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Game‐Based Valley‐Fill Charging Coordination for Large‐Population Plug‐in Electric Vehicles
Author(s) -
Ma Zhongjing,
Ran Long
Publication year - 2015
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.1054
Subject(s) - mathematical optimization , nash equilibrium , population , homogeneous , electricity , grid , coordination game , computer science , greedy algorithm , plug in , game theory , engineering , mathematics , mathematical economics , electrical engineering , demography , geometry , combinatorics , sociology , programming language
Charging coordination of large‐population autonomous plug‐in electric vehicles (PEVs) in the power grid can be formulated as a class of constrained optimization problems. To overcome the computational complexity, a game‐based method is proposed for the charging problems of the PEV population, which is composed of homogeneous subpopulations, such that individuals update their best charging strategies simultaneously with respect to a common electricity price determined by the total demand. To mitigate the oscillation behavior caused by the greedy behavior for the cheap electricity by individuals, a deviation cost is introduced to penalize against the deviation of the individual strategy from the average value of the homogeneous subpopulation. By adopting a proper deviation cost and following a best strategy update mechanism, the game systems may converge to the socially optimal valley‐fill Nash equilibrium. Simulation examples are studied to illustrate the results.