A Dual-Mode Control Architecture for Intelligent Virtual Power Plants: Demand Response as a Real-Time Governance and Optimization Instrument for Distribution Grids

This paper has presented a comprehensive nine-layer architecture for intelligent Virtual Power Plant platforms. The architecture's key innovations—the Demand Governance Layer for dual-mode operation, the canonical control abstraction for device heterogeneity, and the hybrid digital twin for safety validation—enable VPPs to function as true cyber-physical control systems capable of both economic optimization and emergency grid support. The mathematical formulations provide rigorous foundation for fleet modeling, grid constraint evaluation, and multi-objective optimization. The architectural patterns (layered design, pub-sub communication, strategy pattern for modes, adapter pattern for devices) ensure scalability, maintainability, and extensibility. Performance targets include prediction accuracy with MAE below 5%, comfort preservation above 98%, and cost reductions exceeding 20%. As distribution grids face unprecedented stress from electrification and extreme weather, architectures like this provide the foundation for intelligent, human-centric demand response that supports both grid reliability and economic efficiency at scale

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