Intelligent battery energy management and control for vehicle-to-grid via cloud computing network

Applied Energy

Volumn 111, Issue , 2013, Pages 971-981

  Khayyam, Hamid ^a   Abawajy, Jemal ^a   Javadi, Bahman ^b   Goscinski, Andrzej ^a   Stojcevski, Alex ^a   Bab Hadiashar, Alireza ^c  

^a DEAKIN UNIVERSITY   (Australia)

^b UNIVERSITY OF WESTERN SYDNEY   (Australia)

^c RMIT UNIVERSITY   (Australia)

Author keywords

Battery energy management and control; Cloud computing; Fuzzy logic prediction; Intelligent battery energy management; Intelligent scheduling; Vehicle to grid

Indexed keywords

CLOUD COMPUTING; COMPUTER NETWORKS; ENERGY MANAGEMENT; ENERGY MANAGEMENT SYSTEMS; FUZZY LOGIC; SCHEDULING;

BATTERY ENERGY; COMPUTATIONAL SCALABILITY; EXPERIMENTAL ANALYSIS; INTELLIGENT SCHEDULING; MANAGEMENT AND CONTROLS; PLUG-IN ELECTRIC VEHICLES; SCHEDULING SERVICE; VEHICLE TO GRIDS;

CHARGING (BATTERIES);

CONTROL SYSTEM; ELECTRIC VEHICLE; ENERGY PLANNING; FUEL CONSUMPTION; FUZZY MATHEMATICS; NETWORK ANALYSIS;

EID: 84880756591     PISSN: 03062619     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apenergy.2013.06.021     Document Type: Article

References (37)

