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Optimizing power grids: A valley-filling heuristic for energy-efficient electric vehicle charging

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  • Guilherme Gloriano de Souza
  • Ricardo Ribeiro dos Santos
  • Ruben Barros Godoy

Abstract

The expansion of electric vehicles (EVs) challenges electricity grids by increasing charging demand, thereby making Demand-Side Management (DSM) strategies essential to maintaining balance between supply and demand. Among these strategies, the Valley-Filling approach has emerged as a promising method to optimize renewable energy utilization and alleviate grid stress. This study introduces a novel heuristic, Load Conservation Valley-Filling (LCVF), which builds on the Classical and Optimistic Valley-Filling approaches by incorporating dynamic load conservation principles, enabling better alignment of EV charging with grid capacity. We conducted a comprehensive analysis of the heuristic across five EV charging scenarios. In both the Original and Flexible scenarios, LCVF reduced energy demand by up to 10.65%, demonstrating its adaptability and effectiveness. Notably, in the 24-hour Availability scenario, LCVF achieved a reduction of over 20% in energy demand compared to CVF. These findings indicate that LCVF could play a crucial role in enhancing real-world EV charging infrastructure, boosting energy efficiency and grid stability. By integrating DSM strategies like LCVF, energy grids can better accommodate renewable energy sources, promoting more sustainable operations.

Suggested Citation

  • Guilherme Gloriano de Souza & Ricardo Ribeiro dos Santos & Ruben Barros Godoy, 2025. "Optimizing power grids: A valley-filling heuristic for energy-efficient electric vehicle charging," PLOS ONE, Public Library of Science, vol. 20(1), pages 1-36, January.
  • Handle: RePEc:plo:pone00:0316677
    DOI: 10.1371/journal.pone.0316677
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