A game theoretical approach to modeling energy consumption with consumer preference

Bai, Lihui; Xu, Guangyang; Zheng, Qipeng P.

doi:10.1109/pesgm.2014.6938898

Cited by 8 publications

(3 citation statements)

References 11 publications

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“…According to the previous definition, GT may be applied to power systems with the following adaptations: a) participants (typically, end-users) are defined as rational and strategic decision-makers [121]; b) players select the best strategy they can by anticipating the actions of other players [122]; c) consumers make their own decisions through decentralized problem solving [92,123].…”

Section: Game Theorymentioning

confidence: 99%

Electric energy management in residential areas through coordination of multiple smart homes

Celik

Roche

Suryanarayanan

et al. 2017

Renewable and Sustainable Energy Reviews

108

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Grid modernization through philosophies such as the Smart Grid has the potential to meet increasing demand and integrate new distributed generation resources at the same time. Using advanced communication and computing capabilities, the Smart Grid offers a new avenue of controlling end-user assets, including small units such as home appliances. To enable such evolution, shifting from centralized to decentralized control strategies is required. Effective demand-side management (DSM) and demand response (DR) approaches hold the promise for efficient energy management in homes and neighborhood areas, by enabling the precise control of resources to reduce net demand. However, with such strategies, independently taken decisions can cause undesired effects such as rebound peaks, contingencies, and instabilities in the network. Therefore, the interactions between the energy management actions of multiple households is a challenging issue in the Smart Grid. This paper provides a review of the background of residential load modeling with DR and DSM approaches in a single household and concepts of coordinating mechanisms in a neighborhood area. The objective of this paper is to classify, via comparison, the various coordination structures and techniques from recent research. The results of recent research in the field reveal that the coordination of energy management in multiple households can benefit both the utility (i.e., the service provider) and the customer. The paper concludes with a discussion on the prevalent critical issues in this area.

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Section: Game Theorymentioning

confidence: 99%

Electric energy management in residential areas through coordination of multiple smart homes

Celik

Roche

Suryanarayanan

et al. 2017

Renewable and Sustainable Energy Reviews

108

View full text Add to dashboard Cite

show abstract

“…Moreover, Ref. [11] proposes a game theoretical user equilibrium model to describe users' energy consumption behavior. In this user equilibrium model, each user reduces this electricity cost and also increases the convenience of using household appliances during the preferred times.…”

Section: Introductionmentioning

confidence: 99%

Electricity Consumption Scheduling with Consumers' Comfort and Preference in Smart Grid

Zhou

Zhong

et al. 2016

Chin. j. electron.

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“…With the advancement of communication technologies and smart meters within a smart grid, price signals can reach to the consumers in real time and in some cases the local/central operators can directly control the usage of some appliances. This increased ability for consumers and operators to interact within the power system has sparked interests in more decentralized models for describing individual's energy consumption scheduling and its impact on the power system [27].…”

mentioning

confidence: 99%

Optimization models and algorithms for demand response in smart grid.

Xu¹

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A game theoretical approach to modeling energy consumption with consumer preference

Cited by 8 publications

References 11 publications

Electric energy management in residential areas through coordination of multiple smart homes

Electric energy management in residential areas through coordination of multiple smart homes

Electricity Consumption Scheduling with Consumers' Comfort and Preference in Smart Grid

Optimization models and algorithms for demand response in smart grid.

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