پیوندهای مفید
اخبار و اعلانات
آمار
| تعداد نشریات | 158 |
| تعداد شماره‌ها | 6,225 |
| تعداد مقالات | 67,685 |
| تعداد مشاهده مقاله | 114,998,802 |
| تعداد دریافت فایل اصل مقاله | 89,672,845 |
ارزیابی مدل r.sun در برآورد میزان دریافت انرژی خورشیدی در مناطق خشک و نیمه‌خشک (مطالعۀ موردی: استان اصفهان) | ||
| محیط شناسی | ||
| مقاله 12، دوره 41، شماره 2، تیر 1394، صفحه 415-427 اصل مقاله (1.14 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/jes.2015.54991 | ||
| نویسندگان | ||
| محمود ذوقی1؛ مهدیس سادات2؛ امیر هوشنگ احسانی* 3 | ||
| 1دانشجوی کارشناسی ارشد برنامهریزی، مدیریت و آموزش محیط‌زیست، دانشکدۀ محیط‌زیست، دانشگاه تهران، | ||
| 2دانشجوی کارشناسی ارشد برنامهریزی، مدیریت و آموزش محیط‌زیست، دانشکدۀ محیط‌زیست، دانشگاه تهران | ||
| 3دانشیار گروه مهندسی طراحی محیط‌زیست، دانشکدۀ محیط‌زیست، دانشگاه تهران | ||
| چکیده | ||
| از جنبه‌های مهم توسعۀ پایدار ملاحظات زیست‌‌محیطی است که یکی از ارکان آن استفاده از منابع انرژی تجدیدپذیر است. میزان دریافت این انرژی در نقاط مختلف سطح زمین به چندین فاکتور شامل: عرض جغرافیایی، طول جغرافیایی، میزان ساعت آفتابی، رطوبت هوا، تبخیر، دمای هوا، زاویۀ خورشید و سایر عوامل بستگی دارد. از این رو گرایش به سمت استفاده از مدلهای تابش خورشید در سال‌‌های اخیر بیشتر شده است. مدل r.sun در نرم‌‌افزار Grass مدلی است که به محاسبۀ پرتو (مستقیم)، انتشار و بازتاب زمینی اشعه‌‌های خورشیدی با توجه به وضعیت روز، ارتفاع از سطح دریا، شرایط سطحی و اتمسفری می‌‌پردازد. در این مطالعه میزان دریافت انرژی خورشیدی منطقه با این مدل محاسبه شد. بر اساس نتایج، بخش‌‌های شمالی و شمال‌‌شرقی استان اصفهان بیشترین ساعت آفتابی را دارند. زاویۀ تابش خورشیدی در منطقه بیشتر در زاویۀ 45 و 22 درجه است و بالاترین ایرادینس بازتابی برابر با 1194 و کمترین آن 40 وات بر متر مربع محاسبه شد. نتایج این مطالعه از مهم‌ترین معیارها در جهت شناخت پتانسیل منطقه به منظور برنامهریزی برای استفاده از انرژی خورشیدی به شمار می‌رود. بالابودن میزان دریافت انرژی خورشیدی با توجه به توپوگرافی و وضعیت قرارگیری خورشید موجب افزایش پتانسیل ذاتی استان اصفهان برای توسعۀ نیروگاه‌‌های خورشیدی و استقرار صفحه‌‌های خورشیدی برای بهره‌‌گیری از انرژی خورشید است. | ||
| کلیدواژه‌ها | ||
| انرژی تجدیدپذیر؛ انرژی خورشیدی؛ مدل r.sun؛ نیروگاه خورشیدی | ||
| عنوان مقاله [English] | ||
| R.sun evaluation model in estimating the amount of solar energy received in arid and semi-arid (Case study: Isfahan province, Iran) | ||
| نویسندگان [English] | ||
| Mahmood Zoghi1؛ Mahdis Sadat2؛ Amir Houshang Ehsani3 | ||
| 1M. Sc. of environmental Planning and Management. University of Tehran /Faculty of Environment | ||
| 22Management. University of Tehran /Faculty of Environment | ||
| 3Associate professor of Environmental Design Engineering, University of Tehran, Faculty of Environment | ||
| چکیده [English] | ||
| Introduction: The erroneous move towards the modern lifestyles has led to uncontrolled population growth, urbanization, disorderly expansion of cities to natural habitats and ecosystems, destruction of traditional rural communities and farm lands, indiscriminate utilization and destruction of natural resources, growth of air pollution and environment in large cities. On the other hand, the problems of environmental pollutions and exhaustion of energy resources have long been considered as one of the main issues of societies and the utilization of clean and natural solar energy has been introduced as a substantial approach to resolve this issue. Today, one of the important aspects of sustainable development is environmental considerations of which the appropriate use of energy sources is a significant part. It is clear that offering energy consumption patterns and higher utilization of renewable resources can be useful in this regard. As defined, sustainable development of energy includes policies, selection and exploitation of technologies which supply the energy needed for all demands while they contain the minimum expenses in terms of price, environmental and social impacts. Today, the role of energy in world economy indicates the significance of the energy issue more than ever before. In this regard, development and expansion of theories and uses of energy leads to the attainment of new methods for adjusting the issues of energy and environment. The amount of solar energy intake at one point on the earth’s surface depends on various factors including: latitude, longitude, the sundial, humidity, evaporation, air temperature, angle of the sun, and other factors. The amount of solar radiation received by the top of the atmosphere is a function of latitude. After reaching the earth’s atmosphere, some of these solar radiations would