Wind power characteristics of seven data collection sites in Jubail, Saudi Arabia using Weibull parameters

Baseer, Mohammed Abdul; Meyer, Josua P.; Rehman, Shafiqur; Alam, Md. Mahbub

doi:10.1016/j.renene.2016.10.040

Cited by 122 publications

(72 citation statements)

References 16 publications

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“…Based on Baseer et al [27], the highest mean wind speeds at the Jubail industrial site of 5.35 m/s, and the possibility of wind speeds reaching above 3.5 m/s, was 75%. Another study was conducted by the same team [28] to analyse seven sites at Jubail using different tools. The results showed that the highest annual mean wind speed of 4.52 m/s was observed at Jubail [28].…”

Section: Wind Energymentioning

confidence: 99%

Saudi Arabia’s Solar and Wind Energy Penetration: Future Performance and Requirements

Alharbi

Csala

2020

Energies

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Saudi Arabia fully depends on fossil fuels such as oil and natural gas to generate its electricity. Fossil fuels may have limited life and a history of fluctuating costs, which will lead to multiple issues that can affect the energy security of this country in the long-term. Critical Infrastructure Protection (CIP) is a concept different to “energy security”, which must consider the solar and wind energy as basic sources of energy supplies in Saudi Arabia. Monte Carlo Simulation (MCS) and Brownian Motion (BM) approaches were employed to predict the future behaviour of solar and wind energy, along with long-term temperature performance, based on 69 years of historical daily data. MCS and BM were employed to provide a wide range of options for future prediction results. A validation exercise showed that the north-western region was the most highly recommended region for deployment of solar and wind energy applications due to an abundance of solar and wind energy resources with low temperature supported by a clearer sky during the year. This is followed by the southern region, which exhibited good solar and wind energy resources. This study can be considered as a roadmap to meet the climate and sustainability goals by providing a long-term overview of solar energy, wind energy, and temperature performance in some countries that have a lack of long-term future prediction analysis such as Saudi Arabia.

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Section: Wind Energymentioning

confidence: 99%

Saudi Arabia’s Solar and Wind Energy Penetration: Future Performance and Requirements

Alharbi

Csala

2020

Energies

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“…The value of wind speed shear exponent follows the setting of Kim and Hur (2017). A Weibull distribution has won its reputation in analyzing wind speed data (Bagiorgas et al, 2012(Bagiorgas et al, , 2016Baseer et al, 2017;Bassyouni et al, 2015;Rehman et al, 2012). The twoparameter Weibull distribution consists of scale and shape parameters, and the distribution of wind speed can be estimated by Weibull distribution.…”

Section: Wind Power Assessmentmentioning

confidence: 99%

An economic analysis on Taiwanese wind power and regional development

Chen

Zhang

Kung

2020

Energy Exploration & Exploitation

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Due to environmental concern, Taiwan aims to remove nuclear power from its energy structure. Since an increase in fossil fuel-based generation is foreboded by law, the lost nuclear power can only be replaced by renewable energy sources. The maritime climate and constant monsoons make wind power a feasible alternative energy source to Taiwan. With more than 300 potential wind farm sites under consideration, the government does not have enough information to determine the best sites in terms of power generation and capital investments. To explore such information, this study employs a lifecycle analysis to identify the economic components of these sites under the estimates of wind speed data and potential wind power generation obtained in our previous study. We also use a sensitivity analysis to examine the impact of construction cost, maintenance cost, energy sale, and emission trade on the site selection decision. We show that variations in construction costs and energy prices have larger impacts than greenhouse gases prices. In addition, the results point out that most sites pass the cost-benefit examination, but site rankings may alter in the face of capital rationing and climate change. Some policy implications derived from the results are discussed in detail.

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“…We firstly performed a distributional analysis to identify the distribution that better describes our wind speed data. The distributions that are generally employed to fit wind speed data are Weibull [26], Gamma [27], and Generalized Extreme Values (GEV) [28].…”

Section: Data and Exploratory Analysismentioning

confidence: 99%

Periodic fluctuations in correlation-based connectivity density time series: Application to wind speed-monitoring network in Switzerland

Laib

Telesca

Kanevski

2018

Physica A: Statistical Mechanics and its Applications

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In this paper, we study the periodic fluctuations of connectivity density time series of a wind speed-monitoring network in Switzerland. By using the correlogram-based robust periodogram annual periodic oscillations were found in the correlation-based network. The intensity of such annual periodic oscillations is larger for lower correlation thresholds and smaller for higher. The annual periodicity in the connectivity density seems reasonably consistent with the seasonal meteo-climatic cycle.

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Wind power characteristics of seven data collection sites in Jubail, Saudi Arabia using Weibull parameters

Abstract: The wind characteristics of seven locations in Jubail, Saudi Arabia were analysed by using five years of wind data of six sites and three years data of one site at 10 m above ground level (AGL). The highest annual mean wind speed of 4.52 m/s was observed at

Cited by 122 publications

References 16 publications

Saudi Arabia’s Solar and Wind Energy Penetration: Future Performance and Requirements

Saudi Arabia’s Solar and Wind Energy Penetration: Future Performance and Requirements

An economic analysis on Taiwanese wind power and regional development

Periodic fluctuations in correlation-based connectivity density time series: Application to wind speed-monitoring network in Switzerland

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