366

International Journal of Communication Networks and Information Security (IJCNIS) Vol. 13, No. 3, December 2021

Design and simulation of grid connected PV powered EV

charging station
Dr. M.Ramasekhara Reddy
Assistant Professor, Department of Electrical and Electronics Engineering, Jawaharlal Nehru
Technological University(JNTUA),Anantapur, 515002
(email: ramasekharreddy.eee@jntua.ac.in)

ABSTRACT sunshine, the surplus energy produced by the PV

The use of solar-powered charging facilities for panels may be stored in energy storage devices
electric vehicles has increased. This study like batteries or capacitors[6]. This stored
examines and analyses a grid-connected electric energy can then be utilized to charge EVs at
vehicle charging station powered by a night or during periods of low sunlight[7].
photovoltaic solar system and supported by a In order to guarantee the optimal and effective
battery storage pack. The direct current bus use of the available energy, load management
voltage is the most crucial characteristic for entails balancing the charging of several EVs[8].
system supervision. To maintain the bus voltage This may be accomplished by using intelligent
at the required level, the electric vehicle charging charging systems, which prioritize charging for
station can draw power either from the grid or EVs with higher energy requirements or longer
from an energy storage system. The system's charging durations while simultaneously
performance is rigorously evaluated by accounting for the energy needs of other EVs
simulating the charging process under varying plugged into the station[9].
irradiance conditions, while factoring in energy Grid interaction is the process by which the PV
transfer costs and the battery's state of charge. EV charging station is connected to the electrical
The results validate the effectiveness of the grid, enabling energy exchange between the grid
proposed energy management strategy and and the station[10]. This may be advantageous
demonstrate the reliable operation of the electric since electricity can be taken from the grid to
vehicle charging station. augment the energy produced by the PV panels
I. INTRODUCTION in cases when they are not producing enough
An example of a charging station that utilizes energy to fulfill the needs of the EVs for
solar energy to charge electric cars is a charging[11][15].
photovoltaic (PV) electric vehicle (EV) station. To sum up, a PV EV charging station cannot
Solar energy is converted into electricity by the function effectively or efficiently without an
PV panels of the station, which is then utilized to energy management plan[16][19]. This includes
charge the EVs[1]. Since PV charging stations optimizing the use of renewable energy sources
don't release any hazardous gases or pollutants while also ensuring that EV charging is done in
into the environment, its primary benefit is that an efficient manner via the use of energy storage
they are environmentally benign[2]. devices, load management strategies, and grid
The difficulty with using PV charging stations, interaction[20].
however, is that the energy output of the panels
changes with the weather and time of day[3]. To II. LITERATURE SURVEY
fully optimize the utilization of renewable energy Xuan Hieu Nguyen and Minh Phuong Nguyen
sources and guarantee that the EVs are charged articulate that a PV array, comprised of
successfully, an energy management plan is numerous modules, the PV array functions as
needed to address this issue[4]. the core unit for power conversion within a
Energy storage, load management, and grid photovoltaic generator system. The array
interface are among the crucial components of a displays nonlinear behavior, and obtaining its
PV EV charging station's energy management operational curves across different conditions is
plan[5]. When there is an abundance of both expensive and labor-intensive.To overcome
 367
International Journal of Communication Networks and Information Security (IJCNIS) Vol. 13, No. 3, December 2021

these challenges, simplified models of solar necessitates a meticulously designed

