Dual-Mode Adaptive Defocusing Control for Net Energy Yield Optimization in Solar-Integrated Biophotovoltaic Systems

Microalgae biophotovoltaic (BPV) systems convert solar energy into electricity through photosynthetic electron transfer (PET) and have emerged as a promising solar-integrated bioenergy technology. However, high-density tubular arrays suffer from the “canyon effect” at low solar angles and from photoinhibition under peak irradiance (>450 W/m2), where non-photochemical quenching (NPQ) and reactive oxygen species (ROS) dissipate bioelectric potential as heat. To address this, a hysteresis-based dual-mode PID controller with hysteresis switching is proposed within an optical–mechanical–biological co-optimization framework, integrating array self-shading, nonlinear microalgal photoresponse, and tracking parasitic losses. In low-light mode, the system actively tracks the sun to minimize shading; in peak-light mode, it defocuses the incident angle to limit irradiance near the saturation threshold, mitigating the risk of photoinhibition. Structural control boundaries, including tube spacing and connecting rod length, are determined numerically. Under the nominal clear-sky design day, the defocusing mode reduces the daily exposure of the culture to irradiance above the saturation threshold (450 W/m2) from 5.28 h to 3.08 h. Numerical simulations indicate a daily net energy yield improvement of +14.9% over continuous dual-axis tracking and +6.3% over the latitude-based fixed-tilt baseline under idealized clear-sky design-day conditions. These values are simulation-derived estimates; experimental validation with a physical prototype is required before the framework can be interpreted as a validated system-level performance gain.