Neuron Network Prediction Feed-Forwad Wind Speed Network on Mauritania's North Coast: Ballawack Case

The assessment of the suitability of a wind system depends largely on the prediction of the wind potential. Indeed, the variability and uncertainty inherent in renewable energy sources can have a significant impact on accurate and reliable prediction of the power produced. Wind sources are needed at different time stages and at different altitudes. Thus, putting in place tools for predicting these wind resources is essential for their effective integration in the frame of electricity generation. In this context, the paper of this study is to propose a short-term wind energy prediction method through the formation of historical wind velocity data based on neural networks. This assessment involves modelling wind speed using ANN through the feed-forwad network. So, ANN are at the basis of adaptive identification methods and intelligent command laws. In this sense, first, the process of forecasting wind energy involves the creation of a raw data base, which is then filtered by probabilistic neural network. More concretely, the contribution of the work can be given in the form of technical results. These results start with a proposal of the theoretical models, then it is given the approach method that is used, then it is proposed the design of the system and the whole is closed by a performance evaluation. As far as performance evaluation is concerned, it is presented in the form of the results of analysed simulations of the forecast model. In practical terms, it should be noted that the proposed model also provides a high degree of accuracy for the measured data. In the end, normalized average absolute errors were recorded between 4.7% and 4.9%. As, it was found a regression factor R (measures the correlation between output-Target) between 91% and 96% for the site of the northern Mauritanian coast. This is largely acceptable for similar calculations.

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Wind Data Analysis and Wind Flow Simulation Over Large Areas

Mathematical Modelling in Civil Engineering ◽

10.2478/mmce-2014-0005 ◽

2014 ◽

Vol 10 (1) ◽

pp. 38-45

Author(s):

Angel Terziev ◽

Ivan Antonov ◽

Rositsa Velichkova

Keyword(s):

Renewable Energy ◽

Wind Energy ◽

Renewable Energy Sources ◽

Energy Sources ◽

Wind Flow ◽

Energy Potential ◽

Wind Potential ◽

Wind Energy Potential ◽

The Impact

Abstract Increasing the share of renewable energy sources is one of the core policies of the European Union. This is because of the fact that this energy is essential in reducing the greenhouse gas emissions and securing energy supplies. Currently, the share of wind energy from all renewable energy sources is relatively low. The choice of location for a certain wind farm installation strongly depends on the wind potential. Therefore the accurate assessment of wind potential is extremely important. In the present paper an analysis is made on the impact of significant possible parameters on the determination of wind energy potential for relatively large areas. In the analysis the type of measurements (short- and long-term on-site measurements), the type of instrumentation and the terrain roughness factor are considered. The study on the impact of turbulence on the wind flow distribution over complex terrain is presented, and it is based on the real on-site data collected by the meteorological tall towers installed in the northern part of Bulgaria. By means of CFD based software a wind map is developed for relatively large areas. Different turbulent models in numerical calculations were tested and recommendations for the usage of the specific models in flows modeling over complex terrains are presented. The role of each parameter in wind map development is made. Different approaches for determination of wind energy potential based on the preliminary developed wind map are presented.

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A Method for Rockburst Prediction in the Deep Tunnels of Hydropower Stations Based on the Monitored Microseismicity and an Optimized Probabilistic Neural Network Model

Sustainability ◽

10.3390/su11113212 ◽

2019 ◽

Vol 11 (11) ◽

pp. 3212 ◽

Cited By ~ 6

Author(s):

Guangliang Feng ◽

Guoqing Xia ◽

Bingrui Chen ◽

Yaxun Xiao ◽

Ruichen Zhou

Keyword(s):

Neural Network ◽

Firefly Algorithm ◽

Probabilistic Neural Network ◽

Renewable Energy Sources ◽

Prediction Method ◽

The Sustainable Development ◽

Smoothing Factor ◽

Jinping Ii Hydropower Station ◽

Hydropower Stations ◽

Made In

Hydropower is one of the most important renewable energy sources. However, the safe construction of hydropower stations is seriously affected by disasters like rockburst, which, in turn, restricts the sustainable development of hydropower energy. In this paper, a method for rockburst prediction in the deep tunnels of hydropower stations based on the use of real-time microseismic (MS) monitoring information and an optimized probabilistic neural network (PNN) model is proposed. The model consists of the mean impact value algorithm (MIVA), the modified firefly algorithm (MFA), and PNN (MIVA-MFA-PNN model). The MIVA is used to reduce the interference from redundant information in the multiple MS parameters in the input layer of the PNN. The MFA is used to optimize the parameter smoothing factor in the PNN and reduce the error caused by artificial determination. Three improvements are made in the MFA compared to the standard firefly algorithm. The proposed rockburst prediction method is tested by 93 rockburst cases with different intensities that occurred in parts of the deep diversion and drainage tunnels of the Jinping II hydropower station, China (with a maximum depth of 2525 m). The results show that the rates of correct rockburst prediction of the test samples and learning samples are 100% and 86.75%, respectively. However, when a common PNN model combined with monitored microseismicity is used, the related rates are only 80.0% and 61.45%, respectively. The proposed method can provide a reference for rockburst prediction in MS monitored deep tunnels of hydropower projects.

