Developing a Photovoltaic (PV) Wind Battery-Based Direct Current (DC) Microgrid with Neural Network Maximum Power Point Tracking (MPPT) in MATLAB involves creating a comprehensive simulation model. This model integrates PV panels, wind turbines, batteries, DC loads, and a neural network-based MPPT algorithm.
The simulation enables the analysis of various parameters such as solar irradiance, wind speed, battery state of charge, DC load demand, and neural network performance. Engineers can evaluate the effectiveness of the neural network MPPT algorithm in maximizing power extraction from both PV and wind sources under varying environmental conditions.
Furthermore, they can optimize the operation of the microgrid to ensure reliable power supply to DC loads while minimizing reliance on the grid and maximizing renewable energy utilization. This approach facilitates the design and implementation of sustainable DC microgrids that harness the combined power of PV, wind, and battery storage, contributing to energy efficiency and environmental conservation.