Application of support vector regression integrated with firefly optimization algorithm for predicting global solar radiation

Abstract

A fundamental factor for proficient designing of solar energy systems is providing precise estimations of the solar radiation. Global solar radiation (GSR) is a vital parameter for designing and operating solar energy systems. Because records of GSR are not available in many places, especially in developing countries, this research aims to model the GSR using support vector regression (SVR) in a hybrid manner that is integrated with the firefly Optimization algorithm (SVR-FFA). For this purpose, the daily meteorological parameters and GSR measured from beginning of 2011 to the end of 2013 at Tabriz synoptic station were utilized. For assessing the performance of the mentioned methods, different statistical indicators were implemented. For all of the defined predictive models with different combinations of meteorological parameters, the performance of the SVR-FFA hybrid model is better than the classical SVR, evidenced by the higher value of R (~0892-0.982 relative to ~0.891-0.977) and lower values of RMSE and MAE (~1.551-3.725vs.1.748-4.067 and ~0.911-2.862vs.1.103-2.742). As a remarkable point studied empirical equations had higher prediction errors comparing with the developed SVR-FFA models. Conclusively, the obtained results proved the high proficiencies of SVR-FFA method for predicting global solar radiation.

Effect of position of heat flux profile on the absorber surface of parabolic trough solar collector for direct steam generation

“…Solar energy could be considered as the most promising renewable energy source and have the potential to replace fossil fuels used in conventional thermal power plants [1,2]. Most of the existing commercial PTSC power plants uses synthetic oil as heat transfer fluid (HTF) [3,4].…”

Estimation of the switching losses in DC-DC boost converters by various machine learning methods

“…In the study of Eroglu and Seckinler [10], an ANN-based application was developed to estimate early fault of a wind turbine. In another study [11], the value of Global Solar Radiation (GSR), a vital parameter for the design and operation of solar systems, was estimated. For this purpose, Support Vector Regression (SVR) and e Firefly Optimization Algorithm (FFA) algorithms were used as hybrid.…”