Data-driven spatial-temporal prediction of electric vehicle load profile considering charging behavior-Reference-Cited by-同舟云学术

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Data-driven spatial-temporal prediction of electric vehicle load profile considering charging behavior

Published:2020-10 Issue: Volume:187 Page:106469
ISSN:0378-7796
Container-title:Electric Power Systems Research
language:en
Short-container-title:Electric Power Systems Research

Author:

Ge Xiaolin,Shi Liang^ORCID,Fu Yang,Muyeen S.M.,Zhang Zhiquan,He Hongbo

Funder

National Natural Science Foundation of China

Shanghai Engineering Research Center of Green Energy Grid-Connected Technology

Shanghai Science and Technology

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology

Reference34 articles.

1. EV volumes.com. Available:http://www.evvolumes.com.

2. Energy management in smart distribution systems with vehicle-to-grid integrated microgrids;Nunna;IEEE Trans. Smart Grid,2018

3. Integration of plug-in electric vehicles into microgrids as energy and reactive power providers in market environment;Rabiee;IEEE Trans. Ind. Inform.,2016

4. Impact of electric vehicles on the expansion planning of distribution systems considering renewable energy, storage, and charging stations;de Quevedo;IEEE Trans. Smart Grid,2019

5. Managing demand for plug-in electric vehicles in unbalanced LV systems with photovoltaics;Akhavan-Rezai;IEEE Trans. Ind. Inform.,2017

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3. Adaptive Charging Simulation Model for Different Electric Vehicles and Mobility Patterns;Energies;2024-08-14

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