PV–Wind Energy System–Based EV Charging Station

PV–Wind Energy System–Based EV Charging Station

𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧

A PV–Wind Energy System–Based EV Charging Station combines solar and wind power to charge electric-vehicle batteries through a common DC bus. The hybrid arrangement improves energy availability because one renewable source can continue supplying power when the other produces less energy.

PV–Wind Energy System–Based EV Charging Station

PV and Wind Energy Based EV charging Station in MATLAB

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Developed in MATLAB/Simulink, this model demonstrates:

• Solar and wind energy conversion

• Maximum power point tracking

• Common DC-bus integration

• EV battery charging

• Battery-swapping operation

• Renewable-power sharing

• Performance under changing environmental conditions

The model is suitable for students, researchers, and engineers studying renewable-energy conversion, EV charging infrastructure, MPPT control, and hybrid DC microgrids.

𝐒𝐲𝐬𝐭𝐞𝐦 𝐎𝐯𝐞𝐫𝐯𝐢𝐞𝐰

The charging station contains three main units:

Subsystem	Main components	Function
Solar PV system	PV array, boost converter and MPPT controller	Converts solar energy and supplies power to the DC bus
Wind energy system	Wind turbine, PMSG, rectifier and boost converter	Converts wind energy into regulated DC power
EV battery system	EV battery and measurement blocks	Receives charging power and monitors battery performance
Common DC bus	DC connection point	Combines power from the PV and wind sources
Monitoring system	Voltage, current, power and SOC measurements	Evaluates the complete charging operation

The PV and wind systems use separate boost converters. Their outputs are connected to the same DC bus, allowing both sources to charge the EV battery simultaneously.

𝐁𝐚𝐭𝐭𝐞𝐫𝐲-𝐒𝐰𝐚𝐩𝐩𝐢𝐧𝐠 𝐂𝐨𝐧𝐜𝐞𝐩𝐭

The station supports a battery-swapping arrangement:

1. A discharged battery is removed from an EV.

2. A fully charged battery is installed in its place.

3. The discharged battery is connected to the charging station.

4. Solar and wind energy recharge the battery.

5. Once charged, the battery becomes available for another EV.

This approach can reduce the waiting time associated with conventional EV charging. Multiple batteries may also be connected in parallel when the renewable-energy system and converters are sized appropriately.

𝐖𝐨𝐫𝐤𝐢𝐧𝐠 𝐏𝐫𝐨𝐜𝐞𝐬𝐬

Solar PV power generation

• Solar irradiance falls on the PV array.

• The PV array produces DC voltage and current.

• The MPPT controller measures these quantities.

• The controller adjusts the boost-converter duty cycle.

• PWM pulses operate the converter IGBT.

• The regulated PV power is delivered to the common DC bus.

Wind power generation

• Wind rotates the turbine blades.

• The turbine drives the Permanent Magnet Synchronous Generator (PMSG).

• The PMSG generates variable AC power.

• A rectifier converts the AC output into DC power.

• The wind MPPT controller regulates the boost converter.

• The extracted wind power is transferred to the common DC bus.

EV battery charging

• The PV and wind outputs are combined at the DC bus.

• The EV battery draws the available renewable power.

• Negative battery current indicates charging operation.

• Battery SOC rises gradually as charging continues.

• Changes in sunlight or wind speed automatically affect the charging power.

𝐂𝐨𝐧𝐭𝐫𝐨𝐥 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐲

P&O MPPT for the wind system

The wind boost converter uses a Perturb and Observe MPPT algorithm. It receives the rectifier voltage and current as inputs.

The controller:

• Calculates the rectifier power

• Monitors changes in voltage and power

• Adjusts the duty cycle in small increments

• Keeps the duty cycle within predefined limits

• Drives the boost-converter switch through PWM

• Tracks the wind turbine’s maximum operating power

P&O MPPT for the PV system

The PV subsystem also uses P&O-based maximum power point tracking.

The algorithm:

• Measures PV voltage and current

• Determines the direction of power change

• Increases or decreases the duty ratio

• Generates the required PWM switching signal

• Extracts maximum available power as irradiance changes

Independent MPPT controllers allow the solar and wind systems to operate at their respective maximum power points.

𝐒𝐢𝐦𝐮𝐥𝐚𝐭𝐢𝐨𝐧 𝐏𝐚𝐫𝐚𝐦𝐞𝐭𝐞𝐫𝐬

Parameter	Value or range
PV array rated power	Approximately 2000 W
Wind-system output	Approximately 2.5–3 kW
High solar irradiance	1000 W/m²
Reduced solar irradiance	500 W/m²
Irradiance change interval	Every 0.3 seconds
Initial wind speed	12 m/s
Reduced wind speed	10.8 m/s
Wind-speed change interval	Every 1 second
Combined charging power	Approximately 4000 W
Charging current at high generation	Approximately −10 A
Charging current at reduced irradiance	Approximately −7 A

The varying irradiance and wind-speed profiles help test the system under realistic renewable-energy fluctuations.

