Spatial and Temporal Model of Electric Vehicle Charging Demand
By Sungwoo Bae, Alexis Kwasinski. IEEE Transactions on Smart Grid, 2012
414 citations recorded by the source corpus.
Subfields: Automotive Engineering, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/af017fe0fe0c02abbaf9fefaf2100e701b3f7e8b
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In Automotive Engineering
In Electrical and Electronic Engineering
Citations in the corpus
- Network Equilibrium of Coupled Transportation and Power Distribution Systems (2018, methodology): “, arrival rates and timings, as well as amounts of charging requests are specified either in a deterministic or a stochastic manner in advance, which can be determined from data-driven methods [36]–[38] or queueing theory [39], or modeled by a probabilistic model via Markov decision process [40].”
- A Comprehensive Study of Implemented International Standards, Technical Challenges, Impacts and Prospects for Electric Vehicles (2018, methodology): “To alleviate the impacts of charging performed by high power charging levels, the coordinated controlled charging scheme should be employed [49].”
- Electric vehicle charging demand forecasting model based on big data technologies (2016, methodology): “This paper considers both slow and fast charging classifications although previous studies have only considered either a slow charging classification [5,11,15] or a fast charging classification [13,14].”