scholarly journals Evaluation of the Wind Potential and Optimal Design of a Wind Farm in The Arzew Industrial Zone in Western Algeria

2020 ◽  
Vol 9 (2) ◽  
pp. 177-187
Author(s):  
Salah Marih ◽  
Leila Ghomri ◽  
Benaissa Bekkouche
Keyword(s):  
Wind Speed ◽  
Wind Turbines ◽  
Wind Farm ◽  
Clean Energy ◽  
Appropriate Technology ◽  
Environmental Study ◽  
Net Energy ◽  
Electricity Grid ◽  
Wind Potential ◽  
Mean Wind Speed

This work presents an assessment of the wind potential and a design methodology for a 10 MW wind farm in the Arzew industrial region, located in northwest Algeria, to improve the quality of service of the electricity grid and increase Algeria's participation in the use of renewable energy. The hourly wind data of 10 years (2005-2015) that correspond to the wind potential of the site were analyzed, such as: dominant wind directions, probability distribution, Weibull parameters, mean wind speed and power potential. The site has a mean annual wind speed of 4.46 m/s at 10m height, and enough space to locate the wind turbines. A comparative study was carried out between four wind turbine technologies to improve the site's efficiency and select the appropriate technology: PowerWind 56/ 900 kW, Nordex N50/800 kW, Vestas V50/850 kW, NEG-Micon 44/750 kW. The estimate of the energy produced using WAsP software and the choice of the optimal architectural configuration for wind turbines installation was confirmed. A techno-economic and environmental study was carried out by HOMER software, to choose the model that produces the maximum annual net energy with a competitive cost in the global wind energy market, $ 0.068/kWh, and that provides clean energy with a reduced emission of polluting gases. Finally, this work provides a good indicator for the construction of a wind farm in Arzew. ©2020. CBIORE-IJRED. All rights reserved

scholarly journals Performance Enhancement of Proposed Namaacha Wind Farm by Minimising Losses Due to the Wake Effect: A Mozambican Case Study

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4291
Author(s):  
Paxis Marques João Roque ◽  
Shyama Pada Chowdhury ◽  
Zhongjie Huan
Keyword(s):  
Wind Speed ◽  
Wind Power ◽  
Wind Turbines ◽  
Power Output ◽  
Wind Farm ◽  
Wind Farms ◽  
Operating Conditions ◽  
Wake Effect ◽  
Wind Generators ◽  
Wind Potential

District of Namaacha in Maputo Province of Mozambique presents a high wind potential, with an average wind speed of around 7.5 m/s and huge open fields that are favourable to the installation of wind farms. However, in order to make better use of the wind potential, it is necessary to evaluate the operating conditions of the turbines and guide the independent power producers (IPPs) on how to efficiently use wind power. The investigation of the wind farm operating conditions is justified by the fact that the implementation of wind power systems is quite expensive, and therefore, it is imperative to find alternatives to reduce power losses and improve energy production. Taking into account the power needs in Mozambique, this project applied hybrid optimisation of multiple energy resources (HOMER) to size the capacity of the wind farm and the number of turbines that guarantee an adequate supply of power. Moreover, considering the topographic conditions of the site and the operational parameters of the turbines, the system advisor model (SAM) was applied to evaluate the performance of the Vestas V82-1.65 horizontal axis turbines and the system’s power output as a result of the wake effect. For any wind farm, it is evident that wind turbines’ wake effects significantly reduce the performance of wind farms. The paper seeks to design and examine the proper layout for practical placements of wind generators. Firstly, a survey on the Namaacha’s electricity demand was carried out in order to obtain the district’s daily load profile required to size the wind farm’s capacity. Secondly, with the previous knowledge that the operation of wind farms is affected by wake losses, different wake effect models applied by SAM were examined and the Eddy–Viscosity model was selected to perform the analysis. Three distinct layouts result from SAM optimisation, and the best one is recommended for wind turbines installation for maximising wind to energy generation. Although it is understood that the wake effect occurs on any wind farm, it is observed that wake losses can be minimised through the proper design of the wind generators’ placement layout. Therefore, any wind farm project should, from its layout, examine the optimal wind farm arrangement, which will depend on the wind speed, wind direction, turbine hub height, and other topographical characteristics of the area. In that context, considering the topographic and climate features of Mozambique, the study brings novelty in the way wind farms should be placed in the district and wake losses minimised. The study is based on a real assumption that the project can be implemented in the district, and thus, considering the wind farm’s capacity, the district’s energy needs could be met. The optimal transversal and longitudinal distances between turbines recommended are 8Do and 10Do, respectively, arranged according to layout 1, with wake losses of about 1.7%, land utilisation of about 6.46 Km2, and power output estimated at 71.844 GWh per year.

