained by detection by the radar sidelobes and by scattering off increased levels of dust and turbulence. In a detailed analysis, using data from a single radar cell, frequency distributions of all spectral moments were used to study the competition between the weather signal and wind turbine clutter. It is shown that, when weather echoes give rise to higher reflectivity values than those of the wind farm, the negative impact of the wind turbines is greatly reduced for all spectral moments.

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A quantitative analysis of the impact of wind turbines on operational Doppler weather radar data

Atmospheric Measurement Techniques Discussions ◽

10.5194/amtd-7-8743-2014 ◽

2014 ◽

Vol 7 (8) ◽

pp. 8743-8776

Author(s):

L. Norin

Keyword(s):

Quantitative Analysis ◽

Wind Turbines ◽

Wind Farm ◽

Negative Impact ◽

Weather Radar ◽

Radar Data ◽

Doppler Weather Radar ◽

Spectral Moments ◽

Using Data ◽

The Impact

Abstract. In many countries wind turbines are rapidly growing in numbers as the demand for energy from renewable sources increases. The continued deployment of wind turbines can, however, be problematic for many radar systems, which are easily disturbed by turbines located in radar line-of-sight. Wind turbines situated in the vicinity of Doppler weather radars can lead to erroneous precipitation estimates as well as to inaccurate wind- and turbulence measurements. This paper presents a quantitative analysis of the impact of a wind farm, located in southeastern Sweden, on measurements from a nearby Doppler weather radar. The analysis is based on six years of operational radar data. In order to evaluate the impact of the wind farm, average values of all three spectral moments (the radar reflectivity factor, absolute radial velocity, and spectrum width) of the nearby Doppler weather radar were calculated, using data before and after the construction of the wind farm. It is shown that all spectral moments, from a large area at and downrange from the wind farm, were impacted by the wind turbines. It was also found that data from radar cells far above the wind farm (near 3 km altitude) were affected by the wind farm. We show that this is partly explained by changes in the atmospheric refractive index, bending the radar beams closer to the ground. In a detailed analysis, using data from a single radar cell, frequency distributions of all spectral moments were used to study the competition between the weather signal and wind turbine clutter. We show that when weather echoes give rise to higher reflectivity values than that of the wind farm, the negative impact of the wind turbines disappears for all spectral moments.

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Wind turbine impact on operational weather radar I/Q data: characterisation and filtering

Atmospheric Measurement Techniques ◽

10.5194/amt-10-1739-2017 ◽

2017 ◽

Vol 10 (5) ◽

pp. 1739-1753 ◽

Cited By ~ 3

Author(s):

Lars Norin

Keyword(s):

Wind Turbine ◽

Wind Turbines ◽

Negative Impact ◽

Weather Radar ◽

Rapid Expansion ◽

Weather Radars ◽

Radar Systems ◽

Increasing Demand ◽

Yaw Angle ◽

The Impact

Abstract. For the past 2 decades wind turbines have been growing in number all over the world as a response to the increasing demand for renewable energy. However, the rapid expansion of wind turbines presents a problem for many radar systems, including weather radars. Wind turbines in the line of sight of a weather radar can have a negative impact on the radar's measurements. As weather radars are important instruments for meteorological offices, finding a way for wind turbines and weather radars to co-exist would be of great societal value.Doppler weather radars base their measurements on in-phase and quadrature phase (I/Q) data. In this work a month's worth of recordings of high-resolution I/Q data from an operational Swedish C-band weather radar are presented. The impact of point targets, such as masts and wind turbines, on the I/Q data is analysed and characterised. It is shown that the impact of point targets on single radar pulses, when normalised by amplitude, is manifested as a distinct and highly repeatable signature. The shape of this signature is found to be independent of the size, shape and yaw angle of the wind turbine. It is further demonstrated how the robustness of the point target signature can be used to identify and filter out the impact of wind turbines in the radar's signal processor.

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Wind turbine impact on operational weather radar I/Q data: characterisation and filtering

10.5194/amt-2017-12 ◽

2017 ◽

Author(s):

Lars Norin

Keyword(s):

Wind Turbine ◽

Wind Turbines ◽

Negative Impact ◽

Weather Radar ◽

Rapid Expansion ◽

Weather Radars ◽

Radar Systems ◽

Increasing Demand ◽

Yaw Angle ◽

The Impact

Abstract. For the past two decades wind turbines have been growing in number all over the world as a response to the increasing demand for renewable energy. However, the rapid expansion of wind turbines presents a problem for many radar systems, including weather radars. Wind turbines in line-of-sight of a weather radar can have a negative impact on the radar's measurements. As weather radars are important instruments for meteorological offices, finding a way for wind turbines and weather radars to co-exist would be of great societal value. Doppler weather radars base their measurements on in-phase and quadrature phase (I/Q) data. In this work a month worth of recordings of high resolution I/Q data from an operational Swedish C-band weather radar are presented. The impact of point targets, such as masts and wind turbines, on the I/Q data is analysed and characterised. It is shown that the impact of point targets on single radar pulses is manifested as a distinct and highly repeatable signature. The shape of this signature is found to be independent of the size, shape, and yaw angle of the wind turbine. It is further demonstrated how the robustness of the point target signature can be used to identify and filter out the impact of wind turbines in the radar's signal processor.