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Wind Potential Assessment for the Utilization from Wind Energy in the Household Level: A Case Study of Nakhonratchasima Thailand

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.835.749 ◽

2016 ◽

Vol 835 ◽

pp. 749-752

Author(s):

Yuttachai Keawsuntia

Keyword(s):

Wind Speed ◽

Wind Energy ◽

Alternative Energy ◽

Energy Resource ◽

Energy Utilization ◽

Distribution Method ◽

Household Level ◽

Wind Speed Data ◽

Wind Potential

Wind energy is an important alternative energy resource because of it clean, does not cause pollution and it can be used as replacement of a fossil fuel energy. Utilization of the wind energy, the wind speed data has to be analyzed to make sure before use it. In this article is to present the wind speed data analysis by using Weibull distribution method. Wind speed data from the meteorological station at Pakchong district, Nakhonratchasima province, Thailand was used as the case study. The results show that this area has wind speed about 2.5 to 3.5 m/s. The average wind power density was 17.513 W/m2 and the total wind energy was 153.9819 kW·hr/m2 per year. This wind potential of this area can be used for water pumping and electricity generating for use in a household.

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Wind potential estimation and proposed energy production in Southern Punjab using Weibull probability density function and surface measured data

Energy Exploration & Exploitation ◽

10.1177/0144598720920748 ◽

2020 ◽

pp. 014459872092074 ◽

Cited By ~ 2

Author(s):

Muhammad Sumair ◽

Tauseef Aized ◽

Syed Asad Raza Gardezi ◽

Syed Ubaid Ur Rehman ◽

Syed Muhammad Sohail Rehman

Keyword(s):

Wind Speed ◽

Energy Density ◽

Wind Energy ◽

Wind Power ◽

Power Density ◽

Energy Production ◽

Economic Assessment ◽

Weibull Model ◽

Wind Power Density ◽

Wind Potential

Current work focusses on the wind potential assessment in South Punjab. Eleven locations from South Punjab have been analyzed using two-parameter Weibull model (with Energy Pattern Factor Method to estimate Weibull parameters) and five years (2014–2018) hourly wind data measured at 50 m height and collected from Pakistan Meteorological Department. Techno-economic analysis of energy production using six different turbine models was carried out with the purpose of presenting a clear picture about the importance of turbine selection at particular location. The analysis showed that Rahim Yar Khan carries the highest wind speed, highest wind power density, and wind energy density with values 4.40 ms−1, 77.2 W/m2 and 677.76 kWh/m2/year, respectively. On the other extreme, Bahawalnagar observes the least wind speed i.e. 3.60 ms−1 while Layyah observes the minimum wind power density and wind energy density as 38.96 W/m2 and 352.24 kWh/m2/year, respectively. According to National Renewable Energy Laboratory standards, wind potential ranging from 0 to 200 W/m2 is considered poor. Economic assessment was carried out to find feasibility of the location for energy harvesting. Finally, Polar diagrams drawn to show the optimum wind blowing directions shows that optimum wind direction in the region is southwest.

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The Investigation of Wind Energy Potential in Order to Estimate Power Plants in Baladeh Mazandaran, Iran

Jurnal Teknologi ◽

10.11113/jt.v59.1264 ◽

2012 ◽

pp. 29-33

Author(s):

S. Asghar Gholamian ◽

S. Bagher Soltani ◽

R. Ilka

Keyword(s):

Wind Speed ◽

Wind Energy ◽

Wind Power ◽

Power Density ◽

Power Plants ◽

Weather Station ◽

Energy Potential ◽

Wind Power Density ◽

Synoptic Weather ◽

Wind Potential

First step for achieving wind energy is to locate points with appropriate wind power density in a country. Wind data which are recorded in a synoptic weather station, are the best way to study the wind potential of an area. In this paper wind speed period of Baladeh synoptic weather station is studied, since it has the maximum average of wind speed among 15 stations of the MAZANDARAN Province. Weibull factors k and c are calculated for 40 months from September 2006 to December 2009 and wind power density is determined based on these data. The total average of factors k and c for a height for 50 m are 1.442 m/s and 5.1256 respectively. By using the average of factors, wind power density in 50 m height will be 147.40 watt/m2 which is categorized as weak potential in wind class. However by monthly investigation it is shown that with a 50 m wind, this station can be put in medium class in hot months of the year.

