Fuzzy Energy Management in Grid Connected PV Battery Energy Storage System

Fuzzy Energy Management in Grid Connected PV Battery Energy Storage System

𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧

This MATLAB/Simulink model demonstrates the operation of a grid-connected solar PV system integrated with battery energy storage. A fuzzy logic energy management system coordinates power flow among the PV array, battery, AC load, and utility grid.

Fuzzy Energy Management in Grid Connected PV Battery Energy Storage System

Fuzzy Energy Management in grid connected pv battery system in matlab

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The model is designed to:

• Extract maximum available power from the PV array

• Maintain the DC-link voltage at 400 V

• Control battery charging and discharging

• Import power from the grid during an energy deficit

• Export surplus PV and battery power to the grid

• Maintain stable grid frequency and sinusoidal current

The complete system combines MPPT control, bidirectional converter control, fuzzy energy management, PLL synchronization, current control, and grid-connected inverter operation.

𝐒𝐲𝐬𝐭𝐞𝐦 𝐎𝐯𝐞𝐫𝐯𝐢𝐞𝐰

The simulated system consists of the following major components:

• Solar PV array

• Boost converter

• Incremental Conductance MPPT controller

• Battery energy storage system

• Bidirectional DC–DC converter

• Common 400 V DC bus

• Single-phase full-bridge inverter

• LCL output filter

• Fuzzy logic energy management system

• Utility grid and AC load

• PLL-based grid synchronization

• Current control system

Main System Parameters

Parameter	Value
Individual PV panel rating	250 W
PV panel voltage at maximum power	30.7 V
Panels connected in series	8
Parallel PV strings	2
Power per string	2 kW
Total PV array power	4 kW
Approximate PV string voltage	245.6 V
DC-link voltage	400 V
Battery voltage	240 V
Battery arrangement	20 × 12 V
Bidirectional converter switching frequency	10 kHz
Inverter and filter design power	5 kW
Inverter switching frequency	7.5 kHz
Grid voltage	230 V
Grid frequency	50 Hz

𝐏𝐕 𝐀𝐫𝐫𝐚𝐲 𝐂𝐨𝐧𝐟𝐢𝐠𝐮𝐫𝐚𝐭𝐢𝐨𝐧

The PV array contains 16 solar panels.

• Eight panels are connected in series to form one string.

• Two identical strings are connected in parallel.

• Each panel is rated at 250 W.

• One series string produces approximately 2 kW.

• Two parallel strings provide a total rated power of 4 kW.

PV Array Summary

Configuration	Calculation	Result
Power of one series string	8 × 250 W	2,000 W
Total PV array power	2 × 2,000 W	4,000 W
Voltage of one series string	8 × 30.7 V	245.6 V
Total number of panels	8 × 2	16

The boost converter raises the PV voltage from approximately 245.6 V to the regulated 400 V DC bus.

𝐖𝐨𝐫𝐤𝐢𝐧𝐠 𝐏𝐫𝐨𝐜𝐞𝐬𝐬

1. Solar Power Generation

The PV array generates power according to the available solar irradiation. Its voltage and current are continuously measured.

2. Maximum Power Point Tracking

The measured PV voltage and current are supplied to the Incremental Conductance MPPT algorithm.

The MPPT controller determines the required duty cycle and sends it to the PWM generator. The resulting gate pulse controls the boost-converter IGBT.

This process performs two functions:

• Extracts the maximum available PV power

• Boosts the PV voltage to the required DC-link level

3. DC-Link Voltage Regulation

The bidirectional DC–DC converter connects the 240 V battery to the 400 V DC bus.

The measured DC-link voltage is compared with the reference voltage. A PI controller processes the voltage error and produces the converter duty cycle.

The converter then regulates the DC-link voltage by controlling battery power in both directions.

4. Battery Charging and Discharging

The battery supports the system during variations in PV generation and load demand.

• The battery charges when surplus power is available.

• The battery discharges when PV generation is insufficient and its SoC permits discharge.

• The grid can charge the battery when the battery SoC is low.

• Battery current changes direction according to the charging or discharging mode.

5. Grid Power Exchange

The full-bridge inverter enables bidirectional power exchange between the DC system and the utility grid.

• Surplus DC-side power is exported to the AC side.

• Grid power is imported when PV and battery power are insufficient.

• The power-flow direction is determined by the fuzzy energy management system.

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𝐂𝐨𝐧𝐭𝐫𝐨𝐥 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐲

𝐈𝐧𝐜𝐫𝐞𝐦𝐞𝐧𝐭𝐚𝐥 𝐂𝐨𝐧𝐝𝐮𝐜𝐭𝐚𝐧𝐜𝐞 𝐌𝐏𝐏𝐓

The PV boost converter is controlled using the Incremental Conductance MPPT method.

