Dynamic tracking MPP control of offshore bifacial floating photovoltaic systems with improved EMPC accounting for chaotic properties

The deployment of offshore floating bifacial photovoltaic (FBPV) systems is constrained by the inherent challenges posed by harsh marine environments, which induce chaotic movements and fluctuating power outputs. To address this issue, we propose the implementation of an improved Economic Model Predictive Control (EMPC) strategy in conjunction with a Modified Sine Algorithm Guided Dung Beetle Optimization (MSADBO) algorithm for the precise tracking of the maximum power point (MPP). The approach commences with the formulation of dynamic equations for the FBPV’s longitudinal tilt, followed by the confirmation of chaos through the utilization of bifurcation and phase diagrams. Subsequently, a dynamic mathematical model is constructed, taking into account the relationship between irradiance and the component’s tilt angle. Accordingly, a time-varying nonlinear model is formulated, which facilitates the design of an EMPC controller with power generation and switching losses as key performance indicators. The MSADBO algorithm optimizes the controller’s state constraints, thereby improving the accuracy and efficiency of the optimization process and ensuring control robustness. Simulations conducted under different operational conditions demonstrate the effectiveness of the method in stabilizing power output and accurately tracking the MPP. The proposed method shows 1.5 %–2 % better tracking precision and reduces power variation by 30 % compared to traditional EMPC, thereby validating its effectiveness and setting a stage for future research on FBPV grid integration.