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Title An analytical framework for modelling Quality of Service in EV charing with multi-class customers
Degree MS
Author Kihong Ahn
Advisor Kiseon Kim
Graduation Date 2017.08.18 File Link icon
    Date 2017-08-23 13:48
Distribution of limited grid resources among electric vehicles (EVs) with diverse service demands in an unfavorable and unpredictable manner degrades the stability of the grid and overall profit achievable by the operating charging s tation (CS) operators. In fact, inefficient resource management is manifested by customer dissatisfaction arising due to prolonged queuing and blockage of EVs a rriving at the CS for service. In order to expand EVs adoption and support large -scale penetration, designing and modeling of CS infrastructures is significant to facilitate different classes of customer service demands. As more number of c harging stations are being interconnected, controlling demand side requests shou ld be managed efficiently to increase the revenue of the operator and stabilize the grid. 

In this thesis, we propose a mathematical framework for maximizing revenue of the respective CS operator considering the QoS preference in terms of blocking probabilities of the service classes under a dynamic pricing principle . To account for the uncertain stochastic service requests imposed on the grid b y customers and their tendency to retry for service, the model is further extend ed to incorporate additional secondary energy storage option and retrial queuein g of blocked EVs by using the notion of quasi-birth and death (QBD) process. Sim ulation results for the single CS and networked models reveal considerably highe r satisfaction levels for fast charging EV customers and improved attainable sys tem revenue as compared to the baseline scenario.
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광주과학기술원 한·러 MT-IT 융합기술연구센터 광주과학기술원정보통신공학부