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

PLoS One. 2025 Jan 7;20(1):e0316677. doi: 10.1371/journal.pone.0316677. eCollection 2025.

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.

MeSH terms

  • Conservation of Energy Resources / methods
  • Electric Power Supplies*
  • Electricity*
  • Heuristics
  • Renewable Energy*

Grants and funding

Conselho Nacional de Desenvolvimento Científico e Tecnológico Award Number: 160179/2020-3.