This work enhances the performance of a steady-state open-loop optimizer for the automatic operation of solar photo-Fenton plants, an advanced oxidation technology used for the removal of organic microcontaminants from urban wastewater. The proposed strategy dynamically adjusts the reagent dosage in response to real-time variations in solar irradiance, improving process robustness without requiring additional measurements. Simulations under both clear- and cloudy-day conditions showed reductions in process constraint violations of up to 78 % for microcontaminant removal, with only minor increases in reagent consumption (< 15 %) and operating cost (< 2 %). The strategy effectively mitigates the impact of irradiance fluctuations, demonstrating its potential as a practical and cost-efficient solution for the robust optimization of large-scale solar photo-Fenton systems.
A ground-generation airborne wind energy system is considered. The device consists of a kite attached to an oscillating arm in the horizontal plane that generates electricity. The kite’s trajectory is constrained to follow a prescribed lemniscate pattern. An implicit modeling approach is adopted where the control force required to maintain the figure-eight trajectory is computed. This system is reduced to a two-dimensional second-order ordinary differential equation. Its limit cycles are studied numerically, with specific equilibria serving as starting points to obtain physically admissible periodic motions. These cycles depend on several design parameters including line length, arm inertia, and braking coefficient, that are tuned to maximize the average power generated by the arm’s oscillations. The system’s behavior is further analyzed across a typical range of wind speeds, demonstrating robustness to wind variations while maintaining positive line tension throughout the cycle.
