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In this paper, the application of an Adaptive Network-based Fuzzy Inference System (ANFIS) to control a hybrid solar and wind grid-tie inverter in order to reduce power oscillations and enhance power quality is presented. To extract the maximum power from the PV system, a Perturb and Observe (P&O) algorithm is presented that tracks the Maximum Power Point (MPP). Time-domain simulation results of the studied system are performed in MATLAB/SIMULINK under different operating conditions such as changing irradiation and short-circuit faults in the power grid. From the simulation results, it can be concluded that the designed ANFIS controller and the proposed P&O algorithm perform better than the traditional PI controller and improve transient responses under severe operating conditions.

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This paper presents the comparative dynamic-stability analysis of an integration of a doubly-fed induction generator (DFIG)-based offshore wind farm (OWF) and a permanent-magnet synchronous generator (PMSG)-based OWF fed to a large power grid through a high-voltage AC (HVAC) line and a high-voltage direct-current (HVDC) link based on line-commutated converter (LCC). The operating performance of the studied 60-MW PMSG-based OWF is simulated by an equivalent PMSG driven by an equivalent wind turbine (WT) while an equivalent DFIG driven by an equivalent WT through an equivalent gearbox is used to simulate the operating characteristics of the 80-MW DFIG-based OWF. A frequency-domain approach based on a linearized system model using eigenvalue technique and a time-domain scheme based on a nonlinear system model subject to various disturbance conditions are both utilized to compare the damping characteristics contributed by the HVAC line and the proposed LCC-HVDC control scheme. It can be concluded from the simulation results that the proposed LCC-HVDC link is capable of rendering better damping characteristics to stabilize the studied integrated two OWFs fed to power grid subject to a severe fault than the HVAC line.