Resource Management For Power Charging And Discharging In Vehicle-to-grid Systems

Being an environmentally friendly mode of transportation, electric vehicles (EVs)have attracted considerable attention from academic and industry researchers. The efficiency of the charging service is a key factor in the popularization of EVs. With the aid of advanced information, communication and control technology, vehicle-to-grid(V2G) system can realize the bidirectional electricity flow between EVs and the grid.With intelligent planning and scheduling that reasonably incorporates both the charging requirements of the EVs and the dynamic load status of the power grid, EVs can play an important role in maintaining the dynamic balance between supply and demand in smart grid. Such features offer benefits to all stakeholders involved. For instance, utilities have the opportunities to earn higher revenues and the consumers with EVs can save in their electricity bills. This, in turn, enables reliable power generation and flow, contributing towards the stability and long-term operation of the power grid infrastructure. Therefore, V2G system plays a vital role for maintaining power supply and demand balance of the grid, as well as enhances the charging efficiency of electric vehicles.In a V2G system, the energy exchange between EVs and the grid always follows the control information. The vehicular charging/discharging efficiency is very closely coupled with resource management for information transmission and processing. In this thesis, based on the analysis of the relationship and interactions between the resource scheduling of communication, computing and energy resource, we propose a V2G information platform, which can effectively support communication for efficient and reliable charging and discharging of the EVs. As a typical application of the proposed V2G communication system, an EV platoon can get electricity supply from a charging station facilitated by the underlying communications and control commands.The batch arrival characteristic of the EV platoon at the charging station brings a new challenge to the design of the control mechanism for the charging station. How to improve the charging efficiency under the guarantee of EV platoons' charging service quality is also a new challenge. Furthermore, we consider a scenario where there is no power supply from the grid. In this scenario, we leverage the proposed V2G communication system for direct energy exchange between the vehicles. To sum up,my research objectives in this thesis are the joint optimization of the communication resources and power, focusing specifically on charging and discharging of EVs,enabled by the V2G communication sytem. We study the cross domain key problems such as information transmission technology and information processing mechanism,contorl mechanism for charging/discharging of EV platoons, and the direct power exchange mechanism among the EVs.In this thesis, we firstly propose a V2G communication architecture to facilitate EV charging and discharging. To improve spectrum efficiency and to enhance interference management, we incorporate cognitive radio technology into the communication system. Then, we focus on the scenario where the charging reservation from the mobile EVs is transmitted through the proposed V2G communication system.Based on the analysis of the relationship between the mobile characteristics of the vehicles, correct transmission rate of the reservation information, and the vehicle charging benefits, we propose a multi-vehicle collaborative spectrum detection algorithm which maximizes the benefits of the EVs. As poor communication conditions may seriously affect the bit error rate for V2G communication and consequently the operation of the grid, we establish a model to describe the relationship between unreliable communications and the gain of demand response management of the grid. We further propose a multi-domain electricity cooperative scheduling mechanism, which make the grid operate effectively with the unreliable communications.We extend the proposed V2G communication architecture to a V2G computing and transmission platform by adding computing servers on its key nodes, which strengthen the computing and information processing capability of the system. In order to address the challenge, which is posed by the real-time transmission requirements of large-scale electricity grid information on the limited communication resources, we take EVs as the information carrying and transport entity. We also utilize the information processing capacity of the V2G computing and transmission platform to realize data aggregation and compression. Moreover, we combine heterogeneous communication modes with the data processing technology, and design an optimization algorithm for V2G information processing and delivering, which minimizes information delivering cost for the charging station. In addition, we utilize the computing resource of the V2G computing and transmission platform as edge cloud to offload the application tasks of the vehicles. We propose an optimal vehicular task offloading strategy, which maximizes the utility of the edge computing provider.Next, with the information support from the V2G computing and transmission platform, we investigate the charging mechanism of EV platoons. We propose a queuing network based model to characterize the charging process of the EV platoons in a charging station. Based on the distinction of the different types of platoons, we adopt contract theory to design a charging rate allocation scheme for the platoons with incentives. In addition, we introduce charging service quality and dynamic changing characteristic of renewable energy into the design of the charging control scheme. We propose a new contract-based charging rate assignment and admission control schemes for the platoons, which maximize the utility of the charging station under certain charging service quality constraints.Finally, we consider a scenario with no grid involvement in the charging of EVs,and propose a vehicle-to-vehicle energy cloud architecture, which consists of electrical energy exchange station, renewable energy generator, and discharging vehicles. Based on the energy cloud, charging vehicles can get energy directly from the discharging ones. Considering discharging vehicles may have various discharging capacities and characteristics, these vehicles are categorized into multiple types based on the defined range anxiety level concept. Noting that the energy demand and supply state may vary in the vehicle-to-vehicle energy exchange process, we obtain the optimal amount of purchasing energy of the energy exchange station. We also analyze the contribution differences made by various types of discharging vehicles to the profits of the energy exchange station, and propose a contract-based optimal discharging control mechanism,which can distinguish the priority of the different discharging vehicle types in the energy exchange process.