Model-based optimization of public charging infrastructure planning in rural areas

被引:4
|
作者
Niels, Tanja [1 ]
Gerstenberger, Marcus [2 ]
Bogenberger, Klaus [1 ]
Hessel, Christoph [2 ]
Gigl, Andrea [2 ]
Wagner, Katrin [1 ]
机构
[1] Bundeswehr Univ Munich, Werner Heisenberg Weg 39, D-85579 Neubiberg, Germany
[2] Gevas Humberg & Partner Ingenieurgesell Verkehrsp, Grillparzerstr 12a, D-81675 Munich, Germany
关键词
Public charging infrastructure; forecast of charging demand; location allocation;
D O I
10.1016/j.trpro.2019.09.056
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
This paper focuses on the planning of a suitable public charging infrastructure for electric vehicles (EVs), especially in rural areas. A model-based optimization approach is presented that takes four different user groups of public charging infrastructure into account: inhabitants, commuters, hotel guests, and short-term visitors of tourist destinations and central locations. The methodology consists of three steps: In a first step, the dimension of charging demand at public charging stations, i.e. the number of charging events per day, is forecast on a macroscopic level for every municipality and for each of the four user groups. Afterwards, the forecast charging demand is located within the municipality for each customer group, i.e. destinations of the respective customer groups are identified. In a third step, we optimally allocate charging stations according to the dimension and spatial distribution of the forecast demand. We analyze three different scenarios with a growing share of EVs and a growing average range, which represent different stages of the development of electric mobility. The method is applied to a region in the south-east of Germany consisting of 50 municipalities, and results are presented. (C) 2019 The Authors. Published by Elsevier Ltd.
引用
收藏
页码:342 / 353
页数:12
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