Stereo Monitoring and Analysis on Wind Energy Source in Chongqing

2011 ◽  
Vol 347-353 ◽  
pp. 742-749 ◽  
Author(s):  
Yan Ying Chen ◽  
Yang Sheng You ◽  
Yang Hua Gao ◽  
Qin Du ◽  
Yun Hui Tang
Keyword(s):  
Energy Source ◽  
Wind Speed ◽  
Wind Energy ◽  
Vertical Profile ◽  
Monitoring Data ◽  
Wind Data ◽  
Power Exponent ◽  
Technology Level ◽  
Wind Resource

In this paper, sequential 12 months’ wind data was used which is obtained from professional observing towers and meteorological stations in Chongqing. Wind energy source was calculated and analyzed. The results of calculation and analysis based on stereo monitoring data to wind resource in Chongqing showed as following: (1) Data of meteorological stations can be used to accurately evaluate wind energy source in Chongqing; (2) There are developable wind energy source at present technology level in Chongqing; (3) Vertical profile of wind speed fitted power exponent relationship.

scholarly journals Assessment of Wind Energy Potential In Zwara, Libya

2021 ◽  
Vol 8 (2) ◽  
Author(s):  
Alhassan A. Teyabeen ◽  
Fathi R. Akkari ◽  
Ali E. Jwaid ◽  
Ashraf Zaghwan ◽  
Rehab Abodelah
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Power ◽  
Power Density ◽  
Ground Level ◽  
Energy Potential ◽  
Average Wind Speed ◽  
Wind Power Density ◽  
Wind Energy Potential ◽  
Wind Resource

To assess the wind energy potential at any site, the wind power density should be estimated; it evaluates the wind resource and indicates the amount of available wind energy. The purpose of this study is to estimate the monthly and annual wind power density based on the Weibull distribution using wind speed data collected in Zwara, Libya during 2007. The wind date are measured at the three hub heights of 10m, 30m, and 50m above ground level, and recorded every 10 minutes. The analysis showed that the annual average wind speed are 4.51, 5.86, 6.26 m/s for the respective mentioned heights. The average annual wind power densities at the mentioned heights were 113.71, 204.19, 243.48 , respectively.

scholarly journals Comparison of three probability distributions and techno-economic analysis of wind energy production along the coastal belt of Pakistan

2020 ◽  
pp. 014459872093158 ◽  
Author(s):  
Muhammad Sumair ◽  
Tauseef Aized ◽  
Syed Asad Raza Gardezi ◽  
Muhammad Mahmood Aslam Bhutta ◽  
Syed Muhammad Sohail Rehman ◽  
...  
Keyword(s):  
Wind Speed ◽  
Energy Production ◽  
Probability Distributions ◽  
Resource Assessment ◽  
Wind Data ◽  
Coefficient Of Determination ◽  
Resource Estimation ◽  
Wind Resource Assessment ◽  
Coastal Belt ◽  
Wind Resource

Continuous probability distributions have long been used to model the wind data. No single distribution can be declared accurate for all locations. Therefore, a comparison of different distributions before actual wind resource assessment should be carried out. Current work focuses on the application of three probability distributions, i.e. Weibull, Rayleigh, and lognormal for wind resource estimation at six sites along the coastal belt of Pakistan. Four years’ (2015–2018) wind data measured each 60-minutes at 50 m height for six locations were collected from Pakistan Meteorological Department. Comparison of these distributions was done based on coefficient of determination ( R2), root mean square error, and mean absolute percentage deviation. Comparison showed that Weibull distribution is the most accurate followed by lognormal and Rayleigh, respectively. Wind power density ( PD) was evaluated and it was found that Karachi has the highest wind speed and PD as 5.82 m/s and 162.69 W/m2, respectively, while Jiwani has the lowest wind speed and PD as 4.62 m/s and 76.76 W/m2, respectively. Furthermore, feasibility of annual energy production (AEP) was determined using six turbines. It was found that Vestas V42 shows the worst performance while Bonus 1300/62 is the best with respect to annual energy production and Bonus 600/44 is the most economical. Finally, sensitivity analysis was carried out.

