Stackelberg-Game-Based Demand Response for At-Home Electric Vehicle Charging

Yoon, Sung-Guk; Choi, Young‐June; Park, Jong–Keun; Bahk, Saewoong

doi:10.1109/tvt.2015.2440471

Cited by 93 publications

(50 citation statements)

References 29 publications

(43 reference statements)

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“…Then the remaining nodes (followers), depending on the actions selected by the leaders, should choose their most convenient actions. The surveyed papers rely on SGs modelling some MEC use cases: i) offloading mobile computation [45]; ii) efficient cellular communications [171] [172][54] [173]; iii) resource allocation in hierarchical cellular networks [65][37] [66]; iv) multimedia services [48] [174]; and v) management of micro-grids [175] [176].…”

Section: Table VIII a Summary Of Non-cooperative Approaches For The Rmentioning

confidence: 99%

Game Theory for Multi-Access Edge Computing: Survey, Use Cases, and Future Trends

Moura

Hutchison

2019

IEEE Commun. Surv. Tutorials

169

108

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Game Theory (GT) has been used with significant success to formulate, and either design or optimize, the operation of many representative communications and networking scenarios. The games in these scenarios involve, as usual, diverse players with conflicting goals. This paper primarily surveys the literature that has applied theoretical games to wireless networks, emphasizing use cases of upcoming Multi-Access Edge Computing (MEC). MEC is relatively new and offers cloud services at the network periphery, aiming to reduce service latency backhaul load, and enhance relevant operational aspects such as Quality of Experience or security. Our presentation of GT is focused on the major challenges imposed by MEC services over the wireless resources. The survey is divided into classical and evolutionary games. Then, our discussion proceeds to more specific aspects which have a considerable impact on the game's usefulness, namely: rational vs. evolving strategies, cooperation among players, available game information, the way the game is played (single turn, repeated), the game's model evaluation, and how the model results can be applied for both optimizing resource-constrained resources and balancing diverse trade-offs in real edge networking scenarios. Finally, we reflect on lessons learned, highlighting future trends and research directions for applying theoretical model games in upcoming MEC services, considering both network design issues and usage scenarios.

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Section: Table VIII a Summary Of Non-cooperative Approaches For The Rmentioning

confidence: 99%

Game Theory for Multi-Access Edge Computing: Survey, Use Cases, and Future Trends

Moura

Hutchison

2019

IEEE Commun. Surv. Tutorials

169

108

View full text Add to dashboard Cite

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“…One of the main motivations for developing integrated energy systems and what is called energy internet is to manage energy in an optimal way. To make it clear, assume an IoT-based energy system including Electric Vehicles (EVs) [75]. In this attempt, each EV tries to maximize its objective (paying less money), while an energy retailer tries to maximize its own objective (earning more money).…”

Section: Energy Management Systems In Iot Frameworkmentioning

confidence: 99%

Internet of Things for Modern Energy Systems: State-of-the-Art, Challenges, and Open Issues

et al. 2018

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The Internet of Things (IoT) is beginning to shape the future of many industries and emerging markets. One of the target markets for IoT is the energy systems. IoT is a matter of producing, transferring, and processing information, therefore all parts of the system including software and hardware parts should be considered as a whole. In this paper, a state-of-the-art of the IoT-based energy systems is presented to review the recent activities on every component of IoT in energy systems. Challenges in this subject area are discussed, and some solutions are presented thereafter.

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“…The improved particle swarm optimization method has been used to optimize the problem based on the proposed demand response program. In [16], the authors introduced the Stackelberg game-based method to maximize the profits of the costumers and retailers simultaneously. In the proposed home model of [16], electrical loads of customers are elastic based on EVs.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In [16], the authors introduced the Stackelberg game-based method to maximize the profits of the costumers and retailers simultaneously. In the proposed home model of [16], electrical loads of customers are elastic based on EVs. Furthermore, the price-based DR has been implemented in [16].…”

Section: Literature Reviewmentioning

confidence: 99%

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Energy Flexibility Management Based on Predictive Dispatch Model of Domestic Energy Management System

et al. 2017

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This paper proposes a predictive dispatch model to manage energy flexibility in the domestic energy system. Electric Vehicles (EV), batteries and shiftable loads are devices that provide energy flexibility in the proposed system. The proposed energy management problem consists of two stages: day-ahead and real time. A hybrid method is defined for the first time in this paper to model the uncertainty of the PV power generation based on its power prediction. In the day-ahead stage, the uncertainty is modeled by interval bands. On the other hand, the uncertainty of PV power generation is modeled through a stochastic scenario-based method in the real-time stage. The performance of the proposed hybrid Interval-Stochastic (InterStoch) method is compared with the Modified Stochastic Predicted Band (MSPB) method. Moreover, the impacts of energy flexibility and the demand response program on the expected profit and transacted electrical energy of the system are assessed in the case study presented in this paper.

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Stackelberg-Game-Based Demand Response for At-Home Electric Vehicle Charging

Cited by 93 publications

References 29 publications

Game Theory for Multi-Access Edge Computing: Survey, Use Cases, and Future Trends

Game Theory for Multi-Access Edge Computing: Survey, Use Cases, and Future Trends

Internet of Things for Modern Energy Systems: State-of-the-Art, Challenges, and Open Issues

Energy Flexibility Management Based on Predictive Dispatch Model of Domestic Energy Management System

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