Wind energy resource assessment of Kütahya, Turkey using WAsP and layout optimization

2020 ◽  
pp. 095765092093603
Author(s):  
Onur Koşar ◽  
Mustafa Arif Özgür
Keyword(s):  
Wind Speed ◽  
Wind Turbines ◽  
Wind Farm ◽  
Real Life ◽  
Energy Resource ◽  
Resource Assessment ◽  
Capacity Factor ◽  
Strong Wind ◽  
Wind Potential ◽  
Shear Turbulence

Kütahya is considered as a candidate region for a wind farm investment due to Turkey's 2023 energy targets and its proximity to other wind farm investments. In this study, two years of wind data collected from a hill near the Evliya Çelebi Campus of Kütahya Dumlupınar University was used to evaluate the wind farm potential of Kütahya. First, the wind speed, wind direction, wind shear, turbulence intensity and wind speed ramp characteristics were determined. Second, the WAsP software was used to create a wind atlas for the region. Three sites with strong wind potential were evaluated. A techno-economic analysis was conducted using five types of wind turbines selected from the WAsP database. Third, optimization of a wind farm layout was conducted by considering different hub height options for 14 commercial wind turbines using MATLAB software. It was shown theoretically that a wind farm with a power capacity of 25 MW can operate with a capacity factor of 35%. However, due to the relatively high topographical ruggedness index on the wind farm site, the calculated value for the capacity factor could not be reached in a real-life application.

Monte Carlo methods to include the effect of asymmetrical uncertainty sources in wind farm yield assessment

2018 ◽  
Vol 42 (6) ◽  
pp. 624-632 ◽  
Author(s):  
Alexander Gleim ◽  
Rolf-Erik Keck ◽  
John Amund Lund
Keyword(s):  
Monte Carlo ◽  
Wind Speed ◽  
Energy Production ◽  
Wind Farm ◽  
Sensitivity Study ◽  
Uncertainty Sources ◽  
Industry Standard ◽  
Wind Speed Distribution ◽  
Mean Wind Speed ◽  
A Site

This article presents a method for incorporating the effect on expected annual energy production of a wind farm caused by asymmetric uncertainty distributions of the applied losses and the nonlinear response in turbine production. The necessity for such a correction is best illustrated by considering the effect of uncertainty in the oncoming wind speed distribution on the production of a wind turbine. Due to the shape of the power curve, variations in wind speed will result in a skewed response in annual energy production. For a site where the mean wind speed is higher than 50% of the rated wind speed of the turbine (in practice all sites with sufficiently high wind speed to motivate the establishment of a wind farm), a reduction in mean wind will cause a larger reduction in annual energy production than a corresponding increase in mean wind would increase the annual energy production. Consequently, the expected annual energy production response when considering the uncertainty of the wind will be lower than the expected annual energy production based on the most probable incoming wind. This difference is due to a statistical bias in the industry standard methods to calculate expected annual energy production of a wind farm, as implemented in tools in common use in the industry. A method based on a general Monte Carlo approach is proposed to calculate and correct for this bias. A sensitivity study shows that the bias due to wind speed uncertainty and nonlinear turbine response will be on the order of 0.5% – 1.5% of expected annual energy production. Furthermore, the effect on expected annual energy production due to asymmetrical distributions of site specific losses, for example, loss of production due to ice, can constitute additional losses of several percent.

scholarly journals Wake and Turbulence Analysis for Wind Turbine Layouts in an Island

