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The energy transition, while undeniably offering countless advantages, has increasingly subjected electrical systems to stress conditions that may jeopardize their secure operation. To address this challenge, a wide range of control strategies has been developed. This work proposes a proactive and computationally efficient methodology, specifically designed to align with the capabilities of a smart MicroGrid ( μ G). The approach leverages the offline characterization of a feasibility region, defined as a convex structure in the operational space of the electrical system, to ensure secure operation within time frames compatible with real-time management for such a constrained system. The proposed method evaluates the stability and security of an operating point derived from an economic dispatch. When this point fails to meet predefined security requirements, the methodology identifies an alternative operating condition that ensures system security while minimizing deviations from the economically optimal state. The effectiveness of this approach has been validated through a case study replicating a subset of the experimental μ G implemented in the PrInCE Lab at Polytechnic University of Bari. • Geometric analysis using Convex Hull to define the Practical stability Region of a Microgrid. • Identification of secure operational points via Convex Hull to ensure stability. • Strategy for proactive control of MicroGrids’ stability and performance. • Resource optimization to enhance stability and reliability of the system. • Computational effort focused in the offline phase to ensure real-time security.
Amato et al. (Wed,) studied this question.