Short-Term Forecast of Wind Speed through Mathematical Models

The predictability of wind information in a given location is essential for the evaluation of a wind power project. Predicting wind speed accurately improves the planning of wind power generation, reducing costs and improving the use of resources. This paper seeks to predict the mean hourly wind speed in anemometric towers (at a height of 50 meters) at two locations: a coastal region and one with complex terrain characteristics. To this end, the Holt-Winters (HW), Artificial Neural Networks (ANN) and Hybrid time-series models were used. Observational data evaluated by the Modern-Era Retrospective analysis for Research and Applications-Version 2 (MERRA-2) reanalysis at the same height of the towers. The results show that the hybrid model had a better performance in relation to the others, including when compared to the evaluation with MERRA-2. For example, in terms of statistical residuals, RMSE and MAE were 0.91 and 0.62 m/s, respectively. As such, the hybrid models are a good method to forecast wind speed data for wind generation.

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Beneficial role of diurnal smoothing for grid integration of wind power

10.5194/egusphere-egu21-9226 ◽

2021 ◽

Author(s):

Anasuya Gangopadhyay ◽

Ashwin K Seshadri ◽

Ralf Toumi

Keyword(s):

Wind Speed ◽

Wind Power ◽

Diurnal Cycle ◽

Power Plants ◽

Large Scale ◽

Positive Impact ◽

Forecast Error ◽

Wind Generation ◽

Grid Integration ◽

Wind Maximum

Smoothing of wind generation variability is important for grid integration of large-scale wind power plants. One approach to achieving smoothing is aggregating wind generation from plants that have uncorrelated or negatively correlated wind speed. It is well known that the wind speed correlation on average decays with increasing distance between plants, but the correlations may not be explained by distance alone. In India, the wind speed diurnal cycle plays a significant role in explaining the hourly correlation of wind speed between location pairs. This creates an opportunity of &#8220;diurnal smoothing&#8221;. At a given separation distance the hourly wind speeds correlation is reduced for those pairs that have a difference of +/- 12 hours in local time of wind maximum. This effect is more prominent for location pairs separated by 200 km or more and where the amplitude of the diurnal cycle is more than about&#160; 0.5 m/s. &#8220;Diurnal smoothing&#8221; also has a positive impact on the aggregate wind predictability and forecast error. &#8220;Diurnal smoothing&#8221; could also be important for other regions with diurnal wind speed cycles.

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An Assessment of Wind Energy Potential for the Three Topographic Regions of Eritrea

Energies ◽

10.3390/en13071846 ◽

2020 ◽

Vol 13 (7) ◽

pp. 1846 ◽

Cited By ~ 2

Author(s):

Teklebrhan Negash ◽

Erik Möllerström ◽

Fredric Ottermo

Keyword(s):

Wind Speed ◽

Wind Energy ◽

Wind Power ◽

Power Density ◽

Coastal Region ◽

Energy Potential ◽

Wind Power Density ◽

Prevailing Wind Direction ◽

Central Highland ◽

Wind Energy Potential

This paper presents the wind energy potential and wind characteristics for 25 wind sites in Eritrea, based on wind data from the years 2000–2005. The studied sites are distributed all over Eritrea, but can roughly be divided into three regions: coastal region, western lowlands, and central highlands. The coastal region sites have the highest potential for wind power. An uncertainty, due to extrapolating the wind speed from the 10-m measurements, should be noted. The year to year variations are typically small and, for the sites deemed as suitable for wind power, the seasonal variations are most prominent in the coastal region with a peak during the period November–March. Moreover, Weibull parameters, prevailing wind direction, and wind power density recalculated for 100 m above ground are presented for all 25 sites. Comparing the results to values from the web-based, large-scale dataset, the Global Wind Atlas (GWA), both mean wind speed and wind power density are typically higher for the measurements. The difference is especially large for the more complex-terrain central highland sites where GWA results are also likely to be more uncertain. The result of this study can be used to make preliminary assessments on possible power production potential at the given sites.