2018 ◽  
Vol 64 ◽  
pp. 06010
Author(s):  
Bachhal Amrender Singh ◽  
Vogstad Klaus ◽  
Lal Kolhe Mohan ◽  
Chougule Abhijit ◽  
Beyer Hans George
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Energy Production ◽  
Wind Farm ◽  
Full Length Paper ◽  
Turbulence Analysis ◽  
Wake Model ◽  
Wind Resources

There is a big wind energy potential in supplying the power in an island and most of the islands are off-grid. Due to the limited area in island(s), there is need to find appropriate layout / location for wind turbines suited to the local wind conditions. In this paper, we have considered the wind resources data of an island in Trøndelag region of the Northern Norway, situated on the coastal line. The wind resources data of this island have been analysed for wake losses and turbulence on wind turbines for determining appropriate locations of wind turbines in this island. These analyses are very important for understanding the fatigue and mechanical stress on the wind turbines. In this work, semi empirical wake model has been used for wake losses analysis with wind speed and turbine spacings. The Jensen wake model used for the wake loss analysis due to its high degree of accuracy and the Frandsen model for characterizing the turbulent loading. The variations of the losses in the wind energy production of the down-wind turbine relative to the up-wind turbine and, the down-stream turbulence have been analysed for various turbine distances. The special emphasis has been taken for the case of wind turbine spacing, leading to the turbulence conditions for satisfying the IEC 61400-1 conditions to find the wind turbine layout in this island. The energy production of down-wind turbines has been decreased from 2 to 20% due to the lower wind speeds as they are located behind up-wind turbine, resulting in decreasing the overall energy production of the wind farm. Also, the higher wake losses have contributed to the effective turbulence, which has reduced the overall energy production from the wind farm. In this case study, the required distance for wind turbines have been changed to 6 rotor diameters for increasing the energy gain. From the results, it has been estimated that the marginal change in wake losses by moving the down-stream wind turbine by one rotor diameter distance has been in the range of 0.5 to 1% only and it is insignificant. In the full-length paper, the wake effects with wind speed variations and the wind turbine locations will be reported for reducing the wake losses on the down-stream wind turbine. The Frandsen model has been used for analysing turbulence loading on the down-stream wind turbine as per IEC 61400-1 criteria. In larger wind farms, the high turbulence from the up-stream wind turbines increases the fatigues on the turbines of the wind farm. In this work, we have used the effective turbulence criteria at a certain distance between up-stream and down-stream turbines for minimizing the fatigue load level. The sensitivity analysis on wake and turbulence analysis will be reported in the full-length paper. Results from this work will be useful for finding wind farm layouts in an island for utilizing effectively the wind energy resources and electrification using wind power plants.

scholarly journals An Evaluation of the Wind Energy Resources along the Spanish Continental Nearshore

Energies ◽  
2020 ◽  
Vol 13 (15) ◽  
pp. 3986 ◽  
Author(s):  
Florin Onea ◽  
Andrés Ruiz ◽  
Eugen Rusu
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Turbines ◽  
Offshore Wind ◽  
Time Interval ◽  
Average Wind Speed ◽  
Important Conclusion ◽  
Comprehensive Picture ◽  
Mean Wind Speed ◽  
Wind Resources

The main objective of the present work is to provide a comprehensive picture of the wind conditions in the Spanish continental nearshore considering a state-of-the-art wind dataset. In order to do this, the ERA5 wind data, covering the 20-year time interval from 1999 to 2018, was processed and evaluated. ERA stands for ’ECMWF Re-Analysis’ and refers to a series of research projects at ECMWF (European Centre for Medium-Range Weather Forecasts) which produced various datasets. In addition to the analysis of the wind resources (reported for a 100 m height), the performances of several wind turbines, ranging from 3 to 9.5 MW, were evaluated. From the analysis of the spatial maps it was observed that the Northern part of this region presents significant wind resources, the mean wind speed values exceeding 9 m/s in some locations. On the other hand, in regard to the Southern sector, more energetic conditions are visible close to the Strait of Gibraltar and to the Gulf of Lion. Nevertheless, from the analysis of the data corresponding to these two Southern nearshore points it was observed that the average wind speed was lower than 8 m/s in both summer and winter months. Regarding the considered wind turbines, the capacity factor did in general not exceed 20%—however, we did observe some peaks that could reach to 30%. Finally, it can be highlighted that the Northern part of the Spanish continental nearshore is significant from the perspective of extracting offshore wind energy, especially considering the technologies based on floating platforms. Furthermore, because of the clear synergy between wind and wave energy, which are characteristic to this coastal environment, an important conclusion of the present work is that the implementation of joint wind–wave projects might be effective in the Northwestern side of the Iberian nearshore.