Controller Inputs

• PV voltage

• PV current

Controller Output

• Boost-converter duty cycle

Control Sequence

1. Measure PV voltage and current.

2. Estimate the PV operating condition.

3. Determine the required duty cycle.

4. Generate the PWM switching pulse.

5. Control the boost-converter IGBT.

6. Track the maximum available PV power.

This control method allows the PV system to respond to changing irradiation conditions.

𝐁𝐢𝐝𝐢𝐫𝐞𝐜𝐭𝐢𝐨𝐧𝐚𝐥 𝐂𝐨𝐧𝐯𝐞𝐫𝐭𝐞𝐫 𝐂𝐨𝐧𝐭𝐫𝐨𝐥

The battery converter uses a DC-link voltage control method.

Control Sequence

• Measure the DC-link voltage.

• Compare it with the 400 V reference.

• Process the error using a PI controller.

• Generate the required PWM duty cycle.

• Control the bidirectional converter switches.

• Charge or discharge the battery as required.

This controller helps maintain a stable DC bus even when PV generation changes rapidly.

𝐅𝐮𝐳𝐳𝐲 𝐄𝐧𝐞𝐫𝐠𝐲 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭

The fuzzy logic controller determines the inverter current reference based on two operating variables:

• PV power

• Battery state of charge

Both inputs are converted into per-unit values before entering the fuzzy controller.

Fuzzy Controller Inputs and Output

Signal	Actual Range	Normalized Range
PV power	0–4,000 W	0–1 p.u.
Battery SoC	0–100%	0–1 p.u.
Current reference	Control-dependent	−1.3 to +1.3 p.u.

The fuzzy current reference is multiplied by a scaling factor of 10 to obtain the inverter current command.

Input Membership Functions

Input	Membership Levels
PV power	Zero, Small, Medium, Big
Battery SoC	Zero, Small, Medium, Big, Very Big

The fuzzy output represents different levels of grid import and export current.

General Fuzzy Decisions

PV Power	Battery SoC	Current Reference	Operating Decision
Low	Low	Strong negative	Import power from grid
Low	Medium	Negative	Grid supports the DC system
Medium	Medium	Near zero	Balanced power exchange
High	Medium	Positive	Supply power to AC load or grid
High	High	Strong positive	Export surplus power to grid

A negative current reference indicates grid power import, while a positive current reference indicates power transfer from the DC system to the AC side.

𝐈𝐧𝐯𝐞𝐫𝐭𝐞𝐫 𝐂𝐨𝐧𝐭𝐫𝐨𝐥

The grid-connected inverter uses a synchronized current-control structure.

Main Control Steps

1. Measure the grid voltage.

2. Process the voltage through a PLL.

3. Generate a synchronized sinusoidal reference.

4. Multiply the fuzzy output by the synchronized waveform.

5. Convert the reference signal into the control frame.

6. Measure the actual grid current.

7. Compare the measured and reference currents.

8. Process the current errors through PI controllers.

9. Generate inverter modulation signals.

10. Produce PWM gate pulses for the full-bridge inverter.

This structure controls both the magnitude and direction of grid current.

𝐏𝐋𝐋 𝐚𝐧𝐝 𝐆𝐫𝐢𝐝 𝐒𝐲𝐧𝐜𝐡𝐫𝐨𝐧𝐢𝐳𝐚𝐭𝐢𝐨𝐧

The phase-locked loop tracks the phase angle and frequency of the utility voltage.

The PLL provides:

• Grid phase angle

• Sine and cosine reference signals

• Frequency measurement

• Synchronization for inverter current control

Proper synchronization ensures stable operation at the point of common coupling.

𝐋𝐂𝐋 𝐅𝐢𝐥𝐭𝐞𝐫 𝐃𝐞𝐬𝐢𝐠𝐧

An LCL filter is placed between the inverter and the grid to reduce switching harmonics.

The filter is designed using the following system ratings:

Design Parameter	Value
Rated power	5 kW
DC-link voltage	400 V
AC voltage	230 V
Grid frequency	50 Hz
Switching frequency	7.5 kHz

The filter contains:

• Inverter-side inductor

• Grid-side inductor

• Filter capacitor

It improves the quality of the current injected into or drawn from the grid.

𝐓𝐞𝐬𝐭𝐞𝐝 𝐈𝐫𝐫𝐚𝐝𝐢𝐚𝐭𝐢𝐨𝐧 𝐏𝐫𝐨𝐟𝐢𝐥𝐞

The system is evaluated under changing solar irradiation to test the response of the MPPT, battery, and energy management controllers.

Operating Interval	Irradiation	Approximate PV Power
Initial high-irradiation period	1,000 W/m²	4,000 W
Reduced-irradiation period	500 W/m²	2,000 W
Very-low-irradiation period	10 W/m²	Near zero
Recovery period	500 W/m²	2,000 W
Final high-irradiation period	1,000 W/m²	4,000 W

The PV power changes according to irradiation while the battery and grid compensate for the resulting power imbalance.