An integrated GIS-based method for wind-power estimation: application to western Cyprus

2014 ◽  
Vol 6 (1) ◽  
Author(s):  
Ioannis Kastanas ◽  
Andreas Georgiou ◽  
Panagiotis Zavros ◽  
Evangelos Akylas
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Sea Breeze ◽  
Topographic Effects ◽  
Resource Exploitation ◽  
Energy Potential ◽  
Annual Variations ◽  
Integrated Method ◽  
Wind Potential ◽  
Wind Resource

AbstractThis study presents an integrated method for the estimation and analysis of potential wind-energy resources in Cyprus, which is applied at selected sites on the western side of the island. Firstly, a statistical analysis of wind speed and direction data was conducted at six meteorological stations in western Cyprus, establishing daily, monthly and annual variations of wind speed. Also examined were the Weibull distributions of the wind at each site. These wind statistics serve as the basis for estimating corrected statistical distributions over the extended study areas, which were calculated using the Wind Atlas Analysis and Application Program (WAsP) that modifies wind flow estimates based on local topographic effects. As a result, a geographic and wind-resource database was formulated around each station. Aggregation of this data using statistical weighting methods allows the extrapolation of observed results and the visualization for selected hours of the day over the western part of Cyprus. The results indicate the strong influence of the sea-breeze on the island’s wind potential, and identify a number of areas of higher wind-energy potential suitable for wind-resource exploitation. It is hoped that both the methodology applied and results obtained can be further used by potential investors and wind-energy developers.

scholarly journals Can Reanalysis Products Outperform Mesoscale Numerical Weather Prediction Models in Modeling the Wind Resource in Simple Terrain?

2021 ◽  
Author(s):  
Vincent Pronk ◽  
Nicola Bodini ◽  
Mike Optis ◽  
Julie K. Lundquist ◽  
Patrick Moriarty ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Numerical Weather Prediction ◽  
Prediction Models ◽  
Weather Prediction ◽  
Atmospheric Stability ◽  
Negative Bias ◽  
Numerical Weather ◽  
Wind Resource ◽  
Mesoscale Numerical Weather Prediction

Abstract. Mesoscale numerical weather prediction (NWP) models are generally considered more accurate than reanalysis products in characterizing the wind resource at heights of interest for wind energy, given their finer spatial resolution and more comprehensive physics. However, advancements in the latest ERA-5 reanalysis product motivate an assessment on whether ERA-5 can model wind speeds as well as a state-of-the-art NWP model – the Weather Research and Forecasting (WRF) model. We consider this research question for both simple terrain and offshore applications. Specifically, we compare wind profiles from ERA-5 and the preliminary WRF runs of the Wind Integration National Dataset (WIND) Toolkit Long-term Ensemble Dataset (WTK-LED) to those observed by lidars at site in Oklahoma, United States, and in a U.S. Atlantic offshore wind energy area. We find that ERA-5 shows a significant negative bias (~ −1 m s−1 ) at both locations, with a larger bias at the land-based site. WTK-LED-predicted wind speed profiles show a slight negative bias (~ −0.5 m s−1 ) offshore and a slight positive bias (~ +0.5 m s−1) at the land-based site. Surprisingly, we find that ERA-5 outperforms WTK-LED in terms of the centered root-mean-square error (cRMSE) and correlation coefficient, for both the land-based and offshore cases, in all atmospheric stability conditions. We find that WTK-LED’s higher cRMSE is caused by its tendency to overpredict the amplitude of the wind speed diurnal cycle both onshore and offshore.

scholarly journals An Overview of Wind Resource Assessments With Special Reference to The Emirate of Ajman, UAE

2021 ◽  
Vol 6 ◽  
pp. 32
Author(s):  
Kais Muhammed Fasel ◽  
Abdul Salam K. Darwish ◽  
Peter Farrell ◽  
Hussein Kazem
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Clean Energy ◽  
Resource Assessment ◽  
Site Specific ◽  
Onshore Wind ◽  
Wind Resource Assessment ◽  
Wind Potential ◽  
The Government ◽  
Wind Resource

The continuous increase in clean energy demand and reduced CO2 emissions in the UAE and specifically the Emirate of Ajman has put an extreme challenge to the Government. Ajman is one of the seven emirates constituting the United Arab Emirates (UAE). Ajman is located along the Arabian Gulf on its West and bordered by the Emirate of Sharjah on its North, South, and East. The government is taking huge steps in including sustainability principles and clean energy in all of its developments. Successful implementation of green architecture law decree No 10 of 2018 effectively is a sign of such an initiative. Renewable energy sources in this country have had two folds of interest in solar and wind. Recent research works supported the feasibility of using wind energy as an alternative clean source of energy. Site-specific and accurate wind speed information is the first step in the process of bankable wind potential and wind Atlas. This study has compared how wind speed and its distribution varies for similar offshore and onshore locations between two different mesoscale data sources. Also, discussed the main environmental characteristics of Ajman that would influence the implementation of a major wind energy project. In addition, the study made a brief critical overview of the major studies undertaken in the Middle East and North Africa (MENA) region on wind resource assessment. Finally, based on the results, the study makes conclusions, recommendations and a way forward for a bankable wind resources assessment in the Emirate of Ajman. This paper would alert the wind energy industry about the consequence of not considering the best error corrected site specific suitable wind resource data along with other environmental characteristics. The study results show that for offshore, there is 2.9 m/s and for Onshore 4.9 m/s variations in wind speed at the same location between ECMWF Reanalysis (ERA-5) and NASA Satellite data. Hence It is concluded that error corrected site-specific wind resource assessment is mandatory for assessing the available bankable wind potential since there are considerable variations in wind speed distributions between mesoscale data sets for similar locations. The study also identifies that the Emirate of Ajman has limited space for onshore wind farms; hence the offshore site seems to have good potential that can be utilised for energy generation. However, individual wind turbines can be installed for exploiting the available site-specific onshore wind energy. Finally, the study recommends a way forward for a comprehensive wind resource assessment to help the Emirate of Ajman form a sustainable wind power generation policy.

