Stochastic Modeling of Power Demand Due to EVs Using Copula
By A. Lojowska, Dorota Kurowicka, George Papaefthymiou, L. D. Sluis. IEEE Transactions on Power Systems, 2012
208 citations recorded by the source corpus.
Subfields: Automotive Engineering, Electrical and Electronic Engineering, Renewable Energy, Sustainability and the Environment
View Paper: https://www.semanticscholar.org/paper/93ac54e24ed600c1b809f073fa23d33dc6d6fd85
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In Automotive Engineering
In Electrical and Electronic Engineering
In Renewable Energy, Sustainability and the Environment
Citations in the corpus
- Electric vehicles: Battery capacity, charger power, access to charging and the impacts on distribution networks (2020, methodology): “[34] uses a Gaussian Copula method to tie together the separate distributions of the time a vehicle leaves home, the time a vehicle arrives home and the overall distance it travels during the day (from which the charging energy requirement is derived) from the same Dutch travel data as [33].”
- Selecting critical features for data classification based on machine learning methods (2020, background): “…load consumption [61], price forecast of electrical power systems [62], electrical load data [63], electrical circuits [64], stochastic modelling [65], dynamic financial distress [66], Household indebt [67], social vulnerability [68], construction of social vulnerability index [69], financial…”