Optimized Producer Subset Determination for Energy Routing in Smart Grids

Energy routing in smart grids is a critical process for optimizing the distribution of electrical power from multiple producers to a diverse set of consumers. Unlike traditional power grids, smart grids incorporate real-time data, advanced control systems, and distributed generation resources, enabling dynamic adjustments to energy flow. Energy routing in this context aims to achieve efficient energy transfer by selecting the optimal paths that minimize power loss, maximize transmission efficiency, and balance supply-demand conditions. A key challenge in energy routing is determining the optimal subset of producers for each consumer. This paper presents a scalable routing protocol utilizing the simulated annealing optimization algorithm. Simulations demonstrate the protocol’s effectiveness and efficiency, particularly when compared to current approaches. This research marks a significant step forward in improving smart grid management within today’s evolving energy landscape.

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Publication Details

Published
2025-05-06
DOI
https://doi.org/10.1109/ic2em63689.2025.11100568
Primary Topic
Smart Grid Security and Resilience
Type
article
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Optimized Producer Subset Determination for Energy Routing in Smart Grids

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Optimized Producer Subset Determination for Energy Routing in Smart Grids

Lemia Louail, Lina Benchikh, Djamila Mechta, Rahma Berchi, Assala Nacef
article en

Abstract

Energy routing in smart grids is a critical process for optimizing the distribution of electrical power from multiple producers to a diverse set of consumers. Unlike traditional power grids, smart grids incorporate real-time data, advanced control systems, and distributed generation resources, enabling dynamic adjustments to energy flow. Energy routing in this context aims to achieve efficient energy transfer by selecting the optimal paths that minimize power loss, maximize transmission efficiency, and balance supply-demand conditions. A key challenge in energy routing is determining the optimal subset of producers for each consumer. This paper presents a scalable routing protocol utilizing the simulated annealing optimization algorithm. Simulations demonstrate the protocol’s effectiveness and efficiency, particularly when compared to current approaches. This research marks a significant step forward in improving smart grid management within today’s evolving energy landscape.

Centre National de la Recherche Scientifique (FR), University Ferhat Abbas of Setif (DZ), Centre de Recherche en Automatique de Nancy (FR), Université de Lorraine (FR)
Affordable and clean energy
Openalex Percentile: Top 75%
Smart Grid Security and Resilience
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