Sistema de geração de energia eólica conectado à rede elétrica com utilização de sistema de armazenamento de energia e filtro ativo de potência

Abstract

This paper presents a grid-connected wind energy generation system driven by a Squirrel Cage Induction Generator (SCIG), which includes an energy storage system (ESS) configuration with batteries. Additionally, harmonic mitigation of grid currents is performed by the grid-side converter, acting as an Active Power Filter (APF) based on the instantaneous power (p-q) theory. The SCIG was chosen due to advantages such as robustness, simplicity, lower weight, and low cost compared to other machines. It is directly connected to a bidirectional back-to-back power converter, supplying active and reactive power to the grid. The SCIG’s power generation is achieved using a Maximum Power Point Tracking (MPPT) technique based on the optimal tip-speed ratio (lambda) and optimal turbine speed. This technique, implemented through the SCIG’s speed control, allows for more efficient harvesting of the available wind energy. To make the wind generation system reliable against wind fluctuations and variable power production, a battery-based energy storage system is implemented. This system is responsible for managing the power flow, storing energy when generation exceeds demand and injecting it into the grid when generation is lower than demand. The ESS is connected to the back-to-back converter through a DC-DC buck-boost converter. The generator is controlled based on its speed and magnetizing current, while the Grid-Side Converter (GSC) is controlled based on power flow. The battery bank is controlled by regulating the DC bus voltage and the battery current, using PI controllers. The APF functionality, implemented by the GSC, results in a THD of 4.88%, which is within the limits established by international standards, thereby improving power quality. The system is composed of a wind turbine, gearbox, SCIG, back-to-back power electronic converter, DC-DC converter, battery bank, and non-linear loads. The studied system was mathematically modeled and simulated using computational simulation techniques to validate the employed control strategies under different operating conditions. The Matlab/Simulink software was used for the simulations.