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Optimizing power grids: A valley-filling heuristic for energy-efficient electric vehicle charging
Guilherme Gloriano de Souza1, Ricardo Ribeiro Dos Santos1, Ruben Barros Godoy2
1College of Computing, Federal University of Mato Grosso do Sul, Campo Grande, Mato Grosso do Sul, Brazil.
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.
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