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SUMMARY:Control Aspects of the Charging of a Large Population of EVs
DTSTART:20170222T110000
DTEND:20170222T130000
DTSTAMP:20260916T210753Z
UID:74c423a673c4912b994a0d3b0d3c030e62c1e30278a12ea4ce09efd0
CATEGORIES:Conferences - Seminars
DESCRIPTION:Roman Rudnik\nEDIC Candidacy Exam\nExam president: Prof. Mario
  Paolone\nThesis advisor: Prof. Jean-Yves Le Boudec\nCo-examiner: Prof. Ma
 tthias Grossglauser\n\nAbstract\nElectric vehicles (EVs) are already part 
 of today'€™s reality and their number is expected to grow rapidly in the
  near future. Such growth will directly impact the grid\, for instance hig
 her uncoordinated peak load is possible to occur unexpectedly. In literatu
 re\, this problem is addressed by controlling the charging of EVs using so
 ftware agents. The controllability of EV charging power makes it an intere
 sting candidate for demand side management applications. Additionally\, it
  is expected that in the future\, EVs will also be able to provide energy 
 to the grid by discharging their batteries\, in other words to provide veh
 icle-to- grid services. Thus\, the control of EV charging power is of grea
 t importance to optimally manage the EV charging/discharging patterns and 
 provide grid ancillary services. However\, existing solutions require prec
 ise knowledge about the types of all EVs\, their arrival and departure tim
 es\, and hence are limited by the prediction of this information. Furtherm
 ore\, presence of volatile power sources in the distirbution electrical gr
 ids requires the control to be performed in real-time. Hence\, adoption of
  a powerful online optimization framework to perform fast and efficient op
 erations is crucial to control a large population of EVs charging in distr
 ibution grids. In this respect\, we investigate the use of online convex o
 ptimization techniques. Lastly\, in order to efficiently control a large n
 umber of EVs\, we focus on decentralized multi-agent frameworks\, which en
 sure scalability and low computational complexity. We propose to design a 
 controller for EV charging stations that will be responsible for the coord
 inated charging of EVs under grid constraints and for advertising the real
 -time power capabilities and operational preferences of its EVs based on l
 ocal information.\n\nBackground papers\nA Scalable Three-Step Approach for
  Demand Side Management of Plug-in Hybrid Vehicles\, by Vandael S.\, et al
 .\nOptimal Scheduling With Vehicle-to-Grid Regulation Service\, by Lin J.\
 , et al.\nOnline Convex Programming and Generalized Infinitesimal Gradient
  Ascen\, by Zinkevich M.\n 
LOCATION:BC 329 https://plan.epfl.ch/?room==BC%20329
STATUS:CONFIRMED
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