<![CDATA[Voltage Source Converter-High Voltage Direct Current (VSC-HVDC) transmission systems are preferred for long-distance power transmission due to their flexibility and stability. However, maintaining optimal performance and stability during transient conditions and disturbances is challenging. This research analyzes the performance of VSC-HVDC systems using Proportional-Integral Adaptive Neuro-Fuzzy Inference System (PI-ANFIS) control compared to conventional PI control. A VSC-HVDC system model with PI control provides the basis for generating input-output data to train the ANFIS model. Subsequently, a VSC-HVDC model with PI-ANFIS control is developed and optimized. Performance evaluation under transient conditions and both permanent and temporary disturbances reveals that PI-ANFIS significantly enhances system performance. PI-ANFIS reduces overshoot, accelerates settling time in active power, reactive power, and DC voltage control, and improves stability and recovery time during disturbances. The adaptability and learning capabilities of ANFIS offer additional flexibility for dynamic conditions and unexpected disturbances. This study highlights intelligent control technology advancements, promoting reliable and adaptable power transmission systems, and lays the groundwork for future research and practical applications of PI-ANFIS control in VSC-HVDC systems.]]>
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