An integrated dual control framework for self-sustained single-stage solar energy harvesting system in intelligent air ventilation application

Abstract

In low-powered, self-sustaining, multistage photovoltaic (PV) systems, implementation of several control logics at rapid environmental conditions brings large power losses. To overcome such limitation, this work presents an efficient dual-control scheme for a three-level boost converter (TLBC) based single-stage PV system. In this proposed scheme, an optimized perturbation & observe (P&O) algorithm-based input side MPPT is integrated with the output side PID based load voltage regulation in dual-control coordination to operate the TLBC with tuned inner-outer loop parameters. Comprehensive theoretical, simulation, experimental and stability analysis have been carried out for several loading including charge-storage, closed-loop speed control of DC motor and positional control by low powered servo motor. The developed hardware-setup with laboratory-simulator and rooftop experiment incorporates a low-powered microcontroller to implement the proposed dual-control strategy which further contributes to achieve maximum boosting efficiency of 87.04 % with power density of 10.09 mW/cm². The overall circuital loss during self-powered implementation is obtained as only 20.25 %. The developed system has driven multiple sensors including a temperature measuring system to determine the temperature of ambient PV source. Various performance parameters including self-sustaining efficiency and variable irradiance effect have been demonstrated to be superior with respect to existing literature. The dynamic behaviour of the MPPT algorithm under variable irradiance pattern has been extensively studied as well for variable MPPT step sizes. Accordingly, a maximum MPPT tracking efficiency of 99.98 % and tracking time of 63 ms are achieved. The maximum possible overshoot of 16.24 % and undershoot of 3.28 % are observed in the output response. Further, multiple patterns of partial shading cases are analysed with maximum MPPT tracking efficiency of 98.98 % and high power conversion efficiency of > 70.33 % achieving successful global power point tracking for each kind of shading pattern. Finally, two interesting case studies including self-sustainable automated air ventilation control and smart air conditioning system have been demonstrated using the developed set-up.