Voltage Stability Control Strategies for Hybrid Renewable DC Micro grids: A Comprehensive Review

This paper has presented a comprehensive review of voltage stability control strategies for hybrid renewable DC microgrids spanning the 2020–2026 period, covering conventional linear methods, hierarchical droop-based architectures, intelligent soft-computing techniques, robust nonlinear controllers, and emerging hybrid AI-driven approaches. The review establishes that each control paradigm offers distinct, quantifiable trade-offs among voltage regulation performance, communication dependency, computational complexity, and field-deployment readiness, as consolidated in Table I. The most critical research gaps identified—communication-independent autonomous operation, simultaneous multi-objective performance, embedded hardware implement ability, cyber security integration, and large-scale experimental validation—collectively define the primary barriers that must be overcome before intelligent voltage control can transition reliably from academic laboratories into commercial, defence, and critical infrastructure deployments. Emerging directions including physics-informed neural networks, digital twins, federated learning, and hybrid AI-robust control schemes represent promising and increasingly actionable pathways toward autonomous, physically grounded, and privacy-preserving next-generation DC microgrid voltage control. This review is intended to serve as a structured reference roadmap both for researchers advancing the fundamental science of the field and for practicing engineers tasked with designing voltage stability controllers for real-world hybrid renewable DC microgrid installations operating under increasing renewable penetration and increasingly stringent reliability requirements.

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