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Game Theory Based Location-Aware Cha...
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Laha, Aurobinda.
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Game Theory Based Location-Aware Charging Solutions for Networked Electric Vehicles.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Game Theory Based Location-Aware Charging Solutions for Networked Electric Vehicles./
作者:
Laha, Aurobinda.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2020,
面頁冊數:
84 p.
附註:
Source: Dissertations Abstracts International, Volume: 82-03, Section: B.
Contained By:
Dissertations Abstracts International82-03B.
標題:
Electrical engineering. -
電子資源:
https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28028517
ISBN:
9798664777161
Game Theory Based Location-Aware Charging Solutions for Networked Electric Vehicles.
Laha, Aurobinda.
Game Theory Based Location-Aware Charging Solutions for Networked Electric Vehicles.
- Ann Arbor : ProQuest Dissertations & Theses, 2020 - 84 p.
Source: Dissertations Abstracts International, Volume: 82-03, Section: B.
Thesis (Ph.D.)--Illinois Institute of Technology, 2020.
This item must not be sold to any third party vendors.
The recent explosive adoption of electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs) has sparked considerable interest of academia in developing efficient charging schemes. Supported by the advanced vehicle-to-grid (V2G) network, vehicles and charging stations can respectively make better charging and pricing decisions via real-time information sharing. In this research, we study the charging problem in an intelligent transportation system (ITS), which consists of smart-grid enabled charging stations and networked EVs. Each vehicle aims to select a station with the lowest charging cost by considering the charging prices and its location while the objective of a charging station is to maximize its revenue given the charging strategy of the vehicles. We employ a multileader multi-follower Stackelberg game to model the interplay between the vehicles and charging stations, in which the location factor plays an important role. We show that there exists a unique equilibrium for the followers' subgame played by the vehicles, while the stations are able to reach an equilibrium of their subgame with respect to the charging prices. Therefore, the Nash equilibrium of the Stackelberg game is achievable through the proposed charging scheme. We further evaluate the price of anarchy (PoA) of the proposed charging scheme by using a centralized optimization model, in which a modified matching algorithm is applied. In state-of-the-art research works, PHEVs tend to charge or discharge to a smart grid individually. In our extended work, we also consider the discharging scenarios for PHEVs, which is generally during the peak hours of a micro-grid system. We propose that by leveraging the cooperation between charging and discharging PHEVs, the grid will be able to properly disperse the charging load in the load valley and discharging during the load peak hours. As a consequence, the electricity load will be well balanced. In this process, the PHEVs also receive greater benefit, thus serving the PHEV charging and discharging cooperation as a win-win strategy for both the grid and the PHEV users. We formulate and resolve the PHEV charging and discharging cooperation in the framework of a coalition game. Finally, simulation results confirm the uniqueness of the equilibrium in both the game strategies. A performance comparison between the proposed distributed and centralized strategy with existing solutions are presented. We also provide the results of the coalition game when both charging and discharging PHEVs are present in the network. The proper management of charging and discharging of EVs poses one of the most challenging and interesting issues in our research. We aim to provide a complete demand response management solution to PHEVs and micro-grids in a real-time scenario.
ISBN: 9798664777161Subjects--Topical Terms:
649834
Electrical engineering.
Subjects--Index Terms:
Charging
Game Theory Based Location-Aware Charging Solutions for Networked Electric Vehicles.
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The recent explosive adoption of electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs) has sparked considerable interest of academia in developing efficient charging schemes. Supported by the advanced vehicle-to-grid (V2G) network, vehicles and charging stations can respectively make better charging and pricing decisions via real-time information sharing. In this research, we study the charging problem in an intelligent transportation system (ITS), which consists of smart-grid enabled charging stations and networked EVs. Each vehicle aims to select a station with the lowest charging cost by considering the charging prices and its location while the objective of a charging station is to maximize its revenue given the charging strategy of the vehicles. We employ a multileader multi-follower Stackelberg game to model the interplay between the vehicles and charging stations, in which the location factor plays an important role. We show that there exists a unique equilibrium for the followers' subgame played by the vehicles, while the stations are able to reach an equilibrium of their subgame with respect to the charging prices. Therefore, the Nash equilibrium of the Stackelberg game is achievable through the proposed charging scheme. We further evaluate the price of anarchy (PoA) of the proposed charging scheme by using a centralized optimization model, in which a modified matching algorithm is applied. In state-of-the-art research works, PHEVs tend to charge or discharge to a smart grid individually. In our extended work, we also consider the discharging scenarios for PHEVs, which is generally during the peak hours of a micro-grid system. We propose that by leveraging the cooperation between charging and discharging PHEVs, the grid will be able to properly disperse the charging load in the load valley and discharging during the load peak hours. As a consequence, the electricity load will be well balanced. In this process, the PHEVs also receive greater benefit, thus serving the PHEV charging and discharging cooperation as a win-win strategy for both the grid and the PHEV users. We formulate and resolve the PHEV charging and discharging cooperation in the framework of a coalition game. Finally, simulation results confirm the uniqueness of the equilibrium in both the game strategies. A performance comparison between the proposed distributed and centralized strategy with existing solutions are presented. We also provide the results of the coalition game when both charging and discharging PHEVs are present in the network. The proper management of charging and discharging of EVs poses one of the most challenging and interesting issues in our research. We aim to provide a complete demand response management solution to PHEVs and micro-grids in a real-time scenario.
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