A smart parametrisation for robust adaptive PI controller applied on renewable energy power generation systems under weak and uttermost weak grid conditions

Abstract

The increasing penetration of renewable energy systems into the global energy matrix is a necessity for sustainable development. The benefits impact the well-being of humanity and the environment directly. However, these power generation systems demand reliable controllers to regulate the current injection into the electrical grid. Therefore, this paper presents a smart parametrisation for a robust adaptive proportional integral controller applied to grid-injected current control of a voltage inverter source with an LCL filter. Controller parameter optimisation and the initialisation of their gains are performed using the particle swarm optimisation algorithm. Three cost functions are assessed on controller parametrisation, considering the current tracking error minimisation and control action limitations: integral of absolute error (IAE) + integral of absolute control action (IAU), integral of square error (ISE) + IAU, and integral of the time-weighted absolute error (ITAE) + IAU. A framework for performance analysis and an in-depth discussion are presented, providing a systematic decision-support methodology for controller configuration. The function determined as the best one is implemented experimentally and compared with a designer’s experience-based robust adaptive proportional integral controller using a hardware-in-the-loop test bench, where the improvements in controller performance are corroborated, contributing to the enhancement of energy quality in renewable energy systems. In addition, the controller’s robustness is evaluated on a weak grid and an uttermost weak grid, where it presents high robustness and global stability.