Can ML-based maximum power point tracking (MPPT) be used in solar power systems?

By performing a thorough analysis of Machine Learning (ML)-based Maximum Power Point Tracking (MPPT) approaches, which are useful for obtaining maximum power in solar power systems, Refs. 27 and 28 add more to the body of research.

What does MPPT stand for?

It consists of an autonomous solar array, an essential DC–DC boosting converter, a three-phase Voltage Source Inverter (VSI), and an induction motor coupled to a centrifugal pump that circulates water. This combined system functions as the testing ground for three different Maximum Power Point Tracking (MPPT) techniques.

Which MPPT methods are used in a solar water pump system?

In the evaluation of the three MPPT methods [Perturb and Observe (P and O), Incremental Conductance (IC), and beta] for a solar water pump system, the following key findings have been observed: Results in noticeable oscillations in operating voltage and current. High ripple in DC link voltage.

What is maximum power point tracking (MPPT)?

In response, various maximum power point tracking (MPPT) techniques are explored to optimize power generation. The study focuses on three MPPT techniques—perturb and observe, incremental conductance, and the beta method—in the context of solar water pump systems.

How does MPPT work?

When using the MPPT technique, the system measures the PV panel’s voltage and current before calculating the power the panel produces. Based on the direction of the previous perturbation and the direction of the most recent power increase, the decision-making procedure for the subsequent perturbation is established.

Why is MPPT important for solar power production?

With the aid of the implemented MPPT strategy, the DC–DC converter is essential for maintaining the voltage at the DC-link level. To optimize power extraction, the MPPT controller ensures that the produced solar energy is utilized as efficiently as possible.