panels have been created and integrated into infrastructure that integrates renewable energy
various engineering software platforms, such as sources with EV charging stations. This study
Matlab/Simulink. Nevertheless, these models delves into the optimal siting and sizing of
prove inadequatewhen applied to hybrid energy renewable energy sources (RES) and electric
systems, as they require flexible tuning of certain vehicle charging stations (EVCS) in smart grids,
parameters and are not easily comprehensible with an emphasis on leveraging advanced
for individual users to manipulate effectively. optimization techniques to achieve system-wide
Thus, this paper presents a detailed, a detailed efficiency, reliability, and sustainability. The
procedure for simulating PV cells, modules, and proposed system capitalizes on photovoltaic
arrays using Tag tools in Matlab/Simulink, (PV) solar arrays, battery energy storage systems
employing the DS-100M solar panel as a (BESS), and grid connections, ensuring that the
reference model. growing needs of modern transportation and
Ellen De Schepper, Steven Van Passel, and renewable energy integration are met.
Sebastien Lizin delve into the operational The proposed system revolves around the
characteristics of the PV array under a broad integration of solar-powered EV charging
spectrum of operating conditions and physical stations within a grid-connected smart grid
parameters. Their findings reveal that the output framework. Central to this system is the
characteristics of the simulation model align photovoltaic (PV) solar system, which serves as
closely with those of the DS-100M solar panel. the primary source of renewable energy for the
Notably, as solar irradiation decreases from charging stations. To ensure uninterrupted
1000 to 100 W/m², the output power, current, operation and optimal energy usage, the system
and voltage decline correspondingly. Conversely, is supplemented by a battery energy storage
when the temperature drops, there is a marginal system (BESS), designed to store excess solar
increase in output power and voltage, while the energy for later use, especially during periods of
output current remains relatively constant. The reduced solar irradiance or peak demand.
shunt resistance significantly impacts the PV The architecture of the charging stations is
array’s operating curves, as a reduction in carefully designed to ensure that the direct
resistance from 1000 ohms to 0.1 ohms results current (DC) bus voltage remains within a
in diminished power output. predefined threshold, as this voltage serves as
the key parameter for maintaining system
In summary, the proposed procedure offers a stability and performance. The system is
precise, reliable, and easily adjustable model of a equipped with mechanisms that allow it to draw
photovoltaic array. Furthermore, it proves to be power either from the solar PV system, the
highly beneficial for examining the operation of battery storage, or the main electrical grid,
a solar PV array under varying physical depending on real-time energy availability and
parameters—such as series and shunt resistance, demand. This hybrid approach enables optimal
ideality factor—and operating conditions, energy distribution and enhances the resilience
particularly in relation to temperature of the charging stations.
fluctuations, irradiation variations, and the Optimization Techniques:
effects of partial shading. This approach ensures To identify the optimal locations and capacities
a robust framework for accurate simulations, for the renewable energy sources and charging
overcoming the inherent complexities of PV stations, the system utilizes various optimization
array modeling. techniques. These techniques are employed to
minimize operational costs, reduce energy
III. PROPOSED SYSTEM losses, and enhance overall grid efficiency while
The rapid expansion of electric vehicle (EV) adhering to technical and regulatory constraints.
adoption, alongside the escalating demand for Among the optimization methods considered
clean and sustainable energy solutions, are:
 368
International Journal of Communication Networks and Information Security (IJCNIS) Vol. 13, No. 3, December 2021

1. Genetic Algorithms (GA): Genetic algorithms The energy management system is also
are appliedto determine the ideal location and responsible for monitoring the state of charge
capacity of the PV systems... and charging (SOC) of the battery storage and making real-
stations by mimicking the process of natural time adjustments to optimize energy flow.
evolution. This technique efficiently explores the During periods of high solar irradiance, excess
solution space to identify configurations that energy is stored in the battery storage system.
maximize energy production and minimize When solar energy generation is insufficient, the
costs. system either draws power from the BESS or
2. Particle Swarm Optimization (PSO): PSO is taps into the grid to maintain consistent
used to optimize the allocation of resources charging for EVs. The energy management
within the smart grid. By simulating the strategy is also designed to minimize energy
behavior of particles in a swarm, this method transfer costs by prioritizing the use of solar-
iteratively improves the configuration of the generated power and limiting reliance on grid-
system, ensuring that the charging stations are supplied energy during peak periods.
placed in locations where they can offer The performance of the proposed system is
maximum utility while minimizing energy evaluated through simulations that account for
transmission losses. varying irradiance levels, energy costs, and
3. Mixed-Integer Linear Programming (MILP): battery SOC. The simulations confirm that the
MILP is utilized to represent the intricate system can maintain stable DC bus voltage
relationships among the various components of under a wide range of conditions, ensuring
the system—solar PV, battery storage, grid reliable operation of the charging stations.
supply, and EV charging stations. By Additionally, the energy management strategy
formulating the problem as a series of linear proves effective in minimizing energy transfer
equations, MILP identifies the optimal sizing of costs while maximizing the use of renewable
the components to meet energy demand at the energy. The results demonstrate that the
lowest cost. proposed system not only enhances the
4. Fuzzy Logic Control: Fuzzy logic is operational efficiency of EV charging stations
implemented to handle uncertainties in solar but also contributes to a more sustainable and
irradiance and energy demand, providing a resilient energy infrastructure.
flexible approach to control energy flow between The proposed system for the optimal siting and
the PV system, battery storage, and grid. This sizing of renewable energy sources and electric
technique enables the system to adapt to real- vehicle charging stations in smart grids offers a
time conditions, ensuring that the DC bus robust and efficient solution to meet the growing
voltage remains stable. demand for clean transportation and renewable
The energy management strategy is paramount energy integration. By leveraging advanced
in ensuring the smooth operation of the grid- optimization techniques and incorporating a
connected EV charging station. A central flexible energy management strategy, this
controller oversees the distribution of energy system ensures reliable operation, cost-
between the PV system, BESS, and grid, effectiveness, and sustainability in the evolving
ensuring that the charging stations are always energy landscape.
supplied with sufficient power to meet demand.
 369
International Journal of Communication Networks and Information Security (IJCNIS) Vol. 13, No. 3, December 2021

