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. 2024 Oct 29;14(1):25963.
doi: 10.1038/s41598-024-77822-8.

Analysis and control of grid-interactive PV-fed BLDC water pumping system with optimized MPPT for DC-DC converter

J Sevugan Rajesh  1 , R Karthikeyan  2 , R Revathi  3
Affiliations

Analysis and control of grid-interactive PV-fed BLDC water pumping system with optimized MPPT for DC-DC converter

J Sevugan Rajesh et al. Sci Rep. .

Abstract

In this study, a novel water pumping module fed by grid interactive Photo-Voltaic with a bidirectional Power Flow Control was proposed. In addition to improving the pumping system's reliability, a water pump is powered by a brushless DC motor drive. This method enables the pump to work at its maximum capacity for the entirety of that day, regardless of the weather. The entire system becomes more reliable as a result of the motor's increased use of photovoltaic (PV) generated power for pumping applications. Maximum Power Point Tracking (MPPT) controller incorporating Machine Learning algorithm drives bridgeless greater static gain DCDC converter to achieve higher power generation point and increment PV efficiency. The PV array's operation would be managed using the ML back propagation technology to capture the most electricity under any ecological circumstance. A BLDC motor is fed by a Voltage Source Inverter (VSI) that includes a DC bus controlled in both directions by a unit vector template (UVT) approach incorporated in a single-phase voltage source converter (VSC). Additionally, utilizing a PI controller to manage the DC capacitor voltage in the UVT controller at a particular level is not appropriate for the increased PQ capabilities. However, due to tuning problems with the current controller, this controller is unpopular. The aforementioned problems are resolved by employing a unique intelligent-based fuzzy logic controller that achieves good performance features. In this technique, the function of a PV array at its Maximum Power Point (MPP), as well as power quality enhancements and a decrease in Total Harmonic Distortion (THD) of the grid are accomplished. The proposed PI controller attains a significant voltage THD of 3.736. The PI controller, on the other hand, managed to achieve a load voltage THD of 2.629%. The ANFIS method, whose value is 1.739%, is discovered to have a lower THD than all remotes with improved features, it lessens abrupt swings while maintaining steady DC-link voltage.

Keywords: Brushless DC motor; Fuzzy-logic controller (FLC); Maximum power point (MPP); Power quality; Total harmonic distortion (THD); Unit vector template (UVT); Voltage source inverter (VSI).

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Grid and PV-based water pumping system powered by a BLDC motor.
Fig. 2
Fig. 2
Simulink model of the Grid and PV-based water pumping system powered by a BLDC motor.
Fig. 3
Fig. 3
Control of the VSC’s bidirectional power flow based on UVT.
Fig. 4
Fig. 4
The proposed solar prediction models’ flowchart.
Fig. 5
Fig. 5
Predicting monthly solar radiation at Vellore.
Fig. 6
Fig. 6
PV and its control modules are included in the high-gain DC-DC converter.
Fig. 7
Fig. 7
Performance of neural network.
Fig. 8
Fig. 8
Block diagram of proposed power flow control technique.
Fig. 9
Fig. 9
The fuzzy controller diagram.
Fig. 10
Fig. 10
PQ fuzzy logic control diagram.
Fig. 11
Fig. 11
(a) Design of fuzzy (b) Input variable DE (k) Membership functions (c) Input variable E (k) Membership functions (d) Rule viewer.
Fig. 12
Fig. 12
Steady-state response of pumping system supplied by PV in which BLDC motor operation remains simple.
Fig. 13
Fig. 13
Performance at a steady state when the motor is only fed by the grid, as measured by (a) the grid index (b) the grid and motor-pump index (c) the grid’s power quality.
Fig. 14
Fig. 14
(a) Steady-state performance of PV during 1000 W/m2, (b) Steady-state performance of grid during 1000 W/m2, (c) PQ of the grid during 1000 W/m2, (d) PQ when the grid is fed by PV at 1000 W/m2.
Fig. 15
Fig. 15
(a) Steady-state performance of PV during 400 W/m2, (b) Steady-state performance of grid during 400 W/m2, (c) Power quality of grid during 400 W/m2.
Fig. 16
Fig. 16
(a) Dynamic performance of PV during variation of radiation level from 1000 W/m2 to 700 W/m2and (b) Dynamic performance of grid during respective change in variation.
Fig. 17
Fig. 17
Performance during steady conditions when combined PV and grid supplies pump, as shown in (a) power supply to pump by combined grid and PV (b) Quality of grid power.
Fig. 18
Fig. 18
Dynamic performance under grid failure.
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References

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