Climatic potential for wind energy generation in Najaf Governorate
DOI:
https://doi.org/10.36327/ewjh.v1i34.19205Keywords:
climate potential, wind energy, Najaf Governorate, Weibull distributionAbstract
The research aims to estimate and evaluate wind energy in the study area, it was calculated by mathematical methods, as it was caught temporally (hourly, monthly, quarterly, annually) and spatially for all the seven stations of the study area), as well as calculating the maximum and minimum energy from the maximum and minimum wind speed and for three heights (10 m, 30 m, 50 m) - to illustrate the vertical variance of the hydroelectric energy - as the energy generated by the wind was calculated, the actual energy was calculated through the indication of Whipple Probability Density Distribution (WPD) from the parameters of the figure and measurement, the wind energy regions were distributed in The governorate to determine the regions that are efficient to invest this energy, and one of the most important results of the research is the increase in the possible energy calculated from the wind in the summer, and the most generating areas of this energy in the governorate are the network side represented by the Shabiha stations and the natural reserve.
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References
ـ فرید سليم أبو حامد، طاقة الرياح العنفات الريحية، المركز العربي للتعريب والنشر، دمشق، 2017، ص30.
ـ عادل سعيد الراوي وقصي عبد المجيد السامرائي، المناخ التطبيقي، مطبعة دار الحكمة، بغداد، 1990، ص296.
-Johnson Kotz and Balakrishnan, Engineering statistics Handbook Weibull Distribution, chapter 8, p.55.
- Characteristic Effect of the shape scale, location parameter for Weibull distribution, 2006, p.140.
تم حسابها من برنامج اكسل.
- M. Akhlaque Ahmed, Firoz Ahmed, Assessment of Wind Power Potential for Coastal Areas of Pakistan, 2004.
- K. Rosen, An Assessment of the potential for utility- scale wind power Generation in Eritrea, 1998. P. 46.
7. وزارة النقل، الهيئة العامة للأنواء الجوية والرصد الزلزالي، قسم المناخ، بيانات غير منشورة، بغداد، 2020.
8 وزارة الزراعة، مركز الأرصاد الجوية، شعبة البيانات المناخية، بيانات منشورة، بغداد، 2020.
9وزار العلوم والتكنولوجيا، دائرة الطاقات المتجددة، مركز بحوث الطاقة المستحدثة، قسم الإحصاء، بيانات غير منشورة، بغداد، 2020.
10. وزارة التعليم العالي والبحث العلمي، جامعة الفرات الأوسط التقنية، وحدة بحوث الطاقة المتجددة، بيانات غير منشورة النجف، 2020.
11. وزارة الصحة والبيئة، مديرية بيئة النجف الأشرف، قسم الهواء، بيانات غير منشورة، النجف، 2020.
Footnotes and sources
1. Farid Salim Abu Hamid, Wind energy Wind turbines, Arab Center for Arabization and Publishing, Damascus, 2017, p. 30.
2. Adel Saeed Al-Rawi and Qusay Abdul Majeed Al-Samarrai, Applied Climate, Dar Al-Hekma Press, Baghdad, 1990, p. 296
3. Johnson Kotz and Balakrishnan, Engineering statistics Handbook Weibull Distribution, chapter 8, p.55.
4. Characteristic Effect of the shape scale, location parameter for distribution Weibull, 2006, p.140.
5. M. Akhlaque Ahmed, Firoz Ahmed, Assessment of Wind Power Potential for Coastal Areas of Pakistan, 2004.
6. K. Rosen, An Assessment of the potential for utility-scale wind power generation in Eritrea, 1998. p. 46.
7. Ministry of Transport, General Authority for Meteorology and Seismic Monitoring, Climate Department, unpublished data, Baghdad, 2020.
8. Ministry of Agriculture, Meteorological Center, Climatic Data Division, published data, Baghdad, 2020
9. Ministry of Science and Technology, Department of Renewable Energy, Center for New Energy Research, Department of Statistics, unpublished data, 2020, Baghdad.
10. Ministry of Higher Education and Scientific Research, Al-Furat Al-Awsat Technical University, Renewable Energy Research Unit, unpublished data, 2020, Najaf.
11. Ministry of Health and Environment, Najaf Environment Directorate, Air Department, unpublished data, Najaf, 2020.
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