Estimating solar irradiance using genetic programming technique and meteorological records

نویسندگان

  • Rami Al-Hajj
  • Ali Assi
چکیده

Solar irradiance is one of the most important parameters that need to be estimated and modeled before engaging in any solar energy project. This article describes a non-linear regression model based on genetic programming technique for estimating solar irradiance in a specific region in the United Arab Emirates. The genetic programming is an evolutionary computing technique that enables automatic search for complex solutions. The best nonlinear modeling function that can estimate the global solar radiation on horizontal will be developed taking into account measured meteorological data. A reference approach to model the solar radiation is first presented. An enhanced approach is then presented which consists of multi nonlinear functions of regression in a parallel structure where each function is designed to estimate the global solar irradiance in a specific seasonal period of the year. Statistical analysis measures have been used to evaluate the performance of the proposed approaches. The obtained results are comparable with the outcomes of models developed by other researchers in the field.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Estimation of Global Solar Irradiance Using a Novel combination of Ant Colony Optimization and Empirical Models

In this paper, a novel approach for the estimation of global solar irradiance is proposed based on a combination of empirical correlation and ant colony optimization. Empirical correlation has been used to estimate monthly average of daily global solar irradiance on a horizontal surface. The Ant Colony Optimization (ACO) algorithm has been applied as a swarm-intelligence technique to tune the c...

متن کامل

Estimating and modeling monthly mean daily global solar radiation on horizontal surfaces using artificial neural networks

In this study, an artificial neural network based model for prediction of solar energy potential in Kerman province in Iran has been developed. Meteorological data of 12 cities for period of 17 years (1997–2013) and solar radiation for five cities around and inside Kerman province from the Iranian Meteorological Office data center were used for the training and testing the network. Meteorologic...

متن کامل

Assessing Experimental and Intelligent Models in Estimating Reference Evapotranspiration

Introduction: As the most important element in the hydrologic cycle which depends on climate variables such as near-ground wind speed, air temperature, solar radiation, and relative humidity,  reference evapotranspiration (ET0) is normally computed through a variety of methods, each of which requires different and in some cases extensive data that are unavailable in many circumstances, especial...

متن کامل

Scenario based technique applied to photovoltaic sources uncertainty

There is an increasing need to forecast power generated by photovoltaic sources in day-ahead power system operation. The electrical energy generated by these renewable sources is an uncertain variable and depends on solar irradiance, which is out of control and depends on climate conditions. The stochastic programming based on various scenarios is an efficient way to deal with such uncertaintie...

متن کامل

Energetic particle forcing of the Northern Hemisphere winter stratosphere: comparison to solar irradiance forcing

*Correspondence: Annika Seppälä, Earth Observation, Finnish Meteorological Institute, Erik Palmenin Aukio 1, FI-00560 Helsinki, Finland e-mail: [email protected] Variation in solar irradiance is considered an important factor in natural climate forcing. Variations in the solar UV in particular are now regarded as a major source of decadal variability in the stratosphere, influencing surface...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2017