Demonstrates improved energy efficiency using ANN optimized converters in locomotives, suggesting advancements in solar energy applications.
In the proposed paper, a novel ANN optimized converter has been projected for running the solar trains. With the rise in plea for making power with conventional energy resources, the storing of energy and connection of the energy storing element with the grid and for off grid are the major tasks encountered now a days. Storing of energy with battery is utmost appropriate method for the conventional energy resources alike solar, wind etc. A bi-directional DC-DC converter provides the two directional power flow for battery charging and discharging. The duty cycle of the converter regulates the charging and discharging which is founded on the charge of the battery and route of the current. Here a new two-directional DC-DC converter is premeditated that will extract the energy from the sun in the day time and later when sun is unavailable the charged batteries will supply the energy to the load with the help of converter in Boost Mode. For the efficient working of the PV Cell MPPT is determined with different algorithms and is tested with different ANN architectures. ANN based controller works with maximum efficiency when MPP is determined and after that the controller works in two modes i.e. Down Mode and Up Mode The earlier one needs extreme of ANN limits for making, training and initiating the ANN based system while the other mode of operation requires ANN based Controller that can be placed in PV system operations. Derivatives of output power and voltage which are obtained from the PV cell are the inputs to the ANN system when solar isolations and environmental temperatures are given inputs to the PV Panel. The projected ANN optimized converter is tested using MATLAB/Simulink model with a case study of locomotives is demonstrated here.
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Malik et al. (2021) studied this question.
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