𝐒𝐢𝐦𝐮𝐥𝐚𝐭𝐢𝐨𝐧 𝐑𝐞𝐬𝐮𝐥𝐭𝐬

The simulation scopes display the following variables:

• PV voltage

• PV current

• PV power

• DC-link voltage

• Battery voltage

• Battery current

• Battery SoC

• Load power

• Grid power

• Grid voltage

• Grid current

• System frequency

PV Performance

The PV system follows the irradiation profile:

• Approximately 4 kW at 1,000 W/m²

• Approximately 2 kW at 500 W/m²

• Nearly zero power at 10 W/m²

• Recovery to rated power when irradiation returns to 1,000 W/m²

Small initial oscillations can appear while the DC voltage and MPPT controller settle.

DC-Link Performance

The bidirectional converter regulates the common DC bus close to 400 V despite changes in PV power and battery current.

Battery Performance

Battery current changes according to the power balance:

• Charging occurs when excess PV or grid power is available.

• Discharging occurs when additional DC-side power is required.

• SoC increases during charging.

• SoC decreases during discharging.

Grid Voltage and Current

The grid voltage and current remain sinusoidal.

Their phase relationship indicates the power-flow direction:

Voltage–Current Relationship	Power-Flow Condition
Corresponding export phase relationship	Power supplied from the inverter to the grid
Opposite import phase relationship	Power drawn from the grid
Small current magnitude	Limited grid power exchange

Frequency Response

The grid frequency is maintained close to 50 Hz during irradiation changes and power-flow transitions.

𝐋𝐨𝐰-𝐒𝐨𝐂 𝐎𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧

A separate operating condition is tested with the battery SoC set to approximately 10%.

Under this condition:

• Battery discharge is restricted.

• The inverter current reference becomes negative.

• Power is imported from the grid.

• The battery operates mainly in charging mode.

• Grid power supports the load when PV power falls.

• The battery SoC gradually increases.

• Grid frequency remains close to 50 Hz.

This test demonstrates the ability of the fuzzy controller to protect a low-SoC battery while maintaining system operation.

𝐊𝐞𝐲 𝐅𝐞𝐚𝐭𝐮𝐫𝐞𝐬

• 4 kW solar PV array with changing irradiation

• Incremental Conductance MPPT control

• PV boost converter for voltage step-up

• 240 V battery energy storage system

• Bidirectional battery charging and discharging

• Regulated 400 V DC link

• Fuzzy logic energy management system

• PV power and battery SoC-based decision-making

• Per-unit input normalization

• Bidirectional grid power exchange

• PLL-based grid synchronization

• Current-controlled full-bridge inverter

• LCL filter for harmonic reduction

• Grid voltage, current, power, and frequency measurement

• Low-battery-SoC operating mode

• MATLAB/Simulink-based implementation

  
  

𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬

This simulation model is useful for studying:

• Grid-connected photovoltaic systems

• Battery energy storage integration

• Renewable energy power management

• Fuzzy logic controller development

• Smart-grid power-flow control

• Residential solar battery systems

• Bidirectional inverter operation

• Grid import and export management

• DC microgrid control

• Energy storage charging strategies

• Power-electronic converter control

• MPPT algorithm performance

• Grid synchronization techniques

• Renewable energy teaching and laboratory demonstrations

  
  

𝐖𝐡𝐚𝐭 𝐂𝐚𝐧 𝐁𝐞 𝐋𝐞𝐚𝐫𝐧𝐞𝐝

By studying this model, users can understand:

• How PV panels are configured to obtain the required power

• How a boost converter raises the PV voltage

• How MPPT extracts maximum PV power

• How a battery is connected through a bidirectional converter

• How DC-link voltage is regulated

• How fuzzy rules determine grid current reference

• How PV power and battery SoC are normalized

• How an inverter exchanges power in both directions

• How a PLL synchronizes the inverter with the grid

• How grid voltage and current indicate import or export operation

• How the system responds to rapid changes in solar irradiation

  
  

𝐂𝐨𝐧𝐜𝐥𝐮𝐬𝐢𝐨𝐧

The Simulation of Fuzzy Energy Management in Grid Connected PV Battery Energy Storage System demonstrates coordinated operation of a solar PV array, battery storage unit, bidirectional converters, inverter, load, and utility grid.

The Incremental Conductance MPPT controller extracts the available PV power, while the bidirectional converter maintains the 400 V DC-link voltage. The fuzzy logic controller uses normalized PV power and battery SoC to determine whether the system should import power, export power, charge the battery, or support the load.

Simulation results show effective operation under changing irradiation, low battery SoC, and bidirectional power-flow conditions. The model provides a practical platform for students, researchers, and engineers interested in renewable energy integration, intelligent energy management, and grid-connected power-electronic systems.