Adaptive Neuro-Fuzzy Inference System-Based Static Synchronous Compensator for Managing Abnormal Conditions in Real-Transmission Network in Middle Egypt

This paper examines the deployment of a 25 MVA Static Synchronous Compensator (STATCOM) to improve voltage stability in a real 66 kV 525 MVA transmission network in the Middle Egypt Electricity Zone. A MATLAB/Simulink model is developed to assess the performance of the STATCOM in both normal and fault conditions, including single-phase and three-phase faults. The STATCOM regulates the voltage by adjusting it within ±10% of the nominal value and is connected to a shunt with the bus B11. Four control strategies are implemented: a proportional–integral (PI) controller, an adaptive neuro-fuzzy inference system (ANFIS), a fuzzy logic controller (FLC), and an FLC combined with a supercapacitor. FLCs outperform PI controllers in maintaining voltage stability; however, they exhibit limitations regarding their responsiveness to dynamic changes within the network. The findings demonstrate that the STATCOM enhances the voltage and current stability compared to the system without this component. The ANFIS controller demonstrates optimal performance characterized by minimal waveform fluctuations. Under standard conditions, a single STATCOM integrated with an ANFIS elevates the bus voltages to 100.382% (B10) and 101.953% (B11), surpassing the performance of the FLC (100.314% and 101.246%) and the FLC–supercapacitor combination (100.326% and 101.392%). The deployment of two STATCOM units alongside an ANFIS improves the voltage levels to 102.122% (B10) and 102.200% (B11). The findings demonstrate that the AN-FIS-controlled STATCOM enhances system performance under normal operating conditions, voltage source fluctuations, and fault scenarios. The deployment of two STATCOM units, each rated at 25 MVA and controlled by an ANFIS, significantly enhances voltage stability compared to a single unit.