Hardware-in-the-Loop Validation of the Optimized Controller for Stabilizing Islanded Microgrids with Cryptocurrency Mining Loads

The high penetration of renewable energy in modern power systems reduces grid inertia and makes frequency regulation more challenging, especially in islanded microgrids. This paper introduces an optimized load frequency control framework where a PID secondary controller is tuned using the recently developed Birds of Prey-Based Optimization (BPBO) algorithm, constituting the main contribution of this work. In addition, a cryptocurrency mining load is modeled as a fast, controllable demand resource to absorb surplus generation and quickly curtail during shortages, supporting power balance amid renewable variability. The proposed BPBO-PID controller is compared against reported controllers using standard multi-objective performance indices (ISE, IAE, ITSE, and ITAE) and time-domain response metrics under various photovoltaic penetration scenarios, including step changes, stepped variations, and realistic fluctuation profiles. Results demonstrate that BPBO-PID consistently achieves the lowest error indices, reducing these metrics by 23.0 – 41.7% compared to Particle Swarm Optimization-based Proportional-Integral-Derivative (PSO-PID) and by 37.0 – 67.6% compared to Grey Wolf Optimization-based Proportional-Integral-Derivative (GWO-PID), with the maximum reduction observed in ITSE. In the single-step case, BPBO-PID also reduces settling time by 15.2% relative to PSO-PID and by 36.2% relative to GWO-PID. System stability is further validated through analytical methods and hardware-in-the-loop testing on dSPACE and RTDS/RSCAD platforms, demonstrating real-time feasibility.