Charging demand of Plug-in Electric Vehicles: Forecasting travel behavior based on a novel Rough Artificial Neural Network approach

Charging demand of Plug-in Electric Vehicles: Forecasting travel behavior based on a novel Rough Artificial Neural Network approach

The market penetration of Plug-in Electric Vehicles (PEVs) is escalating due to their energy saving and environmental benefits. In order to address PEVs impact on the electric networks, the aggregators need to accurately predict the PEV Travel Behavior (PEV-TB) since the addition of a great number o...

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Bibliographic Details
Main Authors: Ahmadian, A. (Author), Gao, H.O (Author), Golkar, M.A (Author), Jahangir, H. (Author), Miret, J. (Author), Tayarani, H. (Author), Tayarani, M. (Author)
Format: Article
Language:English
Published: Elsevier Ltd 2019
Subjects:
Artificial neural network
Artificial neural network approach
Charging (batteries)
Circuit theory
Degree of uncertainty
Economic analysis
Electric automobiles
Electric power distribution
Energy conservation
Environmental benefits
Feedforward neural networks
Forecasting
Intelligent systems
Losses
Monte Carlo methods
Neural networks
Plug-in electric vehicle
Plug-in electric vehicles
Recurrent artificial neural networks
Recurrent neural networks
Rough neuron
Smart charging
Travel behavior
Travel behaviors
Vehicle electrifications
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