AI Based Hybrid Controlled Grid / Standalone Solar Integrated Unified Power Quality Conditioner for the EV Charging Station

International Journal of Electrical and Electronics Engineering

© 2024 by SSRG - IJEEE Journal

Volume 11 Issue 8

Year of Publication : 2024

Authors : Bomma Shwetha, G. Suresh Babu, G. Mallesham

10.14445/23488379/IJEEE-V11I8P117

How to Cite?

Bomma Shwetha, G. Suresh Babu, G. Mallesham, "AI Based Hybrid Controlled Grid / Standalone Solar Integrated Unified Power Quality Conditioner for the EV Charging Station," SSRG International Journal of Electrical and Electronics Engineering, vol. 11,  no. 8, pp. 188-207, 2024. Crossref, https://doi.org/10.14445/23488379/IJEEE-V11I8P117

Abstract:

Grid-connected sustainable systems are now increasingly vulnerable to PQ problems due to the development of power electronics technology. In actuality, there are two instances in which Electric Vehicle Charging Stations (EVCS) have significant distortions: (1) when they are connected to the grid and (2) when they are operating independently and receiving power from BESD and solar energy. It must be addressed immediately to resolve this and enable the system’s Power Quality upgrade. A hybrid control method, which combines a PIC for the SHPF of the Unified PQ Conditioner (UPQC) with an Artificial Neural Fuzzy Interface System (ANFIS), is suggested for the current UPQC to improve the PQ level. Attaining steady SVDC during variations in loads and sun irradiation changes is the primary objective of UPQC. Other objectives include mitigating disturbance/ swell/ sag and grid voltage imbalances. The developed model’s working using grid and island scenarios is assessed using four distinct test cases. To prove its superiority, it is necessary to compare the suggested technology against industry standards like SMC controllers and Proportional Integral Controllers (PIC). The proposed methodology reduces THD to 2.23%, 2.28%, and 1.84%; nonetheless, it is not as effective as the existing methods indicated by the survey.

Keywords:

Artificial Neuro Fuzzy Interface System, PV system, UPQC, EV charging station, Power quality.

References:

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