Power Management in PV Wind Battery DC Microgrid in MATLAB

Power Management in PV Wind Battery DC Microgrid in MATLAB

𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧

Renewable-energy-based DC microgrids are becoming increasingly important for integrating solar PV, wind energy, battery storage, and DC loads into a common power network.

Power Management in PV Wind Battery DC Microgrid

Power Management in PV Wind Battery DC Microgrid in MATLAB

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This MATLAB/Simulink model demonstrates the complete operation of a PV–Wind–Battery DC Microgrid with intelligent power management. The main objective is to maintain the DC bus voltage at approximately 400 V while continuously balancing the power generated by the PV and wind sources with the load demand.

The system includes:

• Solar PV generation with Incremental Conductance MPPT

• Wind generation using a PMSG

• Wind-side P&O MPPT

• AC–DC rectification for the wind generator

• DC–DC boost converters

• Battery energy storage

• Bidirectional battery converter

• DC-bus voltage regulation

• Dynamic renewable-source variations

• Charging and discharging power management

The model is useful for students, researchers, and power electronics engineers who want to understand renewable DC microgrid control using MATLAB/Simulink.

𝐒𝐲𝐬𝐭𝐞𝐦 𝐎𝐯𝐞𝐫𝐯𝐢𝐞𝐰

The complete DC microgrid contains three main energy sources and one DC load.

Component	Main Function
Solar PV	Supplies renewable DC power
Wind PMSG	Generates variable-frequency AC power
Rectifier	Converts PMSG AC output into DC
Wind Boost Converter	Raises rectified voltage to the DC-bus level
PV Boost Converter	Boosts PV voltage and performs MPPT
Battery	Stores or supplies energy depending on power balance
Bidirectional Converter	Controls battery charging and discharging
DC Bus	Common power-link maintained near 400 V
DC Load	Consumes approximately 3 kW

The power-management system automatically determines whether the battery should charge or discharge according to the instantaneous PV power, wind power, and load demand.

𝐌𝐚𝐢𝐧 𝐒𝐲𝐬𝐭𝐞𝐦 𝐏𝐚𝐫𝐚𝐦𝐞𝐭𝐞𝐫𝐬

The major values discussed in the MATLAB model are summarized below.

Parameter	Approximate Value
Wind generation rating	3000 W
Wind converter input voltage	250 V
Wind converter output voltage	400 V
Wind-side switching frequency	5 kHz
PV power rating	2000 W
PV operating voltage	245–250 V
PV converter output voltage	400 V
Battery configuration	20 × 12 V
Battery nominal voltage	240 V
Battery converter output	400 V
Battery converter switching frequency	10 kHz
DC load power	3000 W
DC-bus reference voltage	400 V

These ratings are used to select the converter components and establish the operating limits of the DC microgrid.

𝐖𝐢𝐧𝐝 𝐄𝐧𝐞𝐫𝐠𝐲 𝐂𝐨𝐧𝐯𝐞𝐫𝐬𝐢𝐨𝐧 𝐒𝐲𝐬𝐭𝐞𝐦

The wind section uses a Permanent Magnet Synchronous Generator (PMSG).

The energy conversion sequence is:

Wind Turbine → PMSG → Rectifier → Boost Converter → 400 V DC Bus

Wind-side operation

• The wind turbine drives the PMSG.

• The PMSG produces three-phase electrical power.

• A rectifier converts the generated AC voltage into DC.

• The resulting DC voltage is approximately 250 V.

• A boost converter increases this voltage to the required 400 V DC bus.

• The converter is controlled using a Perturb and Observe MPPT algorithm.

• Rectifier voltage and current are continuously measured for MPPT operation.

The wind generation shown in the simulation is approximately 2.7–2.8 kW during normal operation.

𝐏&𝐎 𝐌𝐏𝐏𝐓 𝐟𝐨𝐫 𝐖𝐢𝐧𝐝 𝐏𝐨𝐰𝐞𝐫

The wind boost converter uses the Perturb and Observe (P&O) method to obtain maximum power from the wind generation system.

The controller continuously observes:

• Rectifier voltage

• Rectifier current

• Present power

• Previous power

• Present voltage

• Previous voltage

• Duty cycle

The controller determines whether the operating point is moving toward or away from the maximum-power point.

Depending on the observed variation:

• The duty cycle is increased, or

• The duty cycle is decreased, or

• The previous duty cycle is maintained.

Duty-cycle limits are also applied so that the converter operates within its safe control range.

