Award Date

May 2023

Degree Type


Degree Name

Doctor of Philosophy (PhD)


Computer Science

First Committee Member

Wolfgang Bein

Second Committee Member

Laxmi Gewali

Third Committee Member

Fatma Nasoz

Fourth Committee Member

Kazem Taghva

Fifth Committee Member

Shahram Latifi

Number of Pages



The concept of the battery exchange station (BES) as a part of the battery consolidation system (BCS) has certain criteria that make it a significant player in the better adaptation plan of electric vehicles (EVs) in the grid toward the smart grid. In this dissertation, we study the BES optimization problem as a promising approach for EV adaptation in a smart grid. We introduce the concept of BCS, which focuses on optimizing the incorporation and transaction of all of the components in a smart grid. Accordingly, we address three BES optimization problems in the BCS. In the first problem, we focus on finding an efficient joint capacity and placement planning of BESs among candidate zones and the exchange decisions of EV drivers at a BCS (CPPED) with the aim of minimizing the implementation cost of BESs placement, the distance traveled by EVs to exchange their batteries, and the waiting time of EVs at the BESs subject to the limitation on the number of BESs in the system. We formulate the CPPED problem as an optimization problem. Since the stated problem is non-convex, we make it convex and then propose an efficient solution with polynomial-time complexity for addressing the convex problem. We evaluate the performance of the proposed method using numerical results. Through simulation results, we investigate the effect of the number of zones and number of BESs on the performance of the proposed method for addressing the CPPED problem. Our numerical results show that increasing the number of zones and the maximum number of BESs has significant effects on optimizing the CPPED problem; however, after a certain point, their effects become less significant. In the second problem, we study the BESs’ coverage area estimation problem in a BCS. We assume that the battery exchange capacity of BESs is different, which leads to changing the topology of the graph that BESs are sitting on. We formulate the problem of finding the optimum coverage area for each BES using the weighted Voronoi diagram (WVD), where each BES is represented by a point site with a weight representing its capacity. Since the stated problem cannot be solved by directly applying WVD due to not satisfying the WVD properties, we propose an approximation algorithm for estimating the coverage area of weighted BESs by extrapolating the areas when each BES has the same capacity. In the third problem, we study the power grid scheduling problem in a BES as a part of the BCS. We define the power grid scheduling problem as the BES’s service scheduling to exchange batteries of EVs, the battery exchange price scheduling, and the electricity buying scheduling for a day ahead. We mathematically formulate the problem as a multiobjective optimization problem that aims at maximizing the BES’s income and the EVs’ satisfaction, subject to the constraints of servicing all EVs that arrive in the BES during a day, the limitation on the amount of buying electricity, and the limitation on the available full batteries at the beginning of the day. The stated multi-objective optimization problem is non-convex. To have a polynomial-time complexity solution, we first make the problem convex and then propose an efficient solution to address it. We evaluate the performance of the proposed method using numerical results. Our simulation outcomes show that the BES can efficiently schedule the service, the battery exchange price, and the electricity purchases based on the electricity price and the EVs’ arrival distributions for the day ahead by applying our proposed method.


abstract lagrangian duality; battery consolidation system; battery exchange station; computational geometry; voronoi diagram; weighted voronoi diagram


Computer Sciences

Degree Grantor

University of Nevada, Las Vegas




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