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A Study on impact of smartphone addiction on academic performance

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i2.6.10066 ◽

2018 ◽

Vol 7 (2.6) ◽

pp. 50 ◽

Cited By ~ 1

Author(s):

Pamela Chaudhury ◽

Hrudaya Kumar Tripathy

Keyword(s):

Academic Performance ◽

Negative Impact ◽

Pearson Correlation ◽

Machine Learning Techniques ◽

Smartphone Addiction ◽

Active Involvement ◽

Outdoor Sports ◽

Using Data ◽

The Masses ◽

The Impact

Smartphone addiction is increasingly affecting the masses and is negatively impacting the younger generation. Several researches have been done to study the impact of internet and smartphone addiction. However no work has been done to predetermine academic performance from smartphone addiction using data mining techniques. A total of 222 University students participated in the questionnaire. The survey questionnaire consisted of demographic information, internet access pattern and smartphone addiction pattern. Data was analysed using machine learning techniques using classification models. The results further encouraged us to find the correlation between smartphone addiction and academic performance. Pearson’ correlation was used to establish that smartphone usage had a negative impact on academic performance. Additionally other attributes like internet connectivity and active involvement in outdoor sports activities were investigated. Experimental results confirmed a negative correlation of these attributes with academic performance. The findings were of immense use and could be used to reduce the internet addiction amongst the student community and also enhance their academic performance

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The Impact of Public Debt on the Economic Growth of Jordan: An Empirical Study (2000- 2015)

Accounting and Finance Research ◽

10.5430/afr.v6n2p114 ◽

2017 ◽

Vol 6 (2) ◽

pp. 114 ◽

Cited By ~ 1

Author(s):

Tawfiq Ahmad Mousa ◽

Abudallah. M. LShawareh

Keyword(s):

Economic Growth ◽

Empirical Study ◽

Regression Model ◽

Least Squares ◽

Public Debt ◽

Least Squares Method ◽

Negative Impact ◽

External Debt ◽

Using Data ◽

The Impact

In the last two decades, Jordan’s economy has been relied on public debt in order to enhance the economic growth. As such, an understanding of the dynamics between public debt and economic growth is very important in addressing the obstacles to economic growth. The study investigates the impact of public debt on economic growth using data from 2000 to 2015. The study employs least squares method and regression model to capture the impact of public debt on economic growth. The results of the analysis indicate that there is a negative impact of total public debt, especially the external debt on economic growth.

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The Impact of IRCA on the Job Opportunities and Earnings of Mexican-American and Hispanic-American Workers

International Migration Review ◽

10.1177/019791839803200104 ◽

1998 ◽

Vol 32 (1) ◽

pp. 79-95 ◽

Cited By ~ 2

Author(s):

Alberto Dávila ◽

José A. Pagán ◽

Montserrat Viladrich Grau

Keyword(s):

At Risk ◽

Mexican American ◽

Negative Impact ◽

White Male ◽

Wage Structure ◽

Wage Distribution ◽

Hispanic Workers ◽

Using Data ◽

The Impact ◽

Hispanic White

This article studies the earnings gap between Mexican, Hispanic and non-Hispanic white male workers resulting from changes in both the wage structure and immigration laws that occurred during the 1980s. Our results suggest that Mexican and Hispanic workers were adversely affected by these two changes. Using data from the 1980 and 1990 One Percent Public Use Microdata Samples, we show that these “at-risk” workers minimized the negative impact of the increases in the returns to skill by gaining in the non-Hispanic white residual wage distribution. We conclude that at-risk workers increased their work effort to lessen the effects of Act-induced employment losses. Using 1983–1992 data from the National Longitudinal Survey of Youth and EEOC data for this period, we provide support for this contention.

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Impedance Aggregation Method of Multiple Wind Turbines and Accuracy Analysis

Energies ◽

10.3390/en12112035 ◽

2019 ◽

Vol 12 (11) ◽

pp. 2035 ◽

Cited By ~ 2

Author(s):

Liang Chen ◽

Heng Nian ◽

Yunyang Xu

Keyword(s):

Stability Analysis ◽

Reference Frame ◽

Wind Turbines ◽

Power Distribution ◽

Wind Farm ◽

System Level ◽

Small Signal ◽

Impedance Model ◽

The Stability ◽

The Impact

The sequence domain impedance modeling of wind turbines (WTs) has been widely used in the stability analysis between WTs and weak grids with high line impedance. An aggregated impedance model of the wind farm is required in the system-level analysis. However, directly aggregating WT small-signal impedance models will lead to an inaccurate aggregated impedance model due to the mismatch of reference frame definitions among different WT subsystems, which may lead to inaccuracy in the stability analysis. In this paper, we analyze the impacts of the reference frame mismatch between a local small-signal impedance model and a global one on the accuracy of aggregated impedance and the accuracy of impedance-based stability analysis. The results revealed that the impact is related to the power distribution of the studied network. It was found that that the influence of mismatch on stability analysis became subtle when subsystems were balanced loaded. Considering that balanced loading is a common configuration of the practical application, direct impedance aggregation by local small-signal models can be applied due to its acceptable accuracy.

