ANN-Based Design of a Hybrid Renewable Energy System for Hybrid Electric Vehicle Applications - Babu Jarapala Ramesh; Murty M.V.D.S. Krishna; Rajashekar Deva; Susheela N. (E3S Web of Conferences, 2025)
This article examines energy management strategies for hybrid power systems, leveraging an Artificial Neural Network (ANN) to optimize power flow based on real-time needs. The ANN controller ensures maximum power point tracking (MPPT) from renewable sources like photovoltaics (PV), wind turbines (WTs), and fuel cells (FCs), utilizing DC-DC converters. By regulating power flow and dampening fluctuations, the ANN-based method is tested on hybrid setups with PV panels, WTs, and FCs. Simulations in MATLAB/Simulink show that ANN outperforms Fuzzy Logic in MPPT efficiency, particularly for standalone and grid applications at variable loads, enhancing renewable energy reliability.