☀️ Grid-Connected PV Battery System with P&O MPPT in MATLAB 🔋⚡
- lms editor
- 1 day ago
- 3 min read
As renewable energy becomes a cornerstone of modern power systems, integrating solar PV, batteries, and the grid is essential for ensuring reliable, efficient, and stable energy delivery. In this post, we explore a grid-connected PV battery system modeled in MATLAB Simulink, featuring the Perturb and Observe (P&O) Maximum Power Point Tracking (MPPT) algorithm.
This setup demonstrates how PV generation, energy storage, and grid interaction work together for maximum efficiency and stability under fluctuating solar conditions. 🌞
☀️ PV Array Configuration
Panels: 8 panels in series
Power per panel: 250 W
Total output: ~2000 W (2 kW) at ~245 V
Boost converter: Steps up voltage from 245 V → 400 V
👉 The boost converter is controlled by the P&O MPPT algorithm to ensure the system always operates at the maximum power point (MPP) despite irradiance changes.
⚡ Perturb & Observe (P&O) MPPT
The P&O algorithm works by monitoring:
Change in voltage (ΔV)
Change in power (ΔP)
✅ Based on the sign of ΔP and ΔV, the duty cycle of the boost converter is adjusted.✅ This ensures continuous tracking of the MPP even under varying sunlight.✅ Four operating cases are considered, making it a robust control method for real-time operation.
🔋 Battery Integration
Battery specs: 240 V, 48 Ah
Bidirectional DC-DC converter: Enables charging & discharging
Control strategy: Maintains DC bus voltage at 400 V
👉 During low irradiance or nighttime, the battery discharges to support the load.👉 When solar generation is high, the battery charges for later use.👉 SOC (state of charge) management ensures long battery life and efficient usage.
🌐 Grid-Tied Inverter Control
The inverter connects the DC bus to the grid through an LCL filter and uses:
D-Q transformation
PI controllers
Feed-forward decoupling
✅ Manages power exchange with the grid✅ Supplies load demand when PV + battery are insufficient✅ Sends excess power back to the grid when available
📉 Simulation Details
Irradiance levels: 1000 → 500 → 10 W/m² (every 3 seconds)
Simulation length: Demonstrates dynamic response under real-world fluctuations
Results:
Battery charges during high irradiance ☀️
Battery discharges during low irradiance 🌙
Grid imports power when SOC is low 🔌
Grid exports surplus power when PV > load ⚡
📌 Highlights
☀️ Detailed modeling of a 2 kW PV battery grid system🔋 Battery (240V, 48Ah) managed via bidirectional DC-DC converter⚡ P&O MPPT ensures maximum solar power extraction🔄 Dynamic power flow control between PV, battery, grid, and load📉 Simulation shows system response under changing irradiance & SOC🌐 Grid imports power when generation is low and exports excess when available📊 Stable operation through comprehensive control strategy
💡 Key Insights
☀️ PV Array Efficiency – Series connection boosts voltage for stable DC bus operation.
🔄 P&O MPPT Logic – Simple yet effective for tracking maximum power in real time.
⚡ Boost Converter Role – Maintains 400 V DC bus for system stability.
🔋 Battery Management – Bidirectional control enables efficient charging & discharging.
🌐 Grid-Tied Inverter – Ensures smooth synchronization and power quality.
📉 Dynamic Adaptability – Responds quickly to irradiance and SOC variations.
🔍 System Stability – Balanced current flow prevents instability and component stress.
✅ Conclusion
The Grid-Connected PV Battery System with P&O MPPT in MATLAB Simulink demonstrates how solar energy, storage, and grid integration can work in harmony. With maximum power tracking, battery support, and grid interaction, the system ensures:
Reliable power supply 🔌
Efficient energy utilization ⚡
Stable operation under varying conditions 🌞🌙
🚀 This setup highlights the future of smart renewable energy systems, combining control strategies, power electronics, and grid integration for a sustainable energy future.
Comments