Fig.1: proposed simulation circuit

IV. SIMULATION RESULTS

Battery capacity and the ability to accommodate levels: Level 1 (120V AC, typical household
faster charging have both seen significant outlets) being the slowest, Level 2 (240V AC,
advancements, necessitating improvements and upgraded household outlets) providing
adaptations in charging methods. New solutions, moderate charging speed, and Level 3
though still in limited use, have emerged, such (supercharging, 480V DC or higher) delivering
as mobile charging stations and inductive the fastest charge. Level 3 charging can
charging pads. However, diverse requirements replenish 80% of the battery's capacity in as
approach of various manufacturers have little as 30 minutes.
impeded the rapid establishment of standard Despite intense competition among industry
charging protocols. By 2015, the imperative for leaders concerning which standard should
standardization has been widely acknowledged prevail, the need for a unified system remains
across the industry. clear. The time required for a full charge can be
The duration required for charging is contingent calculated using the formula:
uponboth the capacity of the battery and the Charging Time [hours] = Battery Capacity [kWh]
available power... for charging. Simply put, the / Charging Power [kW].
charging rate is determined by the level of This formula serves as a straightforward method
charge being applied, which, in turn, is governed for estimating charging durations determined by
by the voltage capacity of the vehicle’s batteries the battery's energy capacity and the power
and charger electronics. The U.S.-based SAE delivered.
International has categorized these charging
 370
International Journal of Communication Networks and Information Security (IJCNIS) Vol. 13, No. 3, December 2021

Fig 2. Proposed controller

Fig.3 Electric vehicle’s SOC

Fig.4 pv irradiance and voltage

 371
International Journal of Communication Networks and Information Security (IJCNIS) Vol. 13, No. 3, December 2021

Fig 5 SOC for EVs vs time

Fig.6 DC Bus voltage

V. CONCLUSION When wind and PV generation are excess, or

A suggested EV charging station with BES and when the power grid is experiencing valley
PV is built on a multiport converter. The demand, it begins to charge. As a consequence,
purpose of the ABES controller is to reduce the power grid's stability and dependability
voltage sag and balance the power imbalance improvements occur when EV charging, PV
between wind, photovoltaic energy, and the production, and BES are effectively integrated.
demand for EV charging. When wind and PV are combined. Following an investigation into
production are inadequate for local EV charging, the advantages of various operating modes,
as they are during the night, the proposed MATLAB simulation along with thermal models
control architecture causes the BES to discharge. of the multiport converter-based EV charging
 372
International Journal of Communication Networks and Information Security (IJCNIS) Vol. 13, No. 3, December 2021

