Modified Antlion Optimization Based Voltage Control for Five Level Packed U Cell Inverter in Grid Integrated Photovoltaic Charging System for Electric Vehicles.

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Bibliographic Details
Title:	Modified Antlion Optimization Based Voltage Control for Five Level Packed U Cell Inverter in Grid Integrated Photovoltaic Charging System for Electric Vehicles.
Authors:	RAMYA, S.¹ ramyas14101985@outlook.com, SUNDAR, G.¹ Sund_geee@yahoo.co.in
Source:	Technical Gazette / Tehnički Vjesnik. 2026, Vol. 33 Issue 2, p732-741. 10p.
Subjects:	Optimization algorithms, Harmonic suppression filters, Electric vehicle charging stations, Power supply quality, Voltage control, Photovoltaic power systems, Electric inverters
Abstract:	The transportation and energy sectors are increasingly integrating electric vehicles (EVs) as essential components of sustainable development. Photovoltaic (PV)- powered charging stations, comprising PV modules interfaced with the public grid, offer a reliable and cost-effective solution for EV battery charging. However, these stations typically introduce nonlinear loads, leading to significant current distortions that degrade power quality. To mitigate these issues, Shunt Active Power Filters (SAPFs) are employed to suppress harmonic currents and ensure clean energy delivery. The inverter in the SAPF operates as a controlled current source, injecting compensating harmonics in parallel with the nonlinear load. A key component in this system is the DC link voltage controller, which directly influences the accuracy of harmonic compensation. This study proposes a Modified Antlion Optimization Algorithm (MALO) for DC link voltage control in a SAPF using a Five-Level Packed U Cell (PUC5) inverter for a grid-connected PV system with EV charging capabilities. The MALO algorithm surpasses ALO in terms of convergence rate and circumvents the local optima. MALO optimises the parameter of the PI controller in SAPF using the objective function of integral time absolute error (ITAE). The performance of the MALO-based controller is compared against a Particle Swarm Optimization (PSO) approach under identical system configurations. Both models are evaluated using MATLAB/Simulink simulations based on a modified instantaneous reactive power (MIRP) theory for harmonic current extraction. Results demonstrate that the MALO-based control achieves superior harmonic mitigation, reducing Total Harmonic Distortion (THD) to as low as 1.53%, thereby outperforming the PSO-based system. Maximum harmonic compensation of around 96.75% is achieved with the help of the proposed system compared to uncompensated power system. The findings validate the effectiveness of MALO for improving power quality in PV-powered EV charging infrastructures. [ABSTRACT FROM AUTHOR]
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Database:	Engineering Source

Description
Abstract:	The transportation and energy sectors are increasingly integrating electric vehicles (EVs) as essential components of sustainable development. Photovoltaic (PV)- powered charging stations, comprising PV modules interfaced with the public grid, offer a reliable and cost-effective solution for EV battery charging. However, these stations typically introduce nonlinear loads, leading to significant current distortions that degrade power quality. To mitigate these issues, Shunt Active Power Filters (SAPFs) are employed to suppress harmonic currents and ensure clean energy delivery. The inverter in the SAPF operates as a controlled current source, injecting compensating harmonics in parallel with the nonlinear load. A key component in this system is the DC link voltage controller, which directly influences the accuracy of harmonic compensation. This study proposes a Modified Antlion Optimization Algorithm (MALO) for DC link voltage control in a SAPF using a Five-Level Packed U Cell (PUC5) inverter for a grid-connected PV system with EV charging capabilities. The MALO algorithm surpasses ALO in terms of convergence rate and circumvents the local optima. MALO optimises the parameter of the PI controller in SAPF using the objective function of integral time absolute error (ITAE). The performance of the MALO-based controller is compared against a Particle Swarm Optimization (PSO) approach under identical system configurations. Both models are evaluated using MATLAB/Simulink simulations based on a modified instantaneous reactive power (MIRP) theory for harmonic current extraction. Results demonstrate that the MALO-based control achieves superior harmonic mitigation, reducing Total Harmonic Distortion (THD) to as low as 1.53%, thereby outperforming the PSO-based system. Maximum harmonic compensation of around 96.75% is achieved with the help of the proposed system compared to uncompensated power system. The findings validate the effectiveness of MALO for improving power quality in PV-powered EV charging infrastructures. [ABSTRACT FROM AUTHOR]
ISSN:	13303651
DOI:	10.17559/TV-20250614002749