Grid Connected PV Wind and Battery with Fuzzy MPPT
Grid Connected PV Wind and Battery with Fuzzy MPPT
𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧
A Grid Connected PV Wind and Battery with Fuzzy MPPT system combines solar photovoltaic generation, wind energy, battery storage, DC and AC loads, and a utility grid into a single coordinated renewable energy system.
Grid Connected PV Wind and Battery with Fuzzy MPPT
In this MATLAB/Simulink model, Fuzzy Logic MPPT is applied independently to the PV and wind energy conversion systems to extract maximum available renewable power. A bidirectional DC–DC converter regulates the common 400 V DC bus, while a grid-connected inverter manages bidirectional power exchange with the utility grid.
Hybrid renewable energy systems are useful when a single renewable source cannot provide continuous power.
This model combines:
☀️ Solar PV system
🌬️ Wind energy conversion system
🔋 Battery energy storage
🔄 Bidirectional DC–DC converter
⚡ Grid-connected inverter
🏠 AC load
🔌 DC load
🧠 Fuzzy Logic MPPT control
The main objectives are to:
Extract maximum available power from solar PV.
Extract maximum available power from the wind turbine.
Maintain the DC-link voltage at 400 V.
Charge or discharge the battery according to power balance.
Exchange power between the renewable system and utility grid.
Maintain stable operation during changes in irradiance, wind speed, and load.
𝐒𝐲𝐬𝐭𝐞𝐦 𝐎𝐯𝐞𝐫𝐯𝐢𝐞𝐰
The complete MATLAB/Simulink system contains several interconnected subsystems.
Subsystem | Main Components | Function |
Wind system | Wind turbine, PMSG, rectifier, boost converter | Wind power generation |
Solar PV | PV array and boost converter | Solar power generation |
Wind MPPT | Fuzzy logic controller | Maximum wind power extraction |
PV MPPT | Fuzzy logic controller | Maximum PV power extraction |
Battery | Battery and bidirectional converter | Energy storage |
DC bus | Common DC link | Power coupling and distribution |
DC load | DC electrical load | Consumes DC power |
Grid inverter | Full-bridge inverter | Grid power exchange |
Filter | LCL filter | Improves grid-side waveform |
AC load | Grid-connected AC load | Consumes AC power |
Grid | Utility AC supply | Imports or receives power |
The PV, wind, and battery systems are connected through a common DC bus before interfacing with the AC grid.
𝐌𝐚𝐢𝐧 𝐒𝐲𝐬𝐭𝐞𝐦 𝐏𝐚𝐫𝐚𝐦𝐞𝐭𝐞𝐫𝐬
Parameter | Value |
DC bus reference voltage | 400 V |
Wind energy system rating | 3 kW |
Solar PV rating | 2 kW |
Battery nominal voltage | Approximately 220 V |
Battery capacity | 40 Ah |
Grid RMS voltage | 230 V |
Grid frequency | 50 Hz |
Initial AC load | 1000 W |
Additional AC load | 1400 W |
AC load after 2 s | 2400 W |
DC load | 1000 W |
Initial wind speed | 12 m/s |
Wind speed after 2 s | 10.8 m/s |
These operating values are used to test the response of the hybrid system under changing source and load conditions.
𝐖𝐢𝐧𝐝 𝐄𝐧𝐞𝐫𝐠𝐲 𝐂𝐨𝐧𝐯𝐞𝐫𝐬𝐢𝐨𝐧 𝐒𝐲𝐬𝐭𝐞𝐦
The wind energy conversion section consists of:
Wind turbine
Permanent Magnet Synchronous Generator (PMSG)
Rectifier
DC–DC boost converter
Fuzzy MPPT controller
PWM generator
The wind turbine drives the PMSG.
The generated AC voltage is converted into DC using the rectifier. The rectified output then passes through the boost converter before reaching the common DC bus.
The wind subsystem is rated at approximately 3 kW.
𝐅𝐮𝐳𝐳𝐲 𝐌𝐏𝐏𝐓 𝐟𝐨𝐫 𝐖𝐢𝐧𝐝 𝐄𝐧𝐞𝐫𝐠𝐲
The wind MPPT controller receives:
Rectifier voltage
Rectifier current
From these measurements, the controller determines:
Present wind power
Previous wind power
Change in power
Change in rectifier voltage
Operating-point slope
Error
Change in error
The error and change in error are supplied to the Fuzzy Logic Controller.
