Research Information System
International Conference on Modern Practices and Trends in Expert Applications and Security, MP-TEAS 2024, Bhopal, India, 22 - 24 November 2024, vol.1378 LNNS, pp.285-294, (Full Text)
Conventional energy resources play a significant role in energy requirements but show various harmful effect to the environment, including air and water pollution. These resources are reducing due to their limited existence in the universe. As a result, the need of searching for novel energy resources of everlasting nature is highly in demand. So, the renewable power resources have arisen as they present a sustainable feature of energy needs in future. Researchers have found the various energy resources of everlasting nature, including thermal, tidal, wind, and solar, which can be adopted as energy alternative for long-lasting use due to their ability of endless energy production. With the capacity of producing energy, wind and solar seem to be the most existing resources as they have most places for their harvesting. Additionally, the solar energy is the most effective advantages due to its existence globally. As a result, the extracting of solar energy with the ability of harvesting with maximum accuracy comes into existence and becomes operational due to numerous maximum power point tracking (MPPT) method. In our research, we perform the optimization of power extraction with scaled conjugate gradient (SCG) method which train an artificial neural network (ANN) in varying environmental situations. The evolution of solar panel capacity has been directed for MPPT. Simulation based on MATLAB/Simulink has been made for presenting the validation of the method for MPPT. The results show that the SCG algorithm discover its presence for MPPT feature in solar PV generation system.