Electric Vehicle Charging Station Planning: An Overview

With the great popularization of the electric vehicles (EV) around the world, the planning of charging stations has become a key factor affecting user charging experience, grid stability, and socioeconomic benefits. This paper systematically reviews the research in the field of EV charging station planning. The article examines EV charging load forecasting methods, categorizing them into two types based on data sources-charging station history and real vehicle travel data-and analyzes their features and applications. Then, the article elaborates on the planning models for EV charging piles, such as point demand models, flow demand models, coverage models, and composite models. Corresponding solution algorithms are also introduced, including exact solution methods and heuristic algorithms. Finally, this paper summarizes the limitations of current research and provides an outlook on future research directions.

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Publication Details

Published
2025-05-23
DOI
https://doi.org/10.1109/ieecsc64206.2025.11099719
Citations
1
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.73
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article

Electric Vehicle Charging Station Planning: An Overview

Maode Ma
1 citations
Electric Vehicles and Infrastructure
0.73
article

Electric Vehicle Charging Station Planning: An Overview

Maode Ma
article en
1 citations

Abstract

With the great popularization of the electric vehicles (EV) around the world, the planning of charging stations has become a key factor affecting user charging experience, grid stability, and socioeconomic benefits. This paper systematically reviews the research in the field of EV charging station planning. The article examines EV charging load forecasting methods, categorizing them into two types based on data sources-charging station history and real vehicle travel data-and analyzes their features and applications. Then, the article elaborates on the planning models for EV charging piles, such as point demand models, flow demand models, coverage models, and composite models. Corresponding solution algorithms are also introduced, including exact solution methods and heuristic algorithms. Finally, this paper summarizes the limitations of current research and provides an outlook on future research directions.

Chongqing University (CN)
Openalex Percentile: Top 25%
Electric Vehicles and Infrastructure
0.73
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