Power flow control and management strategy applied to DC nanogrids based on Gaussian distribution function.
Electromagnetic Frequency Regulator, Renewable Energy Sources, Hybrid Generation, Control Systems, Active Disturbance Rejection Control, Linear Active Disturbance Rejection Control.
The continuous increase in energy demand, combined with growing social and political concerns about sustainability, has driven research and development in Renewable Energy Sources (RES), with particular emphasis on wind and photovoltaic (PV) generation. The temporal complementarity of different sources and the possibility of utilizing existing infrastructure favor the adoption of hybrid generation systems. In this context, the Electromagnetic Frequency Regulator (EFR) emerges as a promising alternative, enabling electromechanical hybridization through a modified induction machine whose rotating armature is coupled to the wind turbine, while a second primary energy source supplies electrical power to the machine via a Voltage Source Inverter (VSI).
This physical arrangement provides the EFR with important advantages over conventional architectures based on static converters, such as greater electromechanical inertia and reduced harmonic injection into the power grid. Additionally, the EFR simplifies the design of the gearbox in wind systems, resulting in a more compact and efficient setup.
On the other hand, controlling the EFR is challenging due to the strong presence of external disturbances, such as variations in wind profile and the behavior of connected loads. Since the EFR supplies the grid or local loads through a synchronous generator, it becomes essential to maintain a constant rotor speed in order to ensure stability and power quality. In this work, a control strategy based on Field-Oriented Control (FOC) is proposed, in which the outer speed control loop replaces the traditional PI controller—commonly used in machine drives—with two more robust alternatives: Active Disturbance Rejection Control (ADRC) and its linear version (LADRC). These controllers employ an Extended State Observer (ESO) to estimate and reject, in real time, the internal and external disturbances affecting the system, thereby simplifying the plant dynamics for the controller design. The effectiveness of the proposed technique is validated through computational simulations using the MATLAB/Simulink environment and experimental bench tests, considering different operating conditions and disturbance scenarios.