Battery Control for Node Capacity Increase for Electric Vehicle Charging Support

The integration of electric vehicles (EVs) into the power grid poses significant challenges and opportunities for energy management systems. This is especially concerning for parking lots or private building condominiums in which refurbishing is not possible or is costly. This paper presents a real-time monitoring approach to EV charging dynamics with battery storage support over a 24 h period. By simulating EV demand, state of charge (SOC), and charging and discharging events, we provide insights into the operational strategies for energy storage systems to ensure maximum charging simultaneity factor through internal power enhancement. The study uses a time-series analysis of EV demand, contrasting it with the battery’s SOC, to dynamically adjust charging and discharging actions within the constraints of the upstream infrastructure capacity. The model incorporates parameters such as maximum power capacity, energy storage capacity, and charging efficiencies, to reflect realistic conditions. Results indicate that real-time SOC monitoring, coupled with adaptive charging strategies, can mitigate peak demands and enhance the system’s responsiveness to fluctuating loads. This paper emphasizes the critical role of real-time data analysis in the effective management of energy resources in existing parking lots and lays the groundwork for developing intelligent grid-supportive frameworks in the context of growing EV adoption.

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Publication Details

Journal
Energies
Published
2024-11-07
DOI
https://doi.org/10.3390/en17225554
Citations
2
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
0.41

Funders

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article

Battery Control for Node Capacity Increase for Electric Vehicle Charging Support

Salvador Carvalhosa, Alexandre Lucas, Mushtaq Ahmad
2 citations
Energies
Advanced Battery Technologies Research
0.41
article

Battery Control for Node Capacity Increase for Electric Vehicle Charging Support

Salvador Carvalhosa, Alexandre Lucas, Mushtaq Ahmad
article en
2 citations

Abstract

The integration of electric vehicles (EVs) into the power grid poses significant challenges and opportunities for energy management systems. This is especially concerning for parking lots or private building condominiums in which refurbishing is not possible or is costly. This paper presents a real-time monitoring approach to EV charging dynamics with battery storage support over a 24 h period. By simulating EV demand, state of charge (SOC), and charging and discharging events, we provide insights into the operational strategies for energy storage systems to ensure maximum charging simultaneity factor through internal power enhancement. The study uses a time-series analysis of EV demand, contrasting it with the battery’s SOC, to dynamically adjust charging and discharging actions within the constraints of the upstream infrastructure capacity. The model incorporates parameters such as maximum power capacity, energy storage capacity, and charging efficiencies, to reflect realistic conditions. Results indicate that real-time SOC monitoring, coupled with adaptive charging strategies, can mitigate peak demands and enhance the system’s responsiveness to fluctuating loads. This paper emphasizes the critical role of real-time data analysis in the effective management of energy resources in existing parking lots and lays the groundwork for developing intelligent grid-supportive frameworks in the context of growing EV adoption.

EnergiesVol. 17(22)
INESC TEC (PT)
European Commission
Industry, innovation and infrastructure
Openalex Percentile: Top 39%
Advanced Battery Technologies Research
0.41
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Battery Control for Node Capacity Increase for Electric Vehicle Charging Support — Salvador Carvalhosa, Alexandre Lucas, et al. · Energies (2024) | TGRS Research Map | TGRS