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Non-Cooperative and Cooperative Optimization of Scheduling with Vehicle-To-Grid Regulation Services

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Non-Cooperative and Cooperative Optimization of Scheduling with Vehicle-To-Grid Regulation Services 114 IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 69, NO. 1, JANUARY 2020 Non-Cooperative and Cooperative Optimization of Scheduling With Vehicle-to-Grid Regulation Services Xiangyu Chen, Student Member, IEEE, and Ka-Cheong Leung , Member, IEEE Abstract—Due to the increasing popularity of electric vehi- services are provided by controllable generators, which are cles (EVs) and technological advancements of EV electronics, the expensive to be operated. Therefore, in recent years, the research vehicle-to-grid (V2G) technique, which utilizes EVs to provide an- community is exploring cost-effective and efficient approaches cillary services for the power grid, stimulates new ideas in current smart grid research. Since EVs are selfish individuals owned by to providing frequency regulation in place of the controllable different parties, how to motivate them to provide ancillary services generators. becomes an issue. In this paper, game theoretic approaches using Due to the development of intelligent electric vehicle (EV) non-cooperative and cooperative game are proposed to motivate technology, the vehicle-to-grid (V2G) technique, which utilizes EVs to provide frequency regulation services for the power grid. EVs to provide frequency regulation services,1 have become a In a non-cooperative V2G system, the interaction between the EV aggregator and EVs is formulated as a non-cooperative Stackelberg hot research topic in current years. Some recent studies show game. The EV aggregator as the leader decides the electricity that the bidirectional EV chargers [1], [2] and power electronics trading price, and EVs as the followers determine their charg- inside EVs [3] can compensate well for frequency regulation- ing/discharging strategies. In a cooperative V2G system, a potential down and regulation-up signals through battery charging and game is formulated to achieve the optimal social welfare of the discharging. Hence, an aggregation of EVs, which constitutes a V2G system. The existence and uniqueness of the Nash equilibrium of these two games are validated. Our simulation results show distributed energy storage system as vehicle-to-grid (V2G) sys- that the proposed game theoretic approaches can motivate EVs to tem, can bring substantial capabilities for providing frequency smooth out the power fluctuations from the grid while EVs schedule regulation services. their charging/discharging activities to maximize their utilities. When utilizing V2G system for providing frequency regu- This demonstrates the effectiveness of the use of the V2G game lation services, control techniques are required to coordinate in providing regulation services to the grid. Through cooperation and extra information exchange, the social welfare of EVs and the the charging/discharging powers of EVs. Existing control tech- EV aggregator can be improved to the global optimum and the V2G niques for V2G regulation services include: the grid measure- regulation services can also achieve near-optimal performance. ment approach [4], [5] and the optimization-based approach [6], Index Terms—Electric vehicles (EVs), frequency regulation, [7]. These approaches are from the perspective of grid optimiza- game theory, vehicle-to-grid (V2G). tion and assume that EVs follow the schedules dispatched by the grid operator or aggregators. Nevertheless in the real-world I. INTRODUCTION operations, EVs are selfish individuals which are owned by ALANCING power supply and demand in real time is different EV owners. These owners may be more concerned B critical for stable and reliable operation in power grids. about the utilities of their EVs and the degradation issue of the Due to the increasing penetration of renewables, the power gen- EV batteries, instead of grid operations. Therefore, EVs may fail eration becomes difficult to forecast and follow. This brings great to follow the instructions of the grid because of their conflict of challenges to real-time power balance in power grids. Frequency interests. It is thus a pressing issue on how to motivate EVs to regulation, which aims to stabilize the utility frequency within participate into the V2G system. its nominal range through active power compensation, can keep To solve the aforementioned issue, game theory provides an real-time power balance in power grids. Frequency regulation effective framework to analyze the relationship between the services include regulation-up, which requires ramping up of individual utility and the system goal. Instead of following generation assets, and regulation-down, which requires ramp- the