scholarly journals Comparison of three probability distributions and techno-economic analysis of wind energy production along the coastal belt of Pakistan

2020 ◽  
pp. 014459872093158 ◽  
Author(s):  
Muhammad Sumair ◽  
Tauseef Aized ◽  
Syed Asad Raza Gardezi ◽  
Muhammad Mahmood Aslam Bhutta ◽  
Syed Muhammad Sohail Rehman ◽  
...  
Keyword(s):  
Wind Speed ◽  
Energy Production ◽  
Probability Distributions ◽  
Resource Assessment ◽  
Wind Data ◽  
Coefficient Of Determination ◽  
Resource Estimation ◽  
Wind Resource Assessment ◽  
Coastal Belt ◽  
Wind Resource

Continuous probability distributions have long been used to model the wind data. No single distribution can be declared accurate for all locations. Therefore, a comparison of different distributions before actual wind resource assessment should be carried out. Current work focuses on the application of three probability distributions, i.e. Weibull, Rayleigh, and lognormal for wind resource estimation at six sites along the coastal belt of Pakistan. Four years’ (2015–2018) wind data measured each 60-minutes at 50 m height for six locations were collected from Pakistan Meteorological Department. Comparison of these distributions was done based on coefficient of determination ( R2), root mean square error, and mean absolute percentage deviation. Comparison showed that Weibull distribution is the most accurate followed by lognormal and Rayleigh, respectively. Wind power density ( PD) was evaluated and it was found that Karachi has the highest wind speed and PD as 5.82 m/s and 162.69 W/m2, respectively, while Jiwani has the lowest wind speed and PD as 4.62 m/s and 76.76 W/m2, respectively. Furthermore, feasibility of annual energy production (AEP) was determined using six turbines. It was found that Vestas V42 shows the worst performance while Bonus 1300/62 is the best with respect to annual energy production and Bonus 600/44 is the most economical. Finally, sensitivity analysis was carried out.

On the wind resource in Algeria: Probability distributions evaluation

2020 ◽  
pp. 095765092097588
Author(s):  
Houdayfa Ounis ◽  
Nawel Aries
Keyword(s):  
Wind Speed ◽  
Probability Distribution ◽  
Probability Distributions ◽  
Resource Assessment ◽  
Descriptive Statistics ◽  
The Other ◽  
Wind Speeds ◽  
Wind Resource Assessment ◽  
The Mean ◽  
Wind Resource

The present study aims to present a contribution to the wind resource assessment in Algeria using ERA-Interim reanalysis. Firstly, the ERA-Interim reanalysis 10 m wind speed data are considered for the elaboration of the mean annual 10 m wind speed map for a period starting from 01-01-2000 to 31-12-2017. Moreover, the present study intends to highlight the importance of the descriptive statistics other than the mean in wind resource assessment. On the other hand, this study aims also to select the proper probability distribution for the wind resource assessment in Algeria. Therefore, nine probability distributions were considered, namely: Weibull, Gamma, Inverse Gaussian, Log Normal, Gumbel, Generalized Extreme Value (GEV), Nakagami, Generalized Logistic and Pearson III. Furthermore, in combination with the distribution, three parameter estimation methods were considered, namely, Method of Moment, Maximum Likelihood Method and L-Moment Method. The study showed that Algeria has several wind behaviours due to the diversified topographic, geographic and climatic properties. Moreover, the annual mean 10 m wind speed map showed that the wind speed varies from 2.3 to 5.3 m/s, where 73% of the wind speeds are above 3 m/s. The map also showed that the Algerian Sahara is windiest region, while, the northern fringe envelopes the lowest wind speeds. In addition, it has been shown that the study of the mean wind speeds for the evaluation of the wind potential alone is not enough, and other descriptive statistics must be considered. On the other hand, among the nine considered distribution, it appears that the GEV is the most appropriate probability distribution. Whereas, the Weibull distribution showed its performance only in regions with high wind speeds, which, implies that this probability distribution should not be generalized in the study of the wind speed in Algeria.

Wind Resource Assessment for the Kingdom of Bahrain

2008 ◽  
Vol 32 (5) ◽  
pp. 439-448 ◽  
Author(s):  
Hanan Al Buflasa ◽  
David Infield ◽  
Simon Watson ◽  
Murray Thomson
Keyword(s):  
Wind Speed ◽  
Energy Production ◽  
Resource Assessment ◽  
Measured Data ◽  
Shape Parameters ◽  
Main Island ◽  
Wind Resource Assessment ◽  
Mean Wind Speed ◽  
Wind Resource ◽  
Hourly Basis

The geographical distribution of wind speed (the wind atlas) for the kingdom of Bahrain is presented, based on measured data and on calculations undertaken using WAsP,. The data used were recorded by the Meteorological Directorate at a weather station situated at Bahrain International Airport, taken on an hourly basis for a period of time extended for ten years. These data indicate an annual mean wind speed of 4.6 m/s at 10 m height and mean Weibull scale and shape parameters C and k of 5.2 m/s and 1.9 respectively. At a typical wind turbine hub height of sixty metres, these values are extrapolated to 6.9 m/s, 7.8 m/s and 1.8 respectively, which suggests that the area has a good wind resource. The wind atlas shows that several locations in the less populated central and southern regions of the main island of the archipelago of Bahrain are potentially suitable for wind energy production.

