Abstract
Metaheuristic search algorithms (MHSAs) are widely applied to optimization problems in control systems. Their adaptability and search capability make them effective for controller tuning, particularly in nonlinear or time-variant environments. In hardware-in-the-loop (HIL) and real-time simulation (RTS) contexts, these features are invaluable for automating controller optimization. Yet, integration of MHSAs with RTS platforms for autonomous online closed-loop optimization remains limited. This paper introduces a framework that co-simulates MHSAs and online RTSs to enable real-time, optimization of virtual models. Typhoon HIL libraries allow the Pygad genetic algorithm (GA) to execute, evaluate, and optimize electromagnetic transient (EMT) simulations in real time. The approach is demonstrated by tuning the proportional and integral (PI) gains of a secondary controller in a virtual microgrid (MG). Several case studies confirm its effectiveness, achieving a 98.96% reduction in settling time without overshoot. The results demonstrate the potential of MHSA-RTS integration for controller enhancement across diverse optimization tasks.