Model Predictive Control of Electric Spring for Voltage Stabilization in Wind-driven Induction Generator based Microgrids

Renewable energy powered microgrids present a viable option for isolated and rural areas. Within sustainable technologies, wind energy possesses great promise although its intermittent characteristics result in voltage instability and other reliability challenges. While Squirrel Cage Induction Generators (SCIGs) are inexpensive and rugged, the lack of voltage and reactive power regulation in wind systems poses challenges for their broader use. This paper suggests integrating an Electric Spring (ES) with Model Predictive Control (MPC) for maintaining voltage stability over sensitive loads in an SCIG-based wind microgrid. A Battery Energy Storage System (BESS) offers additional resilience in wind power fluctuation by actively balancing energy storage and providing discharge control through a bidirectional DC–DC converter. The effectiveness of the proposed MPC based ES control strategy is tested in MATLAB/Simulink with variable wind and load inputs which are also verified experimentally. The obtained results indicate that MPC outperformed PI control in a significant way, yielding significant improvements in settling time, RMS voltage deviation, and system control while providing reliable operation for critical loads in microgrids.