پیش‌بینی مقدار تشعشع خورشیدی با کمک داده‌های مرسوم هواشناسی برای شهرستان مشهد

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانشجوی دکترای مکانیزاسیون کشاورزی دانشگاه تهران

2 هیئت علمی پردیس کشاورزی و منابع طبیعی دانشگاه تهران

چکیده

با توجه به افزایش جمعیت جهان طی قرن اخیر، نیاز به خوراک و انرژی بیشتر شده است. تأمین انرژی مورد نیاز از مهم‌ترین دغدغه‌های کشورها می­باشد. استفاده از منابع تجدیدپذیر انرژی در دستور کار بسیاری از کشورها قرار گرفته است زیرا منابع فسیلی علاوه بر این که رو به اتمام هستند، باعث آلودگی محیط زیست و انتشار گازهای گلخانه­ای می‌شوند. یکی از مهم­ترین منابع انرژی تجدیدپذیر، خورشید است. برای تخمین میزان تشعشع قابل دریافت از روی داده‌های هواشناسی در مشهد با کمک شبکۀ عصبی مصنوعی، تحقیقی صورت پذیرفت. نتایج نشان دادند شبکۀ عصبی مصنوعی با شش متغیر ورودی شامل دمای میانگین، رطوبت، ساعات آفتابی، تابش خارج از جو، شمارۀ روز سال و درجه حرارت خشک، با دو لایۀ پنهان 37 و 18 نرون، توانست با دقت مناسبی میزان تشعشع را تخمین بزند. مقادیر R، MAE، MSE و RMSE برای مدل مذکور به ترتیب 9533/0، 4391/1، 1790/4 و 0443/2 به­دست آمد. بنابراین در مشهد و نیز مناطقی مشابه با اقلیم مشهد که امکان ثبت تشعشع وجود ندارد، می­توان از داده­های مرسوم هواشناسی به قرار ذکر شده، برای تخمین میزان تشعشع با دقت بالا استفاده کرد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Estimating Solar Radiation with Ordinary Meteorological Data in Mashhad

نویسندگان [English]

  • Hanifreza Motamed Shariati 1
  • Hosein Mobli 2
  • Mohammad Sharifi 2
  • Hojjat Ahmadi 2
چکیده [English]

One of the most main head in governments is to achieve the energy for their countries. As the fossil sources are at their ends and also they cause greenhouse emission and environment pollution, shifting to renewable sources of energy is an indispensable alternative for most countries. The sun is the most important renewable energy source. To assessment reachable solar radiation in Mashhad from the ordinary meteorological data via Artificial Neural Network (ANN), a survey has been conducted. Results showed that the ANN with six variable inputs as daily mean temperature, daily relative humidity, daily sunshine duration, daily extraterrestrial radiation, number of day in the year and daily dry temperature, with two hidden layer included 37 and 18 neurons respectively, had a good estimation with a high accuracy for solar radiation. Measured R, MAE, MSE and RMSE were 0.9533, 1.4391, 4.1790 and 2.0443, respectively. Therefore in Mashhad and also the regions with similar climate to Mashhad, that there is no opportunity to submit the solar radiation data, we can use ordinary meteorological data, as mentioned above, to estimate the solar radiation with a high and acceptable accuracy.

کلیدواژه‌ها [English]

  • renewable energy
  • Estimating
  • Solar radiation
  • ordinary meteorological data
  • Artificial Neural Network

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