Grid-connected PV Battery system with PO MPPT in MATLAB
In this simulation, we delve into the intricacies of grid-connected PV (photovoltaic) battery systems with maximum power point tracking (MPPT). This simulation model demonstrates the integration of PV arrays, batteries, and inverters to optimize power generation and utilization in varying environmental conditions.
PV Array Configuration:
The PV array consists of eight panels connected in series, each capable of producing a maximum power of 250 watts. The total power generation capacity of the array is approximately 2000 watts. To ensure efficient operation, the model includes an I-V (current-voltage) characteristic curve for the PV array, highlighting the importance of operating the array at the maximum power point (MPP) under different irradiation levels.
MPPT Algorithm:
The MPPT algorithm, implemented in the simulation, is based on the perturb and observe (P&O) method. By continuously monitoring the PV voltage and power, the algorithm adjusts the duty cycle of the boost converter to maintain the PV operation at the MPP. When both the change in voltage and power have the same sign (either positive or negative), the duty cycle is adjusted to track the MPP. Conversely, if the signs are different, the duty cycle is adjusted in the opposite direction.
Battery Integration:
A 240-volt battery with a rated capacity of 48 ampere-hours (Ah) is integrated into the system to store excess energy generated by the PV array during the day. The bidirectional DC-DC converter controls the charging and discharging of the battery, ensuring optimal energy management based on system requirements and the state of charge (SoC) of the battery.
Inverter Control:
The grid-connected inverter, equipped with an LCL filter, is controlled using a proportional-integral (PI) controller based on the PV current and battery SoC. The control logic dynamically adjusts the power flow between the PV array, battery, and grid to meet load demand while maximizing self-consumption and minimizing grid dependence.
Simulation and Analysis:
The simulation dynamically adjusts irradiation levels every three seconds to simulate changing environmental conditions. Results from the simulation showcase the system's ability to adapt to varying solar irradiance and load demands. Additionally, the integration of battery storage allows for energy arbitrage, enabling excess energy to be stored for later use during periods of low solar generation.
Conclusion:
Grid-connected PV battery systems with MPPT offer a sustainable solution for optimizing renewable energy utilization and grid interaction. By intelligently managing energy generation, storage, and consumption, these systems contribute to grid stability, reduce reliance on fossil fuels, and promote renewable energy integration. The simulation model presented in this tutorial serves as a valuable tool for studying and optimizing the performance of such systems in real-world applications.