scholarly journals Assessment of wind energy resources in Nigeria – a case study of north-western region of Nigeria

2017 ◽  
Vol 5 (2) ◽  
pp. 83 ◽  
Author(s):  
Boluwaji Olomiyesan ◽  
Onyedi Oyedum ◽  
Paulinus Ugwuoke ◽  
Matthew Abolarin
Keyword(s):  
Power Generation ◽  
Wind Speed ◽  
Wind Energy ◽  
Wind Power ◽  
Large Scale ◽  
Wind Power Generation ◽  
Energy Resources ◽  
Small Scale ◽  
Wind Potential ◽  
Wind Energy Resources

This study assesses the wind-energyresources in Nigeria by reviewing the existing literature on the subject matter, and also evaluates the wind potential in six locations in the northwest region of the country. Twenty-two years’ (1984 – 2005) wind speed data obtained from the Nigerian Meteorological Agencies (NIMET) were used in this study.Weibull two-parameter and other statistical models were employed in this analysis. Wind speed distribution across Nigeria shows that some locations in the northern part of the country are endowed with higher wind potential than others in the southern part of the country. Moreover, assessment of the wind-energy resources in the study locations reveals that wind energy potential in the region is lowest in Yelwa and highest in Kano; WPD varies from 28.30 Wm-2 to 483.72Wm-2 at 10 m AGL, 45.33 Wm-2 to 775.19 Wm-2 at 30 m AGL and 56.43 Wm-2 to 964.77 Wm-2 at 50 m AGL.Thus Kano, Sokoto and Katsina are suitable for large-scale wind power generation, while Gusau is suitable for small-scale wind power generation; whereas Yelwa and Kaduna may not be suitable for wind power production because of their poor wind potential.

scholarly journals Design of Arduino-based small wind power generation system

2018 ◽  
Vol 67 ◽  
pp. 01006 ◽  
Author(s):  
Abdul Goffar Al Mubarok ◽  
Wisnu Djatmiko ◽  
Muhammad Yusro
Keyword(s):  
Power Generation ◽  
Wind Speed ◽  
Wind Energy ◽  
Wind Power ◽  
Wind Direction ◽  
Wind Power Generation ◽  
Generation System ◽  
Remote Location ◽  
Lack Of Information ◽  
Power Generation System

Wind energy is a less-attended renewable energy due to the lack of information about its potential. Some pilot wind turbines were not managed properly and built without considering to the technical feasibility. This study aims to propose a preliminary design of an Arduino-based small wind power generation system. The electricity which is generated by the wind charges the battery. It supplies power of information system which transmits the data of wind speed and wind direction from the remote location to the web server through GPRS network. The remote location which is completed with mobile data coverage is essential for this study. The results of this study are (1) the battery charging stop automatically when the battery is full (2) the data of wind speed and wind direction can be accessed through web browser or Android Smartphone. The data can be used for further analysis to determine the potential of wind energy at the site.

scholarly journals Assessment of Wind Energy Potential as a Power Generation Source: A Case Study of Eight Selected Locations in Northern Cyprus

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2697 ◽  
Author(s):  
Mohamad Alayat ◽  
Youssef Kassem ◽  
Hüseyin Çamur
Keyword(s):  
Power Generation ◽  
Wind Speed ◽  
Wind Energy ◽  
Wind Power ◽  
Actual Data ◽  
Small Scale ◽  
Energy Potential ◽  
Northern Cyprus ◽  
Mean Wind Speed ◽  
Wind Energy Potential

This paper presents a techno-economic assessment of the wind power potential for eight locations distributed over the Northern part of Cyprus. The wind speed data were collected from the meteorological department located in Lefkoşa, Northern Cyprus.Ten distribution models were used to analyze the wind speed characteristics and wind energy potential at the selected locations. The maximum-likelihood method was used for calculating the parameters of the distribution functions.The power law model is utilized to determine the mean wind speed at various heights. In addition, the wind power density for each location was estimated. Furthermore, the performances of different small-scale vertical axis 3–10 kW wind turbines were evaluated to find those that were suitable and efficient for power generation in the studied locations.The results showed that the annual mean wind speed in the regions is greater than 2 m/s at a height of 10 m. Moreover, it is indicated that Generalized Extreme Value distribution provided the best fit to the actual data for the regions of Lefkoşa, Ercan, Girne, Güzelyurt, and Dipkarpaz. However, the Log-Logistic, Weibull, and Gamma distributions gave a better fit to the actual data of Gazimağusa, YeniBoğaziçi, and Salamis, respectively. The Rayleigh distribution does not fit the actual data from all regions. Furthermore, the values of wind power densityat the areas studied ranged from 38.76 W/m2 to 134.29 W/m2 at a height of 50 m, which indicated that wind energy sources in these selected locations are classified as poor. Meanwhile, based on the wind analysis, small-scale wind turbine use can be suitable for generating electricity in the studied locations. Consequently, an Aeolos-V2 with a rating of 5 kW was found to be capable of producing the annual energy needs of an average household in Northern Cyprus.