scholarly journals Potential of Electricity Generation on the Western Coast of Mediterranean Sea in Egypt

2008 ◽  
Vol 45 (5) ◽  
pp. 26-38
Author(s):  
A. Ahmed Shata ◽  
S. Abdelaty ◽  
R. Hanitsch
Keyword(s):  
Wind Turbine ◽  
Mediterranean Sea ◽  
Power Law ◽  
Wind Turbines ◽  
Electricity Generation ◽  
Wind Farm ◽  
Electricity Production ◽  
Energy Output ◽  
Western Coast ◽  
Wind Potential

Potential of Electricity Generation on the Western Coast of Mediterranean Sea in EgyptA technical and economic assessment has been made of the electricity generation by wind turbines located at three promising potential wind sites: Sidi Barrani, Mersa Matruh and El Dabaa in the extreme northwest of Egypt along the Mediterranean Sea. These contiguous stations along the coast have an annual mean wind speed greater than 5.0 m/s at a height of 10 m. Weibull's parameters and the power law coefficient for all seasons have been estimated and used to describe the distribution and behavior of seasonal winds at these stations. The annual values of wind potential at the heights of 70-100 m above the ground level were obtained by extrapolation of the 10 m data from the results of our previous work using the power law. The three stations have a high wind power density, ranging from 340-425 to 450-555 W/m2at the heights of 70-100 m, respectively. In this paper, an analysis of the cost per kWh of electricity generated by two different systems has been made: one using a relatively large single 2 MW wind turbine and the other - 25 small wind turbines (80 kW, total 2 MW) arranged in a wind farm. The yearly energy output of each system at each site was determined, and the electricity generation costs in each case were also calculated and compared with those at using diesel oil, natural gas and photovoltaic systems furnished by the Egyptian Electricity Authority. The single 2 MW wind turbine was found to be more efficient than the wind farm. For all the three considered stations the electricity production cost was found to be less than 2 ϵ cent/kWh, which is about half the specific cost of the wind farm.

scholarly journals Results from a wake-steering experiment at a commercial wind plant: investigating the wind speed dependence of wake-steering performance

2021 ◽  
Vol 6 (6) ◽  
pp. 1427-1453
Author(s):  
Eric Simley ◽  
Paul Fleming ◽  
Nicolas Girard ◽  
Lucas Alloin ◽  
Emma Godefroy ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Wind Direction ◽  
Wind Farm ◽  
Poor Performance ◽  
Power Production ◽  
Wind Rose ◽  
Wind Speeds ◽  
Variability Model

Abstract. Wake steering is a wind farm control strategy in which upstream wind turbines are misaligned with the wind to redirect their wakes away from downstream turbines, thereby increasing the net wind plant power production and reducing fatigue loads generated by wake turbulence. In this paper, we present results from a wake-steering experiment at a commercial wind plant involving two wind turbines spaced 3.7 rotor diameters apart. During the 3-month experiment period, we estimate that wake steering reduced wake losses by 5.6 % for the wind direction sector investigated. After applying a long-term correction based on the site wind rose, the reduction in wake losses increases to 9.3 %. As a function of wind speed, we find large energy improvements near cut-in wind speed, where wake steering can prevent the downstream wind turbine from shutting down. Yet for wind speeds between 6–8 m/s, we observe little change in performance with wake steering. However, wake steering was found to improve energy production significantly for below-rated wind speeds from 8–12 m/s. By measuring the relationship between yaw misalignment and power production using a nacelle lidar, we attribute much of the improvement in wake-steering performance at higher wind speeds to a significant reduction in the power loss of the upstream turbine as wind speed increases. Additionally, we find higher wind direction variability at lower wind speeds, which contributes to poor performance in the 6–8 m/s wind speed bin because of slow yaw controller dynamics. Further, we compare the measured performance of wake steering to predictions using the FLORIS (FLOw Redirection and Induction in Steady State) wind farm control tool coupled with a wind direction variability model. Although the achieved yaw offsets at the upstream wind turbine fall short of the intended yaw offsets, we find that they are predicted well by the wind direction variability model. When incorporating the expected yaw offsets, estimates of the energy improvement from wake steering using FLORIS closely match the experimental results.

