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- Genre: Doctoral Dissertation
- Creators: Arizona State University
- Creators: Gel, Esma
Description
The burgeoning adoption of electric vehicles (EVs) necessitates a comprehensive exploration of the charging infrastructure, delving into both the optimization of EV charger converters and the pivotal role of EV chargers in the power grid. This dissertation comprises six technical chapters, with a focused exploration of converters in Chapters 2 to 4 and an in-depth analysis of the role of EVs in power grids in Chapters 5 to 7.Chapters 2 to 4 showcase advancements in EV charger converters. Chapter 2 introduces a novel active harmonic reduction technique, mitigating the dominant third-order harmonic in the power factor corrector circuit’s input current. This innovation not only enhances grid power quality but also marks a critical step toward efficient and sustainable EV charging. In Chapter 3, a new gate signal modulation method in the dc-dc dual active converter minimizes conduction and switching losses, optimizing the charging process. Chapter 4 extends the converter optimization paradigm with a DC link voltage optimization method, enhancing the efficiency of the entire EV charger across ac-dc and dc-dc stages over the battery charging cycle.
Chapters 5 to 7 transition seamlessly to the role of EV charging systems in the power grid. Chapter 5 explores the optimal utilization of bidirectional EVs for grid frequency support during critical events such as loss of generation and frequency drops. This chapter highlights the potential for EVs not merely as energy consumers but as dynamic contributors to grid stability. Chapter 6 presents a dynamic EV charging pricing strategy to distribute the EVs between charging stations (CSs) uniformly and thereby increase the revenue of the charging station operator (CSO) and enhance the charging satisfaction of EV users. Finally, in Chapter 7, a two-stage stochastic programming approach is developed for electric energy procurement in EV charging stations equipped with battery energy storage and photovoltaic generation. This innovative approach provides a roadmap for sustainable energy procurement, emphasizing the synergy between EV charging stations and renewable energy sources.
In conclusion, this dissertation provides a holistic and pioneering exploration of EV charging systems, from converter optimization to grid integration. The research contributes significantly to the advancement of EV charging technology, offering solutions to enhance efficiency, power quality, and grid stability. The findings not only address current challenges in electric mobility but also lay a foundation for a sustainable and resilient energy future.
ContributorsKazemtarghi, Abed (Author) / Mallik, Ayan (Thesis advisor) / Johnson, Nathan (Committee member) / Hedman, Mojdeh (Committee member) / Arizona State University (Publisher)
Created2024
Description
Vehicles powered by electricity and alternative-fuels are becoming a more popular form of transportation since they have less of an environmental impact than standard gasoline vehicles. Unfortunately, their success is currently inhibited by the sparseness of locations where the vehicles can refuel as well as the fact that many of the vehicles have a range that is less than those powered by gasoline. These factors together create a "range anxiety" in drivers, which causes the drivers to worry about the utility of alternative-fuel and electric vehicles and makes them less likely to purchase these vehicles. For the new vehicle technologies to thrive it is critical that range anxiety is minimized and performance is increased as much as possible through proper routing and scheduling. In the case of long distance trips taken by individual vehicles, the routes must be chosen such that the vehicles take the shortest routes while not running out of fuel on the trip. When many vehicles are to be routed during the day, if the refueling stations have limited capacity then care must be taken to avoid having too many vehicles arrive at the stations at any time. If the vehicles that will need to be routed in the future are unknown then this problem is stochastic. For fleets of vehicles serving scheduled operations, switching to alternative-fuels requires ensuring the schedules do not cause the vehicles to run out of fuel. This is especially problematic since the locations where the vehicles may refuel are limited due to the technology being new. This dissertation covers three related optimization problems: routing a single electric or alternative-fuel vehicle on a long distance trip, routing many electric vehicles in a network where the stations have limited capacity and the arrivals into the system are stochastic, and scheduling fleets of electric or alternative-fuel vehicles with limited locations to refuel. Different algorithms are proposed to solve each of the three problems, of which some are exact and some are heuristic. The algorithms are tested on both random data and data relating to the State of Arizona.
ContributorsAdler, Jonathan D (Author) / Mirchandani, Pitu B. (Thesis advisor) / Askin, Ronald (Committee member) / Gel, Esma (Committee member) / Xue, Guoliang (Committee member) / Zhang, Muhong (Committee member) / Arizona State University (Publisher)
Created2014
Description
Due to environmental and geopolitical reasons, many countries are embracing electric vehicles (EVs) as an alternative to gasoline powered automobiles. Other alternative-fuel vehicles (AFVs) powered by compressed gas, hydrogen or biodiesel have also been tested for replacing gasoline powered vehicles. However, since the associated refueling infrastructure of AFVs is sparse and is gradually being built, the distance between recharging points (RPs) becomes a crucial prohibitive attribute in attracting drivers to use such vehicles. Optimally locating RPs will both increase demand and help in developing the refueling infrastructure.
The major emphasis in this dissertation is the development of theories and associated algorithms for a new set of location problems defined on continuous network space related to siting multiple RPs for range limited vehicles.
This dissertation covers three optimization problems: locating multiple RPs on a line network, locating multiple RPs on a comb tree network, and locating multiple RPs on a general tree network. For each of the three problems, finding the minimum number of RPs needed to refuel all Origin-Destination (O-D) flows is considered as the first objective. For this minimum number, the location objective is to locate this number of RPs to minimize weighted sum of the travelling distance for all O-D flows. Different exact algorithms are proposed to solve each of the three algorithms.
In the first part of this dissertation, the simplest case of locating RPs on a line network is addressed. Scenarios include single one-way O-D pair, multiple one-way O-D pairs, round trips, etc. A mixed integer program with linear constraints and quartic objective function is formulated. A finite dominating set (FDS) is identified, and based on the existence of FDS, the problem is formulated as a shortest path problem. In the second part, the problem is extended to comb tree networks. Finally, the problem is extended to general tree networks. The extension to a probabilistic version of the location problem is also addressed.
The major emphasis in this dissertation is the development of theories and associated algorithms for a new set of location problems defined on continuous network space related to siting multiple RPs for range limited vehicles.
This dissertation covers three optimization problems: locating multiple RPs on a line network, locating multiple RPs on a comb tree network, and locating multiple RPs on a general tree network. For each of the three problems, finding the minimum number of RPs needed to refuel all Origin-Destination (O-D) flows is considered as the first objective. For this minimum number, the location objective is to locate this number of RPs to minimize weighted sum of the travelling distance for all O-D flows. Different exact algorithms are proposed to solve each of the three algorithms.
In the first part of this dissertation, the simplest case of locating RPs on a line network is addressed. Scenarios include single one-way O-D pair, multiple one-way O-D pairs, round trips, etc. A mixed integer program with linear constraints and quartic objective function is formulated. A finite dominating set (FDS) is identified, and based on the existence of FDS, the problem is formulated as a shortest path problem. In the second part, the problem is extended to comb tree networks. Finally, the problem is extended to general tree networks. The extension to a probabilistic version of the location problem is also addressed.
ContributorsSong, Yazhu (Author) / Mirchandani, Pitu B. (Thesis advisor) / Wu, Teresa (Committee member) / Sefair, Jorge A (Committee member) / Sen, Arunabha (Committee member) / Arizona State University (Publisher)
Created2020