This process executes continuously during simulation and allows the wind converter to track its maximum available power.

𝐒𝐨𝐥𝐚𝐫 𝐏𝐕 𝐒𝐲𝐬𝐭𝐞𝐦

The solar PV array is connected to the common DC bus through a DC–DC boost converter.

The approximate PV-side voltage is around 245–250 V, whereas the required DC-bus voltage is 400 V.

The PV conversion path is:

Solar PV → Boost Converter → 400 V DC Bus

The converter performs two important tasks:

• Voltage boosting

• Maximum power extraction

The PV system uses an Incremental Conductance MPPT algorithm.

𝐈𝐧𝐜𝐫𝐞𝐦𝐞𝐧𝐭𝐚𝐥 𝐂𝐨𝐧𝐝𝐮𝐜𝐭𝐚𝐧𝐜𝐞 𝐌𝐏𝐏𝐓

The Incremental Conductance controller measures the instantaneous PV voltage and current.

The algorithm stores and updates quantities such as:

• Previous PV voltage

• Previous PV current

• Previous PV power

• Present PV voltage

• Present PV current

• Present PV power

• Previous duty cycle

• Present duty cycle

The controller determines whether the PV array is operating:

• Before the maximum-power point

• At the maximum-power point

• After the maximum-power point

Based on this operating condition, the converter duty cycle is adjusted.

Duty-cycle boundaries are checked before the final switching command is sent to the PWM generator.

This allows the PV array to continue extracting maximum available power even when solar irradiance changes.

𝐁𝐚𝐭𝐭𝐞𝐫𝐲 𝐄𝐧𝐞𝐫𝐠𝐲 𝐒𝐭𝐨𝐫𝐚𝐠𝐞

The model uses approximately 20 series-connected 12 V batteries, giving a nominal battery-bank voltage of about 240 V.

The battery connects to the 400 V DC bus through a bidirectional DC–DC converter.

The battery is not simply a backup source. It acts as the main balancing element of the microgrid.

Battery operating modes

Power Condition	Battery Operation
Renewable power > load demand	Charging
Renewable power ≈ load demand	Minimum battery contribution
Renewable power < load demand	Discharging
PV generation falls sharply	Battery increases discharge support
PV and wind produce excess energy	Battery absorbs available surplus

Therefore, the direction of battery current changes automatically according to the renewable generation and load requirement.

𝐁𝐢𝐝𝐢𝐫𝐞𝐜𝐭𝐢𝐨𝐧𝐚𝐥 𝐃𝐂–𝐃𝐂 𝐂𝐨𝐧𝐯𝐞𝐫𝐭𝐞𝐫

The battery converter enables power transfer in both directions.

During discharge

Battery → Bidirectional Converter → DC Bus → Load

The converter raises the battery-side voltage from approximately 240 V toward the 400 V DC-bus level.

During charging

PV/Wind → DC Bus → Bidirectional Converter → Battery

Excess renewable power is transferred back into the battery.

This bidirectional operation is essential because renewable generation continuously varies with environmental conditions.

𝐃𝐂-𝐁𝐮𝐬 𝐕𝐨𝐥𝐭𝐚𝐠𝐞 𝐂𝐨𝐧𝐭𝐫𝐨𝐥

One of the most important objectives of the model is maintaining the common DC bus close to:

𝐕𝐝𝐜 ≈ 𝟒𝟎𝟎 𝐕

The actual DC-bus voltage is compared with the 400 V reference.

The resulting voltage error is processed through a controller to generate the required converter command.

The control path is essentially:

DC-Bus Voltage Measurement → Reference Comparison → PI Control → Duty Cycle → PWM Generator → Bidirectional Converter

When renewable generation changes, the battery converter quickly adjusts its power so that the DC-bus voltage remains almost constant.

𝐏𝐨𝐰𝐞𝐫 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐲

The power-management concept is based on balancing:

PV generation + Wind generation + Battery contribution → Load requirement

The controller continuously evaluates the source and load conditions.

Operating Situation	Expected Response
High PV + high wind	Battery can charge
Low PV + sufficient wind	Wind supplies most of the load
Low PV + insufficient wind	Battery discharges
PV power becomes nearly zero	Battery supplies the renewable-power deficit
Renewable generation increases again	Battery discharge reduces or charging begins
Load remains constant	Battery compensates for source variations

This strategy keeps the load supplied even when renewable power changes rapidly.