scholarly journals Wind Resource Assessment for southern part of Libya: Case Study of Hun

2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Hiba Shreif ◽  
W El-Osta ◽  
A Yagub
Keyword(s):  
Wind Energy ◽  
Power Density ◽  
Wind Turbines ◽  
Scale Parameter ◽  
Energy Resource ◽  
Capacity Factor ◽  
Wind Data ◽  
Maximum Speed ◽  
Average Wind Speed ◽  
Wind Resource

The purpose of this study is to analyze the wind energy resource potential at Hun. Wind data was analyzed using different statistical models and calculations were performed to forecast wind energy & power density at the site. Energy production was estimated using different wind turbines which were selected according IEC standards criteria and performance of these wind turbines. Detailed wind resource data analysis was performed for the proposed site using Excel spreadsheet for one-year period from (April 2011 to March 2012). The wind data are measured at four heights of (20 m, 40m, 60m and 61m) above ground level (a.g.l). The analysis showed that the annual average wind speed is 5.69 m/s and the power density is about 190 W/m2 at 61m height. It could be noticed that at 61m height, the highest scale parameter is 7.25 m/s in April while the lowest scale parameter is 5.71 m/s in October. The annual shape and scale parameters range from 2.27 at 61m to 2 at 20m, and from 6.42 m /s at 61m to 5 m /s at 20m, respectively. 90% of the speeds are below 11m/s, 84% are below 10m/s and 50% are above 6 m/s. The maximum speed is 21 m/s with 0.14% occurrence. The wind shear exponent was evaluated as 0.18 and the roughness length for the site as 0.17 m, which indicates that the roughness class for the location is 2.5. According to the performed analysis, the wind turbines suitable for this site should be of class III/B. Comparison of three wind turbines indicated that Vestas V112-3000 gave the highest capacity factor of 42% in April and an availability of 83% while Nordex N100-2500 gave capacity factor of 41% for the same month and availability of 83.7%.

Wind Energy Potential Assessment for Nosrat Abad Station

2012 ◽  
Vol 622-623 ◽  
pp. 1113-1118
Author(s):  
P. Alamdari ◽  
O. Nematollahi ◽  
A.A. Alemrajabi
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Power Density ◽  
Wind Data ◽  
Energy Potential ◽  
Water Pumping ◽  
Mean Wind Speed ◽  
Wind Characteristic ◽  
Wind Energy Development ◽  
A Site

Wind characteristic at a site is one of the most important parameters for wind energy development projects. Statistical analysis on wind data will reveal the quantity and quality of wind energy at a site. In the present study, wind data for Nosrat Abad at Sistan and Baluchistan Province of Iran, has been statistically analyzed to determine the potential of wind for power generation. The wind speed data for 2007 has been gathered at three heights, i.e. 10 m, 30 m and 40 m. Mean wind speed, wind speed distribution function, and mean wind power density have been evaluated for the site. The magnitude of Power density at 40 m height is estimated at 170 W/m¬¬¬2 which is suitable for water pumping and battery charging.

scholarly journals An intercomparison of mesoscale models at simple sites for wind energy applications

2017 ◽  
Vol 2 (1) ◽  
pp. 211-228 ◽  
Author(s):  
Bjarke T. Olsen ◽  
Andrea N. Hahmann ◽  
Anna Maria Sempreviva ◽  
Jake Badger ◽  
Hans E. Jørgensen
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Farm ◽  
Weather Prediction ◽  
Atmospheric Stability ◽  
Resource Assessment ◽  
Offshore Wind ◽  
Grid Spacing ◽  
Energy Applications ◽  
Wind Resource