The fuzzy controller produces the required:
Duty-cycle command
PWM switching command
Boost-converter control signal
By continuously adjusting the boost-converter duty cycle, the controller tracks the operating point that provides maximum available wind power.
𝐒𝐨𝐥𝐚𝐫 𝐏𝐕 𝐒𝐲𝐬𝐭𝐞𝐦
The solar PV subsystem has a rated output of approximately 2000 W.
Its major components are:
Solar PV array
PV voltage measurement
PV current measurement
Fuzzy MPPT controller
PWM generator
Boost converter
The PV array is connected to the 400 V DC bus through a boost converter.
𝐅𝐮𝐳𝐳𝐲 𝐌𝐏𝐏𝐓 𝐟𝐨𝐫 𝐒𝐨𝐥𝐚𝐫 𝐏𝐕
The PV Fuzzy MPPT receives two main inputs:
PV voltage
PV current
The controller continuously evaluates changes in PV operating conditions.
It determines:
Variation in PV power
Variation in PV voltage
MPPT error
Change in MPPT error
These signals are processed by the Fuzzy Logic Controller to determine the required duty cycle.
The duty cycle is sent to the PWM generator, which controls the boost-converter switch.
This enables the PV array to operate close to its maximum power point even when solar irradiance changes rapidly.
𝐏𝐕 𝐈𝐫𝐫𝐚𝐝𝐢𝐚𝐧𝐜𝐞 𝐂𝐨𝐧𝐝𝐢𝐭𝐢𝐨𝐧𝐬
The simulation tests the PV system under several irradiance levels.
Simulation Time | Solar Irradiance | Approx. PV Power |
Initial condition | 1000 W/m² | 2000 W |
Around 0.3 s | 500 W/m² | 1000 W |
Around 0.6 s | 10 W/m² | Near 0 W |
Around 0.9 s | 500 W/m² | Around 1000 W |
After 1.2 s | 1000 W/m² | Around 2000 W |
This variation is useful for observing the dynamic tracking performance of the Fuzzy MPPT controller.
𝐏𝐕 𝐑𝐞𝐬𝐩𝐨𝐧𝐬𝐞
At 1000 W/m², the PV array operates close to its rated output of 2 kW.
When irradiance decreases:
PV current decreases significantly.
PV output power decreases.
PV voltage changes according to the operating condition.
The Fuzzy MPPT adjusts the boost-converter duty cycle.
Typical values observed in the simulation include:
Condition | Approximate Value |
PV power at 1000 W/m² | 2000 W |
PV power at 500 W/m² | 1000 W |
PV power at 10 W/m² | Near 0 W |
PV current at high irradiance | Around 8 A |
PV current at 500 W/m² | Around 4 A |
PV voltage during normal operation | Around 245 V |
PV voltage at very low irradiance | Around 50 V |
The response shows that PV power closely follows the available solar energy.
𝐁𝐚𝐭𝐭𝐞𝐫𝐲 𝐄𝐧𝐞𝐫𝐠𝐲 𝐒𝐭𝐨𝐫𝐚𝐠𝐞
The battery is connected to the common DC bus through a bidirectional DC–DC converter.
Its main purposes are:
Absorb excess renewable energy.
Supply power when renewable generation is insufficient.
Support DC-bus voltage regulation.
Improve overall power balance.
Reduce sudden variations in DC-link power.
The battery current can therefore flow in both directions.
𝐁𝐚𝐭𝐭𝐞𝐫𝐲 𝐏𝐚𝐫𝐚𝐦𝐞𝐭𝐞𝐫𝐬
Parameter | Value |
Battery voltage | Approximately 220 V |
Battery capacity | 40 Ah |
DC bus reference | 400 V |
Converter | Bidirectional DC–DC |
Control method | DC-link voltage control |
Power flow | Charging and discharging |
𝐃𝐂-𝐁𝐮𝐬 𝐕𝐨𝐥𝐭𝐚𝐠𝐞 𝐂𝐨𝐧𝐭𝐫𝐨𝐥
A major objective of the battery converter is to maintain the DC bus close to 400 V.
The controller performs the following steps:
Measure the actual DC-bus voltage.
Compare it with the 400 V reference.
Generate a DC-link voltage error.
Process the error using a PI controller.
Generate the required duty-cycle command.
Send the duty cycle to the PWM generator.
Control the bidirectional converter switches.
Charge or discharge the battery as required.
This control method helps maintain stable DC-link voltage despite changes in PV power, wind power, and load.
