Electric Charging Demand Forecast and Capture for Infrastructure Placement Using Gravity Modelling: A Case Study-Reference-Cited by-同舟云学术

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Electric Charging Demand Forecast and Capture for Infrastructure Placement Using Gravity Modelling: A Case Study

Published:2023-09-24 Issue: Volume: Page:2112-2117
ISSN:
Container-title:2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)
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Author:

Rodrigues Gonçalo¹,Barbosa Flávia²,Schuller Pedro³,Silva Diogo³,Pereira João³,Azevedo Rui³,Guimarães Luis⁴

Affiliation:

1. University of Porto,Faculty of Engineering,Porto,Portugal

2. INESC TEC, Faculdade de Engenharia, Universidade do Porto, Porto, Portugal

3. LTPlabs S.A.,Porto,Portugal

4. LTPlabs S.A.,Porto, Portugal INESC TEC, Faculdade de Engenharia, Universidade do Porto, Porto, Portugal

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10420842/10420843/10421918.pdf?arnumber=10421918

Reference26 articles.

1. MOBI.DATA - Mobility, Portugal;MOBLE,2022

2. Vehicles and fleet | Portugal | European Alternative Fuels Observatory;EAFO,2022

3. A location model for electric vehicle (EV) public charging stations based on drivers’ existing activities

4. How will electric vehicles affect traffic congestion and energy consumption: an integrated modelling approach

5. A stochastic flow-capturing model to optimize the location of fast-charging stations with uncertain electric vehicle flows

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