Optimizing Solar and Wind Energy Integration in Grid-Connected EV Fast Charging Systems using Fuzzy Logic Control for Improved Stability and Power Quality

This paper presents the complete approach to integrating solar and wind renewable energy sources into grid-connected Electric Vehicle (EV) quick charging systems. The solar system utilizes a Perturb and Observe (P&O) Maximum Power Point Tracking (MPPT) boost converter to maximize energy extraction from the photovoltaic panels. In contrast, the wind energy system employs a similar MPPT technique to maximize wind power consumption. The proposed fuzzy logic controller system ensures consistent and efficient power conversion management during EV charging activities, improving system stability. Neutral-Point Clamped (NPC) voltage source converters are further utilised to optimise power conversion, improve voltage balance, and reduce switching losses. Reducing voltage fluctuations and resolving power quality issues helps the fuzzy logic controller significantly increase system stability. MATLAB simulations show that the combined use of MPPT for solar and wind, fuzzy logic control, and NPC converters results in effective energy distribution, enhanced load balancing, and reduced Total Harmonic Distortion (THD). Apart from fast-charging electric vehicles, the system is supposed to manage residential linear and nonlinear loads. The findings imply that whilst preserving power grid stability and improving general system performance for different load types, this integrated system successfully allows large-scale EV rapid charging utilising renewable energy.

Authors

Publication Details

Journal
International Journal of Electrical and Electronics Engineering
Published
2024-12-31
DOI
https://doi.org/10.14445/23488379/ijeee-v11i12p111
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
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article

Optimizing Solar and Wind Energy Integration in Grid-Connected EV Fast Charging Systems using Fuzzy Logic Control for Improved Stability and Power Quality

Chandra Sekhar G, M. Anitha, N.C. Kotaiah, Srinu Naick J
International Journal of Electrical and Electronics Engineering
Electric Vehicles and Infrastructure
article

Optimizing Solar and Wind Energy Integration in Grid-Connected EV Fast Charging Systems using Fuzzy Logic Control for Improved Stability and Power Quality

Chandra Sekhar G, M. Anitha, N.C. Kotaiah, Srinu Naick J
article en

Abstract

This paper presents the complete approach to integrating solar and wind renewable energy sources into grid-connected Electric Vehicle (EV) quick charging systems. The solar system utilizes a Perturb and Observe (P&O) Maximum Power Point Tracking (MPPT) boost converter to maximize energy extraction from the photovoltaic panels. In contrast, the wind energy system employs a similar MPPT technique to maximize wind power consumption. The proposed fuzzy logic controller system ensures consistent and efficient power conversion management during EV charging activities, improving system stability. Neutral-Point Clamped (NPC) voltage source converters are further utilised to optimise power conversion, improve voltage balance, and reduce switching losses. Reducing voltage fluctuations and resolving power quality issues helps the fuzzy logic controller significantly increase system stability. MATLAB simulations show that the combined use of MPPT for solar and wind, fuzzy logic control, and NPC converters results in effective energy distribution, enhanced load balancing, and reduced Total Harmonic Distortion (THD). Apart from fast-charging electric vehicles, the system is supposed to manage residential linear and nonlinear loads. The findings imply that whilst preserving power grid stability and improving general system performance for different load types, this integrated system successfully allows large-scale EV rapid charging utilising renewable energy.

International Journal of Electrical and Electronics EngineeringVol. 11(12)
Affordable and clean energy
Openalex Percentile: Top 77%
Electric Vehicles and Infrastructure
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