𝐒𝐢𝐦𝐮𝐥𝐚𝐭𝐢𝐨𝐧 𝐓𝐞𝐬𝐭 𝐂𝐨𝐧𝐝𝐢𝐭𝐢𝐨𝐧𝐬

The PV irradiance is intentionally varied to verify the response of the energy-management system.

Solar Irradiance	Approximate PV Power
1000 W/m²	2000 W
500 W/m²	1000 W
10 W/m²	Nearly 0 W

This test clearly demonstrates how the battery compensates when solar generation decreases.

𝐒𝐢𝐦𝐮𝐥𝐚𝐭𝐢𝐨𝐧 𝐑𝐞𝐬𝐮𝐥𝐭𝐬

The MATLAB/Simulink results show the dynamic behavior of the complete microgrid.

1. PV voltage

PV voltage changes according to the irradiance and MPPT operating point.

Despite large changes in solar conditions, the PV converter continues adjusting its operating point.

2. PV current

The current decreases significantly when solar irradiance is reduced.

At very low irradiance, PV current approaches a very small value.

3. PV power

The results show approximately:

• 2 kW at 1000 W/m²

• 1 kW at 500 W/m²

• Nearly 0 kW at very low irradiance

This confirms the expected variation of solar power.

𝐖𝐢𝐧𝐝 𝐏𝐨𝐰𝐞𝐫 𝐑𝐞𝐬𝐮𝐥𝐭

The wind generation remains approximately around:

2.7–2.8 kW

after the initial transient.

The wind-side P&O MPPT controller continuously adjusts the boost-converter operating point to extract the available wind energy.

Minor variations visible in the waveform are associated with MPPT operation and converter dynamics.

𝐁𝐚𝐭𝐭𝐞𝐫𝐲 𝐂𝐡𝐚𝐫𝐠𝐢𝐧𝐠 𝐚𝐧𝐝 𝐃𝐢𝐬𝐜𝐡𝐚𝐫𝐠𝐢𝐧𝐠

The battery waveform clearly demonstrates the purpose of the power-management controller.

When sufficient PV and wind power are available:

Battery → Charging Mode

When PV power decreases and the renewable sources cannot completely satisfy the load:

Battery → Discharging Mode

For example, when PV generation falls close to zero, wind generation alone may provide roughly 2.7 kW while the load requires around 3 kW.

The battery then provides the missing power.

As renewable generation changes again, battery power automatically changes direction or magnitude.

𝐃𝐂-𝐋𝐨𝐚𝐝 𝐑𝐞𝐬𝐮𝐥𝐭

The DC load is approximately:

3 kW

Even though PV power changes significantly, the DC load continues receiving the required power because the wind source and battery compensate for the renewable-energy variations.

The load results demonstrate:

• Stable DC-bus voltage

• Approximately constant load current

• Approximately constant load power

• Effective source-power sharing

• Smooth battery compensation

𝐃𝐂-𝐁𝐮𝐬 𝐕𝐨𝐥𝐭𝐚𝐠𝐞 𝐑𝐞𝐬𝐮𝐥𝐭

The simulation shows that the DC bus settles near the required:

400 V

There may be small transient disturbances when source power changes, but the battery voltage-control loop brings the DC bus back to its reference value.

This is an important indication that the energy-management and bidirectional converter control are working correctly.

𝐏𝐨𝐰𝐞𝐫 𝐅𝐥𝐨𝐰 𝐄𝐱𝐚𝐦𝐩𝐥𝐞

A simplified operating example is shown below.

Source / Load	Example Power
Wind generation	~2800 W
PV generation	~2000 W initially
DC load	~3000 W
Battery	Charges or discharges according to power difference

When both renewable sources generate sufficient power, surplus energy can charge the battery.

When PV power decreases, the battery automatically changes its operating condition to maintain the required load power.

𝐂𝐨𝐧𝐭𝐫𝐨𝐥 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐲 𝐒𝐮𝐦𝐦𝐚𝐫𝐲

Subsystem	Control Technique	Main Objective
Wind PMSG	P&O MPPT	Maximum wind-power extraction
Wind Boost Converter	MPPT-based duty control	Boost voltage toward DC-bus level
Solar PV	Incremental Conductance MPPT	Maximum PV-power extraction
PV Boost Converter	MPPT-based PWM	Boost PV voltage to DC bus
Battery	DC-bus voltage control	Maintain approximately 400 V
Bidirectional Converter	PI/PWM control	Battery charging and discharging
DC Bus	Voltage regulation	Stable common DC voltage

