Ramiz Gorkem Birdal^*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4015-4028, 2024, DOI:10.32604/cmc.2024.048324

Abstract Maintaining a steady power supply requires accurate forecasting of solar irradiance, since clean energy resources do not provide steady power. The existing forecasting studies have examined the limited effects of weather conditions on solar radiation such as temperature and precipitation utilizing convolutional neural network (CNN), but no comprehensive study has been conducted on concentrations of air pollutants along with weather conditions. This paper proposes a hybrid approach based on deep learning, expanding the feature set by adding new air pollution concentrations, and ranking these features to select and reduce their size to improve efficiency. In order to improve the accuracy… More >

P. Rajesh^1,*, K. S. Saji²

Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1531-1545, 2022, DOI:10.32604/iasc.2022.023331

Abstract Electricity can be generated from a photovoltaic cell depending on the amount of solar radiation received from the solar system. But due to some factors such as partial shade conditions, as the thickness of the shade increases, the peak power output from the solar photovoltaic system decreases. Photovoltaic cells can be connected in parallel and in series to generate the required voltage and power. Peak power can be obtained even under shade conditions using the appropriate configuration of solar cells. A novel configuration as Total Cross Tied-Inverted Triangle View (TCT-ITV) is developed in the research by augmenting the Total Cross… More >