be destroyed due to the atmospheric diffusion and absorption phenomena and this amount would increase when the sky is cloudy or when there are more particles in the air. Knowing the amount of solar radiation in each area has a great significance for many practical issues such as evaporation, transpiration, architectural design, agricultural crop growth models, etc. However, despite the importance of measuring these parameters, due to economical problems, the right tools and equipment for measuring radiation are not available in all regions, as is the case with other meteorological parameters such as temperature and rain and it has to be somehow estimated. Consequently, the need for the researchers’ inclination to utilizing radiation models has increased. This study is an endeavor to model and calculate the amount of solar energy intake in Isfahan Province by using the new research approaches based on the r.sun model. Isfahan province is located between latitudes 30° 43´ to 34° 27´ North and longitudes 49° 36´ to 55° 31´ East and covers an area of 107017 square kilometers, equivalent to 0.5% of the total Iran country territory by having 23 cities, 106 towns and 126 villages. Because of the number of major industrial workshop and industries and industrial estates, Esfahan is one of the most important industrial centers in Iran. All factors above have caused high consumption for electricity power in this province. This province is one of the arid and semi-arid regions of the country generally in term of climate. Material and Methods: In this study, the GRASS geographic information system, or GIS was applied for modeling solar radiation, taking into consideration the diversity of different modeling algorithms. To this end, the r.sun rule as one of the location models of solar energy was used and analyzed. R.sun computes beam (direct), diffuse and ground reflected solar irradiation raster maps for given day, latitude, surface and atmospheric conditions. Solar parameters (e.g. time of sunrise and sunset, declination, extraterrestrial irradiance, daylight length) are stored in the resultant maps' history files. Alternatively, the local time can be specified to compute solar incidence angle and/or irradiance raster maps. The shadowing effect of the topography is optionally incorporated. This can be done either by calculating the shadowing effect directly from the digital elevation model or using rasters of the horizon height which is much faster. The solar geometry of the model is based on the works of Krcho, later improved by Jenco. The equations describing Sun – Earth position as well as an interaction of the solar radiation with atmosphere were originally based on the formulas suggested by Kitler and Mikler. This component was considerably updated by the results and suggestions of the working group co-ordinated by Scharmer and Greif (this algorithm might be replaced by SOLPOS algorithm-library included in GRASS within r.sunmask command). The model computes all three components of global radiation (beam, diffuse and reflected) for the clear sky conditions, i.e. not taking into consideration the spatial and temporal variation of clouds. The extent and spatial resolution of the modelled area, as well as integration over time, are limited only by the memory and data storage resources. The model is built to fulfil user needs in various fields of science (hydrology, climatology, ecology and environmental sciences, photovoltaic, engineering, etc.) for continental, regional up to the landscape scales. As an option the model considers a shadowing effect of the local topography. The r.sun program works in two modes. In the first mode it calculates for the set local time a solar incidence angle [degrees] and solar irradiance values [W.m-2]. In the second mode daily sums of solar radiation [Wh.m-2.day-1] are computed within a set day. By a scripting the two modes can be used separately or in a combination to provide estimates for any desired time interval. The model accounts for sky obstruction by local relief features. Several solar parameters are saved in the resultant maps' history files, which may be viewed with the r.info command. Discussion and Results: According to the outcomes, northern and north-eastern parts of the province and the southern parts as well, contain the most sundials; the north-eastern parts also have the least sundials. Maximum hour of receiving sunshine in the province is 3392 hours and the least is 2918 hours (Fig 1). The analyses obtained from modeling