امکان سنجی استفاده از انرژی تابشی خورشید با استفاده از سنجش از دور و الگوریتم سبال مطالعه موردی: شهرستان الشتر

استفاده از تصاویر ماهواره‌ای و مدل‌های سنجش از دور به عنوان ابزاری مناسب و کم‌هزینه برای تخمین تابش خورشیدی، در سال‌های اخیر مورد توجه محققین قرار گرفته است. در این پژوهش مقدار انرژی تابش خورشیدی رسیده به زمین با استفاده از داده‌های تصاویر ماهواره لندست و با بکارگیری الگوریتم سبال در شهرستان الشتر، در ماه‌های ژانویه تا نوامبر محاسبه شد. میانگین بیش‌ترین تابش موج کوتاه ورودی به مقدار 996 وات بر متر مربع در ماه ژوئن و کم‌ترین مقدار در ژانویه به میزان460 وات بر متر مربع محاسبه شد. هم‌چنین بیش‌ترین مقدار تابش خالص خورشیدی رسیده به سطح زمین در ماه سپتامبر به اندازه 602 وات بر متر مربع و کم‌ترین مقدار مربوط به ژانویه با 261 وات بر متر مربع بوده است. نتایج حاصل از این مطالعه بیانگر آن است که بیش‌ترین درصد تابش خالص در سپتامبر در دسته 800-600 وات بر متر مربع با مقدار 69.86 درصد و در ژانویه در دسته 600-400 وات بر مترمربع با مقدار60.12 درصد بوده است. با توجه به دامنه حساسیت سلول‌های فتوولتائیک به تابش و مقدار تابش خالص محاسبه شده در منطقه مورد مطالعه، می‌توان نتیجه گرفت که تابش خورشیدی در این منطقه، پتانسیل لازم برای اجرای طرح‌های فتوولتائیک خورشیدی را دارا می‌باشد.

The feasibility of utilizing solar energy using remote sensing and SEBAL algorithmCase study: Alshtar County

IntroductionThe sun is known as the source of energy, the origin of life, and the origin of all other energies. The global solar radiation is one of the fundamental structures of any climatic range. Hence, recognition of the features and the prediction of these basic structures have a great impact on energyrelated planning. One way to gainaccess to the solar energy information is the direct measurements of solar energy by measuring devices such as Pyranometer and Pyrheliometer Unfortunately, the measurement of the solar radiation is not always carried out in many parts due to the high cost, maintenance and the need for the equipment calibration. Remote sensing techniques ​​can be an appropriate alternative to the experimental and old methods in this field due to the high accuracy and speed in predicting the net radiation values. In general, remote sensing models have a better performance in estimating solar radiation, and can be used as one of the suitable and low cost tools for estimating solar radiation. Considering the importance of solar radiation as a clean, availableand free of any environmental destructive pollutants, identifying the radiation areas to be introduced to the relevant authorities is essential and the aim of the research. In this research, it was attempted to study the feasibility of utilizing solar energy in the region of Alashtar County using the SEBALalgorithm and remote sensing technology. Materials and MethodsTo investigate and study the feasibility of using solar radiation energy, the Landsat8 satellite images over a 12month period of the year 2017, 1: 50,000 digital topographic maps of the Armed Forces Geographic Organization and the climatic data of the study area including temperature, precipitation, wind speed and the number of sunny days were used. The ENVI software was used to perform the calculations related to SEBALmodel and the ArcGIS software was used to implement the model. In this study, the feasibility of using solar energy in Salsala city was studied using SEBALalgorithm and remote sensing technology. In this method, the instantaneous values of pure radiation are obtained by measuring the sun’s incident radiation from the cloudless images and using surface albedo, surface emission and surface temperature. In this method, instantaneous values of pure radiation are obtained by measuring the sun’s incident radiation from cloudless images using surface albedo, surface emission and surface temperature. After calculating the parameters of the SEBAL algorithm, the net surface radiation flux was calculated.Discussion and ResultsThe results showed that the average maximum shortwave radiation was 996 watts per square meter in June and the minimum was 460 watts per square meter in January, while the highest amount of net radiation in September was calculated to be 602 watts per square meter and the lowest amount in January was calculated to be 261 watts per square meter. Also, the highest percentages of net radiation distribution in the ranges of 0200, 200400, 400600, 600800 and 8001000 watts per square meter were in August, November, April, September and June. The highest percentage of net radiation distribution was in the range of 600800 watts per square meter with 69.86% of total net radiation in September and the lowest percentage was in the range of 800800 watts per square meter in January. ConclusionIn order to carry out the research, the Landsat 8 ETM satellite images for the 12 month period of the year 2017 were provided. But, since the images of February, March and December were completely cloudy, they were not used. Then the preprocessing operation in ENVI software was used on all bands of images. The amount of pure radiation in the study area was calculated in watts per square meter in January to November in ENVI software environment and by the utilization of SEBAL algorithm, using the prepared images (Table 2). The results of Table (2) show that the average maximum input shortwave radiation is 996 watts per square meter in June, the lowest amount input is 460 watts per square meter in January, the highest output long wave radiation is 539 watts per square meter in July and the lowest output is 391 watts per square meter in January. Finally, the highest amount of net radiation reaching the surface of the Earth was 602 watts per square meter in September and the lowest amount was 261 watts per square meter in January. The highest percentage of net radiation in the range of 600800 watts per square meter was 69.86% in September 2017 and the highest percentage of net radiation in the range of 600400 watts per square meter was 60.12% in January 2017.The difference in the amount of net radiation reaching the ground in the study area is due to the difference in the angle of the sunlight and the number of sunny hours in different months of the year.The results obtained from of the information in Tables 2 to 11 prove this fact. Also, given the sensitivity of the photovoltaic cells that are sensitive to the solar radiation from the radiation threshold of up to 1000 watts per square meter and receive them, it can be concluded that solar radiation in the city of Alshtar has the potential to implement the solar photovoltaic plans in 9 months of January to November.