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Statistical analysis of wind speed and wind power potential of Port Elizabeth using Weibull parameters

Journal of Energy in Southern Africa ◽

10.17159/2413-3051/2012/v23i2a3160 ◽

2012 ◽

Vol 23 (2) ◽

pp. 30-38 ◽

Cited By ~ 21

Author(s):

Temitope R Ayodele ◽

Adisa A. Jimoh ◽

Josiah L. Munda ◽

John T. Agee

Keyword(s):

Wind Speed ◽

Wind Power ◽

South African ◽

Shape Parameter ◽

Scale Parameter ◽

Average Wind Speed ◽

Weibull Parameters ◽

Average Wind ◽

Port Elizabeth ◽

Power Project

This paper analyses wind speed characteristics and wind power potential of Port Elizabeth using statistical Weibull parameters. A measured 5–minute time series average wind speed over a period of 5 years (2005 - 2009) was obtained from the South African Weather Service (SAWS). The results show that the shape parameter (k) ranges from 1.319 in April 2006 to 2.107 in November 2009, while the scale parameter (c) varies from 3.983m/s in May 2008 to 7.390 in November 2009.The average wind power density is highest during Spring (September–October), 256.505W/m2 and lowest during Autumn (April-May), 152.381W/m2. This paper is relevant to a decision-making process on significant investment in a wind power project.

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Impacts of Integration of Wind Farms on Power System Transient Stability

Applied Sciences ◽

10.3390/app8081289 ◽

2018 ◽

Vol 8 (8) ◽

pp. 1289 ◽

Cited By ~ 11

Author(s):

Shiwei Xia ◽

Qian Zhang ◽

S.T. Hussain ◽

Baodi Hong ◽

Weiwei Zou

Keyword(s):

Power Generation ◽

Wind Speed ◽

Power System ◽

Wind Power ◽

Transient Stability ◽

Wind Farms ◽

Wind Power Generation ◽

Wind Generation ◽

System Operation ◽

Power System Operation

To compensate for the ever-growing energy gap, renewable resources have undergone fast expansions worldwide in recent years, but they also result in some challenges for power system operation such as the static security and transient stability issues. In particular, as wind power generation accounts for a large share of these renewable energy and reduces the inertia of a power network, the transient stability of power systems with high-level wind generation is decreased and has attracted wide attention recently. Effectively analyzing and evaluating the impact of wind generation on power transient stability is indispensable to improve power system operation security level. In this paper, a Doubly Fed Induction Generator with a two-lumped mass wind turbine model is presented firstly to analyze impacts of wind power generation on power system transient stability. Although the influence of wind power generation on transient stability has been comprehensively studied, many other key factors such as the locations of wind farms and the wind speed driving the wind turbine are also investigated in detail. Furthermore, how to improve the transient stability by installing capacitors is also demonstrated in the paper. The IEEE 14-bus system is used to conduct these investigations by using the Power System Analysis Tool, and the time domain simulation results show that: (1) By increasing the capacity of wind farms, the system instability increases; (2) The wind farm location and wind speed can affect power system transient stability; (3) Installing capacitors will effectively improve system transient stability.

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A Nonlinear Dynamics Approach for Incorporating Wind-Speed Patterns into Wind-Power Project Evaluation

PLoS ONE ◽

10.1371/journal.pone.0115123 ◽

2015 ◽

Vol 10 (1) ◽

pp. e0115123 ◽

Cited By ~ 6

Author(s):

Ray Huffaker ◽

Marco Bittelli

Keyword(s):

Nonlinear Dynamics ◽

Wind Speed ◽

Wind Power ◽

Project Evaluation ◽

Power Project

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Power system reliability impacts of wind generation and operational reserve requirements

Ingeniería e Investigación ◽

10.15446/ing.investig.v35n1sup.53698 ◽

2015 ◽

Vol 35 (1Sup) ◽

pp. 82-88 ◽

Cited By ~ 4

Author(s):

Esteban Gil

Keyword(s):

