Stochastic Park-and-Charge Balancing for Fully Electric and Plug-in Hybrid Vehicles

Motivated by the need to provide services to alleviate range anxiety of electric vehicles, we consider the problem of balancing charging demand across a network of charging stations. Our objective is to reduce the potential for excessively long queues to build up at some charging stations, although other charging stations are underutilized. A stochastic balancing algorithm is presented to achieve these goals. A further feature of this algorithm is that it is fully decentralized and facilitates a plug-and-play type of behavior. Using our system, the charging stations can join and leave the network without any changes to, or communication with, a centralized infrastructure. Analysis and simulations are presented to illustrate the efficacy of our algorithm.

[1]  Michael O. Harpster,et al.  The Electrification of the Automobile: From Conventional Hybrid, to Plug-in Hybrids, to Extended-Range Electric Vehicles , 2008 .

[2]  Hua Qin,et al.  Charging scheduling with minimal waiting in a network of electric vehicles and charging stations , 2011, VANET '11.

[3]  Andreas Klappenecker,et al.  Finding available parking spaces made easy , 2010, DIALM-POMC '10.

[4]  C. Ratti,et al.  COMPARISON OF METHODOLOGIES FOR COMPUTING SKY VIEW FACTOR IN URBAN ENVIRONMENTS , 2001 .

[5]  Bernhard Hofmann-Wellenhof,et al.  GNSS - Global Navigation Satellite Systems: GPS, GLONASS, Galileo, and more , 2007 .

[6]  Robert Shorten,et al.  Growth Conditions for the Global Stability of High-Speed Communication Networks With a Single Congested Link , 2008, IEEE Transactions on Automatic Control.

[7]  Michael Mitzenmacher,et al.  The Power of Two Choices in Randomized Load Balancing , 2001, IEEE Trans. Parallel Distributed Syst..

[8]  Abdul Nasir Matori,et al.  Quality Assessment of DTM Generated from RTK GPS Data on Area with Various Sky Views , 2008 .

[9]  Scott Shenker,et al.  The Optimal Control of Heterogeneous Queueing Systems: A Paradigm for Load-Sharing and Routing , 1989, IEEE Trans. Computers.

[10]  W. Hong,et al.  New Indicator of Signal Blocking Degree to Describe GNSS Signal Receiving Environment in Land Road , 2013 .

[11]  Anne Harris Charge of the electric car - [power electric vehicles] , 2009 .

[12]  Ioannis Stavrakakis,et al.  Value of information exposed: Wireless networking solutions to the parking search problem , 2011, 2011 Eighth International Conference on Wireless On-Demand Network Systems and Services.

[13]  Lee Chapman,et al.  Sky‐view factor approximation using GPS receivers , 2002 .

[14]  J. E. Hay,et al.  The Determination of Sky View-Factors in Urban Environments Using Video Imagery , 1986 .

[15]  Lee Chapman,et al.  Real-Time Sky-View Factor Calculation and Approximation , 2004 .

[16]  T. GÁL,et al.  COMPARISON BETWEEN SKY VIEW FACTOR VALUES COMPUTED BY TWO DIFFERENT METHODS IN AN URBAN ENVIRONMENT , 2007 .

[17]  M. Englehart Computer aided control system design (cacsd) , 1999, Gateway to the New Millennium. 18th Digital Avionics Systems Conference. Proceedings (Cat. No.99CH37033).

[18]  T. M. Sweda,et al.  Simultaneous vehicle routing and charging station siting for commercial Electric Vehicles , 2012, 2012 IEEE International Electric Vehicle Conference.

[19]  A. Keane,et al.  Optimal Charging of Electric Vehicles in Low-Voltage Distribution Systems , 2012, IEEE Transactions on Power Systems.

[20]  A. Schlote,et al.  Stochastically Balanced Parking and Charging for Fully Electric and Plug-in Hybrid Vehicles , 2012, 2012 International Conference on Connected Vehicles and Expo (ICCVE).

[21]  Donald F. Towsley,et al.  Adaptive load sharing in heterogeneous systems , 1989, [1989] Proceedings. The 9th International Conference on Distributed Computing Systems.

[22]  Enrique Herrera-Viedma,et al.  A Bibliometric Analysis of the Intelligent Transportation Systems Research Based on Science Mapping , 2014, IEEE Transactions on Intelligent Transportation Systems.

[23]  C. S. B. Grimmond,et al.  Rapid methods to estimate sky‐view factors applied to urban areas , 2001 .

[24]  Björn Schünemann,et al.  V2X simulation runtime infrastructure VSimRTI: An assessment tool to design smart traffic management systems , 2011, Comput. Networks.

[25]  Panta Lucic,et al.  Intelligent parking systems , 2006, Eur. J. Oper. Res..

[26]  Amos Fiat,et al.  Making commitments in the face of uncertainty: how to pick a winner almost every time (extended abstract) , 1996, STOC '96.

[27]  Jonn Axsen,et al.  Batteries for Plug-in Hybrid Electric Vehicles (PHEVs): Goals and the State of Technology circa 2008 , 2008 .

[28]  Christos G. Cassandras,et al.  Dynamic resource allocation in urban settings: A “smart parking” approach , 2011, 2011 IEEE International Symposium on Computer-Aided Control System Design (CACSD).

[29]  K. Blennow Sky View Factors from High-Resolution Scanned Fish-eye Lens Photographic Negatives , 1995 .

[30]  R. Shorten,et al.  Growth conditions for the global stability of highspeed communication networks , 2008 .

[31]  Robert Shorten,et al.  Stochastic algorithms for parking space assignment , 2013 .

[32]  Environmental Assessment of Plug-In Hybrid Electric Vehicles Volume 1 : Nationwide Greenhouse Gas Emissions , 2007 .

[33]  G. A. Putrus,et al.  Impact of electric vehicles on power distribution networks , 2009, 2009 IEEE Vehicle Power and Propulsion Conference.

[34]  D. Vere-Jones Markov Chains , 1972, Nature.

[35]  Yue Yuan,et al.  Modeling of Load Demand Due to EV Battery Charging in Distribution Systems , 2011, IEEE Transactions on Power Systems.

[36]  Emilio Frazzoli,et al.  Adaptive and Distributed Algorithms for Vehicle Routing in a Stochastic and Dynamic Environment , 2009, IEEE Transactions on Automatic Control.

[37]  K. Schneider,et al.  Impact assessment of plug-in hybrid vehicles on pacific northwest distribution systems , 2008, 2008 IEEE Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century.