1. Khayyam H., Ranjbarzadeh H., Marano V. Intelligent control of vehicle to grid power. J Power Sources 2012, 201:1-9.
2. Schroeder A. Modeling storage and demand management in power distribution grids. Appl Energy 2011, 88:4700-4712.
3. Kyriakarakos G., Piromalis D.D., Dounis A.I., Arvanitis K.G., Papadakis G. Intelligent demand side energy management system for autonomous polygeneration microgrids. Appl Energy 2013, 103:39-51.
4. McKenna E., McManus M., Cooper S., Thomson M. Economic and environmental impact of lead-acid batteries in grid-connected domestic PV systems. Appl Energy 2013, 104:239-249.
5. Marano V., Rizzoni G., Tulpule P., Gong Q., Khayyam H. Intelligent energy management for plug-in hybrid electric vehicles: the role of ITS infrastructure in vehicle electrification. Oil Gas Sci Technol 2012, 67:575-587.
6. Bergveld H.J., Kruijt W.S., Notten P.H.L. Battery management systems design by modelling 2002, Kluwer, Norwell (MA).
7. Sousa T., Morais H., Soares J., Vale Z. Day-ahead resource scheduling in smart grids considering vehicle-to-grid and network constraints. Appl Energy 2012, 96:183-193.
8. Su W., Chow M.-Y. Computational intelligence-based energy management for a large-scale PHEV/PEV enabled municipal parking deck. Appl Energy 2012, 96:171-182.
9. Foley A., Tyther B., Calnan P., Gallachóir B.O. Impacts of electric vehicle charging under electricity market operations. Appl Energy 2013, 101:93-102.
10. Markel T. Plug-in electric vehicle infrastructure: a foundation for electrified. Transportation 2010.
11. Hutson C, Venayagamoorthy GK, Corzine KA. Intelligent scheduling of hybrid and electric vehicle storage capacity in a parking lot for profit maximization in grid power transactions. In: Presented at the Atlanta, GA USA 17-18 November; 2008.
12. Saber A.Y., Venayagamoorthy G.K. Intelligent unit commitment with vehicle-to-grid-a cost-emission optimization. J Power Sources 2010, 195:898-911.
13. Del Valle Y., Venayagamoorthy G.K., Mohagheghi S., Hernandez J.-C., Harley R.G. Particle swarm optimization: basic concepts, variants and applications in power systems. IEEE Trans Evaloutionaary Comput 2008, 12:171-195.
14. Clement-Nyns K., Haesen E., Driesen J. The impact of vehicle-to-grid on the distribution grid. Electric Power Syst Res 2011, 81:185-192.
15. Guille C., Gross G. A conceptualframeworkforthe vehicle-to-grid (V2G) implementation. Energy Policy 2009, 37:4379-4390.
16. Venayagamoorthy GK, Mitra P, Corzine K, Huston C. Real-time modeling of distributed plug-in vehicles for v2g transactions. In: Energy conversion congress and expo, ECCE; September 2009.
17. Quinn C., Zimmerle D., Bradley T.H. The effect of communication architecture on the availability, reliability, and economics of plug-in hybrid electric vehicle-to-grid ancillary services. J Power Sources 2010, 195:1500-1509.
18. Vaquero L., Rodero-Marino L., Caceres J., Lindner M. A break in the clouds: towards a cloud definition. SIGCOMM Comput Commun Rev 2009, 39:137-150.
19. Kondo D, Javadi B, Malecot P, Cappello F, Anderson DA. Cost-benefit analysis of cloud computing versus desktop grids. In: IEEE 18th international heterogeneity in computing workshop ed. Rome, Italy; 2009.
20. Johnson V.H. Battery performance models in ADVISOR. J Power Sources 2002, 110:321-329.
21. Vasallo M.J., Bravo J.M., Andújar J.M. Optimal sizing for UPS systems based on batteries and/or fuel cell. Appl Energy 2013, 105:170-181.
22. Ehsani M., Gao Y., Gay S., Emadi A. Modern electric, hybrid electric, and fuel cell vehicles: fundamentals, theory, and design 2005, CRC Press, New York.
23. Khayyam H., Kouzani A.Z., Hu E.J., Nahavandi S. Coordinated energy management of vehicle air conditioning system. Appl Therm Eng 2011, 31:750-764.
24. Khayyam H, Kouzani AZ, Hu EJ. An intelligent energy management model for a parallel hybrid vehicle under combined loads. In: IEEE international conference on vehicular electronics and safety Columbus, OH, USA; 2008, p. 145-50.
25. Khayyam H., Nahavandi S., Davis S. Adaptive cruise control look-ahead system for energy management of vehicles. Expert Syst Appl 2012, 39:3874-3885.
26. Khayyam H., Nahavandi S., Eric H., Kouzani A., Chonka A., Abawajy J., et al. Intelligent energy management control of vehicle air conditioning via look-ahead system. Appl Therm Eng 2011, 31:3147-3160.
27. Khayyam H., Abawajy J., Jazar R.N. Intelligent energy management control of vehicle air conditioning system coupled with engine. Appl Therm Eng 2012, 48:211-224.
28. Buyya R., Broberg J., Goscinski A. Cloud computing principles and paradigms 2010, A John Wiley & Sons, Inc., Publication, New Jersey, USA.
29. http://www.toyota.com/entune/what-is-entune/.
30. Shaw M.J., Park S., Raman N. Intelligent scheduling with machine learning capabilities: the induction of scheduling knowledge. IIE Trans 1992, 24:156-168.
31. Khayyam H. Adaptive intelligent control of vehicle air conditioning system. Appl Therm Eng 2013, 51:1-8.
32. Jang J.-S.R. ANFIS: adaptive-network-based fuzzy inference system. IEEE Trans Syst, Man Cybernetics 1993, 23:665-685.
33. ITU Internet Report, digital.life. <>; 2006 [Chapter 3]. http://www.itu.int/osg/spu/publications/digitalife/.
34. Amazon Web Services. <> [Online]. http://www.aws.amazon.com/ec2/#pricing.
35. Wittie MP, Stone-Gross B, Almeroth KC, Belding EM. MIST: Cellular data network measurement for mobile applications. In: Presented at the fourth international conference on in broadband communications, networks and systems; 2007.
36. Khayyam H. Stochastic models of road geometry and wind condition for vehicle energy management and control. IEEE Trans Veh Technol 2013, 62:61-68.
37. CAISO, California Independent System Operator, Daily Market Watch, http://www.caiso.com.