An Empirical Study of Two Numerical Models for Wind Resource Simulation in Complex Terrain

2014 ◽  
Vol 535 ◽  
pp. 8-12 ◽  
Author(s):  
Zhen Wei ◽  
Yuan Chang Deng ◽  
Wei Zhang ◽  
Zheng Hao Yang
Keyword(s):  
Wind Speed ◽  
Complex Terrain ◽  
Resource Assessment ◽  
Wind Data ◽  
Simulation Accuracy ◽  
Wind Resource Assessment ◽  
Generation Capacity ◽  
Wind Resource ◽  
Simulated Wind ◽  
Simulated Wind Speed

The choice of wind measured data and numerical simulation method has an important impact on the results of wind resource assessment. This paper will take a wind farm, in Yangjiang City, Guangdong Province, for an example and discuss the simulation accuracy by linear model WAsP and nonlinear model based on simulation software Fluent. First of all, contrast mean absolute percentage error (MAPE) about simulated wind speed under four kinds of wind conditions, which are simulated by four sets of wind data in WAsP, and then select the wind data with the smallest . Then, using WAsP and CFD method simulates wind field by the optimal wind data. Compare simulated wind speed and annual generation capacity. In this paper, the simulated wind speed in the simulation model CFD based on Fluent is closer to the measured wind speed. The MAPE of wind speed and annual generation capacity by CFD model is smaller than that by WAsP. Therefore, for the wind resource assessment in the complex terrain, the nonlinear model CFD based on Fluent will be qualified to response the relationship between wind resource and terrain, simulation accuracy, and has higher simulation accuracy than the linear model WAsP.

Distributed wind resource assessment: Comparing measured annual energy production with predictions from computational fluid dynamics

2019 ◽  
Vol 43 (6) ◽  
pp. 657-672
Author(s):  
Devon L Martindale ◽  
Thomas L Acker
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Wind Turbine ◽  
Energy Production ◽  
Resource Assessment ◽  
Energy Output ◽  
Wind Resource Assessment ◽  
Production Values ◽  
The Us ◽  
Wind Resource

The US Department of Energy’s Distributed Wind Resource Assessment Workshop identified predicting the annual energy production of a kilowatt-sized wind turbine as a key challenge. This article presents the methods and results for predicting the annual energy production of two 2.1 kW Skystream 3.7 wind turbines using computational fluid dynamics, in this case Meteodyn WT. When compared with actual production data, annual energy production values were uniformly underpredicted, with errors ranging from 1% to in excess of 30%, depending on the solver settings and boundary conditions. The most accurate of the simulations with errors consistently less than 10% were achieved when using recommended solver settings of neutral atmospheric stability, and roughness values derived from the US National Land Cover Database. The software was used to create an annual energy production map for the modeling domain, which could be a valuable tool in estimating the energy output and economic value of a proposed wind turbine.

Component Size Optimization of a Wind-Integrated Microgrid System With Dispatch Strategy and Resource Uncertainty

2014 ◽  
Author(s):  
Tzu-Chieh Hung ◽  
Kuei-Yuan Chan
Keyword(s):  
Alternative Energy ◽  
High Reliability ◽  
Design Procedure ◽  
Resource Assessment ◽  
Integrated System ◽  
Wind Data ◽  
Wind Model ◽  
Storage Devices ◽  
Wind Resource Assessment ◽  
Wind Resource

The global quest for energy sustainability has motivated the development of technology for efficiently transforming various natural resources into energy. Combining these alternative energy sources with existing power systems requires systematic assessments and planning. The present study investigates the conversion of an existing power system into one with a wind-integrated microgrid. The standard approach applies wind resource assessment to determine suitable wind farm locations with high potential energy and then develops specific dispatch strategies to meet the power demand for the wind-integrated system with low cost, high reliability, and low impact on the environment. However, the uncertainty in wind resource results in fluctuating power generation. The installation of additional energy storage devices is thus needed in the dispatch strategy to ensure a stable power supply. The present work proposes a design procedure for obtaining the optimal sizing of wind turbines and storage devices considering wind resource assessment and dispatch strategy under uncertainty. Two wind models are developed from real-world wind data and apply in the proposed optimization framework. Based on comparisons of system reliability between the optimal results and real operating states, an appropriate wind model can be chosen to represent the wind characteristics of a particular region. Results show that the trend model of wind data is insufficient for wind-integrated microgrid planning because it does not consider the large variation of wind data. The wind model should include the uncertainties of wind resource in the design of a wind-integrated microgrid system to ensure high reliability of optimal results.

scholarly journals Uncertainty Analysis in MCP-Based Wind Resource Assessment and Energy Production Estimation