also confirm the high potential of the region in receiving solar energy. Isfahan province naturally possesses a great potential and good share in receiving solar energy since it is mainly situated in the angle between 46 and 67 degrees (Fig 2). The highest reflection irradiance of Isfahan province is assessed as 1194 and the lowest is 40 watts per square meter (Fig 3). Most of Isfahan’s zones have the average level and receive an amount between 600 and 1000 watts per square meter. The important point in this research is that highlands, i.e. mountain peaks have the most irradiance. Namely, 90 degree angles receive the irradiance higher than 1000 watts per square meter. Generally speaking, the region’s condition in terms of receiving solar energy can be assessed as adequate. Based on the results, the number of sunshine hours is with a gentle slope that represents the damping of the area sundial. The area is in a balanced state in term of mean radiation. Irradiance reflection map from the surface shows that observed fluctuations are variant due to topographic lines and area altitude; and the higher the altitude the more slope with a larger number. Moreover, radiance angle has constant changes that are directly associated with total solar irradiance changes. Generally, the area situation can be assessed as suitable for investments and the utilization of energy in terms of most solar energy parameters and its received energy. Conclusion: Solar energy is an essential parameter in various models related to energy in industries, landscaping, vegetation, evaporation and transpiration, snowmelt, and or remote sensing. Maps of solar radiation angles can be useful in correcting radiometric and topography of mountainous and hilly regions. Moreover, the outcomes of this study can be cited as one of the most significant criteria of the region’s potential to organize and plan the utilization of solar energy. All in all, the innate potential of the region has made Isfahan province capable of developing solar power plants and establishing solar panels in order to exploit solar energy. In addition, to improve the researches in this field, we propose further study on energy zoning and locating potential zones for establishing solar power plants in the province, such that we can see the sustainable development of energy in the region and utilization of clean and renewable solar energies. | ||
| کلیدواژه‌ها [English] | ||
| renewable energy, r.sun model, Solar Energy, Solar Power | ||
| مراجع | ||
|
حسینی‌شکرایی، ح. س.، عبدلی، م. ع.، گیتی‌پور، س.، دهقانی، ع. 1388. اثرات کاربرد سیستم‌های انرژی خورشیدی در مصرف انرژی و آلاینده‌های محیط‌زیست (مطالعۀ موردی: شهر تهران)، پایان‌نامۀ کارشناسی ارشد، دانشکدۀ محیط‌زیست، دانشگاه تهران. خلیلی، ع.، اسحاق‌مرادی، غ. 1381. مقایسۀ مدلهای مختلف برآورد تابش مستقیم خورشید بر روی سطوح شیب‌دار، دومین همایش بهینه‌سازی مصرف سوخت در ساختمان، تهران، ایران. خلیلی، ع. 1376. برآورد تابش خورشید در گسترۀ ایران بر مبنای داده‌های اقلیمی، تحقیقات جغرافیایی، شمارۀ 46، صص 27- 34. ربانی‌فر، ع. 1386. اثرات اتلاف مصرف انرژی در تهران بر آلودگی محیط‌زیست، پایان‌نامۀ کارشناسی ارشد، دانشکدۀ محیط‌زیست. سلمان‌ماهینی، ع.، کامیاب، ح. 1390. سنجش از دور و سامانۀ اطلاعات جغرافیایی کاربردی با نرم‌‌افزار ایدریسی، ویرایش دوم، انتشارات مهر، تهران، 610 صفحه. سایت وزارت نیروی جمهوری اسلامی ایران. 1392. www.moe.gov.ir. صمیمی، ج. 1364. انرژی خورشید برای ایران، فیزیک، سال اول، شمارۀ 2، جلد سوم، صص 18- 30. علیزاده ا.، خلیلی، ن. 1388. تعیین ضرایب مدل آنگستروم و توسعۀ یک مدل رگرسیونی برآورد تابش خورشیدی (مطالعۀ موردی: منطقۀ مشهد)، علوم و صنایع کشاورزی (آب و خاک)، سال اول، شمارۀ 1، صص 229- 238. علوی‌‌پناه، ک. 1388. اصول سنجش از دور نوین و تصاویر ماهواره‌ای و عکس‌های هوایی، انتشارات دانشگاه تهران، تهران، 782 صفحه. کمالی، م.، مهاجرزاده، م.، معصومی، ر. 1389. اصول و معیارهای مکانی صنایع راهبردی، انتشارات مبنای خرد، تهران، 264 صفحه. کمالی، غ.، مرادی، ا. 1384. تابش خورشید- اصول کاربردها در کشاورزی و انرژی‌های نو، انتشارات پژوهشکدۀ هواشناسی، تهران، 300 صفحه. گزانه، ا.، بیگلری، م. 1393. ارزیابی ردیاب خورشیدی و زاویۀ بهینه برای سیستم‌های فتوولتائیک، دهمین همایش بین‌المللی انرژی، تهران، ایران. مرادی، ا. 1381. برآورد شدت تابش خورشیدی در سطوح شیب‌دار، پایان‌نامۀ کارشناسی ارشد هواشناسی کشاورزی، دانشگاه تهران. یزدان‌پناه، ح.، میرمجربیان، ر.، برقی، ح. 1389. برآورد تابش کلی خورشید در سطح افقی زمین در اصفهان، جغرافیا و برنامهریزی محیطی، سال بیست و یکم، شمارۀ 37، صص 95- 105. Alamdari, P., Nematollahi,O., and Alemrajabi, A. 2013. Solar energy potentials in iran, Renewable and Sustainable Energy Reviews, 21: 778-788.
