PV/ Wind/ Battery/ Grid Integrated Hybrid Energy System for EV

Charging Station

Meghana Sonar, Sanjana Aralikatti

Mruthyunjaya Belavatagi and Siddarameshwar H N

Dept of Electrical and Electronics, KLE Technological University, Vidyanagar, Hubballi, India

Keywords: RES, HES, Wind System, PV System, Fuzzy MPPT, EV Charging

Abstract: As fossil fuel supplies run out, renewable energy sources, or RESs, are becoming increasingly important. Due

to their accessibility and user-friendliness, solar and wind energy systems are the most popular RESs. In order

to improve energy efficiency and dependability, this work combines solar (PV) panels, wind energy systems,

and electric vehicle (EV) charging stations into a hybrid energy system (HES). A Maximum Power Point

Tracking (MPPT) system based on fuzzy logic is used to maximize energy conversion in wind and

photovoltaic systems. A fuzzy MPPT controller is used by the wind subsystem to maximize turbine output

under variable wind conditions, while the PV system adapts to changing irradiance, temperature, and

nonlinear circumstances for optimal solar energy harvesting. A charge controller regulates battery energy,

ensuring efficient charging and state of charge (SOC) monitoring. A grid-connected inverter transforms DC

to AC for grid interfacing and a boost converter controls DC voltage for DC loads. Buck-boost converters

control voltage and provide real-time SOC, current, and voltage monitoring for EV batteries. When paired

with pulse width modulation (PWM), the fuzzy MPPT algorithm ensures efficient power flow throughout the

system. Key performance variables, including battery state of charge, load voltage, and current, are

continuously monitored. This hybrid system aims to enhance sustainability and energy efficiency for EV

charging applications in MATLAB/Simulink.

1 INTRODUCTION

The growing need for efficient and sustainable energy

solutions emphasizes how important renewable

energy sources are to solving the world's energy

problems. In particular, solar and wind energy

provide clean, plentiful, and environmentally friendly

substitutes for traditional fossil fuels, which makes

them crucial for cutting greenhouse gas emissions and

halting climate change. In hybrid energy systems,

combining photovoltaic (PV) and wind energy units

takes advantage of their complementary qualities,

where wind may make up for decreased solar output

low light levels, guaranteeing a more steady and

dependable energy supply. Furthermore, by

optimizing energy extraction under various

environmental conditions, Maximum Power Point

Tracking (MPPT) algorithms increase the efficiency

of these systems, maximizing performance and

lowering operating costs.

Hybrid energy systems not only improve energy

reliability, but they also help to maintain grid stability

by eliminating variations in power generation and

demand. By incorporating energy storage

technologies such as modern battery systems, these

setups may store extra energy created during peak

production periods and release it during high-demand

periods, assuring continuous energy availability.

Furthermore, the hybrid approach reduces the chance

of power interruptions, especially in rural or off-grid

areas, making it an excellent choice for increasing

energy access in underserved areas.

Grid connectivity strengthens these systems by

allowing for bi-directional energy flow, where

surplus energy may be supplied back into the grid,

generating additional revenue streams and

encouraging a circular energy economy. This also

enables flawless synchronization with the main grid

during periods of high demand, improving system

adaptability and scalability for future energy

requirements.

This work aims to create an integrated energy

system that maximizes the possibilities of renewable

energy and innovative storage technologies. It

220

Sonar, M., Aralikatti, S., Belavatagi, M. and H N, S.

PV/ Wind/ Battery/ Grid Integrated Hybrid Energy System for EV Charging Station.

DOI: 10.5220/0013612500004664

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 3rd International Conference on Futuristic Technology (INCOFT 2025) - Volume 3, pages 220-228

ISBN: 978-989-758-763-4

includes sophisticated control systems to ensure

energy efficiency and system stability. The

technology seeks to serve essential applications like

EV charging infrastructure by offering a sustainable

and efficient energy solution. This approach not only

promotes the adoption of electric vehicles by

addressing their charging needs, but it also helps to

achieve the larger aims of lowering greenhouse gas

emissions, improving energy security, and fostering

energy independence. Furthermore, the hybrid

system's adaptability allows for scaling, making it

suitable for a variety of geographical regions and

energy demands. This ensures its relevance in both

urban and remote places, encouraging widespread

adoption of sustainable energy technologies.