𝐖𝐢𝐧𝐝 𝐒𝐩𝐞𝐞𝐝 𝐓𝐞𝐬𝐭 𝐂𝐨𝐧𝐝𝐢𝐭𝐢𝐨𝐧
The wind turbine is also tested under changing wind speed.
Time Range | Wind Speed | Approx. Wind Power |
0–2 s | 12 m/s | Around 3000 W |
After 2 s | 10.8 m/s | Around 2100 W |
When wind speed decreases from 12 m/s to 10.8 m/s, the available wind power also decreases.
The Fuzzy MPPT adjusts the boost converter to extract the maximum available power at the new operating condition.
𝐀𝐂 𝐚𝐧𝐝 𝐃𝐂 𝐋𝐨𝐚𝐝𝐬
The model contains both AC and DC loads.
DC Load
The DC load is approximately:
1000 W
It is directly supplied through the common DC system.
AC Load
The AC load changes during the simulation.
Time | AC Load |
Before 2 s | 1000 W |
Additional load at 2 s | 1400 W |
Total after 2 s | 2400 W |
This load step is useful for evaluating how quickly the grid, battery, PV, and wind systems respond to a sudden increase in demand.
𝐆𝐫𝐢𝐝-𝐂𝐨𝐧𝐧𝐞𝐜𝐭𝐞𝐝 𝐈𝐧𝐯𝐞𝐫𝐭𝐞𝐫
The DC system is connected to a 230 V, 50 Hz utility grid using a controlled full-bridge inverter.
The grid interface contains:
Full-bridge inverter
LCL filter
Voltage measurement
Current measurement
Reference-current generator
Coordinate transformation
Current PI controller
PWM generator
The inverter supports bidirectional power flow.
It can:
Deliver renewable power toward the AC side.
Import power from the grid when required.
𝐈𝐧𝐯𝐞𝐫𝐭𝐞𝐫 𝐂𝐨𝐧𝐭𝐫𝐨𝐥 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐲
The inverter controller uses system measurements to determine the required grid-current reference.
The demonstrated simulation logic considers:
PV current
Battery SOC
The operating conditions described in the model are:
PV/Battery Condition | Current Reference | Operating Intention |
PV current < 0.5 A, SOC < 10% | −10 A peak | Import power from grid |
PV current > 0.5 A, SOC > 10% | +2 A peak | Renewable/grid-support mode |
The sign of the current reference determines the direction of power exchange.
𝐆𝐫𝐢𝐝 𝐂𝐮𝐫𝐫𝐞𝐧𝐭 𝐂𝐨𝐧𝐭𝐫𝐨𝐥
The grid-current controller performs several stages.
1. Grid Voltage Measurement
The grid voltage is measured to obtain the synchronization signals required by the controller.
2. Reference Current Generation
The required current magnitude is converted into a sinusoidal reference aligned with the grid waveform.
3. Coordinate Transformation
The reference and measured inverter currents are processed in transformed reference frames for easier current regulation.
4. Current Comparison
The actual inverter current is compared with the desired current reference.
5. PI Current Control
Current errors are processed using PI controllers.
6. PWM Generation
The controller output is converted into switching pulses for the full-bridge inverter.
The result is controlled bidirectional current exchange between the renewable energy system and the utility grid.
𝐏𝐨𝐰𝐞𝐫 𝐅𝐥𝐨𝐰 𝐎𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧
The power-flow direction depends on:
Available solar power
Available wind power
Battery SOC
Battery charge/discharge condition
DC load
AC load
Inverter current reference
The controller continuously responds to these quantities.
Renewable Power Available
When sufficient PV and wind power are available:
Renewable sources support the connected loads.
Battery operation depends on the remaining power balance.
Grid power requirement can be reduced.
Renewable Power Insufficient
When PV power falls significantly and the battery SOC is low:
The inverter current reference changes.
Power is imported from the grid.
The grid supports the load and DC-side energy requirement.
𝐒𝐢𝐦𝐮𝐥𝐚𝐭𝐢𝐨𝐧 𝐂𝐨𝐧𝐝𝐢𝐭𝐢𝐨𝐧𝐬
The complete dynamic test can be summarized as follows.
Parameter | Initial Condition | Changed Condition |
Wind speed | 12 m/s | 10.8 m/s after 2 s |
PV irradiance | 1000 W/m² | Dynamically varied |
PV rating | 2 kW | — |
Wind rating | 3 kW | — |
DC load | 1 kW | Constant |
AC load | 1 kW | 2.4 kW after 2 s |
DC-bus voltage | 400 V | Regulated |
Battery capacity | 40 Ah | — |
Grid voltage | 230 V RMS | — |
Grid frequency | 50 Hz | — |
𝐒𝐢𝐦𝐮𝐥𝐚𝐭𝐢𝐨𝐧 𝐑𝐞𝐬𝐮𝐥𝐭𝐬
The simulation monitors several important electrical quantities.
