Open Access

ARTICLE

A Flexible Decision Method for Holonic Smart Grids

Ihab Taleb, Guillaume Guerard^*, Frédéric Fauberteau, Nga Nguyen, Pascal Clain

De Vinci Higher Education, De Vinci Research Center, Paris La Defense Cedex, 92916, France

* Corresponding Author: Guillaume Guerard. Email:

(This article belongs to the Special Issue: Advanced Artificial Intelligence and Machine Learning Methods Applied to Energy Systems)

Computer Modeling in Engineering & Sciences 2025, 145(1), 597-619. https://doi.org/10.32604/cmes.2025.070517

Received 18 July 2025; Accepted 29 September 2025; Issue published 30 October 2025

Abstract

Isolated power systems, such as those on islands, face acute challenges in balancing energy demand with limited generation resources, making them particularly vulnerable to disruptions. This paper addresses these challenges by proposing a novel control and simulation framework based on a holonic multi-agent architecture, specifically developed as a digital twin for the Mayotte island grid. The primary contribution is a multi-objective optimization model, driven by a genetic algorithm, designed to enhance grid resilience through intelligent, decentralized decision-making. The efficacy of this architecture is validated through three distinct simulation scenarios: (1) a baseline scenario establishing nominal grid operation; (2) a critical disruption involving the failure of a major power plant; and (3) a localized fault resulting in the complete disconnection of a regional sub-grid. The major results demonstrate the system’s dual resilience mechanisms. In the plant failure scenario, the top-level holon successfully managed a global energy deficit by optimally reallocating shared resources, prioritizing grid stability over complete demand satisfaction. In the disconnection scenario, the affected holon demonstrated true autonomy, transitioning seamlessly into a self-sufficient islanded microgrid to prevent a cascading failure. Collectively, these findings validate the holonic model as a robust decision-support tool capable of managing both systemic and localized faults, thereby significantly enhancing the operational resilience and stability of isolated smart grids.

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Keywords

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