This paper presents an effective hybrid renewable energy system. This system utilizes primary energy sources represented by both photovoltaic (PV) and wind energy conversion system (WECS). In addition, integrating the battery energy storage system (BESS), the hydrogen energy storage system (HESS), and the supercapacitor energy storage system (SESS), as backup sources which providing reliable simultaneous power supply and loading. A new design for a wind energy conversion system based on a hybrid excitation permanent magnet synchronous generator (HEPMSG) is proposed, and then artificial intelligence strategies are utilized to determine the optimal flow of energy when the system is operating immediately. Moreover, new hybrid maximum power point tracking (MPPT) techniques have been proposed including zebra optimization algorithm (ZOA)-ANFIS-based MPPT and gorilla troops optimizer (GTO)-ANFIS-based MPPT to obtain the maximum power of solar panels and wind turbines, which leads to enhancing the performance of these energy sources. The implemented power flow management (PFM) model is designed by MATLAB/Simulink, considering three various operating cases to evaluate the performance and effectiveness of various backup system configurations under different operating scenarios. According to the results, power can be generated, and load requirements can be efficiently met by applying the proposed PFM strategy, and this leads to the system operating at optimal performance. When comparing two optimization techniques, it will become clear that both give robust performance, but ZOA technique significantly outperforms the GTO technique in the computation time (26.17 % reduction) for the photovoltaic system. On the other hand, in the case of the wind energy conversion system, the ZOA technique achieves a significant reduction in calculation time by 35.5 %. The ZOA technique achieves computation times of 1616.80 s and 672.43 s for the photovoltaic and wind energy conversion system, respectively.