تحقیقات کاربردی علوم جغرافیایی

تحقیقات کاربردی علوم جغرافیایی

ارزیابی تغییرات فضایی ـ زمانی تابش خورشیدی دریافتی سطح زمین در استان کرمانشاه با مدل "لیو و جُردن"

نویسندگان
فیروز مجرد 1
امان الله فتح نیا 2
سعید رجایی نجف آبادی: 3
1 دانشیار اقلیم شناسی، گروه جغرافیا، دانشگاه رازی، کرمانشاه، کرمانشاه، ایران
2 استادیار اقلیم شناسی، گروه جغرافیا، دانشگاه رازی، کرمانشاه، کرمانشاه، ایران
3 دانشجوی دورۀ دکتری اقلیم شناسی، گروه جغرافیا، دانشگاه رازی،کرمانشاه،کرمانشاه، ایران
چکیده
این مطالعه با هدف برآورد میزان تابش دریافتی در سطح استان کرمانشاه به­منظور گسترش سایت­های خورشیدی با استفاده از مدل لیو و جُردن به­انجام رسیده است. با استفاده از شاخصی به­نام شاخص شفافیت آسمان () مقدار حذف اتمسفری در هر ماه محاسبه و بر روی شیب­ها­، جهات شیب و ارتفاع­های­ مختلف اِعمال گردید. سپس با توجه به نتایج به­دست­آمده، مقادیر تابش مستقیم، پراکنده و کل در توپوگرافی­های مختلف منطقه محاسبه و نقشه­های مربوطه رسم گردید. نتایج نشان داد مقدار حداقل حذف اتمسفری و در نتیجه بیشترین مقدار تابش دریافتی در سطح استان به­دلیل افزایش شاخص در اواخر فصول بهار و تابستان با حداکثر ماه می به­میزان 1360 کالری بر سانتی­متر مربع در روز رخ می­دهد. در مقابل، کمترین مقدار تابش دریافتی متعلق به ماه ژانویه به میزان 3/386 کالری بر سانتی­متر مربع است. تغییرات تابش در سطح استان بین مناطق پست و مرتفع در ماه­های ژانویه و دسامبر با توجه به نقش زاویۀ تابش و تغییرات قابل توجه ارتفاعی زیاد است. اما در تابستان به­دلیل ارتفاع زیاد خورشید، توزیع تابش در سطح زمین تقریباً یکسان شده و مقدار انحراف­معیار مقادیر تابش رسیده کاهش می­یابد. بیشترین مقدار تابش در شهرستان جوانرود به‌میزان 1/528 کالری بر سانتی‌متر مربع در روز به‌دلیل ارتفاع بیشتر، و کمترین آن در شهرستان قصرشیرین به‌میزان 6/443 کالری بر سانتی‌متر مربع در روز به دلیل ارتفاع کمتر دریافت می‌شود.
کلیدواژه‌ها
تابش دریافتی
تغییرات فضایی
مدل لیو و جُردن
شاخص شفافیت
استان کرمانشاه

عنوان مقاله English

Evaluation of Spatial-Temporal Variations of Incoming Solar Radiation in Kermanshah Province Using "Liu and Jordan" Model

نویسندگان English

Firouz Mojarrad 1
Amanollah Fathnia 2
Saeed Rajaee Najafabadi 3
چکیده English

The aim of this study was to provide a reliable estimate of the amount of solar radiation in Kermanshah province by using “Liu and Jordan” model in order to develop solar sites. The amount of atmospheric elimination in each month was calculated using an index called clearness index () and the results were applied on different slopes, aspects and heights. Then, according to the obtained results, amounts of direct, diffuse and total radiation were calculated in different slopes of the region and the relevant maps were consequently drawn. The results showed that the minimum amount of atmospheric elimination and thus the maximum amount of received radiation in the province occurs in late spring and summer due to the increase of clearness index () with a maximum of 1360 cal/cm2/day in May. the least amount of received radiation occurs in Janury equal to 386.3 cal/cm2/day. Radiation variations at the provincial level are high between lowlands and highlands in Janury and December, according to the angle of radiation and significant elevation changes in the region. However, in summer, distribution of surface radiation is almost identical because of high solar radiation, and thus standard deviation amount of received radiation is reduced. The highest amount of radiation is received in Javanrood city as much as 528.1 cal/ cm2/day due to greater heights, and the lowest amount is received in Qasr-e Shirin city as much as 443.6 cal/ cm2/day due to lower heights.

