Control of Parallel AC Voltage Source Converter High-Voltage DC System Using an Adaptive PI Evolutionary-Based Controller

Abstract

High-voltage direct current (HVDC) transmission system based on voltage source converter technology gains attraction in recent years for the grid integration due to many advantages like connecting wind farms to power grids, underground power links, connecting asynchronous grids, and providing efficient long-distance power transmission, etc. To acquire the best output from the above topologies, it is crucial to design a better controller strategy for the converter control. With this objective, this paper presents an adaptive PI controller based on evolutionary optimization for a parallel AC voltage source converter HVDC system. Looking at the extensive application of constant gain PI controller type, an adaptively changing gain parameter PI controller based on tan hyperbolic (tanh) function is proposed in this study. To enhance further its performance, a Modified Teaching Learning-Based Optimization (MTLBO) is used to find optimally the parameters of the proposed control strategy. To justify the effectiveness of the proposed controller, different test cases in terms of faults, parameter variation, and load & reference power variation are studied and analyzed. Comparative analysis with a conventional tuned PI controller, PI-MTLBO controller, and proposed API-MTLBO controller is demonstrated for indicating a substantial improvement in the damping system oscillations with better controllability and stability of the proposed approach.