Al-Ayed, MS., AI-Dhafiri, AM., and Bin Mahfoodh, M. 1998. Global, direct and diffuse solar Irradiance in Riyadh. Saudi Arabia, Renewable Energy, 14: 249–54.
Almorox, J., Benito, M., and Hontoria, C. 2005. Estimation of monthly Angstrom–Prescott equation coefficients from measured daily data in Toledo- Spain, Renewable Energy, 30: 931–936.
Bagheri, N., Moghaddam, S., Mousavi, M., Nasiri, M., Moallemi, EA, and Yousefdehi, H. 2011. Wind energy status of Iran: evaluating Iran’s technological capability in manufacturing wind turbines, Renewable & Sustainable Energy Reviews, 14:4200–4211.
Benghanem, M., and Joraid, A. 2007. A multiple correlation between different solar parameters in Medina. Saudi Arabia, Renewable Energy, 32: 2424–2435.
Bristow, m. 2003. On the relationship between incoming solar radiation and atmospheric parameters, Agri & for met. 31: 15-22.
Chegaar, M., and Chibani, A. 2001. Global solar radiation estimation in Algeria, Energy Conversion and Management, 42: 967–73.
Dincer, I., Midili, A., and Kuchuk, H. 2014. Covers new technologies, strategic solution and engineering applications related to the generation of sustainable energy, Springer, 0-745.
ECJRC, 2007, European Commission Joint Research Center, http://re.jrc.ec.europa.eu/pvgis/index.htm.
Iziomon, M.G., and Mayer, H. 2002. Assessment of some global solar radiation parameterizations, Journal of Atmospheric and Solar-Terrestrial Physics, 64: 1631–1643.
Jacovides, CP., Tymviosa, FS, Assimakopoulosc, VD. And Kaltsounidesa, NA. 2006. Comparative study of various correlations in estimating hourly diffuse fraction of global solar radiation, Renewable Energy, 31: 2492- 2504.
José, Á., Mitasova, H. and Lee Allen1, H. 2011. chilean journal of agricultural research 71(4): 601-609.
Louis, E., and Sunday, E. 2003. Relationship between Global solar radiation & sunshine duration for onne, Nigeria, Turkish Journal of Physics, 27: 161- 167.
Lopez, G., Rubio M.A., and Batlles, F.J. 2000. Estimation of hourly direct normal from measured global solar irradiance in Spain, Renewable Energy, 21: 175-186.
Matgorzata, P., Pawet, N, 2011, the method of assessment of solar potential for selected area with use Geographical Information Systems, 2nd European Energy Conference, 33: 8.
Miller, G.t.j. 2002. Sustaining the earth, an integrated approach, Cole, Thomson learning.
Nguyen, H.T., Pearce, J.M. 2010. Estimating Potential Photovoltaic Yield with r.sun and the Open Source Geographical Resources Analysis Support System” Solar Energy, 84: pp. 831-843.
Rehman, S. 1998. Solar radiation over Saudi Arabia and comparisons with empirical models. Energy, 23: 1077–1082.
Rivingtom, M., Bellocchi, G., Matthews, K.B., and Buchan, K. 2005. Evaluation of three model estimations of solar radiation at 24 UK statron, agri & for met, Agricultural and Forest Meteorology, 132: 228- 243.
Sailor, D. 1994. Simulated urban climate response modifications in surface albedo and vegetative cover, Journal of applied meteorology, 34: 1694-1705.
Sorapipatana, C. 2010. An assessment of solar energy potential in Kampuchea, Renewable & Sustainable Energy Reviews, 14: 2174–2178.
Sozne, A. 2005. Solar energy potential in Turkey, Applied Energy, 80: 367-381.
Sabziparavar, A., and Shetaee, H. 2007. Estimation of global solar radiation in arid and Semi-arid climates of east and west Iran, Energy, 32: 649–655.
Tester, J. W., Drake, E. M., Driscoll, M. J., Golay, M. W., and Peters, W. A. 2012. Sustainable energy; choosing among options, The MIT Press, 2:1056.
Wohlegemuth, N., and Missfelhlt,F. 2000. The Kyoto mechanisms and the prospects of renewable energy technologies, Solar Energy, 69: 305-314.
WEC, World energy council. 1992. New Renewable Energy Resources, a Guide to the Future, Clays, WEC, London. | ||
|
آمار تعداد مشاهده مقاله: 14,308 تعداد دریافت فایل اصل مقاله: 1,653 |
||