2008 ◽  
Vol 130 (3) ◽  
Author(s):  
Matthew A. Lackner ◽  
Anthony L. Rogers ◽  
James F. Manwell
Keyword(s):  
Wind Energy ◽  
Energy Production ◽  
Closed Form Solution ◽  
Resource Assessment ◽  
Form Solution ◽  
Mathematical Framework ◽  
Site Assessment ◽  
Wind Resource Assessment ◽  
Uncertainty Sources ◽  
Wind Resource

This paper presents a mathematical framework to properly account for uncertainty in wind resource assessment and wind energy production estimation. A meteorological tower based wind measurement campaign is considered exclusively, in which measure-correlate-predict is used to estimate the long-term wind resource. The evaluation of a wind resource and the subsequent estimation of the annual energy production (AEP) is a highly uncertain process. Uncertainty arises at all points in the process, from measuring the wind speed to the uncertainty in a power curve. A proper assessment of uncertainty is critical for judging the feasibility and risk of a potential wind energy development. The approach in this paper provides a framework for an accurate and objective accounting of uncertainty and, therefore, better decision making when assessing a potential wind energy site. It does not investigate the values of individual uncertainty sources. Three major aspects of site assessment uncertainty are presented here. First, a method is presented for combining uncertainty that arises in assessing the wind resource. Second, methods for handling uncertainty sources in wind turbine power output and energy losses are presented. Third, a new method for estimating the overall AEP uncertainty when using a Weibull distribution is presented. While it is commonly assumed that the uncertainty in the wind resource should be scaled by a factor between 2 and 3 to yield the uncertainty in the AEP, this work demonstrates that this assumption is an oversimplification and also presents a closed form solution for the sensitivity factors of the Weibull parameters.

scholarly journals Wind Speed using Improved Mixture Weibull Distribution

2019 ◽  
Vol 8 (6) ◽  
pp. 1871-1874
Keyword(s):  
Wind Speed ◽  
Probability Distribution ◽  
Weibull Distribution ◽  
Wind Farms ◽  
Resource Assessment ◽  
Estimation Of Parameters ◽  
Basic Properties ◽  
Wind Resource Assessment ◽  
Proposed Model ◽  
Wind Resource

Wind is random in nature both in space and in time. Several technologies are used in wind resource assessment (WRA).The appropriate probability distribution used to calculate the available wind speed at that particular location and the estimation of parameters is the essential part in installing wind farms. The improved mixture Weibull distribution is proposed model which is the mixture of two and three parameter Weibull distribution with parameters including scale, shape, location and weight component. The basic properties of the proposed model and estimation of parameters using various methods are discussed.

scholarly journals An Overview of Wind Resource Assessments With Special Reference to The Emirate of Ajman, UAE

2021 ◽  
Vol 6 ◽  
pp. 32
Author(s):  
Kais Muhammed Fasel ◽  
Abdul Salam K. Darwish ◽  
Peter Farrell ◽  
Hussein Kazem
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Clean Energy ◽  
Resource Assessment ◽  
Site Specific ◽  
Onshore Wind ◽  
Wind Resource Assessment ◽  
Wind Potential ◽  
The Government ◽  
Wind Resource

The continuous increase in clean energy demand and reduced CO2 emissions in the UAE and specifically the Emirate of Ajman has put an extreme challenge to the Government. Ajman is one of the seven emirates constituting the United Arab Emirates (UAE). Ajman is located along the Arabian Gulf on its West and bordered by the Emirate of Sharjah on its North, South, and East. The government is taking huge steps in including sustainability principles and clean energy in all of its developments. Successful implementation of green architecture law decree No 10 of 2018 effectively is a sign of such an initiative. Renewable energy sources in this country have had two folds of interest in solar and wind. Recent research works supported the feasibility of using wind energy as an alternative clean source of energy. Site-specific and accurate wind speed information is the first step in the process of bankable wind potential and wind Atlas. This study has compared how wind speed and its distribution varies for similar offshore and onshore locations between two different mesoscale data sources. Also, discussed the main environmental characteristics of Ajman that would influence the implementation of a major wind energy project. In addition, the study made a brief critical overview of the major studies undertaken in the Middle East and North Africa (MENA) region on wind resource assessment. Finally, based on the results, the study makes conclusions, recommendations and a way forward for a bankable wind resources assessment in the Emirate of Ajman. This paper would alert the wind energy industry about the consequence of not considering the best error corrected site specific suitable wind resource data along with other environmental characteristics. The study results show that for offshore, there is 2.9 m/s and for Onshore 4.9 m/s variations in wind speed at the same location between ECMWF Reanalysis (ERA-5) and NASA Satellite data. Hence It is concluded that error corrected site-specific wind resource assessment is mandatory for assessing the available bankable wind potential since there are considerable variations in wind speed distributions between mesoscale data sets for similar locations. The study also identifies that the Emirate of Ajman has limited space for onshore wind farms; hence the offshore site seems to have good potential that can be utilised for energy generation. However, individual wind turbines can be installed for exploiting the available site-specific onshore wind energy. Finally, the study recommends a way forward for a comprehensive wind resource assessment to help the Emirate of Ajman form a sustainable wind power generation policy.

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