Open AccessAggregated optimal charging and vehicle‐to‐grid control for electric vehicles under large electric vehicle population
Author(s) -
Tang Yuchen,
Zhong Jin,
Bollen Math
Publication year - 2016
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2015.0133
Subject(s) - electric vehicle , vehicle to grid , control (management) , grid , process (computing) , computer science , population , optimal control , automotive engineering , engineering , mathematical optimization , mathematics , artificial intelligence , geometry , quantum mechanics , power (physics) , physics , demography , sociology , operating system
Effective charging and vehicle‐to‐grid (V2G) control strategies can utilise the properties of electric vehicles (EVs) to obtain various benefits. EVs are modelled as individuals in existing charging control algorithms. In this study, a new modelling method of EVs and an optimal charging control strategy are proposed so that all EVs in a control area can be regarded as a single object in the optimisation process. The strategy minimises the total charging cost of EVs, and can be further expanded to serve V2G control. With the new modelling method, the computational burden of the optimisation algorithm can be reduced significantly and does not increase with the number of EVs. Thus the strategy is extremely effective when the number of EVs becomes large, and the implementation cost could be more reasonable since less computational capacity is required. Case studies are presented to illustrate the performance of the strategy.