sj-pdf-1-wie-10.1177_0309524X211027356 – Supplemental material for Potential of wind energy in Medina, Saudi Arabia based on Weibull distribution parameters
Type
Data FileAuthors
AlQdah, Khaled S
Alahmdi, Raed L.
Alansari, Abdulrahman
Almoghamisi, Abdulrahman
Abualkhair, Mohanad
Awais, Muhammad
Date
2021Permanent link to this record
http://hdl.handle.net/10754/674290Metadata
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Supplemental material, sj-pdf-1-wie-10.1177_0309524X211027356 for Potential of wind energy in Medina, Saudi Arabia based on Weibull distribution parameters by Khaled S AlQdah, Raed Alahmdi, Abdulrahman Alansari, Abdulrahman Almoghamisi, Mohanad Abualkhair and Muhammad Awais in Wind EngineeringCitation
AlQdah, K. S., Alahmdi, R., Alansari, A., Almoghamisi, A., Abualkhair, M., & Awais, M. (2021). sj-pdf-1-wie-10.1177_0309524X211027356 – Supplemental material for Potential of wind energy in Medina, Saudi Arabia based on Weibull distribution parameters. SAGE Journals. https://doi.org/10.25384/SAGE.14869943Publisher
SAGE JournalsRelations
Is Supplement To:- [Article]
AlQdah, K. S., Alahmdi, R., Alansari, A., Almoghamisi, A., Abualkhair, M., & Awais, M. (2021). Potential of wind energy in Medina, Saudi Arabia based on Weibull distribution parameters. Wind Engineering, 0309524X2110273. doi:10.1177/0309524x211027356. DOI: 10.1177/0309524x211027356 Handle: 10754/669812
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Potential of wind energy in Medina, Saudi Arabia based on Weibull distribution parameters(SAGE Journals, 2021) [Dataset]This study aims to assess the potential of wind energy in Medina by using Weibull probability distribution to provide an insight concerning the energy production from the selected wind turbine Aventa AV-7. Scale factors $\textit{c}$ and shape $\textit{k}$ of Weibull distribution, were determined for wind speed frequency. Significant findings included a wind speed recurrence of 2.9 m/s with a probability of 30% approximately. The average $\textit{c}$ and $\textit{k}$ were found to be 3.467 and 2.923 m/s, respectively. The estimated average $\textit{k}$ is relatively high, which indicates that the spread in wind speeds is small. Aventa AV-7 turbine was chosen to test the power generation of wind in Medina. It was found that this wind turbine can generate 8648 kWh/year in the Medina region, which is only 15.2% of the maximum power production. This turbine is expected to generate the maximum possible power output at a wind speed of 7 m/s.
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Potential of wind energy in Medina, Saudi Arabia based on Weibull distribution parameters(Wind Engineering, SAGE Publications, 2021-06-28) [Article]This study aims to assess the potential of wind energy in Medina by using Weibull probability distribution to provide an insight concerning the energy production from the selected wind turbine Aventa AV-7. Scale factors c and shape k of Weibull distribution, were determined for wind speed frequency. Significant findings included a wind speed recurrence of 2.9 m/s with a probability of 30% approximately. The average c and k were found to be 3.467 and 2.923 m/s, respectively. The estimated average k is relatively high, which indicates that the spread in wind speeds is small. Aventa AV-7 turbine was chosen to test the power generation of wind in Medina. It was found that this wind turbine can generate 8648 kWh/year in the Medina region, which is only 15.2% of the maximum power production. This turbine is expected to generate the maximum possible power output at a wind speed of 7 m/s.
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Interactive seismic interpretation with piecewise global energy minimization(2011 IEEE Pacific Visualization Symposium, Institute of Electrical and Electronics Engineers (IEEE), 2011-03) [Conference Paper]Increasing demands in world-wide energy consumption and oil depletion of large reservoirs have resulted in the need for exploring smaller and more complex oil reservoirs. Planning of the reservoir valorization usually starts with creating a model of the subsurface structures, including seismic faults and horizons. However, seismic interpretation and horizon tracing is a difficult and error-prone task, often resulting in hours of work needing to be manually repeated. In this paper, we propose a novel, interactive workflow for horizon interpretation based on well positions, which include additional geological and geophysical data captured by actual drillings. Instead of interpreting the volume slice-by-slice in 2D, we propose 3D seismic interpretation based on well positions. We introduce a combination of 2D and 3D minimal cost path and minimal cost surface tracing for extracting horizons with very little user input. By processing the volume based on well positions rather than slice-based, we are able to create a piecewise optimal horizon surface at interactive rates. We have integrated our system into a visual analysis platform which supports multiple linked views for fast verification, exploration and analysis of the extracted horizons. The system is currently being evaluated by our collaborating domain experts. © 2011 IEEE.
