This dissertation presents a passivity-based control (PBC) scheme for the Switched Reluctance Generator (SRG) in small-scale wind energy conversion systems (WECSs) for DC microgrid application. The main objective is to stabilize the output voltage in case the system supplies constant power loads (CPLs) and operates with maximum power point tracking (MPPT). Stability improvement and dc-link ripple reduction in the presence of CPLs is achieved using system level modeling of SRG-based DC microgrid through the Euler-Lagrange system (ELS) from the view point of the machine physical structure. Compared with other control methods, the proposed MPPT method based on passivity-based speed controller employs the back-EMF in the generation process as a position-dependent voltage source to overcome the major challenge of SRG complicated uncertain dynamic model. To deal with the time-varying inductance and back-emf of SRG, an adaptation mechanism is incorporated in proposed adaptive PBC and the control design is constructed by using the Lyapunov theorem where the closed-loop stability is ensured. To maximize the recovered energy during battery charging the proposed algorithm employs the maximum power recovery (MPR) process. The proposed MPR operation is first based on the maximization of the extracted power from the machine and then the maximization of the power transferred to the battery. The maximum power extraction (MPE) from SRG is based on maximizing the energy conversion ratio by the calculation of the optimum turn-on, and turn-off angles. By using the impedance matching theorem that allows the maximum power transfer (MPT) of the MPE, the proposed MPR is achieved. The parametric averaged value modeling of the machine phase currents in the chopping control mode is used for MPR realization. By following this model, a nonlinear equivalent input resistance is derived for the battery internal resistance matching. The effectiveness of the proposed method in avoiding instability effects of SRG and CPL with voltage ripple reduction and precise wind turbine speed tracking is investigated with simulation results and validated with experimental by using a four-phase, 8/6 SRG drive system.
