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An Innovative Metaheuristic Strategy for Solar Energy Management through a Neural Networks Framework

doi: 10.3390/en14041196
handle: 11250/2832135
Proper management of solar energy as an effective renewable source is of high importance toward sustainable energy harvesting. This paper offers a novel sophisticated method for predicting solar irradiance (SIr) from environmental conditions. To this end, an efficient metaheuristic technique, namely electromagnetic field optimization (EFO), is employed for optimizing a neural network. This algorithm quickly mines a publicly available dataset for nonlinearly tuning the network parameters. To suggest an optimal configuration, five influential parameters of the EFO are optimized by an extensive trial and error practice. Analyzing the results showed that the proposed model can learn the SIr pattern and predict it for unseen conditions with high accuracy. Furthermore, it provided about 10% and 16% higher accuracy compared to two benchmark optimizers, namely shuffled complex evolution and shuffled frog leaping algorithm. Hence, the EFO-supervised neural network can be a promising tool for the early prediction of SIr in practice. The findings of this research may shed light on the use of advanced intelligent models for efficient energy development.
- Oxford Brookes University United Kingdom
- TU Dresden Germany
- Óbuda University Hungary
- Norwegian University of Life Sciences Norway
- Duy Tan University Viet Nam
Technology, machine learning, T, solar power, electrical power modeling, solar energy, solar irradiance; solar energy; solar power; electrical power modeling; metaheuristic; machine learning; artificial neural networks; artificial intelligence; big data; deep learning; photovoltaic, solar irradiance, metaheuristic
Technology, machine learning, T, solar power, electrical power modeling, solar energy, solar irradiance; solar energy; solar power; electrical power modeling; metaheuristic; machine learning; artificial neural networks; artificial intelligence; big data; deep learning; photovoltaic, solar irradiance, metaheuristic
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