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

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.