Overview of the PV System Design
The simulation model focuses on a 5 MW PV system connected to the grid, where the panels are configured with multiple strings and modules. The system consists of 11 PV panels connected in series, with each panel rated at 23.15 W, providing a maximum voltage of 29V and a current of 7.35 A under optimal conditions. The open circuit voltage is 36.3V, while the short circuit current is 7.84 A.
The PV modules are connected to a boost converter, which helps regulate the voltage before feeding it to the grid inverter. The terminal voltage of the panels under standard test conditions is 319V, and the system is designed to maintain a dieseling voltage of 800V.
Boost Converter and Control Design
The system design involves a boost converter, which is controlled to ensure that the voltage at the panels is optimal for power extraction. The boost converter's ripple inductor current and capacitor voltage are key parameters that determine its efficiency. The design of the boost converter is crucial, and the duty cycle is adjusted dynamically to maintain maximum power point tracking (MPPT).
To achieve this, the system utilizes an Incremental Conductance MPPT algorithm that adjusts the duty cycle of the boost converter to maximize the power extraction from the PV system, taking into account the fluctuations in irradiation and temperature.
Role of MPPT in Power Extraction
The MPPT algorithm ensures that the PV system operates at its peak power point by continuously adjusting the operating conditions. The Incremental Conductance MPPT is based on two main parameters: the PV voltage (VPV) and PV current (IPV). These two parameters are used to compute the changes in power and voltage, helping determine if the system is at its maximum power point.
Here’s how the Incremental Conductance MPPT works:
It checks if the change in voltage and the change in power are zero. If true, the system is at maximum power and no adjustments are made.
If the change in voltage is greater than the change in current, the system will need to decrease the voltage to bring the system back to the maximum power point.
If the voltage increase is smaller than the current increase, the system will increase the voltage to return to the optimal operating point.
This feedback loop ensures that the system always operates at the best possible efficiency, even as environmental conditions fluctuate.
Inverter and Grid Connection
The PV system is connected to the grid through an inverter, which converts the DC voltage from the panels into AC voltage that is suitable for the grid. The inverter operates under a combined voltage control and current control system, which ensures stable and efficient energy transfer.
Voltage Control: The DC voltage is maintained at 800V by comparing the actual DC voltage with a reference voltage and adjusting accordingly.
Current Control: A current controller regulates the inverter’s output current by comparing the actual grid current with a reference current.
The inverter’s output is modulated using a sinusoidal PWM technique to inject power into the grid at the correct frequency and voltage. The system uses Park Transformation to convert the three-phase grid voltage and current into a reference frame (DQ form) for easier control.
System Simulation and Performance
The MATLAB simulation demonstrates the system's ability to operate at 5 MW of power generation under ideal conditions. Key performance indicators such as PV voltage, current, and power are constantly monitored to ensure optimal operation. The dieseling voltage is consistently maintained at 800V, which is critical for stable operation.
During the simulation, the following results were observed:
Under normal conditions, the system operated at a maximum power of 5 MW, with the PV voltage stabilizing around 319V and the current around 15,000A.
The grid current and inverter voltage are shown to adjust accordingly to maintain synchronization with the grid.
Impact of Changing Irradiation Conditions
One of the advantages of the Incremental Conductance MPPT is its ability to adjust dynamically to changes in irradiation and temperature. In a real-world scenario, irradiation can fluctuate, leading to a reduction in the power output of the PV system.
During the simulation, the irradiation was reduced to 500 W/m², and the system responded as expected:
The current from the PV system decreased, dropping to approximately 7.5 kA.
The power output of the system reduced to about 2.5 MW, but the system continued to operate efficiently, adjusting the duty cycle to maximize the available power.
Despite the reduction in power, the dieseling voltage remained stable at 800V, ensuring that the system could continue feeding power into the grid.
Conclusion
The simulation of a 5 MW grid-tied PV system using the Incremental Conductance MPPT algorithm demonstrated the effectiveness of this method in maximizing energy extraction from photovoltaic systems. The system was able to adapt to changes in environmental conditions, maintaining optimal power output and stability throughout the operation.
This model provides a clear insight into how MPPT algorithms can be implemented in large-scale renewable energy systems to ensure maximum efficiency and reliable integration with the electrical grid.
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