Modeling Large-Scale Wind Farms for Reliability Analysis Considering Wake Effect

2014 ◽  
Vol 543-547 ◽  
pp. 647-652
Author(s):  
Ye Zhou Hu ◽  
Lin Zhang ◽  
Pai Liu ◽  
Xin Yuan Liu ◽  
Ming Zhou
Keyword(s):  
Power Generation ◽  
Wind Speed ◽  
Wind Power ◽  
Large Scale ◽  
Wind Farm ◽  
Wind Farms ◽  
Wind Power Generation ◽  
Wake Effect ◽  
Effect Model ◽  
The Individual

Large scale wind power penetration has a significant impact on the reliability of the electric generation systems. A wind farm consists of a large number of wind turbine generators (WTGs). A major difficulty in modeling wind farms is that the WTG not have an independent capacity distribution due to the dependence of the individual turbine output on the same energy source, the wind. In this paper, a model of the wind farm output power considering multi-wake effects is established according to the probability distribution of the wind speed and the characteristic of the wind generator output power: based on the simple Jenson wake effect model, the wake effect with wind speed sheer model and the detail wake effect model with the detail shade areas of the upstream wind turbines are discussed respectively. Compared to the individual wake effect model, this model takes the wind farm as a whole and considers the multi-wakes effect on the same unit. As a result the loss of the velocity inside the wind farm is considered more exactly. Furthermore, considering the features of sequentially and self-correlation of wind speed, an auto-regressive and moving average (ARMA) model for wind speed is built up. Also the reliability model of wind farm is built when the output characteristics of wind power generation units, correlation of wind speeds among different wind farms, outage model of wind power generation units, wake effect of wind farm and air temperature are considered. Simulation results validate the effectiveness of the proposed models. These models can be used to research the reliability of power grid containing wind farms, wind farm capacity credit as well as the interconnection among wind farms

An Assessment on the Wind Energy Potential and Possible Solutions for Power Generation in Baltimore County in Maryland, USA

2014 ◽  
Author(s):  
N. Goudarzi ◽  
W. D. Zhu ◽  
R. Delgado ◽  
A. St. Pé
Keyword(s):  
Power Generation ◽  
Wind Speed ◽  
Wind Energy ◽  
Urban Areas ◽  
Large Scale ◽  
Energy Resource ◽  
Mean Value ◽  
Baltimore County ◽  
Wind Speeds ◽  
Wind Potential

The statistical data of five years wind speed measurements at University of Maryland, Baltimore County are used to find out the availability of wind energy resource for power generation. Wind speeds are measured at an approximately 30 meters above the ground; the monthly and yearly mean wind speeds are calculated and evaluated by using the Weibull distribution function. The annual values of k (dimensionless Weibull shape parameter) ranged from 1.78 to 1.99 with a five-year mean value of 1.87. The annual values of c (Weibull scale parameter) ranged from 3.15 to 3.60 with a five-year mean value of 3.28. The results show the highest and lowest wind power potential occurs in February and July, respectively. While this site is not appropriate for large-scale power generation, this study shows the availability of enough wind potential for non-grid connected electrical and mechanical applications. Different residential wind harvesting technologies in urban areas have been studied and more promising ones are introduced as solutions to provide larger-scale power generation at this site with a low annual mean wind speed.

scholarly journals Methodical aspects of the assessment of the wind power potential

2011 ◽  
pp. 313-319
Author(s):  
M. Syrotyuk ◽  
O. Grynda
Keyword(s):  
Wind Energy ◽  
Key Words ◽  
Wind Power ◽  
Local Level ◽  
The State ◽  
Energy Resources ◽  
Wind Potential ◽  
Potential Formation ◽  
Wind Energy Resources

The methodical aspects of the assessment of the wind power potential have been considered. The state of the methodics of the wind power energetic in Lviv region has been characterized. Factors of the wind potential formation for small wind energetic at the local level have been analyzed. Key words: wind energy, wind power potential, assessment of wind energy resources.

scholarly journals Assessment of the Resources of Wind Energy in Various Regions of Algeria

2021 ◽  
Vol 16 (4) ◽  
pp. 641-650
Author(s):  
Derradji Mederreg ◽  
Mohamed Salmi ◽  
Maouedj Rachid ◽  
Hijaz Ahmad ◽  
Giulio Lorenzini ◽  
...  
Keyword(s):  
Wind Energy ◽  
Wind Power ◽  
Energy Resources ◽  
Wind Potential ◽  
Mean Wind Speed ◽  
Seasonal Wind ◽  
The Mean ◽  
Almost All ◽  
Wind Energy Resources ◽  
The Given

Details on the wind potential during a period of about thirteen years in Algeria is given in the present work. The inspection is performed for sixteen regions covering almost all the territory of the country. The density of the mean wind power is determined for the different regions. The maps of annual and seasonal wind energy resources are also established. The characteristics of the wind velocity, as well as the potential of wind power, are determined by the Weibull distribution. From the given results, the highest values of annual mean wind speed and the annual mean wind power density are found in Adrar (P10 = 283.12 W/m2 and P50 = 646.91 W/m2), while the lowest values are observed in Skikda (P10 = 40.61 W/m2 and P50 = 115.51 W/m2, respectively).

Power Electronics for Grid Integration of Wind Power Generation System

2016 ◽  
Vol 9 ◽  
pp. 10 ◽  
Author(s):  
Michael S Okundamiya
Keyword(s):  
Power Generation ◽  
Wind Energy ◽  
Power Electronics ◽  
Wind Power ◽  
Renewable Energy Sources ◽  
Wind Power Generation ◽  
Generation System ◽  
Electricity Grid ◽  
Power Generation System ◽  
Promising Source

The rising demands for a sustainable energy system have stimulated global interests in renewable energy sources. Wind is the fastest growing and promising source of renewable power generation globally. The inclusion of wind power into the electric grid can severely impact the monetary cost, stability and quality of the grid network due to the erratic nature of wind. Power electronics technology can enable optimum performance of the wind power generation system, transferring suitable and applicable energy to the electricity grid. Power electronics can be used for smooth transfer of wind energy to electricity grid but the technology for wind turbines is influenced by the type of generator employed, the energy demand and the grid requirements. This paper investigates the constraints and standards of wind energy conversion technology and the enabling power electronic technology for integration to electricity grid.

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