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STUDI EKSPERIMENTAL PERFORMANSI TURBIN SAVONIUS DI PESISIR PANTAI KABUPATEN DEMAK TERHADAP DAYA LISTRIK YANG DIHASILKAN

Jurnal Ilmiah Pendidikan Teknik dan Kejuruan ◽

10.20961/jiptek.v14i1.45215 ◽

2021 ◽

Vol 14 (1) ◽

pp. 16

Author(s):

Wahyu Santoso ◽

Herman Saputro ◽

Husin Bugis

Keyword(s):

Renewable Energy ◽

Wind Speed ◽

Wind Energy ◽

Wind Turbine ◽

Raw Material ◽

Power Coefficient ◽

Speed Ratio ◽

Generator Type ◽

Wind Potential ◽

Savonius Wind Turbine

Energy from fossil fuels consisting of petroleum, coal, natural gas containing raw material for energy fulfillment in Indonesia is still very central through the use of raw materials from renewable energy is still very low. In Indonesia the potential for renewable energy such as wind energy needs to be optimized. One of the uses of wind energy is through savonius wind turbine as electricity generators. Characteristics of savonius wind turbine with vertical axis rotors which gave a simple shape, and that able to control low speeds. This is in accordance with regions in Indonesi which have low average speeds. This experimental study, aims to determine the description of wind potential and determine the performance of savonius wind turbines on the coast of Demak regency on the electrical energy produced. Savonius wind turbine used is made of galvalum material in the form of an S type rotor with diameter 1.1 m and height 1.4 m, using pulley transmission system with multiplication ratio 1:6 dan using generator type PMG 200 W. This research uses the method experiment. Data collection in the form of wind speed, humidity, temperature, rotor rotation speed, voltage and electric curret is carried out at 14.30 to 17.30 Western Indonesian Time. Data Analysis in this study uses quantitative descriptive analysis. The result showed the potential of wind on the coast of Demak regency have an average wind speed of 2,02 m/s with a temperature of 31,34 0C and humidity of 76,96. And the performance of the installed wind turbine produces the highest power 3.5 watt with an electric power coefficient of 0,181 and tip speed ratio around 1,75. From these result, the potensial of wind with performance savonius turbine can generate electricity used for pond lighting in the village Berahan Kulon Kecamatan Wedung.

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Hybrid Forecasting Model Based Data Mining and Cuckoo Search: A Case Study of Wind Speed Time Series

The Open Fuels & Energy Science Journal ◽

10.2174/1876973x01609010065 ◽

2016 ◽

Vol 9 (1) ◽

pp. 65-76 ◽

Cited By ~ 1

Author(s):

Xiangdong Xu ◽

Xi Song ◽

Qian Wang ◽

Zhiyuan Liu ◽

Jing Wang ◽

...

Keyword(s):

Wind Speed ◽

Wind Energy ◽

Renewable Energy Sources ◽

Eastern China ◽

Wind Farms ◽

Cuckoo Search ◽

Original Data ◽

Vital Role ◽

Forecasting Model ◽

Hybrid Forecasting

Wind energy has been part of the fastest growing renewable energy sources that is clean and pollution-free, which has been increasingly gaining global attention, and wind speed forecasting plays a vital role in the wind energy field, however, it has been proven to be a challenging task owing to the effect of various meteorological factors. This paper proposes a hybrid forecasting model, which can effectively make a preprocess for the original data and improve forecasting accuracy, the developed model applies cuckoo search(CS) algorithm to optimize the parameters of the wavelet neural network (WNN) model. The proposed hybrid method is subsequently examined on the wind farms of eastern China and the forecasting performance shows that the developed model is better than some traditional models.

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A Probabilistic Model of Extrapolated Wind Speed Data for Wind Energy Prediction at Alangarapeta, Anantapur District, Andhra Pradesh, India

Journal of Earth Science Research ◽

10.18005/jesr0203005 ◽

2014 ◽

pp. 113-117

Author(s):

Sandeep Chinta

Keyword(s):

Wind Speed ◽

Wind Energy ◽

Probabilistic Model ◽

Andhra Pradesh ◽

Energy Prediction ◽

Wind Speed Data

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Assessment of Wind Energy Potential in Three Different Locations of Malaysia

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.785.621 ◽

2015 ◽

Vol 785 ◽

pp. 621-626

Author(s):

R. Shamsipour ◽

M. Fadaeenejad ◽

M.A.M. Radzi

Keyword(s):

Wind Speed ◽

Energy Density ◽

Wind Energy ◽

Wind Power ◽

Weibull Model ◽

Energy Potential ◽

Wind Speeds ◽

Wind Potential ◽

Mean Wind Speed ◽

Wind Energy Potential

In this study, wind energy potential in three different stations in Malaysia in period of 5 years is analyzed. Base on Weibull distribution parameters, the mean wind speed, wind power density and wind energy density is estimated for each defined location. Although there are many works about wind potential in Malaysia, however a few of them have been provided a comprehensive study about wind power in different places in Malaysia. According to the findings, the annual mean wind speeds indicates that the highest wind speed variation is about 2 m/s and is belonged to the Subang station and the highest wind speed is 3.5 m/s in in Kudat. It is also found that the maximum wind power densities among these three sites are 22 W/m2, 24 W/m2 and 22 W/m2 in Kudat station in January, February and September respectively. The results of the study show that as the second parameter for Weibull model, the highest wind energy density has been 190 kWh/m2 per year in Kudat and the lowest one has been about 60 kWh/m2 in Kuching.

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

Open Geosciences ◽

10.2478/s13533-012-0162-3 ◽

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.

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