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This paper presents a novel power flow management algorithm for remote microgrids based on artificial intelligence (AI) algorithms. The objectives of this power management system are enhancing microgrid reliability, improving renewable energy source (RES) integration, and performing active/reactive power control for remote microgrids using the fuzzy logic. This paper evaluates the performance of the proposed algorithm, which consists of both sharing diesel genset active power and regulating reactive power by using stepped and variable profiles of the load, wind speed and solar irradiation. According to the simulation results, better performance is achieved regardless of the rapid variation of different profiles. Thus, both stability and reliability of remote microgrids are demonstrated with the proposed algorithm. Indeed, the active/reactive power control algorithm responds quickly to different events on the remote microgrid, especially to rapid voltage/frequency variations on the AC-link system.

This chapter deals with a comprehensive overview study of the direct‐driven (DD) permanent magnet synchronous generator (PMSG) for wind‐energy generation system for stand‐alone applications. The dynamic model of PMSG is presented, and different maximum power point tracking (MPPT) algorithms have been realized in the aim to compare their performance. A comparison of performances of the conventional P&O MPPT and the fuzzy logic P&O (FLC P&O) MPPT is presented. Control technique for the presented system is presented and analyzed for the generator side converter. The simulation results carried out using Matlab/Simulink software show the effectiveness of the wind turbine control system.