Interactive teaching–learning optimiser for parameter tuning of VSC‐HVDC systems with offshore wind farm integration

Abstract

This study proposes a novel interactive teaching–learning optimiser (ITLO) for voltage source converter based high voltage direct current (VSC‐HVDC) systems with offshore wind farm integration. Conventional vector control strategy is adopted, in which the parameters of eight proportional–integral loops are optimally tuned to achieve a reliable and satisfactory control performance under various operation conditions. Multiple classes are employed to realise a wider exploration compared with that of original teaching–learning based optimisation. Moreover, a small world network is incorporated for an interactive learning among the teachers or students from different classes, such that a deeper exploitation can be resulted in. Hence, ITLO can effectively avoid a local optimum due to the appropriate trade‐off between explorations and exploitations. Three case studies are carried out, such as active and reactive power tracking, short‐circuit fault at power grid, and offshore wind farm connection. Simulation results verify the effectiveness and advantages of ITLO over that of existing meta‐heuristic optimisation algorithms.