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Autonomous control is increasingly relevant to smart-grid operation, where control systems may support voltage regulation, frequency control, dispatch, and anomaly response. Yet their trustworthiness remains uncertain when decisions are opaque, intervention options are unclear, and cyber-physical conditions are unstable. Existing research often treats explainability, operator intervention, and cyber-physical uncertainty as separate design or evaluation issues. This separation limits theory development because trust in autonomous grid control depends on how these mechanisms operate together. This article develops a conceptual theory of trustworthy autonomous smart-grid control. The theory links explainability, operator intervention, and cyber-physical uncertainty to both perceived and operational trustworthiness. The article uses theory-building logic rather than empirical testing. It synthesizes concepts from trustworthy AI, human-automation interaction, explainable AI, and cyber-physical security to construct mechanisms and derive propositions. The proposed model specifies causal pathways through which explanation quality, intervention capability, and uncertainty handling shape trustworthiness. It also identifies interaction effects, boundary conditions, and testable propositions for future research. The theory provides a foundation for designing, evaluating, and empirically testing trustworthy autonomous control systems in smart-grid environments. It emphasizes that trustworthiness is not produced by transparency, human oversight, or robustness alone, but by their coordinated operation.