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Smart collaborations among the smart grid, electric vehicles, and aggregators will provide range of benefits to stakeholders involved in an intelligent transportation system (ITS). The EVs, nowadays, are becoming the epicenter of smart power system research towards the electrification of transport. However, massive penetration of EVs will pose management threats to the supporting smart grid in the foreseeable future. This work proposes a risk averse optimization framework for smart charging management of electric vehicles. Adopting conditional value at risk (CVaR) for estimating the risks, the work attempts to propose an optimized bidding strategy for the smart charging stations (SCS) that act on behalf of aggregators for managing the financial risk caused by the uncertainties. Finally, a fuzzified translation model is discussed along with notable methodologies as a solution strategy to the risk averse cost optimization problem.
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W. Jing, Y. Yan, I. Kim, and M. Sarvi, “Electric vehicles: A review of network modelling and future research needs,” Adv. Mech. Eng., vol. 8, no. 1, pp. 1–8, 2016.
D. Thoshitha Gamage, David Anderson, C. H. Bakken, Kenneth Birman, Anjan Bose, and and R. van R. Ketan Maheshwari, “Mission-Critical Cloud Computing for Critical Infrastructures,” pp. 1–16.
V. Razo, S. Member, and C. Goebel, “Vehicle-Originating-Signals for Real-Time Charging Control of Electric Vehicle Fleets,” IEEE Trans.Transportation Electrification vol. 1, no. 2, pp. 150–167, 2015.
N. G. Omran, S. Member, S. Filizadeh, and S. Member, “Location-Based Forecasting of Vehicular Charging Load on the Distribution System,” IEEE Trans. Smart Grid, vol. 5, no. 2, pp. 632–641, 2014.
Y. He, B. Venkatesh, and L. Guan, “Optimal scheduling for charging and discharging of electric vehicles,” IEEE Trans. Smart Grid, vol. 3, no. 3, pp. 1095–1105, 2012.
L. Pieltain Fernández, T. Gómez San Román, R. Cossent, C. Mateo Domingo, and P. Frías, “Assessment of the impact of plug-in electric vehicles on distribution networks,” IEEE Trans. Power Syst., vol. 26, no. 1, pp. 206–213, 2011.
EVI, “Global EV Outlook 2016: Beyond one million electric cars,” 2016.
“smart charging : steering the charge, driving the change,” no. March, 2015.
D. Alahakoon and X. Yu, “Smart Electricity Meter Data Intelligence for Future Energy Systems : A Survey,” IEEE Trans. Industrial Informatics, vol. 12, no. 1, pp. 425–436, 2016.
H. Wu and M. Shahidehpour, “A Game Theoretic Approach to Risk-Based Optimal Bidding Strategies for Electric Vehicle Aggregators in Electricity Markets With Variable Wind Energy Resources,” IEEE Trans. Sustainable Energy, vol. 7, no. 1, pp. 374–385, 2016.
R. Y. and R. Clarke, “Framework for Risk Analysis in Smart Grid Perspective Based Approach,” Proc. 8th Int’l Conf. Crit. Inf. Infrastructures Secur. (CRITIS 2013), Amsterdam, 16–18 Sept. 2013.
S. Deilami et al., “Real-Time Coordination of Plug-In Electric Vehicle Charging in Smart Grids to Minimize Power Losses and Improve Voltage Profile,” IEEE Trans. Smart Grid, vol. 2, no. 3, pp. 456–467, 2011.
- A Risk Averse Business Model for Smart Charging of Electric Vehicles
Md. Muzakkir Hussain
Mohammad Saad Alam
M.M. Sufyan Beg
- Springer Singapore
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