Wind Speed ◽

Power System ◽

Wind Power ◽

System Reliability ◽

Energy Resource ◽

Wind Generation ◽

Power System Reliability ◽

Font Size ◽

Interconnected System ◽

Reserve Requirements

Due to its variability, wind generation integration presents a significant challenge to power system operators in order to maintain adequate reliability levels while ensuring least cost operation. This paper explores the trade-off between the benefits associated to a higher wind penetration and the additional operational reserve requirements that they impose. Such exploration is valued in terms of its effect on power system reliability, measured as an amount of unserved energy. The paper also focuses on how changing the Value of Lost Load (VoLL) can be used to attain different reliability targets, and how wind power penetration and the diversity of the wind energy resource will impact quality of supply (in terms of instances of unserved energy). The evaluation of different penetrations of wind power generation, different wind speed profiles, wind resource diversity, and different operational reserve requirements, is conducted on the Chilean Northern Interconnected System (SING) using statistical modeling of wind speed time series and computer simulation through a 24-hour ahead unit commitment algorithm and a Monte Carlo simulation scheme. Results for the SING suggest that while wind generation can significantly reduce generation costs, it can also imply higher security costs to reach acceptable reliability levels.<br style="font-style: normal; font-variant: normal; font-weight: normal; letter-spacing: normal; line-height: normal; orphans: 2; text-align: -webkit-auto; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px;" />

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Impact of the accuracy of NWP wind speed forecasts on wind power forecasting

8th Renewable Power Generation Conference (RPG 2019) ◽

10.1049/cp.2019.0312 ◽

2019 ◽

Author(s):

Yimei Wang ◽

Yongqian Liu ◽

Peng Song ◽

Hui Liu ◽

Zechun Hu

Keyword(s):

Wind Speed ◽

Wind Power ◽

Wind Power Forecasting ◽

Power Forecasting

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Perancangan Pembangkit Listrik Tenaga Angin Dengan Turbin Ventilator Sebagai Penggerak Generator

BULETIN FISIKA ◽

10.24843/bf.2017.v18.i02.p05 ◽

2017 ◽

Vol 18 (2) ◽

pp. 68

Author(s):

Made Padmika ◽

I Made Satriya Wibawa ◽

Ni Luh Putu Trisnawati

Keyword(s):

Wind Speed ◽

Power Plant ◽

Wind Power ◽

Wind Power Plant ◽

Maximum Output ◽

Dc Voltage ◽

Input And Output ◽

Instrument Testing

A prototype of a wind power plant had been created using a ventilator as a generator spiner. This power plant utilizes wind speed as its propulsion. Electricity generated in the DC voltage form between 0 volts up to 7.46 volts. The MT3608 module is used to stabilize and raise the voltage installed in the input and output of the charging circuit. For instrument testing, the wind speed on 0 m/s up to 6 m/s interval used. Maximum output of this tool with a wind speed of 6 m/s is 7.46 volts.

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The Research of Wind Power Project Company’s Engineering Management System

Journal of Physics Conference Series ◽

10.1088/1742-6596/1634/1/012106 ◽

2020 ◽

Vol 1634 ◽

pp. 012106

Author(s):

Hualong Cai ◽

Wanchao Xie ◽

Dongliang Lin

Keyword(s):

Wind Power ◽

Management System ◽

Engineering Management ◽

Power Project

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Multi-step real-time wind speed prediction based on convolution memory network

Wind Engineering ◽

10.1177/0309524x21998266 ◽

2021 ◽

pp. 0309524X2199826

Author(s):

Guowei Cai ◽

Yuqing Yang ◽

Chao Pan ◽

Dian Wang ◽

Fengjiao Yu ◽

...

Keyword(s):

Feature Extraction ◽

Wind Speed ◽

Real Time ◽

Wind Power ◽

Spatial Correlation ◽

Prediction Accuracy ◽

Spatial Information ◽

Spatial Association ◽

Spatial Feature ◽

Time Prediction

Multi-step real-time prediction based on the spatial correlation of wind speed is a research hotspot for large-scale wind power grid integration, and this paper proposes a multi-location multi-step wind speed combination prediction method based on the spatial correlation of wind speed. The correlation coefficients were determined by gray relational analysis for each turbine in the wind farm. Based on this, timing-control spatial association optimization is used for optimization and scheduling, obtaining spatial information on the typical turbine and its neighborhood information. This spatial information is reconstructed to improve the efficiency of spatial feature extraction. The reconstructed spatio-temporal information is input into a convolutional neural network with memory cells. Spatial feature extraction and multi-step real-time prediction are carried out, avoiding the problem of missing information affecting prediction accuracy. The method is innovative in terms of both efficiency and accuracy, and the prediction accuracy and generalization ability of the proposed method is verified by predicting wind speed and wind power for different wind farms.

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