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Alcohol-related harm to others in England: a cross-sectional analysis of national survey data

BMJ Open ◽

10.1136/bmjopen-2017-021046 ◽

2019 ◽

Vol 9 (5) ◽

pp. e021046 ◽

Cited By ~ 2

Author(s):

Caryl Beynon ◽

David Bayliss ◽

Jenny Mason ◽

Kate Sweeney ◽

Clare Perkins ◽

...

Keyword(s):

Negative Impact ◽

Cross Sectional Survey ◽

Cross Sectional ◽

Factors Associated ◽

Harm To Others ◽

Using Data ◽

Socioeconomic And Demographic Factors ◽

The Impact ◽

Alcohol Related Harm ◽

Related Harm

ObjectivesTo estimate the prevalence, the frequency and the perpetrators of alcohol-related harm to others (AHTO) and identify factors associated with experiencing harm and aggressive harm.DesignCross-sectional survey.SettingEngland.ParticipantsAdults (general population) aged 16 and over.Outcome measuresPercentage of respondents who experienced harm. Socioeconomic and demographic factors associated with the outcomes. Outcomes were (1) experienced harm/did not experience harm and (2) experienced aggressive harm (physically threatened, physically hurt and forced/pressured into something sexual)/did not experience an aggressive harm (no aggressive harm plus no harm at all).ResultsData to support a response rate calculation were not collected; 96.3% of people surveyed completed the AHTO questions. The weighted sample was 4874; 20.1% (95% CI 18.9 to 21.4, N=980) reported experiencing harm in the previous 12 months and 4.6% (95% CI 4.0 to 5.4, N=225) reported experiencing an aggressive harm. Friends and strangers were the dominant perpetrators. Most harms (74.8%) occurred less than monthly. Factors associated with experiencing harm were: younger age (p<0.001), drinking harmfully/hazardously (p<0.001), white British (p<0.001 compared to other white groups and Asian groups and p=0.017 compared to black groups), having a disability (p<0.001), being educated (p<0.001 compared to no education) and living in private rented accommodation (p=0.004 compared with owned outright). Being in the family stage of life (defined as having children in the household) had significantly lower odds of harm (p=0.006 compared to being single), as did being retired (p<0.001 compared to being employed). Factors associated with experiencing an aggressive harm were similar.ConclusionsThis exploratory study, using data collected through the Alcohol Toolkit Survey, shows that AHTO affects 20.1% of the population of England. Even apparently minor harms, like being kept awake, can have a negative impact on health, while aggressive harms are clearly of concern. Using a standard methodology to measure harm across studies would be advantageous. Policies that focus on alcohol must take into consideration the impact of drinking on those other than the drinker.

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Improved Control Strategy of MMC–HVDC to Improve Frequency Support of AC System

Applied Sciences ◽

10.3390/app10207282 ◽

2020 ◽

Vol 10 (20) ◽

pp. 7282

Author(s):

Zicong Zhang ◽

Junghun Lee ◽

Gilsoo Jang

Keyword(s):

Wind Turbines ◽

Wind Farm ◽

Control Method ◽

Short Circuit ◽

Synchronous Generator ◽

Frequency Stability ◽

Offshore Wind ◽

Inertial Response ◽

Control Evaluation ◽

The Impact

With the continuous development of power electronics technology, variable-speed offshore wind turbines that penetrated the grid system caused the problem of inertia reduction. This study investigates the frequency stability of synchronous, offshore wind-farm integration through a modular-multilevel-converter high-voltage direct-current (MMC–HVDC) transmission system. When full-scale converter wind turbines (type 4) penetrate the AC grid, the AC system debilitates, and it becomes difficult to maintain the AC system frequency stability. In this paper, we present an improved inertial-response-control method to solve this problem. The mathematical model of the synchronous generator is based on the swing equation and is theoretically derived by establishing a MMC–HVDC. Based on the above model, the inertia constant is analyzed using a model that integrates the MMC–HVDC and offshore synchronous generator. With the new improved control method, a more sensitive and accurate inertia index can be obtained using the formula related to the effective short-circuit ratio of the AC system. Moreover, it is advantageous to provide a more accurate inertial control evaluation for AC systems under various conditions. Furthermore, the impact of the MMC–HVDC on system safety is assessed based on the capacitor time constant. This simulation was implemented using the PSCAD/EMTDC platform.

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