6.5 MW Grid-connected PV System in MATLAB
Introduction:
In this discussion, we explore the design and control aspects of a photovoltaic (PV) system integrated with the grid. The primary goal is to optimize the power extraction from the PV panels and efficiently feed it into the grid. The design involves the use of a Boost converter, MPPT (Maximum Power Point Tracking) algorithm, and a three-phase inverter for grid integration.
PV Panel Specification:
The PV panel chosen for this system has a single-panel rating of 360 watts. The maximum power point is at 38.6 volts with a current of 9.33 amps. To achieve the desired power output, 130 panels are connected in series, resulting in a total voltage of 5018 volts under standard test conditions (1000 W/m², 25°C).
Design of Boost Converter:
To match the PV system with an 11 kV grid, a Boost converter is employed. The DC link voltage is set at 20 kV, and the Boost converter design involves calculating the values for the inductor (L) and input capacitor (C). These values are determined using formulas based on power rating and system parameters.
MPPT Algorithm:
The Perturb and Observe (P&O) MPPT algorithm is utilized to continuously track the maximum power point of the PV system. The algorithm adjusts the duty cycle of the Boost converter to optimize power extraction. By comparing changes in voltage and power, the algorithm intelligently adjusts the duty cycle to maximize power output.
Inverter Control:
The inverter is controlled using a voltage control method and a current control method. The DC link voltage is compared with a reference voltage of 20 kV, and a Proportional-Integral (PI) controller generates the current reference (ID). The inverter sends real power to the grid, and the ID reference is used for current control. The inverter also incorporates a speed-voltage generator for synchronization with the grid.
Grid Integration:
The power generated by the PV system is efficiently fed into an 11 kV grid. The inverter adjusts its operation to match the grid's voltage and frequency, ensuring a seamless integration of renewable energy into the existing power infrastructure.
Simulation and Performance: Simulations of the system under different irradiation levels demonstrate the effectiveness of the MPPT algorithm and the overall control strategy. The system consistently adapts to varying solar conditions, maximizing power extraction and maintaining stability when connected to the grid.
Conclusion:
The designed PV system, coupled with intelligent control algorithms, showcases a robust solution for grid-integrated solar power generation. The combination of the Boost converter, MPPT algorithm, and three-phase inverter ensures optimal energy conversion and efficient grid integration, contributing to the advancement of renewable energy technologies.
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