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 southeast of Germany consisting of 50 municipalities, and results are presented. Model-based optimization of public charging infrastructure planning in rural areas | Request PDF. Available from: https://www.researchgate.net/publication/325846878_Model-based_optimization_of_public_charging_infrastructure_planning_in_rural_areas [accessed Aug 21 2018].    «

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,...    »