scholarly journals Integrated wind farm layout and control optimization

2020 ◽  
Author(s):  
Mads M. Pedersen ◽  
Gunner C. Larsen
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Wind Farm ◽  
Design Space ◽  
Wind Farm Layout ◽  
Control Optimization ◽  
Mean Wind Speed ◽  
The Individual ◽  
And Control ◽  
Selection Of

Abstract. Design of an optimal wind farm topology and wind farm control scheduling depends on the chosen metric. The objective of this paper is to investigate the influence of optimal wind farm control on the optimal wind farm layout in terms of power production. A successful fulfilment of this goal requires: 1) an accurate and fast flow model; 2) selection of the minimum set of design parameters that rules the problem; and 3) selection of an optimization algorithm with good scaling properties. For control of the individual wind farm turbines, the two most obvious strategies are wake steering based on active wind turbine yaw control and wind turbine derating. The present investigation is a priori limited to wind turbine derating. A high-speed linearized CFD RANS solver models the flow field and the crucial wind turbine wake interactions inside the wind farm. The actuator disk method is used to model the wind turbines, and utilizing an aerodynamic model, the design space of the optimization problem is reduced to only three variables per turbine – two geometric and one carefully selected variable specifying the individual wind turbine derating setting for each mean wind speed and direction. The full design space spanned by these (2N + Nd Ns N) parameters, where N is the number of wind farm turbines, Nd is the number of direction bins, and Ns is the number of mean wind speed bins. This design space is decomposed in two subsets, which in turn define a nested set of optimization problems to achieve the fastest possible optimization procedure. Following a simplistic sanity check of the platform functionality regarding wind farm layout and control optimization, the capabilities of the developed optimization platform is demonstrated on the Swedish offshore wind farm. For this particular wind farm, the analysis demonstrates that the expected annual energy production can be increased by 4 % by integrating the wind farm control in the design of the wind farm layout, which is 1.2 % higher than what is achieved by optimizing the layout only.

scholarly journals An Innovative Correction Method of Wind Speed for Efficiency Evaluation of Wind Turbines

ACTA IMEKO ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 46
Author(s):  
Alessio Carullo ◽  
Alessandro Ciocia ◽  
Gabriele Malgaroli ◽  
Filippo Spertino
Keyword(s):  
Wind Speed ◽  
Wind Turbines ◽  
Wind Farm ◽  
Southern Italy ◽  
Wind Farms ◽  
Correction Method ◽  
Turbine Rotor ◽  
Meteorological Station ◽  
Efficiency Evaluation ◽  
Horizontal Axis Wind Turbines

The performance of horizontal axis Wind Turbines (WTs) is strongly affected by the wind speed entering in their rotor. Generally, this quantity is not available, because the wind speed is measured on the nacelle behind the turbine rotor, providing a lower value. Therefore, two correction methods are usually employed, requiring two input quantities: the wind speed on the back of the turbine nacelle and the wind speed measured by a meteorological mast close to the turbines under analysis. However, the presence of this station in wind farms is rare and the number of WTs in the wind farm is high. This paper proposes an innovative correction, named “Statistical Method” (SM), that evaluates the efficiency of WTs by estimating the wind speed entering in the WTs rotor. This method relies on the manufacturer power curve and the data measured by the WT anemometer only, thus having the possibility to be also applied in wind farms without a meteorological station. The effectiveness of such a method is discussed by comparing the results obtained by the standard methods implemented on two turbines (rated power = 1.5 MW and 2.5 MW) of a wind power plant (nominal power = 80 MW) in Southern Italy.

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