How intelligent is a PV inverter system?

Although various intelligent technologies have been used in a PV inverter system, the intelligence of the whole system is still at a rather low level. The intelligent methods are mainly utilized together with the traditional controllers to improve the system control speed and reliability.

Which AI methods are used in PV inverter system optimization?

Other AI methods such as expert systems (ES), artificial neural networks (ANN or NNW), genetic algorithms (GA), and adaptive neuro-fuzzy algorithms (ANFIS) have also been applied to PV inverter system optimization .

How can artificial intelligence improve the performance of PV inverters?

Control system optimization based on artificial intelligence is an effective way to improve the performance of PV inverters, allowing them to handle complicated control issues such as nonlinear dynamic interaction and multiple time-scale coupling .

What is the control performance of PV inverters?

The control performance of PV inverters determines the system’s stability and reliability. Conventional control is the foundation for intelligent optimization of grid-connected PV systems. Therefore, a brief overview of these typical controls should be given to lay the theoretical foundation of further contents.

What is a PV inverter?

As clearly pointed out, the PV inverter stands for the most critical part of the entire PV system. Research efforts are now concerned with the enhancement of inverter life span and reliability. Improving the power efficiency target is already an open research topic, as well as power quality.

What is a typical structure for PV inverters based on ANFIS?

A typical structure for PV inverters based on ANFIS is shown in Figure 14, Among them, the symbol “&” represents the sum of the input signal, and the symbol “N” represents the ratio of the triggering intensity of the i -th node to the sum of all rule triggering intensities. Figure 14. Droop control of inverter based on ANFIS.