Forecasting plug-in electric vehicles load profile using artificial neural networks
MetadataShow full item record
Plug-in electric vehicles (PEVs) are becoming very popular these days and consequently, their load management will be a challenging issue for the network operators in the future. This paper proposes an artificial intelligence approach based on neural networks to forecast daily load profile of individual and fleets of randomly plugged-in PEVs, as well as the upstream distribution transformer loading. An artificial neural network (ANN) model will be developed to forecast daily arrival time (Ta) and daily travel distance (Dtr) of individual PEV using historical data collected for each vehicle in the past two years. The predicted parameters are then will be used to forecast transformer loading with PEV charging activities. The results of this paper will be very beneficial to coordination and charge/discharge management of PEVs as well as demand load management, network planning and operation proposes. Detailed simulations are presented to investigate the feasibility and accuracy of the proposed forecasting strategy.
Showing items related by title, author, creator and subject.
Mostafa, Fahed. (2011)Market risk refers to the potential loss that can be incurred as a result of movements inmarket factors. Capturing and measuring these factors are crucial in understanding andevaluating the risk exposure associated with ...
A Receding Predictive Horizon Approach to the Periodic Optimization of Community Batery Energy Storage SystemsWolfs, Peter; Reddy, S. (2012)Community scale battery energy storage systems can improve the utilization of network assets and increase the uptake of intermittent renewable energy sources. This paper presents an efficient algorithm for optimizing the ...
Battery time of discharge setting for maximum effectiveness in a distribution smart grid applicationHosseinzadeh, N.; Wolfs, Peter (2014)© 2014 IEEE. Distributed Generation (DG) is a feature of smart grids in power distribution networks. The DG comprises of various types of renewable energy. Battery storages may be used along with the DG sources to store ...