instructions from a centralized controller, in game theory, ing down of generation assets. Traditionally, these regulation each decision-maker makes its own strategy that maximizes its utility. Applying game theoretic approaches to V2G regu- Manuscript received January 16, 2019; revised June 28, 2019, August 27, lation ensures the fulfillment of EV’s utility since each EV can 2019, and October 10, 2019; accepted October 10, 2019. Date of publication choose its optimal charging/discharging strategy to maximize November 11, 2019; date of current version January 15, 2020. This work was supported by the Research Grants Council of the Hong Kong Special its utility. Therefore, game theoretic approaches can motivate Administrative Region, China, under Grant 17261416. The review of this article the participation of EVs in V2G regulation. Existing work has was coordinated by Prof. S. Manshadi. (Corresponding author: Ka-Cheong studied using game theoretic approaches to solve EV schedul- Leung.) X. Chen is with the Department of Electrical and Electronic Engineering, The ing problem [8]–[15], which can be further categorized into University of Hong Kong, Hong Kong (e-mail: [email protected]). K.-C. Leung is with the School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen 518055, China (e-mail: [email protected]). 1The regulation services provided by EVs are secondary frequency regulation Digital Object Identifier 10.1109/TVT.2019.2952712 services, which balance the grid power within 5–15 minutes. 0018-9545 © 2019 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information. CHEN AND LEUNG: NON-COOPERATIVE AND COOPERATIVE OPTIMIZATION OF SCHEDULING WITH V2G 115 non-cooperative game approaches [8], [10], [12]–[14] and co- An electricity pricing model is also devised to motivate EVs to operative game approaches [9], [11], [15]. provide regulation services implicitly. The performance of these However, there remain some research gaps in the current two game theoretic approaches are compared. Our simulation game theoretic approaches. First, the authors in [10]–[13], [15] results show that the proposed non-cooperative game theoretic only considered the games among EVs and the authors in [8] approach, together with the devised electricity pricing model, only considered the bidding game among EV aggregators in can autonomously motivate EVs to smooth out the power fluc- an electricity market. An hierarchical game among the grid tuations from the grid when EVs maximize their own utilities. operator, aggregators, and EVs in an electricity market, was By using the cooperative game approach, the social welfare not studied. Second, in [8]–[13], EV charging behaviours were of EVs and the EV aggregator can be further improved to the coordinated while EV discharging was not considered. This global optimum and the V2G regulation services can also obtain means that EVs cannot provide V2G regulation services nor sell near-optimal performance, though with small communication electricity back to the power grid. Third, though in [14], [15], the overhead. coordination of EV charging and discharging was investigated The contributions of this work are summarized as follows: using the non-cooperative game approach [14] and cooperative 1) Different from [10]–[13], [15] that have only considered game approach [15], the strategy set of an individual EV was games in the EV level, this work studies a hierarchical assumed to have three states only, namely, charging, idle, and game which consists of a V2G game among EVs and a discharging. This assumption oversimplifies the strategy set of pricing game of the EV aggregator. This helps to under- EVs and thus fails to consider the case that the strategy set of stand how EVs and the aggregator interact in different EVs has infinitely many elements. Besides, [14] only consid- levels of the V2G market. ers non-cooperative game and [15] only considers cooperative 2) Different from the existing work [14], [15], our proposed game. They do not compare the performance on V2G regulation games are infinite games in which the number of alterna- achieved by the non-cooperative game and cooperative game tives available to each EV is a continuum. This continuous approaches, implying that the merits and drawbacks of these game model is more general and practical than [14], two approaches cannot be validated. Moreover, the approaches [15] since EVs can choose any charging and discharging in [14], [15] suppose that EVs get payment from the grid if they powers within their feasible regions. respond to the regulation requests. These approaches sacrifice 3) Instead of explicitly giving payments to EVs for V2G some benefits of the power grid companies so as to explicitly regulation services [14], [15], we devise an electricity motivate EVs to provide regulation services. This inspires
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