DocumentCode
2834101
Title
Optimal management and integration of electric vehicles to the grid: Dynamic programming and game theory approach
Author
Ovalle, Andres ; Hably, Ahmad ; Bacha, Seddik
Author_Institution
Grenoble Electr. Eng. Lab., Univ. de Grenoble Alpes, Grenoble, France
fYear
2015
fDate
17-19 March 2015
Firstpage
2673
Lastpage
2679
Abstract
This paper provides a Dynamic Programming (DP) approach to optimally manage the charging schedule of electrical vehicles (EV) based on a decentralized global optimization frame given by the use of a Game Theory approach. The paper provides a detailed explanation of a forward induction DP algorithm and shows its adaptation to the problem of optimal charging of one EV with the corresponding constraints of limiting power consumption, minimal and maximal states of charge, desired states of charge, etc. The extension to multiple EVs is provided by the adaptation of a N-person non-cooperative game approach. In this game, the payoff of each player is based on a utility function that aims to reduce the distance between the total load and the average load, achieving load curve flattening.
Keywords
dynamic programming; game theory; hybrid electric vehicles; power grids; N-person noncooperative game approach; average load; decentralized global optimization frame; desired states-of-charge; dynamic programming approach; electric vehicle integration; forward induction DP algorithm; limiting power consumption constraints; load curve flattening; maximal states-of-charge; minimal states-of-charge; optimal charging schedule management; optimal electric vehicle management; plug-in hybrid electric vehicles; total load; Batteries; Dynamic programming; Game theory; Games; Heuristic algorithms; Optimization; Schedules; Dynamic Programming; Game theory; Interfacing and Control of Energy Storage Technology; N-person non-cooperative game; Optimization; Peak shaving; Plug-In Hybrid Electric Vehicles; Smart charging; Valley filling; Vehicle-to-Grid;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Technology (ICIT), 2015 IEEE International Conference on
Conference_Location
Seville
Type
conf
DOI
10.1109/ICIT.2015.7125492
Filename
7125492
Link To Document