Hybrid Controlled DVR-Based Optimization for Power Quality Enhancement in Multi-Bus Grid Systems Using Enhanced Dung Bettle Optimizer Algorithm (Enhn-DBOA)

International Journal of Electrical and Electronics Engineering

© 2025 by SSRG - IJEEE Journal

Volume 12 Issue 3

Year of Publication : 2025

Authors : S. Sudharani, Godwin Immanuel D

10.14445/23488379/IJEEE-V12I3P118

How to Cite?

S. Sudharani, Godwin Immanuel D, "Hybrid Controlled DVR-Based Optimization for Power Quality Enhancement in Multi-Bus Grid Systems Using Enhanced Dung Bettle Optimizer Algorithm (Enhn-DBOA)," SSRG International Journal of Electrical and Electronics Engineering, vol. 12,  no. 3, pp. 185-201, 2025. Crossref, https://doi.org/10.14445/23488379/IJEEE-V12I3P118

Abstract:

This manuscript presents a comparative analysis of FOPID, FLC, and ANN-controlled Dynamic Voltage Restorer (DVR) systems in a grid-connected atmosphere, emphasizing the Optimization approach for enhancing performance. The Reboost converter is integrated with a DVR, and it is employed to enhance the voltage stability of a multi-bus system. The hybrid energy system consists of Photovoltaic (PV), Battery, and Wind Energy, which provides a robust interface to mitigate the voltage instability in weak bus systems. The output of the inverter is injected into the grid to compensate for the voltage sag caused by the increased load demand. To optimize control strategies, the parameters of FOPID, FLC, and ANN controllers are fine-tuned using an Enhanced Dung Bettle Optimizer Algorithm (Enhn-DBOA), providing optimal performance across a variety of operational conditions. The Dung Bettle Optimizer Algorithm (DBOA) is enhanced using the Ebola Search Optimization Algorithm (ESOA), and then it is named the Enhanced Dung Bettle Optimizer Algorithm (Enhn-DBOA). The FOPID, FLC, and ANN-controlled DVR systems are modeled in MATLAB/Simulink, and simulation results for bus voltage, real power, and reactive power are examined. According to the optimization-driven methodology, the ANN-controlled DVR system outperforms the FOPID and FLC-controlled systems in time-domain performance, with faster response times, higher voltage stability, and superior compensation for voltage sags. This paper emphasizes the effectiveness of optimization strategies in boosting DVR control performance for grid-connected systems.

Keywords:

Dynamic Voltage Restorer (DVR), Power Quality (PQ), Artificial Neural Networks (ANN), Fractional Order PID (FOPID), Fuzzy Logic Controllers (FLC), Static VAR Compensators (SVCs).

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