MATLAB Implementation of a Single-Stage Three-Phase Grid-Connected PV System
- lms editor
- Apr 3, 2025
- 4 min read
1. Introduction to Grid-Connected PV Systems
Grid-connected PV systems are designed to harness solar energy and feed the generated power directly into the electrical grid. In this tutorial, we will design a 100 kW system, aiming for efficient energy conversion and power delivery. We start by selecting the necessary components, such as the PV array and inverter, and calculate the required configurations to achieve 100 kW of power.
2. Calculating the PV Panel Configuration
The first task in designing a grid-connected PV system is to determine the number of solar panels and their configuration to generate the required power. For a 100 kW system, we begin by considering the maximum power point (MPP) of a single panel. The voltage at MPP for one panel is 29V, and the current is 7.35A. Using the inverter voltage of 900V, we calculate the number of series-connected panels required. Dividing 900V by 29V gives us approximately 31 panels in series.
Next, to ensure the system generates 100 kW, we calculate the number of parallel strings needed. By using the appropriate formulas, we determine that 15 parallel strings of 31 panels each will meet the 100 kW power requirement.
3. Maximum Power Point Tracking (MPPT) Control
To maximize the efficiency of the PV system, we need to operate it at the maximum power point (MPP) of the PV panels. The Perturb and Observe (P&O) MPPT algorithm is employed to achieve this. By continuously measuring the panel’s voltage and current, the algorithm adjusts the reference voltage to keep the system operating at optimal power output.
The reference voltage is updated based on the difference in power and voltage. If the system is not at MPP, the algorithm adjusts the voltage to bring the system back to its maximum power output. This ensures that the solar panels operate efficiently even under varying environmental conditions.
4. Inverter and Grid Connection
The PV array is connected to an inverter, which converts the DC power from the PV system into AC power that can be fed into the grid. The inverter is connected through a series RLC (resistor, inductor, and capacitor) filter to ensure smooth operation and reduce harmonics in the output.
The system uses a universal bridge with IGBT (Insulated Gate Bipolar Transistor) diodes to control the inverter’s switching. This setup ensures that the generated power is properly synchronized with the grid and meets the required voltage and current specifications.
5. Designing the Control Logic for the Inverter
A crucial aspect of the system’s performance is the inverter control logic, which manages the conversion of DC to AC power. In this design, the control logic is implemented using a decoupling control scheme with a Phase-Locked Loop (PLL) to synchronize the inverter with the grid.
The control system uses two main components:
Voltage Control: This ensures that the inverter’s output voltage matches the reference voltage, optimizing power transfer to the grid.
Current Control: This ensures that the current fed into the grid is also optimized, preventing overloading or underperformance.
PID (Proportional-Integral-Derivative) controllers are used to maintain the desired voltage and current levels. These controllers adjust the system’s parameters to maintain stable operation, minimizing oscillations and improving the overall efficiency of the power conversion.
6. Simulation and Tuning the Controller
Once the system design and control logic are in place, we simulate the model in MATLAB to assess its performance. During the simulation, we observe the system’s voltage, current, and power output. Any discrepancies or oscillations in the power output are corrected by tuning the controller parameters, such as the gain values for the PID controllers.
Simulation tools like the PD Tuner App are used to fine-tune the system’s response. The process involves adjusting the controller’s parameters and evaluating the system’s behavior under different conditions, including variations in irradiation levels and grid conditions.
7. Testing the System Under Different Irradiation Conditions
One of the key advantages of a grid-connected PV system is its ability to adjust to changes in environmental conditions. In this simulation, we test the system’s performance under various irradiation levels.
At 1000 W/m² (standard solar irradiance), the system generates close to 100 kW of power, and the grid current increases as expected.
Under reduced irradiation, such as 500 W/m², the power output decreases accordingly, and the inverter adjusts the current to match the available energy.
This dynamic response to changing environmental conditions highlights the system’s efficiency and ability to integrate seamlessly with the grid, ensuring reliable power delivery even under varying sunlight.
8. Performance Evaluation and Harmonic Distortion Analysis
After the system is fully tuned, we evaluate its performance in terms of harmonic distortion (THD). Harmonics can distort the power quality, so minimizing THD is essential. We perform a Fast Fourier Transform (FFT) analysis on the inverter’s current and voltage to assess the quality of the power being fed into the grid.
By adjusting the controller parameters, we can reduce harmonic distortion, achieving a THD of below 5%, which is an acceptable value for grid-connected systems.
9. Conclusion
In conclusion, the MATLAB implementation of the single-stage, three-phase grid-connected PV system has been successfully designed and tested. By utilizing MPPT control, advanced inverter control, and harmonic distortion analysis, the system ensures optimal power generation and efficient grid integration.
The system has been tested under various conditions and demonstrates excellent performance in terms of power conversion efficiency, current stability, and harmonic control. This approach provides a solid foundation for anyone interested in designing and simulating PV grid-connected systems using MATLAB.
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