1.1 MPPT METHODS

MPPT (Maximum Power Point Tracking) is an

algorithm in charge controllers that maximizes the

output power of PV modules by changing the

operating point to the maximum power point. This

maximizes the energy yield from sunlight, increasing

the efficiency of solar power systems.

The efficiency of The HES (Hybrid Energy

System) based EV Charging Station can be enhanced

by applying following MPPT algorithms:

1.1.1 Perturb and Observe Technique

(P&O)

The Perturb and Observe (P&O) technique tracks the

maximum power point (MPP) by gradually adjusting

PV voltage. While oscillations can happen near the

maximum power point (MPP) in steady-state settings,

it tends to shift toward the MPP as power increases.

It is extensively used because of its versatility and

simplicity, and improvements increase its efficiency.

1.1.2 Incremental Conductance (INC)

The Incremental Conductance method calculates

the maximum power point (MPP) by comparing

incremental conductance to array conductance. It

carefully adjusts voltage to maintain MPP under

changing situations. In comparison to P&O, this

approach is speedier and less likely to cause

oscillations.

1.1.3 Modified Perturb and Observe (P&O)

The modified P&O MPPT algorithm improves on

classic P&O by decreasing oscillations around the

MPP and increasing tracking speed. It handles quick

variations in irradiance or temperature by using

adaptive step sizes or anticipatory adjustments. This

improves both efficiency and stability in power

extraction.

1.1.4 Fuzzy MPPT

The fuzzy MPPT algorithm uses fuzzy logic to

determine the maximum power point (MPP) by

modifying step size in response to irradiance and

temperature. It provides rapid, steady, and adaptive

tracking with minimal oscillations, making it perfect

for dynamic environments.

Among the MPPT algorithms stated above, the

fuzzy MPPT method was chosen for the hybrid

energy EV charging station because it is fast,

adaptive, resistant to nonlinearity, and successfully

manages hybrid system integration.

Because of its versatility, accuracy, and dynamic

reaction, the fuzzy MPPT algorithm is favoured for

managing abrupt changes in temperature and

irradiance. It employs fuzzy logic to deliver faster,

more reliable tracking of the maximum power point

(MPP) with fewer oscillations than traditional

techniques like P&O and INC. It effectively harvests

maximum power under a variety of scenarios by

dynamically altering step sizes, guaranteeing the

smooth integration of grid, PV, wind, and battery

systems. This outperforms conventional MPPT

algorithms in terms of energy yield, stability, and

overall hybrid energy system performance for EV

charging.

2 LITERATURE SURVEY

The proposed work(Muthammal, 2018) focuses

on a hybrid solar and wind energy system for EV

recharging to meet long-distance travel needs. A

MATLAB-Simulink model demonstrates significant

power generation under various scenarios. Battery

swapping reduces charging time, increasing EV

adoption and lowering emissions.

In this work titled (Jatoth, 2024)

MATLAB/Simulink is used to demonstrate a multi-

input transformer-coupled active bridge converter

with PV, wind, and battery storage. The stand-alone

system maintains steady DC and AC voltages and

utilizes P&O MPPT to maximize power extraction. It

PV/ Wind/ Battery/ Grid Integrated Hybrid Energy System for EV Charging Station

221

ensures consistent power delivery under fluctuating

load and environmental circumstances.

In the study (Savio, Juliet, et al. , 2019), the author

proposed an on-grid solar and wind hybrid system for

EV charging that provides dependable power while

decreasing grid dependency. It reduces renewable

intermittency, lowers carbon emissions, and provides

long-term savings. The system promotes green

transportation and encourages the use of hybrid

renewable energy systems.

