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Grid connected PV Wind and Battery with Fuzzy MPPT

Grid connected PV Wind and Battery with Fuzzy MPPT

Introduction

Welcome to LMS Solution! In today's discussion, we'll delve into the intricacies of a connected battery system equipped with a Fuzzy MPPT (Maximum Power Point Tracking) algorithm. This algorithm is implemented not only for solar PV systems but also for wind energy conversion systems, ensuring optimal power extraction from both wind and solar sources.



Wind Energy Conversion System

Let's start by exploring the Wind Energy Conversion System. The primary components include a wind turbine, a Permanent Magnet Synchronous Generator (PMSG), a rectifier boost converter, and a DC bus maintaining a voltage of 400 volts. The wind turbine has a maximum rating of three kilowatts. The boost converter is controlled by a Fuzzy MPPT algorithm, taking inputs from the rectifier voltage and differential current. The Fuzzy Logic Controller generates a duty cycle, controlling the MOSFET of the boost converter to extract maximum power from the wind energy conversion system.

Solar PV System

Moving on to the Solar PV System, rated at 2000 watts, it is connected to the DC bus through a boost converter. Similar to the wind energy system, the boost converter here is controlled by a CMP BTL controller. The Fuzzy MPPT algorithm takes inputs from PV voltage and current, generating a duty cycle to optimize power extraction.

Battery Energy Conversion System

In the Battery Energy Conversion System, a 220-volt battery with a capacity of 40 ampere-hours is connected to a bidirectional converter. The converter, maintaining the DC bus voltage at 400 volts, is controlled via a voltage control method. The DC bus voltage, combined with a reference voltage, undergoes a comparison, and the error is processed by a PI controller. The generated duty cycle is then used to control the bidirectional converter, ensuring optimal DC voltage maintenance.

Grid Integration

The system is integrated with the grid, featuring a 230-volt RMS, 50 Hz supply. Two loads, initially 1000 watts and later 1400 watts, are connected to an LCL filter and an inverter. The inverter is controlled using a kernel control concept, determining the reference current based on the associated PV current. The system intelligently decides whether to draw power from or supply power to the grid based on predefined conditions.

Simulation Model

The simulation model accounts for changing parameters such as wind speed, irradiation, AC load, DC load, and more. The simulation results provide insights into the behavior of the PV, wind, and battery systems, as well as their interactions with the grid.

Results

Detailed results showcase the dynamic nature of PV power, wind power, battery charging, and grid interactions. The system responds to varying conditions, adjusting power flow to and from the grid based on predefined logic and control algorithms.

Conclusion

In conclusion, the connected battery system with a Fuzzy MPPT algorithm demonstrates effective power extraction from both solar and wind sources. The integration with the grid allows for dynamic responses to changing conditions, optimizing power flow in a sustainable and efficient manner.

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