Determination of Solar Chimney Inlet Temperature by Regression Methods

Abstract

Abstract Because the greenhouse gases caused by fossil fuels contribute to global warming, the orientation toward renewable energy sources is increasing rapidly. One of these sources is solar chimneys. The region where a solar chimney is installed is important for its efficiency, and if the energy to be produced from the solar chimney can be determined, comments can be made about the region where it will be installed. In determining the energy to be produced from a solar chimney, the chimney inlet temperature must be known. In this study, it is planned to make an application on a solar chimney in Isparta province. First, a prototype solar chimney was installed on the campus of Süleyman Demirel University (SDU) by the SDU Renewable Energy Resources Research and Application Center. A unique data set was created with input data from sensors in the collector area of the solar chimney and output data from a sensor located at the mouth of the chimney. In this study, the flue inlet temperature values were estimated by using 10 different regression methods, one of which was a model specific to this study. In addition, hyperparameter adjustments of the regression models were made with different optimization methods. With Random Forest- Elastic-Lasso.Net (REL.Net) and ElasticNet architecture among the 10 methods, the chimney inlet temperature was obtained with accuracy rate of approximately 99 %.