Intelligence Based Controlling Models for Effective Power Tracking and Voltage Enhancement in Grid-PV Systems

The underlying research work is focused on enhancement in the efficiency and voltage gain for solar PV systems with the help of designing a novel regulating framework that includes advanced converter topologies integrated with intelligent control techniques. Optimization in extracting energy from the solar panel at different climatic conditions, voltage gain with minimum losses, and enhancing overall system efficiency and power quality are major tasks to be undertaken. The proposed control architecture presents a new Fractional Order Proportional-Integral-Derivative Control (FOPTC) technique and its adaptation mechanism for correct MPPT under dynamic variations of meteorological conditions. Consequently, it offers improved energy harvesting because it is able to identify the global maximum power point with higher speed and precision than traditional control techniques that apply hybrid approaches. The improved topological structure will ensure a substantial rise in voltage gain and efficiency with reduced voltage and current stresses upon the circuit components. In addition, the idea of a Neuro Feed Quadratic Controller (NFQC) is introduced to generate the regulating pulses for switching components of the converter for optimizing the voltage conversion process. Simulation and analytical studies confirm the higher efficiency, improved voltage gain, and reduced total harmonic distortion in the proposed framework over conventional systems. Doi: 10.28991/ESJ-2025-09-01-015 Full Text: PDF