کلیدواژه‌ها English

Received Radiation
Spatial Varitions
Liu and Jordan Model
Clearness Index
Kermanshah Province
Al-Alawi, S., & Al-Hinai, H. (1998). An ANN-based Approach for Predicting Global Radiation in Locations with no Direct Measurement Instrumentation. Renewable Energy, 14, 199-204.

Angstrom, A. (1924). Solar and Terrestrial Radiation. Quart. J. Roy. Met. Soc., 50, 121-125.

Bahadorinejad, M., & Yaghoobi, M. (2006). Ventilation and Natural Cooling in Iranian Traditional Buildings. 1st Edition, Tehran: Academic Publication Center.

Behrang, M. A., Assareh, E., Ghanbarzadeh, A., & Noghrehabadi, A. R. (2010). The Potential of Different Artificial Neural Network (ANN) Techniques in Daily Global Solar Radiation Modeling Based on Meteorological Data. Solar Energy, 84, 1468-1480.

Belcher, B. N., & DeGaetano, A. T. (2007). A Revised Empirical Model to Estimate Solar Radiation using Automated Surface Weather Observations. Solar Energy, 81(3), 329-345.

Chaar, L., & Lamont, L. A. (2010). Global Solar Radiation: Multiple on-Site Assessments in Abu Dhabi, UAE. Renewable Energy, 35(7), 1596-1601.
3- Chen, R.; Kang, E.; Lu, S.; Yang, J.; Ji, X.; Zhang, Z.; & Zhang, J. (2006). New Methods to Estimate Global Radiation Based on Meteorological Data in China. Energy Conversion and Management, 47(18-19), 2991–2998.

Cooper, P. I. (1969). The Absorption of Solar Radiation in Solar Sills. Solar Energy, 12, 333-346.

Danny, H. W., Ernest, Li., Tsang, K. W., Cheung, K. L., & Tam, C. O. (2010). An Analysis of Light-Pipe System via Full-Scale Measurements. Applied Energy, 87(9), 799-805.

De Souza, J. L., Nicacio, R. M., & Moura, M. A. L. (2005). Global Solar Radiation Measurements in Maceio, Brazil. Renewable Energy, 30, 1203-1220.

Diodato, N., & Bellocchi, G. (2007). Modelling Solar Radiation over Complex Terrains using Monthly Climatological Data. Agricultural and Forest Meteorology, 144 (1-2), 111-126.

Dincer, I. (2000). Renewable Energy and Sustainable Development: A Crucial Review. Renewable and Sustainable Energy Reviews, 4(2), 157-175.

Duffie, J. A., & Beckman, W. A. (2006). Solar Engineering of Thermal Processes. 3nd Edition, New York: John Wiley & Sons.

El-Metwally, M. (2005). Sunshine and Global Solar Radiation Estimation at Different Sites in Egypt. Journal of Atmospheric and Solar-Terrestrial Physics, 67(14), 1331-1342.

Guofeng, W., Yaolin, L., & Tiejun, W. (2007). Methods and Strategy for Modeling Daily Global Solar Radiation with Measured Meteorological Data – A case Study in Nanchang Station, China. Energy Conversion and Management, 48, 2447-2452.

Hofierka, J., & Kaňuk, J. (2009). Assessment of Photovoltaic Potential in Urban Areas using Open-Source Solar Radiation Tools. Renewable Energy, 34(10), 2206-2214.

