The increasing demand for energy worldwide has led to a significant interest in renewable energy sources, particularly solar energy, due to its universal availability, environmentally friendly nature, and lower operational and maintenance costs. However, solar panels possess nonlinear electrical characteristics, with a unique maximum power point (MPP), under uniform solar irradiance and temperature. To efficiently extract and deliver maximum power from photovoltaic (PV) systems, Maximum Power Point Tracking (MPPT) control strategies are employed.
MPPT strategies have been developed to optimize the operation of the PV system, including offline, online, and hybrid techniques. Offline strategies require some PV values to generate the control signal essential for operating the system at its MPP. Online techniques, on the other hand, use PV current and voltage in real-time to achieve the MPP. Hybrid MPPT control strategies combine both online and offline control strategies, using two loops to track the MPP.
Despite their potential, traditional MPPT control strategies often fail under varying meteorological conditions and are incapable of operating under partial shading conditions. This issue can lead to significant energy loss and degradation of the overall system performance and efficiency.
To address these challenges, a robust integral backstepping (RIB) based MPPT control strategy has been proposed. This control strategy consists of two loops, where the first loop generates the real-time offline reference peak power voltage through an adaptive neuro-fuzzy inference system (ANFIS) network. The second loop uses the estimated reference peak power voltage as a set-point value for generating a control signal, thus forcing the PV system to operate at this set-point by continuously adjusting the duty ratio of the power converter.
The RIB based MPPT control strategy has shown promising results, outperforming traditional backstepping and integral backstepping techniques in terms of lesser rising time, faster convergence, and minimum output tracking error. Moreover, this technique has demonstrated robustness against plant parametric uncertainties, plant voltage and current faults, and dynamic load, providing a more reliable and efficient solution for harnessing solar power.
The introduction of robust and efficient MPPT control strategies, such as the RIB based MPPT controller, plays a crucial role in unleashing the full potential of renewable energy sources. By overcoming the limitations of traditional MPPT strategies, these advanced control techniques can significantly enhance the efficiency and reliability of PV systems, paving the way for a more sustainable and green future.