In this work (Katageri, Nisahathfareen, et al. ,

2021) the researcher, In order to reduce pollution and

grid reliance, the author developed a hybrid fast-

charging system that uses local renewable energy. For

EV charging, a MATLAB-Simulink model illustrates

how solar and wind energy operate under various

circumstances. By cutting down on charging time,

battery switching encourages EV adoption and

contributes to a cleaner environment.

In the proposed work (Reddy and Birudala, 2024),

the researcher developed an off-grid PV-based EV

charging station that uses energy storage systems

(ESS) rather than grid electricity. The system

produces enough energy based on irradiance and

temperature, with ESS providing backup when solar

power is insufficient. The model is both cost-effective

and sustainable. It demonstrates the potential for

future EV charging applications.

In this work (Kumar and Rajan, et al. , 2023), the

author in order to efficiently satisfy load demands,

MATLAB/Simulink was used to simulate a hybrid

energy system (HES) that included PV, WECS, a

diesel generator, and battery storage. MPPT

algorithms and converters ensure voltage

management and consistent performance. The

method is ideal for both remote communication and

precise watering. During periods of low demand,

surplus power can be fed back into the system.

3 METHODOLOGY

Fig.1 shows the block diagram of the proposed

method and the motivation behind developing the

HES based EV Charging station is to promote a

cleaner and eco-friendly transportation instead of

depending on fossil fuels.

Figure 1: Block Diagram of HES based EV Charging

Station

This block diagram illustrates a hybrid energy

system that combines wind, solar (PV), battery

storage, and the AC grid to power EV charging

stations.

The wind and PV systems create DC power,

which is optimized with fuzzy MPPT controllers and

DC/DC converters. Excess energy is stored in the

battery bank and regulated by a charge controller.

When renewable sources are insufficient, the AC grid

provides electricity, which is converted to DC using

a full-bridge inverter. The DC bus takes electricity

from multiple sources and transfers it to three EV

charging stations, ensuring efficient and long-lasting

power delivery.

The proposed system Illustrates the

MATLAB/Simulink model of HES based EV

Charging Station.

In order to guarantee a dependable

power source for EV charging, the hybrid energy

system integrates solar (PV) and wind energy with

battery storage, charge controllers, and grid

connectivity. Energy from renewable sources is

controlled and directed by charge controllers to either

the DC bus for instant consumption or the battery for

storage. While buck-boost regulators effectively

charge EV batteries, the grid-connected inverter

synchronizes with the grid for energy consumption or

output.

Hence let’s understand the working of whole

model in a Detailed manner :

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Figure 2: Shows the Simulation of the proposed system

3.1 Wind System

The figure depicts the wind system which has a

variable input source. In a In a hybrid energy system,

wind energy is converted into electrical power using

a turbine, generator, rectifier, and boost converter

with MPPT management. The generated electricity is

fed into a DC bus, which charges batteries, powers

the grid, and provides renewable energy for EV

charging. It ensures effective energy use and

complements solar PV. Therefore, the specifications

of Wind System are illustrated in the given below

Table 1

Table 1: Specifications of Wind System

Nominal mechanical out

owe

2.5kW

Base power of the electrical generato

2777.8VA

Base wind spee

12m/s

Maximum power at base wind spee

1pu

Base rotational s

1.3m/s

Figure 3: Simulation of Wind System

Figure 4: Turbine Speed vs Turbine output power

characteristics of wind Turbine for 6 to 12m/s

PV/ Wind/ Battery/ Grid Integrated Hybrid Energy System for EV Charging Station

223

The above figure depicts the speed vs output

power characteristics of WECS or Wind system of

EV Charging station for 6 to 12m/s and a fixed pitch

angle (β=0 degrees). The turbine highlights the ideal

operating locations for the greatest efficiency at each

wind speed by achieving maximum power at a certain

turbine speed.

3.2 PV System

Figure 5: Simulation of PV system

The above figure illustrates the PV system in

which the hybrid energy arrangement that turns solar

irradiance into DC electricity via solar panels. A DC-

DC converter with MPPT optimizes power

production, and energy is stored in batteries or

delivered directly for EV charging. It integrates

smoothly with wind and grid inputs to ensure

consistent energy delivery.

