پیش بینی شدت تابش خورشیدی در ایستگاه یزد با بکارگیری مدل رگرسیونی مبتنی بر مولفه های اصلی (PCR)

نوع مقاله : مقاله پژوهشی

نویسنده

دانشیار گروه علوم و مهندسی آب، دانشکده کشاورزی و منابع طبیعی دانشگاه اردکان

چکیده

تابش خورشیدی رسیده به سطح زمین یکی از مهم‌ترین متغیرهای مورد استفاده در پروژه‌های انرژی خورشیدی، مدل‌سازی هیدورولوژی، تبخیر و تعرق، هواشناسی و کشاورزی می‌باشد. در این تحقیق قابلیت عملکرد روش آنالیز مولفه‌های اصلی و رگرسیون چند متغیره خطی، در پیش‌بینی مقدار تابش خورشیدی در ایستگاه یزد در حد فاصل سال‌های 2010 تا 2014 و 2015 تا 2021 بررسی شد. متغیرهای میانگین دما، دمای کمینه، دمای بیشینه، ساعات آفتابی، رطوبت نسبی و تابش خورشیدی بصورت روزانه از سازمان هواشناسی دریافت و متغیرهای تابش فرازمینی، فاصله نسبی زمین تا خورشید، زاویه میل خورشیدی و حداکثر ساعات آفتابی با روابط موجود محاسبه و به عنوان ورودی روش آنالیز مولفه اصلی انتخاب شدند. همبستگی این پارامترها با مقدار تابش خورشیدی نشان از وجود رابطه معنی‌دار مثبت در سطح 1 درصد بین مقادیر تابش خورشیدی و تابش فرازمینی، نسبت ساعات آفتابی، دمای میانگین و فاصله نسبی زمین تا خورشید و با زاویه میل خورشیدی در سطح 5 درصد و همبستگی منفی معنی‌دار در سطح 1 درصد با مقادیر رطوبت نسبی دارد. نتایج حاصل از بررسی مولفه های اصلی نشان داد که می توان دو مولفه اول را با توجه به مقادیر ویژه حاصل از پارامترها و درصد واریانس، به عنوان مولفه اصلی انتخاب کرد. ضریب همبستگی مولفه‌های اول و دوم با تابش خورشیدی به ترتیب 893/0و 168/0- به دست آمد و در نتیجه مولفه اول نسبت به مولفه دوم با مقدار تابش خورشیدی همبستگی بیشتری دارد. مقدار دوران شده بارگذاری، در مولفه اول نشان می‌دهد که دمای کمینه، دمای بیشینه، میانگین دما و رطوبت نسبی با تابش خورشیدی همبستگی بیشتری دارند و همبستگی بقیه عوامل (تابش فرازمینی، زاویه میل خورشیدی و فاصله نسبی زمین تا خورشید و نسبت ساعات آفتابی) در این مولفه کم است. بررسی رابطه بین تابش خورشیدی و مقادیر مولفه‌های اصلی بدست آمده از PC1 و PC2 با استفاده از رگرسیون خطی چند متغیره نشان داد که اثر پارامترهای هواشناسی بر تابش خورشیدی معنی‌دار (001/0>p) و ضریب تبیین آن (R2) به میزان 89/0 درصد تعیین شد. معیارهای ارزیابی روش‌های PCR و MLR بیانگر توانائی روش PCA برای برآورد تابش خورشیدی است.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Prediction of solar radiation intensity in Yazd station by using regression model based on principal components (PCR)

نویسنده [English]

  • Somayeh Soltani-Gerdefaramarzi
Associated Professor, Department of Water Engineering and Sciences, Faculty of Agriculture and Natural Resources, Ardakan University
چکیده [English]

Solar radiation reaching the earth's surface is one of the most important variables used in solar energy projects, hydrological modeling, evaporation and transpiration, meteorology and agriculture. In this research, the functionality of principal component analysis and linear multivariate regression was investigated in predicting the amount of solar radiation in Yazd station between 2010 to 2014 and 2015 to 2021. Variables of average temperature, minimum temperature, maximum temperature, hours of sunshine, relative humidity and solar radiation are received from the Meteorological Organization on a daily basis and variables of extraterrestrial solar radiation, relative distance from the earth to the sun, solar inclination angle and maximum hours of sunshine are calculated with the existing relations and was chosen as input of Principal component analysis method. The correlation of these parameters with the amount of solar radiation shows the presence of a significant positive relationship at the level of 1% between the amount of solar radiation and extraterrestrial radiation, the ratio of sunny hours, the average temperature and the relative distance from the earth to the sun, and with the solar inclination angle at the level of 5% and was observed a significant negative correlation at the level of 1% with relative humidity values. The results of the analysis of the main components showed that the first two components can be selected as the main components according to the eigenvalues of the parameters and the percentage of variance. The correlation coefficient of the first and second components with solar radiation was 0.893 and -0.168, respectively, and as a result, the first component has a higher correlation with the amount of solar radiation than the second component. The rotated value of loading in the first component shows that the minimum temperature, maximum temperature, average temperature and relative humidity are more correlated with solar radiation and the correlation of other factors (extraterrestrial radiation, solar inclination angle and relative distance from the earth to the sun and the ratio of sunny hours) is low in this component. Investigating the relationship between solar radiation and the values of the main components obtained from PC1 and PC2 using multivariate linear regression showed that the effect of meteorological parameters on solar radiation is significant (p < 0.001) and its R2 is was determined as 0.89%. The evaluation criteria of PCR and MLR methods show the ability of PCA method to estimate solar radiation.

کلیدواژه‌ها [English]

  • Multivariate regression
  • Principal components analysis
  • Solar radiation
  • VIF.Yazd
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