Abstract. Understanding uncertainties in wind resource assessment associated with the use of the output from numerical weather prediction (NWP) models is important for wind energy applications. A better understanding of the sources of error reduces risk and lowers costs. Here, an intercomparison of the output from 25 NWP models is presented for three sites in northern Europe characterized by simple terrain. The models are evaluated using a number of statistical properties relevant to wind energy and verified with observations. On average the models have small wind speed biases offshore and aloft (< 4 %) and larger biases closer to the surface over land (> 7 %). A similar pattern is detected for the inter-model spread. Strongly stable and strongly unstable atmospheric stability conditions are associated with larger wind speed errors. Strong indications are found that using a grid spacing larger than 3 km decreases the accuracy of the models, but we found no evidence that using a grid spacing smaller than 3 km is necessary for these simple sites. Applying the models to a simple wind energy offshore wind farm highlights the importance of capturing the correct distributions of wind speed and direction.

scholarly journals An Assessment of Onshore and Offshore Wind Energy Potential in India Using Moth Flame Optimization

Energies ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 3063 ◽  
Author(s):  
Krishnamoorthy R ◽  
Udhayakumar K ◽  
Kannadasan Raju ◽  
Rajvikram Madurai Elavarasan ◽  
Lucian Mihet-Popa
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Power ◽  
Likelihood Method ◽  
Wind Speeds ◽  
Speed Distribution ◽  
Wind Speed Distribution ◽  
South West Monsoon ◽  
Wind Distribution ◽  
Wind Resource

Wind energy is one of the supremely renewable energy sources and has been widely established worldwide. Due to strong seasonal variations in the wind resource, accurate predictions of wind resource assessment and appropriate wind speed distribution models (for any location) are the significant facets for planning and commissioning wind farms. In this work, the wind characteristics and wind potential assessment of onshore, offshore, and nearshore locations of India—particularly Kayathar in Tamilnadu, the Gulf of Khambhat, and Jafrabad in Gujarat—are statistically analyzed with wind distribution methods. Further, the resource assessments are carried out using Weibull, Rayleigh, gamma, Nakagami, generalized extreme value (GEV), lognormal, inverse Gaussian, Rician, Birnbaum–Sandras, and Bimodal–Weibull distribution methods. Additionally, the advent of artificial intelligence and soft computing techniques with the moth flame optimization (MFO) method leads to superior results in solving complex problems and parameter estimations. The data analytics are carried out in the MATLAB platform, with in-house coding developed for MFO parameters estimated through optimization and other wind distribution parameters using the maximum likelihood method. The observed outcomes show that the MFO method performed well on parameter estimation. Correspondingly, wind power generation was shown to peak at the South West Monsoon periods from June to September, with mean wind speeds ranging from 9 to 12 m/s. Furthermore, the wind speed distribution method of mixed Weibull, Nakagami, and Rician methods performed well in calculating potential assessments for the targeted locations. Likewise, the Gulf of Khambhat (offshore) area has steady wind speeds ranging from 7 to 10 m/s with less turbulence intensity and the highest wind power density of 431 watts/m2. The proposed optimization method proves its potential for accurate assessment of Indian wind conditions in selected locations.

scholarly journals Assessing Wind Data from Reanalyses for the Upper Midwest

2019 ◽  
Vol 58 (3) ◽  
pp. 429-446 ◽  
Author(s):  
Jacob J. Coburn
Keyword(s):  
Wind Speed ◽  
Resource Assessment ◽  
Reanalysis Data ◽  
Wind Data ◽  
Upper Midwest ◽  
Wind Speeds ◽  
Potential Applications ◽  
Mitigate Climate Change ◽  
Wind Resource

AbstractWind is an important atmospheric variable that is receiving increased attention as the world seeks to shift from carbon-based fuels in order to mitigate climate change. This has resulted in increased need for more temporally and spatially continuous wind information, which is often met through the use of reanalysis data. However, limited work has been done to assess the long-term accuracy of the wind data against observations in the context of specific applications. This study focuses on the representation of daily and monthly average 10-m wind speed data in the upper Midwest by six global reanalysis datasets. The accuracy of the datasets was assessed using several measures of skill, as well as the associated wind speed distributions and long-term trends. While it was found that higher resolution and complexity in more recent generations of reanalyses produced more accurate simulations of wind in the region, important biases remained. High variability in the observed data resulted in lower correlations at the monthly time scale. As with previous research, linear trends calculated from the reanalyzed wind speeds were significantly underestimated compared to observed trends. While it is expected that future improvements in model resolution, physics, and data assimilation will further improve wind representation in reanalyses, accounting for the differences between the available datasets and their associated biases will be important for potential applications of the output, particularly wind resource assessment.

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