Table 2: Specifications of PV System

Maximum Power

(

)

250.205

Open circuit voltage Voc (V) 37.3

Short circuit current Isc (A) 8.66

Voltage at maximum power point Vmp (V) 30.7

Current at maximum

ower

oint Im

(

)

8.15

Figure 6(a): V-I Characteristics of PV Panel

Figure 6 (b): P-V Characteristics of PV Panel

Figure 6(a) Illustrates the V-I Characteristics of

PV Panel Which is a plot of Current(A) vs Voltage

(V) of PV Panel where the results reveal that the

voltage and current oscillate steadily following

transients, and the power stabilizes at a constant

amount. This demonstrates that the recommended

control technique is successful.

Figure 6(b) Illustrate the P-V Characteristics of

PV Panel under varying irradiance levels, which is

plot of Power (W) vs Voltage (V) of PV Panel that

shows the system's versatility that indicate a change

in the maximum power point with increasing

irradiance. This demonstrates how adaptable it is to

changes in the environment.

The PV installation has to ensure that the panels

receive the most sunlight possible, and the charging

station's solar plant area (Area α Power output) is

minimal. Some may suggest using high-power

concentrators to boost power production; however,

doing so raises the cost.

The plant's cost and upkeep. Choosing hybrid

solutions like wind, biomass, or small hydro plants

is a better idea. For dry regions, a solar-wind hybrid

is the greatest choice when taking integration costs

and efficiency into account.

The PV installation has to ensure that the panels

receive the most sunlight possible, and the charging

station's solar plant area (Area α Power output) is

minimal. Some may suggest using high-power

concentrators to boost power production; however,

doing so raises the cost.

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The plant's cost and upkeep. Choosing hybrid

solutions like wind, biomass, or small hydro plants

is a better idea. For dry regions, a solar-wind hybrid

is the greatest choice when taking integration costs

and efficiency into account.

3.2 Fuzzy MPPT controller for Wind

and PV System

Figure 7: Simulation of Fuzzy MPPT controller

The fuzzy MPPT controller uses fuzzy logic to

calculate the appropriate duty cycle for the DC-DC

converter. It uses inputs such as PV voltage and

current to track the maximum power point (MPP)

under changing irradiance and temperature

conditions, assuring maximum energy extraction

from the PV system.

3.3 Charge Controller

Figure 8: Simulation of Charge controller

The above figure illustrates the charge controller

controls the flow of power between the battery, EVs,

and PV/wind energy sources. It keeps the battery

from being overcharged or deeply discharged,

extending its lifespan. For optimum system efficiency

and smooth grid integration, it also controls energy

distribution. Let’s understand the working of charge

controller in depth

The producing plant uses MPPT control, and the

charging control is mostly reliant on the ESS's SOC

and power supply. The terms Power from Hybrid

Plant (Hp), Power Demand (Pd), and SOC of ESS

(Se) refer to its four operating modes.

Mode 1:

When PP > PD and SE is within maximum

and minimum limits, electricity is given to the EV and

surplus power is sent to ESS.

Mode 2: When PP>PD and SE is out of limits, the

surplus power will be given to grid or connected to

dummy loads for Power balance.

Mode 3:

When PP, PD, and SE are between

limitations, ESS supplies the demand from EV.

Mode 4: When Hp < Pd and Se < minimal value,

energy demand is taken from grid to DC bus. If our

charging station is in an off- grid area, we intend to

operate in the above 3 modes. Similar to a solar plant.

Figure 9: Battery Voltage vs Time, Battery Current vs

Time, SOC vs Time output

The above figure illustrates the output of battery

whose working is observed in Charge controller.

The

battery voltage stabilizes, the current varies while

charging, and the state of charge (SOC) increases

linearly with time, according to the data. This attests

to the battery charging system's efficient operation.

