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Data-driven EV charging infrastructure with uncertainty based on a spatial-temporal flow-driven (STFD) models

Talal Alharbi1, Ahmed Abdalrahman2, Mostafa H Mostafa3

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Summary
This summary is machine-generated.

Integrating energy storage systems (ESS) into microgrids (MGs) optimizes electric vehicle (EV) charging infrastructure placement. This enhances voltage stability, reduces power losses, and improves economic efficiency for sustainable urban transport.

Keywords:
Charging infrastructureCharging stationEnergy storage systemsRenewable energySmart citiesSustainable Development Goals (SDGs)Uncertainty

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Area of Science:

  • Electrical Engineering
  • Sustainable Transportation
  • Energy Systems

Background:

  • Electric vehicles (EVs) are crucial for achieving UN Sustainable Development Goals, but their integration into microgrids (MGs) presents challenges like increased power losses and voltage instability.
  • Effective placement of EV charging infrastructure and energy storage systems (ESS) is vital for mitigating these impacts and ensuring grid stability.

Purpose of the Study:

  • To develop a comprehensive planning methodology for optimizing the placement of EV charging stations and ESS within urban MGs.
  • To address challenges posed by increased EV adoption, including power losses, voltage profile deterioration, and voltage stability issues.
  • To enhance overall MG performance and economic efficiency through integrated planning.

Main Methods:

  • A spatial-temporal traffic flow analysis was used to optimize EV charging station placement.
  • Stochastic modeling was employed to determine optimal ESS locations, considering variable loads and renewable energy uncertainties.
  • A multi-objective optimization framework was applied to improve voltage stability, reduce power losses, and enhance voltage profiles.
  • Economic evaluation of ESS integration costs was incorporated.

Main Results:

  • The integrated planning approach effectively mitigated adverse impacts of EV integration on MG performance.
  • ESS integration significantly improved voltage stability (VSI increased from 0.5848 to 0.8631).
  • Power losses were reduced by 33.34%, transformer loading decreased by 19.5%, and economic efficiency was enhanced.
  • Sodium-Nickel Chloride (Na-NiCl2) ESS demonstrated the highest savings (6.99%).

Conclusions:

  • Optimized placement of EV charging stations and ESS is essential for sustainable urban transportation and stable microgrid operation.
  • The proposed stochastic methodology effectively addresses uncertainties in electrical loads and renewable energy generation.
  • ESS integration offers substantial technical and financial benefits, improving microgrid resilience and economic viability.