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In order to improve power system stability and suppress low power oscillations, active power regulation using variable frequency transformer (VFT) plays an important role. The literature has already documented in‐depth research on active power transfer control principles of VFT. The VFT, which is basically a wound rotor induction machine consumes reactive power because of magnetizing winding. In terms of the power flow interchange in a two‐area power system incorporating VFT, this work gives an extensive analysis to comprehend the reactive power needs under various operating circumstances. In the context of reactive power compensation, the present study explores two distinct methodologies: the implementation of a fixed shunt capacitor and the utilization of an artificial neural network (ANN)‐based static synchronous compensator (STATCOM). The STATCOM‐based control technique outperforms the conventional fixed shunt capacitor by demonstrating improved capabilities in reducing reactive power imbalances and stabilizing the power system. Further, a control scheme based on voltage regulation is implemented for integrating the STATCOM to enhance the fault ride through capability of a three‐phase bus fault. Additionally, two‐area test system is exposed to a reactive load shift to evaluate the operation of STATCOM, which restores the bus voltage to its pre‐specified value. [ABSTRACT FROM AUTHOR]

Summary: Modern power systems face challenges with stability, especially due to interconnections through weak tie‐lines, which can lead to power oscillations. These oscillations occur when the rotor fails to provide sufficient damping force to balance electrical output and mechanical input. Without a reliable damping system, these oscillations can persist, posing a threat to power system stability. In this article, a novel solution is proposed to curb low‐frequency oscillations by implementing a new power transmission technology called variable frequency transformer (VFT) in a two‐area power system. The VFT is equipped with an industrially applied proportional integral derivative controller trained by an artificial neural network to regulate power flow between the two areas. Additionally, a power oscillation damping controller is introduced that utilizes intelligent tuning through salp swarm optimization to enhance the damping capabilities of the VFT. The intelligent tuning of the power oscillation damping controller using salp swarm optimization enhances the damping capabilities of the VFT, resulting in a 25% increase in the damping ratio. To evaluate the performance of the VFT‐based system, it has been compared with a well‐established high voltage direct current (HVDC) system through a three‐phase fault analysis and reactive power requirement. Quantitatively, the proposed VFT system achieves a significant improvement in damping power oscillations, reducing their amplitudes by 30% compared to the HVDC system. Furthermore, the system is linearized under specific operating conditions, and eigenvalue analysis is conducted to assess power system stability for both VFT and HVDC cases. Through time‐domain simulations and eigenvalue analysis, our findings demonstrate that the VFT system surpasses the HVDC system in various operational and control aspects, highlighting its positive impact on power system stability. [ABSTRACT FROM AUTHOR]

This paper deals with MATLAB/SIMULINK simulation and analysis of a position sensor-less field oriented control of permanent magnet synchronous motor. Adaptive position estimators are required as the parameters of the machines like rotor resistance, inductance changes sometimes. Adaptive position and speed estimators viz. SMO, MRAS are much discussed in literature but the artificial neural network, adaptive neuro-fuzzy inference based estimators are least discussed. In this paper a MATLAB study of MRAS, ANN and ANFIS based position estimator in a Field oriented control of a permanent magnet synchronous motor drive is being done. MRAS, ANN, ANFIS estimators adaptive in nature so these estimators can adapt if there is any parameters change online. The performances of these three drives are analyzed, and results are compared. It is seen that ANFIS based system performance is better even when the parameters of the machines vary with time. This work is limited to analysis and simulation only and could be extended to a practical realization in future work. [ABSTRACT FROM AUTHOR]