Solar PV Results
The PV scope displays:
PV voltage
PV current
PV power
The results show the expected variation with solar irradiance.
At high irradiance:
PV current increases.
PV output power increases.
The system reaches approximately its 2 kW rated power.
At very low irradiance:
PV current becomes very small.
PV power approaches zero.
𝐖𝐢𝐧𝐝 𝐏𝐨𝐰𝐞𝐫 𝐑𝐞𝐬𝐮𝐥𝐭𝐬
The wind subsystem displays:
Rectifier power
Boost-converter output power
At 12 m/s, the system produces approximately 3 kW.
After the wind speed is reduced to 10.8 m/s, the power decreases to approximately 2.1 kW.
The boost-converter response confirms that the Fuzzy MPPT adapts to the new wind condition.
𝐁𝐚𝐭𝐭𝐞𝐫𝐲 𝐑𝐞𝐬𝐮𝐥𝐭𝐬
The battery scope monitors:
Battery voltage
Battery current
Battery SOC
The battery current changes according to the power balance of the system.
Typical current levels observed during different operating intervals include approximately:
Operating Interval | Battery Current |
Initial condition | Around 10 A |
Subsequent operating condition | Around −15 A |
Further transition | Around −17 A |
High charging condition | Around −22 A |
The current direction indicates whether the battery is supplying or absorbing energy according to the model's sign convention.
𝐃𝐂-𝐁𝐮𝐬 𝐑𝐞𝐬𝐮𝐥𝐭𝐬
The DC-side measurements include:
DC-bus voltage
DC-load current
DC-load power
Despite changes in:
Solar irradiance
Wind speed
AC load
Battery current
Grid power
the DC-link controller works to maintain the bus around the desired 400 V reference.
This is important for stable operation of all converters connected to the common DC link.
𝐆𝐫𝐢𝐝 𝐏𝐨𝐰𝐞𝐫 𝐑𝐞𝐬𝐮𝐥𝐭𝐬
The grid measurement scope displays:
Grid voltage
Grid current
Grid power
The grid power changes significantly according to renewable availability and load demand.
Representative values described in the simulation include:
Operating Condition | Approx. Grid Power |
Initial operating period | Around 700 W |
Low PV / grid-support condition | Around 2500 W |
Increased AC load condition | Around 4100 W |
When renewable power decreases or AC load increases, the required grid contribution increases.
𝐄𝐟𝐟𝐞𝐜𝐭 𝐨𝐟 𝐋𝐨𝐚𝐝 𝐂𝐡𝐚𝐧𝐠𝐞
At 2 seconds, the AC load increases from:
1000 Wto
2400 W
At approximately the same time, wind speed falls from:
12 m/sto
10.8 m/s
Therefore:
AC power demand increases.
Wind generation decreases.
Battery current changes.
Grid power demand increases.
The DC-bus controller compensates for the imbalance.
This combined disturbance provides a useful test of the complete energy-management system.
𝐈𝐧𝐯𝐞𝐫𝐭𝐞𝐫 𝐕𝐨𝐥𝐭𝐚𝐠𝐞 𝐚𝐧𝐝 𝐂𝐮𝐫𝐫𝐞𝐧𝐭
The phase relationship between inverter voltage and current helps indicate power-flow direction.
During one operating mode:
Inverter voltage and current are approximately in phase.
During the reverse-power operating mode:
The current direction changes relative to the voltage.
Power exchange reverses between the grid and the hybrid renewable system.
This confirms the bidirectional capability of the grid-connected inverter.
𝐂𝐨𝐦𝐩𝐥𝐞𝐭𝐞 𝐖𝐨𝐫𝐤𝐢𝐧𝐠 𝐏𝐫𝐨𝐜𝐞𝐬𝐬
The overall operation can be summarized in the following sequence:
Wind turbine converts wind energy into mechanical energy.
PMSG converts mechanical energy into electrical energy.
Rectifier converts generator AC output into DC.
Wind Fuzzy MPPT controls the wind boost converter.
Solar PV generates DC power according to irradiance.
PV Fuzzy MPPT controls the PV boost converter.
Both renewable sources supply the common DC bus.
The battery exchanges power through a bidirectional converter.
The battery converter regulates the DC bus around 400 V.
