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Original Article

MOPSO-Optimized Fuzzy Logic-Based Vector Control for Robust DC-Link Regulation in Grid-Connected Hybrid PV– Wind Energy Systems

Adel Elgammal1

1 Professor, Utilities and Sustainable Engineering, The University of Trinidad & Tobago UTT

Published Online: January-April 2026

Pages: 55-67

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Abstract

This article proposes a new control strategy based on multi-objective particle swarm optimization (MOPSO)-based fuzzy logic vector control for the robust DC-link voltage regulation of grid-connected hybrid photovoltaic (PV)–wind energy systems. However, under changing irradiance and different wind speed as well as grid failures, in hybrid renewable systems, stable DC-link is critical for reliable power exchange between renewables sources and the grid. However, traditional PID based controller have poor dynamic performance, large overshoot and strong sensitivity against parameter uncertainties. In order to overcome these drawbacks, the proposed technique combines fuzzy logic control (FLC) with vector control and employs MOPSO to optimally tune controller parameters for improved dynamic response and robustness. The proposed unified DC-link control strategy is developed to coordinate the operation of photovoltaic (PV) subsystem, wind energy conversion system (WECS), and grid-side inverter. To enhance the performance of a nonlinear system, particularly to address larger settling times and overshoot as well as steady-state errors and control effort, the traditional linear regulator is replaced by a fuzzy logic controller in addition to employing Multi-Objective Particle Swarm Optimization (MOPSO) for performance objectives. Verified MATLAB/Simulink simulation results in various environment and grid conditions, such as sudden solar irradiance change, repeated wind speed switch (8 m/s to 12 m/s), and grid voltage disturbance demonstrating high frequency variations illustrate the effectiveness of the proposed method. The simulation study shows that the MOPSO-tuned fuzzy logic vector control outperforms classical PI-based control considerably in system performance. The DC-link voltage overshoot decreases from 15.2% to 4.3%, and the settling time enhances from 0.48 s to 0.19 s, it corresponds a regional of 60.4% reduction in full-range range. The voltage deviation in the steady-state is limited to within ±1.1% as against the PI control where it was ±4.6%. Moreover, with this control strategy, the total harmonic distortion (THD) of grid current is decreased from 5.1% to 2.2%, complying with grid code. In terms of grid disturbance analysis, the proposed controllers return to nominal operating conditions in 0.13 s versus 0.34 s for conventional control methods. In addition, the developed system shows higher than 97.8% power tracking efficiency in highly dynamic operating conditions. This control strategy has proven to be robust, efficient and adaptive for the DC-link regulation of hybrid PV–wind systems. This, in addition with the employment of MOPSO optimization enhanced dynamic performance along with insensitivity to uncertainties which resulted into better power quality establishment makes the integrated approach a highly suitable and future ready for keeping high penetration integration levels of renewable energy systems

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Citations

Adel Elgammal, “MOPSO-Optimized Fuzzy Logic-Based Vector Control for Robust DC-Link Regulation in Grid-Connected Hybrid PV–Wind Energy Systems”, Indian Journal of Electrical and Electronics Engineering, Volume 03, Issue 01, January-April 2026, PP: 55-67.

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© 2026 The Author(s). Published by Fifth Dimension Research Publication.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/ ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.

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