⚡ 100 kW Grid-Connected PV System with Fuzzy & P&O MPPT: A Comparative Study 🌞🔋

The growing demand for renewable energy has pushed solar photovoltaic (PV) systems to the forefront of sustainable power generation. One of the most critical aspects of PV systems is maximum power point tracking (MPPT), which ensures the highest possible power extraction under varying environmental conditions.

In this blog, we explore a 100 kW grid-connected PV system and compare two popular MPPT techniques:👉 Fuzzy Logic MPPT (F-MPPT)👉 Perturb & Observe MPPT (P&O)

🌞 PV System Configuration

• PV Panels: 330 W modules

• Arrangement: 5 panels in series per string × 66 parallel strings

• Peak Power: ~100.7 kW at 1000 W/m² irradiance

• Boost Converter: Controlled by MPPT algorithms

• Inverter: Three-level inverter with dq-axis control

• Transformer: Step-up from 260 V to 23 kV for grid integration

🤖 Fuzzy Logic MPPT (F-MPPT)

The fuzzy MPPT controller uses intelligent decision-making to extract maximum power.

• Inputs:🔹 Power difference (ΔP)🔹 Voltage difference (ΔV)🔹 Rate of change of ΔP & ΔV

• Controller: A fuzzy inference system with 14 rules

• Output: Duty cycle adjustment for the boost converter

👉 This method adapts quickly to changing irradiance and temperature, ensuring smoother and more stable tracking of the maximum power point.

⚙️ Inverter Control for Grid Synchronization

The inverter control employs:

• dq-axis transformations

• PI controllers

• Feed-forward decoupling control

✅ Ensures stable synchronization with the grid✅ Regulates real power injection while maintaining zero reactive power

📊 Simulation Setup

The PV system was tested under:

• Irradiance variation: 1000 W/m² → 250 W/m²

• Temperature range: 2°C → 50°C

Parameters monitored:

• Power output

• Duty cycle behavior

• Inverter voltage & modulation index

• Grid-injected power

🔑 Key Findings

✨ Fuzzy Logic MPPT (F-MPPT)

• Faster convergence to maximum power point ⚡

• Higher power output under dynamic conditions 🌞

• Stable duty cycle → less stress on power electronics 🔧

• Improved grid power injection 📈

✨ Perturb & Observe (P&O)

• Slower response and more oscillations 🔄

• Less efficient under rapidly changing irradiance 🌥️

• Continuous duty cycle variations → higher component stress

📌 Highlights

⚡ Comprehensive comparison between fuzzy MPPT and P&O MPPT in a 100 kW PV system🔋 PV array configuration: 330 W panels, 5S × 66P → 100.7 kW peak🔄 Fuzzy logic MPPT explained with 14-rule inference system⚙️ dq-axis inverter control ensures stable grid connection🌞 Simulation tested across wide irradiance & temperature range📊 F-MPPT outperforms P&O with higher efficiency & stability

💡 Key Insights

1. ⚡ Higher Efficiency with Fuzzy Logic – Handles nonlinearities better, extracts more power.

2. 🔄 Stable Duty Cycle – Reduces oscillations, improves reliability.

3. 🌞 Environment Impact – Higher temperature reduces PV power; fuzzy adapts better.

4. ⚙️ Advanced Inverter Control – Ensures smooth synchronization with the grid.

5. 📈 Faster Dynamic Response – Reaches peak power quickly under changing conditions.

✅ Conclusion

This comparative study shows that Fuzzy Logic MPPT (F-MPPT) is superior to the traditional P&O MPPT for a 100 kW grid-connected PV system. It achieves:

• Faster response ⏱️

• Higher efficiency ⚡

• More stable performance 🔋

As the renewable energy sector grows, adopting advanced intelligent control methods like fuzzy logic can significantly enhance energy yield and improve grid integration.