Islam, M. D., Alili, A. A., Kubo, I., & Ohadi, M. (2010). Measurement of Solar-Energy (Direct Beam Radiation) in Abu Dhabi, UAE. Renewable Energy, 35, 515-519.
Janjai, S., Pankaew, P., Laksanaboonsong, J., & Kitichantaropas, P. (2011). Estimation of Solar Radiation over Cambodia from Long-Term Satellite Data. Renewable Energy, 36(4), 1214-1220.

Jianfeng, L., Jing, D., & Jianping, Y. (2010). Heat Transfer Performance of an External Receiver Pipe under Unilateral Concentrated Solar Radiation. Solar Energy, 84(11), 1879-1887.

Kaskaoutis, D. G., Kambezidis, H. D., Jacovides, C. P., & Steven, M. D. (2006). Modification of solar Radiation Components Under Different Atmospheric Conditions in the Greater Athens Area, Greece. Journal of Atmospheric and Solar-Terrestrial Physics, 68(10), 1043-1052.

Liu, B. Y. H., & Jordan, R. C. (1963). A Rational Procedure for Predicting the Long-Term Average Performance of Flat-Plate Solar-Energy Collectors with Design Data for the U. S., Its Outlying Possessions and Canada. Solar Energy, 7(2), 53–74.

Martin, L., Zarzalejo, L. F., Polo, J., Navarro, A., Marchante, R., & Cony, M. (2010). Prediction of Global Solar Irradiance Based on Time Series Analysis: Application to Solar Thermal Power Plants Energy Production Planning. Solar Energy, 84(10), 1772-1781.

Montero, G., Escobar, J. M., Rodrίguez, E., & Montenegro, R. (2009). Solar radiation and shadow modelling with adaptive triangular meshes. Solar Energy, 83(7), 998-1012.

Muneer, T., Younes, S., & Munawwar, S. (2007). Discourses on Solar Radiation Modeling. Renewable and Sustainable Energy Reviews, 11(4), 551-602.

Muzathik, A. M., Ibrahim, M. Z., Samo, K. B., & Wan Nik, W. B. (2011). Estimation of Global Solar Irradiation on Horizontal and Inclined Surfaces Based on the Horizontal Measurements. Energy, 36(2), 812-818.

Notton, G., Cristofari, C., Poggi, P., & Muselli, M. (2002). Calculation of Solar Irradiance Profiles from Hourly Data to Simulate Energy Systems Behavior. Renewable Energy, 27(1), 123-142.

Prescott, J. A. (1940). Evaporation from a Water Surface in Relation to Solar Radiation. Trans. R. Soc. S. Austr., 64, 114-118.

Rahman, S., & Mohandes, M. (2008). Artificial Neural Network Estimation of Global Solar Radiation using Air Temperature and Relative Humidity. Energy Policy, 36(2), 571-576.

Saberifar, R. (2010). Potentials of Utilization of Solar Energy in Southern Khorasan. Energy Economy, 131-132, 43-47.

Sozen, A., Arcaklioglub, E., Ozalpa, M., & Caglar, N. (2005). Forecasting Based on Neural Network Approach of Solar Potential in Turkey. Renewable Energy, 30, 1075-1090.

Šúri, M., Huld, T. A., Dunlop, E. D., & Ossenbrink, H. A. (2007). Potential of Solar Electricity Generation in the European :union: Member States and Candidate Countries. Solar Energy, 81, 1295-1305.

Tymvios, F. S., Jacovides, C. P., Michaelides, S. C., & Scouteli, C. (2005). Comparative Study of Angstrom’s and Artificial Neural Networks’ Methodologies in Estimating Global Solar Radiation. Solar Energy, 78(6), 752-762.

Yorukoglu, M., & Celik, A. N. (2006). A Critical Review on the Estimation of Daily Global Solar Radiation from Sunshine Duration. Energy Conversion and Management, 47, 2441-2450.

Zarzalejo, L. F., Polo, J., Martín, L., Ramírez, L., & Espinar, B. (2009). A New Statistical Approach for Deriving Global Solar Radiation from Satellite Images. Solar Energy, 83(4), 480-484.