The DC load receives power directly from the DC bus.
The inverter connects the DC bus to the AC grid.
The current controller determines grid power-flow direction.
The LCL filter improves the grid-side current waveform.
The grid supplies or receives power according to system conditions.
𝐂𝐨𝐧𝐭𝐫𝐨𝐥 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐲
The complete system uses three major control loops.
Controller | Controlled System | Main Purpose |
Fuzzy MPPT | Wind boost converter | Maximum wind power extraction |
Fuzzy MPPT | PV boost converter | Maximum solar power extraction |
PI voltage control | Battery converter | Maintain 400 V DC bus |
PI current control | Grid inverter | Regulate grid current |
PWM control | Power converters | Generate switching pulses |
The combination of these controllers enables coordinated operation during source and load variations.
𝐖𝐡𝐲 𝐔𝐬𝐞 𝐅𝐮𝐳𝐳𝐲 𝐌𝐏𝐏𝐓?
Fuzzy MPPT is particularly useful for renewable energy systems because it can respond to nonlinear and rapidly changing operating conditions.
Key advantages include:
Fast response to changing irradiance.
Good response to changing wind speed.
No need for an exact mathematical model of the renewable source.
Flexible rule-based control.
Suitable for nonlinear PV characteristics.
Suitable for nonlinear wind-generator characteristics.
Improved dynamic MPPT performance.
Easy integration with power-electronic converters.
𝐊𝐞𝐲 𝐅𝐞𝐚𝐭𝐮𝐫𝐞𝐬
✅ PV–wind hybrid renewable generation
✅ Fuzzy MPPT for solar PV
✅ Fuzzy MPPT for wind energy
✅ PMSG-based wind generation
✅ PV and wind boost converters
✅ 400 V regulated DC bus
✅ Battery energy storage
✅ Bidirectional battery converter
✅ Grid-connected full-bridge inverter
✅ Bidirectional grid power flow
✅ LCL grid filter
✅ PI-based DC-link voltage control
✅ PI-based grid current control
✅ Dynamic irradiance testing
✅ Dynamic wind-speed testing
✅ AC load variation
✅ DC load integration
✅ Battery SOC-based operating logic
✅ MATLAB/Simulink implementation
𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬
This type of hybrid renewable energy system can be studied for:
Renewable-energy microgrids
Smart-grid integration
Solar–wind hybrid systems
Battery energy-storage systems
Residential renewable power systems
Commercial renewable installations
Grid-support applications
Distributed generation
Bidirectional power converters
Renewable energy management
Intelligent MPPT research
Fuzzy control studies
Power-electronics controller development
Energy-storage coordination
Grid-connected converter analysis
𝐖𝐡𝐚𝐭 𝐂𝐚𝐧 𝐁𝐞 𝐀𝐧𝐚𝐥𝐲𝐳𝐞𝐝 𝐅𝐫𝐨𝐦 𝐓𝐡𝐢𝐬 𝐌𝐨𝐝𝐞𝐥?
Students, researchers, and engineers can use this system architecture to understand:
How PV power varies with irradiance.
How wind power varies with wind speed.
How Fuzzy MPPT controls a boost converter.
How battery charging and discharging occur.
How DC-link voltage regulation works.
How renewable sources share power.
How grid current can be controlled.
How load changes affect system power balance.
How power can flow in either direction through an inverter.
How renewable, battery, load, and grid subsystems interact dynamically.
𝐂𝐨𝐧𝐜𝐥𝐮𝐬𝐢𝐨𝐧
The Grid Connected PV Wind and Battery with Fuzzy MPPT model demonstrates coordinated operation of solar PV, wind generation, battery storage, DC loads, AC loads, and the utility grid in MATLAB/Simulink.
The solar PV and wind subsystems use Fuzzy Logic MPPT to extract maximum available renewable power under changing environmental conditions. The battery and bidirectional DC–DC converter maintain the common 400 V DC bus, while the grid-connected inverter controls bidirectional power exchange.
Simulation results demonstrate the system response to:
Irradiance variation from 1000 W/m² to very low levels
Wind-speed variation from 12 m/s to 10.8 m/s
PV power variation from approximately 2 kW to near zero
Wind power variation from approximately 3 kW to 2.1 kW
AC load increase from 1 kW to 2.4 kW
Battery charging and discharging
Grid power import and renewable power support
Overall, the model provides a clear platform for understanding Fuzzy MPPT, hybrid renewable energy integration, battery storage, DC-link regulation, and grid-connected power management.
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