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DC Microgrid Operation and Control in MATLAB

DC Microgrid Operation and Control in MATLAB


Introduction

We will discuss the simulation model of a DC microgrid developed using MATLAB. This model incorporates a solar PV system, a battery energy storage system, and a supercapacitor, all connected to a DC bus through various converters. We will delve into the components of this model, the control strategies employed, and the results obtained from simulating different irradiation conditions.




Model Components and Configuration

The DC microgrid model consists of several key components:

  1. Solar PV System: The PV system, with a small rating for demonstration purposes, is connected to the DC bus via a boost converter.

  2. Battery Energy Storage System: Two lithium-ion batteries rated at 3.6V each are connected in series and linked to the DC bus via a bidirectional converter.

  3. Supercapacitor: A supercapacitor with a rating of 58 farads and a voltage of 16V is also connected to the DC bus through a bidirectional converter.

  4. DC Load: A DC load with a power rating of 4 watts is integrated into the system.

  5. Voltage Regulation: The DC bus voltage is maintained at 24V.

Designing Converters

The design of the converters involves calculating the inductance (L) and capacitance (C) values based on the voltage levels of the PV system, battery, and supercapacitor. The boost converter for the PV system is controlled using an incremental conductance Maximum Power Point Tracking (MPPT) algorithm to maximize power extraction under varying irradiation conditions.

Control Strategies

The bidirectional DC-DC converters for the battery and supercapacitor are controlled using voltage and current control techniques:

  • Voltage Control: The load voltage or DC bus voltage is measured and compared with a reference voltage. The error is processed through a PI controller to generate a current reference.

  • Current Control: The current reference for the battery and supercapacitor is filtered to remove oscillations and compared with their actual currents. The error is then used to generate the duty cycle for the PWM generator, which controls the converters.



Simulation Setup

The simulation involves changing the irradiation conditions every two seconds to test the system's response:

  • Irradiation Levels: The irradiation is varied from 1000 to 800, 500, 300, and 100 W/m², and then increased back to 300, 500, and 800 W/m².

  • Monitoring Parameters: The PV voltage, current, and power; battery voltage, current, and power; supercapacitor voltage, current, and power; State of Charge (SoC) of the battery; and DC bus voltage regulation are monitored.

Results and Discussion

The results from the simulation demonstrate the system's ability to maintain the DC bus voltage at 24V and effectively manage power distribution between the PV system, battery, and supercapacitor under varying irradiation conditions:

  • PV System Performance: The PV system's power output adjusts according to the irradiation levels, with the incremental conductance MPPT algorithm ensuring maximum power extraction.

  • Battery and Supercapacitor Dynamics: During transitions in irradiation, the supercapacitor responds quickly to supply or absorb power, while the battery adjusts its charging and discharging states to maintain power balance.

  • DC Load and Bus Voltage: The DC load remains stable at 4 watts, and the DC bus voltage is consistently regulated at 24V, demonstrating the effectiveness of the control strategies.

Conclusion

The MATLAB simulation model of the DC microgrid showcases the integration and control of a solar PV system, battery energy storage, and supercapacitor. By employing advanced control strategies and MPPT algorithms, the system efficiently manages power distribution and maintains voltage stability under varying conditions. This model serves as a valuable tool for understanding the dynamics and operation control of DC microgrids.

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