Optimal Charge Control of Plug-In Hybrid Electric Vehicles in Deregulated Electricity Markets

By Niklas Rotering, Marija D. Ilic. IEEE Transactions on Power Systems, 2011

660 citations recorded by the source corpus.

Subfields: Automotive Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/ca5d6d1a437f763118d6ff9e31a0e36748961060

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Citations in the corpus

Economics of Electric Vehicle Charging: A Game Theoretic Approach (2012, methodology): “In [2], the optimal charge control of PEVs is analyzed”
A Stochastic Multi-Layer Agent-Based Model to Study Electricity Market Participants Behavior (2015, background): “Since the importance of energy conservation and environmental protection is growing, renewable resources, plug-in electric vehicles (PEVs) and demand response (DR) can favorably affect the future smart grid [7]–[9].”
Distribution Locational Marginal Pricing for Optimal Electric Vehicle Charging Management (2014, background): “There is some diversity regarding the optimal manner in which to coordinate charging and the proposed objectives for such coordination include minimization of losses [7], maximization of EV penetration [9], and minimization of customer charging costs [12], [13].”
A Game-Theoretic Approach to Energy Trading in the Smart Grid (2013, background): “Developing a distributed energy storage system for transferring photovoltaic power to electric vehicles as well as introducing efficient power management schemes between storage units and the smart grid have been studied in [5] and [10], respectively.”
A Distributed Demand Response Algorithm and Its Application to PHEV Charging in Smart Grids (2012, methodology): “Compared to previous work such as [14], [15] and [13] where there is often a centralized control entity that computes optimal solutions using techniques such as dynamic programming, our algorithm is fully distributed and can scale to a large number of PHEVs.”
Optimal Bidding Strategy for Electric Vehicle Aggregators in Electricity Markets (2013, background): “EV participation in energy and ancillary services markets has been studied in [5], [15], and [16].”
The rise of electric vehicles—2020 status and future expectations (2021, neutral): “Rotering and Ilic (2011) develop a dynamic-optimization-based approach to control EV charging and bidirectional V2G services (with a focus on the provision of ancillary services).”
Day ahead optimization of an electric vehicle fleet providing ancillary services in the Los Angeles Air Force Base vehicle-to-grid demonstration (2018, background): “Some models explicitly consider the point of view of the charging services aggregator [11,13,18,21] or market participation, constraints and bidding timelines [13,22,23], however these models focus on available price data, often from the PJM market, and are never interested in participation rules of”
Optimal deployment of public charging stations for plug-in hybrid electric vehicles (2013, background): “…Ext. 1455; Email: yafeng@ce.ufl.edu Although currently most PHEVs in the U.S. are conversions of conventional hybrid electric vehicles, major vehicle manufactures, including Toyota, General Motors and Ford, have their PHEVs available in the market starting 2011 (Rotering and Ilic, 2011).”
Electric vehicle fleet management in smart grids: A review of services, optimization and control aspects (2016, positive): “Rotering and Ilic [31] studied the participation of V2G in the ancillary service markets for the independent system operator of California.”
Modeling of Plug-in Hybrid Electric Vehicle Charging Demand in Probabilistic Power Flow Calculations (2012, methodology): “A control strategy was proposed in [10] to optimize the energy consumption stemming from PHEV charging in a residential use case; another two strategies were presented in [11] to optimize charging time and energy flows of a PHEV, considering forecasted electricity price and system auxiliary service.”
Optimal Scheduling of Vehicle-to-Grid Energy and Ancillary Services (2012, methodology): “It also allows asymmetric bidding of regulation up and down as well as a biased POP in either direction, which were not considered in [7] and [17].”
Coordinated Charging of Electric Vehicles for Congestion Prevention in the Distribution Grid (2014, methodology): “2) Similar methods: • Implement centralized control/marketing method to maximize business values [1]–[7]; • Optimize the charging process of EVs [6], [8]–[11].”