Study of Combined Forecast Model of Wind Power Output Based on GM-Weibull Wind Speed Distribution

2014 ◽  
Vol 670-671 ◽  
pp. 1566-1569
Author(s):  
Yun Teng ◽  
Qian Hui ◽  
Xin Yu ◽  
Zheng Liu ◽  
Yong Gang Zhang

The grey theory is employed to establish the grey prediction-wind speed Weibull distribution model and calculate the Weibull distribution parameters according to the randomness and intermittence of the wind power output. The wind speed distribution of the wind farm and the effective wind power density are predicted accurately, the wind power and the electric fan efforts in generating capacity and other important data can be obtained according to the actual terrain wind farm wind speed data.

2018 ◽  
Vol 43 (2) ◽  
pp. 190-200 ◽  
Author(s):  
Ijjou Tizgui ◽  
Fatima El Guezar ◽  
Hassane Bouzahir ◽  
Brahim Benaid

To estimate a wind turbine output, optimize its dimensioning, and predict the economic profitability and risks of a wind energy project, wind speed distribution modeling is crucial. Many researchers use directly Weibull distribution basing on a priori acceptance. However, Weibull does not fit some wind speed regimes. The goal of this work is to model the wind speed distribution at Agadir. For that, we compare the accuracy of four distributions (Weibull, Rayleigh, Gamma, and lognormal) which have given good results in this yield. The goodness-of-fit tests are applied to select the effective distribution. The obtained results explain that Weibull distribution is fitting the histogram of observations better than the other distributions. The analysis deals with comparing the error in estimating the annual wind power density using the examined distributions. It was found that Weibull distribution presents minimum error. Thus, wind energy assessors in Agadir can use directly Weibull distribution basing on a scientific decision made via statistical tests. Moreover, assessors worldwide can use the followed methodology to model their wind speed measurements.


Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4291
Author(s):  
Paxis Marques João Roque ◽  
Shyama Pada Chowdhury ◽  
Zhongjie Huan

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.


2013 ◽  
Vol 336-338 ◽  
pp. 1114-1117 ◽  
Author(s):  
Ying Zhi Liu ◽  
Wen Xia Liu

This paper elaborates the effect of wind speed on the output power of the wind farms at different locations. It also describes the correction of the power curve and shows the comparison chart of the standard power curve and the power curve after correction. In China's inland areas, wind farms altitude are generally higher, the air density is much different from the standard air density. The effect of air density on wind power output must be considered during the wind farm design.


2013 ◽  
Vol 448-453 ◽  
pp. 1835-1839
Author(s):  
Zhong Hua Cai ◽  
Ting Ting An ◽  
Hong Tu Zhang

Due to the significant instability, anti-peak-regulation and intermittency of wind power, wind power integration needs an accurate prediction technique to be a basis. At present, the difficulty of wind power integration has resulted in a large number of wind curtailment phenomena and wasted a lot of renewable energy. Grey prediction model has many advantages such as requiring little historical data and the simple model, with high prediction accuracy and convenient calculation, and without regard to regularities of distribution, etc. This paper puts forward the method for short-term wind power prediction using gray model GM (1, 1) and carries out simulation study and empirical analysis using the data from a wind farm of Jilin province, which shows the science and operability of the proposed model. It provides a new research method for the wind power prediction.


2020 ◽  
Vol 16 (2) ◽  
pp. 65-71
Author(s):  
Vadim Romanuke

Abstract In order to accurately estimate wind farm output and subsequently optimise it, a method of wind speed distribution approximation is suggested. The method is based on period-by-period accumulation of wind speed measurements, transforming them into empirical probabilities, and observing the moving approximation to the expected power produced by the wind turbine or entire wind farm. A year is a minimal term during which wind statistics are to be accumulated. The sufficient validity and reliability of the wind speed distribution approximation is supported by controlling root -mean-square deviations and maximal absolute deviations with respect to the moving average of the expected power. The approximation quality can be regulated by adjusting constants defining the requirements to the moving deviations.


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