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Faustino Adlinde M*
Department of Electrical and Electronics Engineering, St. Mother Theresa Engineering College, Tuticorin 628102, Tamil Nadu, India
faustinoadlinde607@gmail.com
Ravi A
Department of Electrical and Electronics Engineering, Francis Xavier Engineering College, Tirunelveli 627003, Tamil Nadu, India
Daniel Sathyaraj J
Department of Electrical and Electronics Engineering, Francis Xavier Engineering College, Tirunelveli 627003, Tamil Nadu, India

Abstract

The transition toward decentralized renewable energy systems necessitates advanced optimization strategies capable of ensuring stable, efficient, and resilient microgrid operation under variable generation and load conditions. This paper proposes a comprehensive hybrid renewable microgrid framework integrating photovoltaic (PV) generation through a novel Z-Source Luo Converter (ZSLC), wind energy through a Doubly Fed Induction Generator (DFIG) with Proportional-Integral (PI)-based droop control, and battery energy storage with intelligent charge management. A novel Grey Wolf Optimized Whale Algorithm (GWO-WA) is developed to jointly optimize converter duty cycles, droop control coefficients, and energy storage dispatch decisions in real time. The GWO-WA hybridizes the social hierarchy of grey wolf optimization with the spiral bubble-net hunting mechanism of the whale algorithm, achieving superior exploration-exploitation balance compared to each constituent algorithm independently. Continuous-time simulation in MATLAB/Simulink demonstrates a peak efficiency of 96.5% for the proposed Z-Source Luo Converter, Total Harmonic Distortion (THD) of 0.83% in simulation and 1.61% in hardware validation, and a settling time of 0.52 ms under step load changes—representing improvements of 35–48% over conventional single-algorithm approaches. The microgrid transitions seamlessly between grid-connected and islanded modes upon detection of grid disturbances, with frequency and voltage deviations maintained within IEEE 1547 standard limits. Industrial information integration aspects are addressed through a SCADA-compatible supervisory control interface enabling real-time monitoring and remote optimization parameter updates. The proposed framework provides a technically viable pathway for community-scale microgrid deployment in regions with high renewable penetration

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How to Cite

Adlinde M, F., A, R., & Sathyaraj J., D. (2022). Grey Wolf Optimized Whale Algorithm for Hybrid Renewable Microgrid Control: Z-Source Luo Converter Integration and DFIG-Based Droop Control Strategy. Journal of Intelligent Industrial Convergence, 2(1), 1-11. https://doi.org/10.63646/jiic.2022.020101