𝐖𝐨𝐫𝐤𝐢𝐧𝐠 𝐏𝐫𝐨𝐜𝐞𝐬𝐬

The complete model operation can be understood in the following sequence:

1. Wind energy drives the PMSG.

2. PMSG AC output is converted into DC using a rectifier.

3. The wind boost converter increases the rectified voltage to the DC-bus level.

4. P&O MPPT extracts maximum available wind power.

5. The solar PV array supplies power through another boost converter.

6. Incremental Conductance MPPT tracks maximum PV power.

7. Both renewable sources feed the 400 V DC bus.

8. The DC load continuously draws approximately 3 kW.

9. The controller evaluates the difference between generation and demand.

10. The battery charges when excess renewable power is available.

11. The battery discharges when renewable power is insufficient.

12. The bidirectional converter regulates the common DC-bus voltage.

𝐊𝐞𝐲 𝐅𝐞𝐚𝐭𝐮𝐫𝐞𝐬

• PV–Wind–Battery hybrid DC microgrid

• 400 V regulated DC bus

• 3 kW wind generation system

• 2 kW solar PV system

• 3 kW DC load

• PMSG-based wind-energy conversion

• Wind-side rectifier and boost converter

• P&O MPPT for wind generation

• Incremental Conductance MPPT for solar PV

• Bidirectional battery converter

• Automatic battery charging and discharging

• Dynamic solar irradiance testing

• Renewable-source power balancing

• DC-bus voltage regulation

• Complete MATLAB/Simulink implementation

• Source, battery, load and DC-bus waveform analysis

𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬

This MATLAB model is useful for studying:

• Renewable-energy DC microgrids

• PV and wind hybrid generation

• Battery energy-storage control

• DC distribution networks

• Hybrid renewable power systems

• PMSG-based wind generation

• MPPT controller development

• Bidirectional converter control

• Energy-management strategies

• DC-bus voltage regulation

• Renewable power-sharing analysis

• Battery charging and discharging behavior

𝐖𝐡𝐚𝐭 𝐂𝐚𝐧 𝐁𝐞 𝐋𝐞𝐚𝐫𝐧𝐞𝐝 𝐟𝐫𝐨𝐦 𝐓𝐡𝐢𝐬 𝐌𝐨𝐝𝐞𝐥?

By studying this simulation, users can understand:

• How PV and wind sources are integrated into one DC bus.

• Why separate MPPT techniques are required for different renewable sources.

• How a PMSG-based wind generation system connects to a DC microgrid.

• How DC–DC boost converters interface renewable sources.

• How a battery balances renewable-power fluctuations.

• How bidirectional power flow is achieved.

• How a DC bus can be maintained near a fixed voltage.

• How irradiance variation affects PV power.

• How battery power changes according to generation and load demand.

• How different source powers combine to satisfy a constant DC load.

𝐀𝐝𝐯𝐚𝐧𝐭𝐚𝐠𝐞𝐬 𝐨𝐟 𝐭𝐡𝐞 𝐏𝐫𝐨𝐩𝐨𝐬𝐞𝐝 𝐏𝐨𝐰𝐞𝐫 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭

The system offers several important advantages:

• Better utilization of renewable energy

• Reduced impact of intermittent PV generation

• Continuous load-power support

• Stable DC-link operation

• Automatic source-power balancing

• Effective battery utilization

• Maximum renewable-power extraction

• Smooth transition between battery charging and discharging

• Independent MPPT control for PV and wind sources

• Easy analysis of different renewable operating conditions

𝐂𝐨𝐧𝐜𝐥𝐮𝐬𝐢𝐨𝐧

The Power Management in PV Wind Battery DC Microgrid in MATLAB model demonstrates an effective method for integrating solar PV, wind generation, battery storage, and a DC load through a regulated common DC bus.

The P&O MPPT controller extracts available power from the PMSG-based wind generation system, while the Incremental Conductance MPPT controller tracks maximum power from the solar PV array.

When renewable generation exceeds the load demand, the battery absorbs the surplus energy. When generation becomes insufficient, the battery automatically supplies the required deficit.

Simulation results demonstrate that the system can maintain the DC bus close to 400 V, keep the 3 kW DC load supplied, and dynamically manage battery charging and discharging during variations in solar generation.

Overall, the model provides a clear MATLAB/Simulink platform for understanding renewable energy integration, MPPT control, bidirectional conversion, battery energy management, and DC microgrid power balancing.