stations and the proposed SiC counterpart, has 9. X. Liu, M. Chauhan, and J. G. Zhu, “Dynamic
been developed.. wireless charging system for electric vehicles
with a non-isolated three-port DC/DC
REFERENCES converter,” IEEE Transactions on Power
1. V. Rallabandi, D. Lawhorn, J. He, and D. M. Electronics, vol. 34, no. 11, pp. 11206–11216,
Ionel, “Current weakening control of coreless Nov. 2019.
AFPM motor drives for solar race cars with a 10. P. N. Prudhvi and P. K. Hota, “Design and
three-port bi-directional DC/DC converter,” in simulation of a bidirectional DC-DC converter
2017 IEEE 6th International Conference on for electric vehicle charging station,” in 2018
Renewable Energy Research and Applications International Conference on Power,
(ICRERA), Nov 2017, pp. 739–744. Instrumentation, Control and Computing
2. Y. Liu, Y. Tang, J. Shi, X. Shi, J. Deng, and K. (PICC), Dec. 2018, pp. 1–5.
Gong, “Application of small-sized SMES in an 11. M. N. Marwali and A. Keyhani, “Control of
EV charging station with DC bus and PV distributed generation systems - part II: Load
system,” IEEE Transactions on Applied sharing control,” IEEE Transactions on Power
Superconductivity, vol. 25, no. 3, pp. 1–6, June Electronics, vol. 19, no. 6, pp. 1551–1561, Nov.
2015. 2004.
3. M. Ahmadi, N. Mithulananthan, and R. 12. M. E. Glavin and W. G. Hurley,
Sharma, “A review on topologies for fast “Ultracapacitor and battery hybrid for solar
charging stations for electric vehicles,” in 2016 energy storage,” in 2006 IEEE Power
IEEE International Conference on Power System Electronics Specialists Conference, June 2006,
Technology (POWERCON), Sep. 2016, pp. 1–6. pp. 1–5.
4. J. C. Mukherjee and A. Gupta, “A review of 13. N. A. Orlando, M. Liserre, and R. A.
charge scheduling of electric vehicles in smart Mastromauro, “A survey on control of electric
grid,” IEEE Systems Journal, vol. 9, no. 4, pp. vehicle charging stations,” in 2018 IEEE
1541–1553, Dec. 2015. International Conference on Electrical Systems
5. H. Zhu, D. Zhang, B. Zhang, and Z. Zhou, “A for Aircraft, Railway, Ship Propulsion and Road
nonisolated three-port DC-DC converter and Vehicles & International Transportation
three-domain control method for PV-battery Electrification Conference (ESARS-ITEC), Nov.
power systems,” IEEE Transactions on 2018, pp. 1–6.
Industrial Electronics, vol. 62, no. 8, pp. 4937– 14. H. Mahmood, A. Michael, and K. Saeed,
4947, Aug. 2015. “Optimized integration of electric vehicle
6. A. Hassoune, M. Khafallah, A. Mesbahi, and charging stations with renewable energy
T. Bouragba, “Smart topology of EVs in a PV- resources,” IEEE Access, vol. 6, pp. 26439–
grid system-based charging station,” in 2017 26450, May 2018.
International Conference on Electrical and 15. P. Bauer, Y. Zhou, and J. Dougal, “Smart
Information Technologies (ICEIT), Nov. 2017, charging of electric vehicles: Challenges and
pp. 1–6. opportunities,” IEEE Transactions on Industrial
7. G. Goh, M. A. S. Masoum, and P. J. Wolfs, Informatics, vol. 10, no. 2, pp. 307–318, May
“Optimal sizing of renewable energy sources and 2014.
battery storage for electric vehicle charging 16. S. Amamra, S. Mercier, and M. G. Simoes,
stations,” IEEE Transactions on Industrial “Three-port DC/DC converter for electric vehicle
Informatics, vol. 13, no. 6, pp. 3112–3121, Dec. fast charging station with power factor
2017. correction,” IEEE Transactions on Industry
8. S. Moon, J. Park, and J. Lee, “Analysis of the Applications, vol. 52, no. 4, pp. 3307–3316, July
impact of electric vehicle charging demand on 2016.
the power system under different charging 17. M. Ahmadi and R. Sharma, “Design of fast
scenarios,” IEEE Transactions on Smart Grid, electric vehicle charging stations with energy
vol. 9, no. 2, pp. 1152–1161, March 2018. storage,” IEEE Transactions on Industrial
 373
International Journal of Communication Networks and Information Security (IJCNIS) Vol. 13, No. 3, December 2021

Electronics, vol. 62, no. 5, pp. 3131–3141, May

2015.
18. C. H. Lai, Y. C. Wang, and Y. H. Yang, “A
photovoltaic energy storage system with
bidirectional DC-DC converter and bidirectional
inverter for electric vehicle fast charging,” IEEE
Transactions on Power Electronics, vol. 29, no.
12, pp. 5731–5745, Dec. 2014.
19. J. Li and Y. Hu, “Research on electric vehicle
charging station integration with smart grid,” in
2017 IEEE International Conference on
Mechatronics and Automation (ICMA), Aug.
2017, pp. 1–6.
20. N. Andwari, A. Pesiridis, and S. Rajakaruna,
“Optimal scheduling of electric vehicle charging
stations for integration with renewable energy
sources,” in 2016 IEEE Power and Energy
Conference at Illinois (PECI), Feb. 2016, pp. 1–
6.