𝐒𝐢𝐦𝐮𝐥𝐚𝐭𝐢𝐨𝐧 𝐑𝐞𝐬𝐮𝐥𝐭𝐬

Operating-condition comparison

Operating condition	PV power	Wind power	Approximate battery response
Irradiance at 1000 W/m² and wind speed at 12 m/s	2000 W	2500 W	Around 4000 W charging power and −10 A current
Irradiance reduced to 500 W/m²	Reduced PV output	Around 2500 W	Charging continues at approximately −7 A
Irradiance close to zero	Negligible	Around 2500 W	Battery continues charging from wind power
Irradiance increases again	PV power rises	Wind remains available	Charging current increases and charging becomes faster

Main observations

• The PV array generates approximately 2000 W at high irradiance.

• The wind turbine produces close to 2500 W under the stated operating condition.

• Some generated power is lost in the converters and electrical components, so the battery receives approximately 4000 W rather than the full combined source power.

• The charging current reaches nearly −10 A when both sources provide substantial power.

• When PV output decreases, the wind system continues supporting the battery.

• When solar irradiance becomes negligible, wind energy maintains the charging process.

• Battery SOC increases steadily during charging.

• Higher renewable power produces a larger charging current and faster SOC growth.

𝐌𝐞𝐚𝐬𝐮𝐫𝐞𝐝 𝐏𝐚𝐫𝐚𝐦𝐞𝐭𝐞𝐫𝐬

The MATLAB/Simulink model monitors the following signals:

• PV voltage

• PV current

• PV power

• Rectifier power

• Wind boost-converter power

• Wind power

• Battery voltage

• Battery current

• Battery charging power

• Battery state of charge

These measurements make it easier to study power balance, converter behavior, MPPT performance, and EV battery charging.

𝐊𝐞𝐲 𝐅𝐞𝐚𝐭𝐮𝐫𝐞𝐬

• Hybrid solar PV and wind energy generation

• Renewable-energy-based EV battery charging

• Common DC-bus architecture

• PMSG-based wind energy conversion

• Separate boost converters for PV and wind sources

• P&O MPPT control for maximum power extraction

• PWM-controlled converter switching

• Battery-swapping support

• Continuous charging under changing weather conditions

• Real-time voltage, current, power, and SOC monitoring

• Expandable configuration for multiple EV batteries

• Complete implementation in MATLAB/Simulink

𝐁𝐞𝐧𝐞𝐟𝐢𝐭𝐬 𝐨𝐟 𝐇𝐲𝐛𝐫𝐢𝐝 𝐏𝐕–𝐖𝐢𝐧𝐝 𝐂𝐡𝐚𝐫𝐠𝐢𝐧𝐠

Benefit	Explanation
Improved energy availability	Wind power can support charging when solar generation decreases
Better use of renewable energy	MPPT controllers extract the maximum available power
Reduced source dependence	The battery is not dependent on a single renewable source
Continuous charging support	Charging can continue when one source becomes weak
Flexible expansion	Source and converter ratings can be increased for more batteries
Faster EV service	Battery swapping reduces vehicle waiting time
Useful performance analysis	Simulink scopes display source and battery behavior clearly

𝐀𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬

This system architecture can be applied to:

• Renewable-powered EV charging stations

• EV battery-swapping facilities

• Highway and remote-area charging points

• Commercial EV fleet charging

• Electric bus and delivery-vehicle depots

• Campus and industrial charging infrastructure

• Hybrid renewable DC microgrids

• Renewable-energy converter control studies

• MPPT algorithm evaluation

• Battery charging and SOC analysis

𝐒𝐜𝐚𝐥𝐚𝐛𝐢𝐥𝐢𝐭𝐲

The model can be expanded by:

• Increasing the PV array capacity

• Increasing the wind-turbine rating

• Connecting additional EV batteries

• Adding bidirectional DC–DC converters

• Including battery current and voltage regulation

• Introducing battery SOC limits

• Adding grid support during low renewable generation

• Including stationary battery energy storage

• Developing an intelligent energy-management system

• Implementing coordinated parallel charging

Converter current limits, DC-bus stability, battery specifications, and available renewable power must be considered when multiple batteries are charged simultaneously.

𝐂𝐨𝐧𝐜𝐥𝐮𝐬𝐢𝐨𝐧

The PV–Wind Energy System–Based EV Charging Station demonstrates an effective method for charging EV batteries using two complementary renewable sources. Solar PV and wind systems feed a common DC bus through independently controlled boost converters, while P&O MPPT algorithms improve energy extraction under changing environmental conditions.

The results show that the wind system can maintain battery charging when solar irradiance decreases or approaches zero. When solar power returns, the combined renewable output increases the charging current and accelerates SOC improvement. The battery-swapping concept further improves the practicality of the charging station by allowing discharged batteries to be replaced and recharged separately.

This MATLAB/Simulink model provides a clear platform for studying hybrid renewable generation, power-electronic converters, MPPT control, EV battery charging, and system scaling.