PV/ Wind/ Battery/ Grid Integrated Hybrid Energy System for EV Charging Station

225

3.3 Grid connected Full bridge DC-AC

Converter

Figure 9: Simulation of Grid connected Full bridge DC-AC

Converter

The hybrid energy system's grid-connected full-

bridge DC-AC converter converts DC power from

renewable sources and batteries into AC power that is

synced with the voltage and frequency of the power

grid. It allows the system to either export surplus

energy to the grid or draw energy when demand

exceeds generation, guaranteeing a consistent power

supply for EV charging.

Figure 10: Grid Voltage vs Time, Grid Current vs Time,

Grid power vs Time outputs

Figure 10 illustrates the output Grid whose

working is observed in Grid connected Full bridge

DC-AC Converter. Here we can observe that battery

performs efficiently when the SOC rises gradually,

the voltage stays constant, and the current

dynamically fluctuates in response to changes in the

load.

Figure 11. Inverter Voltage vs Time, Inverter Current vs

Time, Grid Current vs Time output

Figure 11 illustrates the outputs of inverter whose

working is observed in Grid connected Full bridge

DC-AC Converter. The results indicate that after

initial transients, inverter voltage and current stabilize,

and grid current synchronizes. This attests to reliable

functioning and good grid integration.

3.4 EV Charging Station

Figure 12: Simulation of EV Charging Station

If the EV charging station above is not linked to

the hybrid energy system, it gets its electricity straight

from the grid. Power converters transform the AC

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power from the grid into the proper DC voltage.

Buck-boost regulators guarantee that the voltage is

changed to satisfy the unique charging needs of the

EV battery, resulting in safe and effective charging.

The Specifications of EV battery are shown below.

Table 2. Specifications of EV Battery

e Lithium-Ion

Nominal Volta

(

)

Rated Ca

acit

(

)

100

Initial State-of-Charge(%) 75

Battery response time (s) 30

Figure 13: Simulation of Buck-Boost Regulator of EV

Charging Station

An EV charging station's buck-boost regulator

modifies the hybrid energy system's voltage to meet

the needs of the EV battery. In order to ensure a

steady and effective charging process and safeguard

the battery from overvoltage or undervoltage

situations, it adjusts the input voltage as necessary.

In this way all the subsystems integrated with Hybrid

energy system collectively work together.

4 RESULTS

4.1 Results for EV Charging Station 1

The simulation results in Figure 14 indicate that

while charging, SOC increases linearly, current

decreases exponentially, and voltage stabilizes with

time. This attests to the system's effective and

regulated battery charging mechanism.

Figure 14: SOC, current and voltage vs time for EV

Charging Station 1

4.2 Results for EV Charging Station 2

Figure 15: SOC, current and voltage vs time for EV

Charging Station 2

The simulation results in Figure 15 demonstrate

the battery's performance under load, with SOC

dropping linearly, current stabilizing following an

initial transient, and voltage attaining steady state,

assuring a consistent energy supply.

4.3 Results for EV Charging Station 3

The simulation results demonstrate the battery's

behaviour under load, with SOC dropping linearly,

current stabilizing after an initial transient, and

voltage attaining steady state, resulting in constant

energy production.

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Figure 16: SOC, current and voltage vs time for EV

Charging Station 3

5 CONCLUSIONS

The PV/Wind/Battery/Grid Integrated Hybrid Energy

System for EV Charging Stations provides an

economical and environmentally friendly way to

satisfy the increasing energy needs of EVs. The

system guarantees a consistent and dependable power

supply by utilizing renewable energy sources such as

wind and solar power, in addition to battery storage

and grid connectivity.

It limits reliance on non-renewable energy

sources, maximizes energy use, and lowers carbon

emissions. Sophisticated power converters, charge

controllers, and energy management systems enhance

its overall efficiency and operating stability. In

addition to meeting EV charging requirements, this

hybrid strategy makes a substantial contribution to the

worldwide shift to cleaner and greener energy

systems.

6 FUTURE SCOPE

Future improvements include incorporating AI-

powered smart grids, blockchain for energy trading,

and vehicle-to-grid (V2G) technology to improve

energy management. Improvements in battery

technology, Calculation of both SOC and SOH. Ultra-

fast charging will boost system performance.

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