Nonlinear adaptive control of PV inverter for maximum solar energy harvesting using democratic joint

Abstract

This study designs a novel nonlinear adaptive controller (NAC) of photovoltaic inverter in order to generate the maximum energy of solar power under different condition. Inverter nonlinearities, uncertain grid/inverter parameters, as well as inverter modelling uncertainties are aggregated into a perturbation. Then, a linear extended state observer (ESO), is applied for estimate the perturbation online. Meanwhile, a state feedback controller is used to calculate the perturbation in the real-time. Particularly, its optimal control parameters are effectively and efficiently tuned by a novel meta-heuristic algorithm, called democratic joint operations algorithm (DJOA), such that a satisfactory control property could be resulted in. Case studies verifies the effectiveness and advantages of NAC compared to conventional linear control, e.g., PID controller, and typical nonlinear control, e.g., feedback linearization controller (FLC), under solar irradiation variation and temperature variation.

Inverter Design and Droop Parallel Control Strategy Based on Virtual Impedance

“…In the field of inverter technology, parallel AC power supply has attracted increasing attention. The success of control schemes and concrete products has set a crucial benchmark for the high-performance development of parallel inverter power systems [19,20]. Parallel inverter operation is deeply studied based on the successful experience of paralleling process.…”