Dependable Demand Response Management in the Smart Grid: A Stackelberg Game Approach

Maharjan, Sabita; Zhu, Quanyan; Zhang, Yan; Gjessing, Stein; Başar, Tamer

doi:10.1109/tsg.2012.2223766

Cited by 690 publications

(338 citation statements)

References 19 publications

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“…The work [16] addressed the DRM problem in a network of multiple utility companies and consumers where every entity is concerned about maximizing its own benefit. In their model, utility companies communicate with each other, while users receive price information from utility companies and transmit their demand to them.…”

Section: B Similar Workmentioning

confidence: 99%

The Fog Computing Paradigm: Scenarios and Security Issues

Stojmenović¹,

Wen²

2014

Annals of Computer Science and Information Systems

800

441

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Abstract-Fog Computing is a paradigm that extends Cloud computing and services to the edge of the network. Similar to Cloud, Fog provides data, compute, storage, and application services to end-users. In this article, we elaborate the motivation and advantages of Fog computing, and analyse its applications in a series of real scenarios, such as Smart Grid, smart traffic lights in vehicular networks and software defined networks. We discuss the state-of-the-art of Fog computing and similar work under the same umbrella. Security and privacy issues are further disclosed according to current Fog computing paradigm. As an example, we study a typical attack, man-in-the-middle attack, for the discussion of security in Fog computing. We investigate the stealthy features of this attack by examining its CPU and memory consumption on Fog device.

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Section: B Similar Workmentioning

confidence: 99%

The Fog Computing Paradigm: Scenarios and Security Issues

Stojmenović¹,

Wen²

2014

Annals of Computer Science and Information Systems

800

441

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“…Wang et al [33] presented a game-theoretic double auction market model that allows the incorporation of power markets with multiple users and multiple suppliers, where a noncooperative game was formulated among distributed storage units in an SG. Maharjan et al [34] established a model for multiple utility companies and multiple consumers as a Stackelberg game to maximize the revenue of each company and the payoff of each consumer. Different from only one game model being employed for the scenario with multiple utility companies in the above papers, Chai et al [35] proposed the conception of a two-level game, in which the first-level among multiple utility companies was formulated as a non-cooperative game and the second-level among end users was formulated as a evolutionary game.…”

Section: Related Workmentioning

confidence: 99%

Autonomous Household Energy Management Based on a Double Cooperative Game Approach in the Smart Grid

et al. 2015

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Taking advantage of two-way communication infrastructure and bidirectional energy trading between utility companies and customers in the future smart grid (SG), autonomous energy management programs become crucial to the demand-side management (DSM). Most of the existing autonomous energy management schemes are for the scenario with a single utility company or the scenario with one-way energy trading. In this paper, an autonomous household energy management system with multiple utility companies and multiple residential customers is studied by considering the bidirectional energy trading. To minimize the overall costs of both the utility companies and the residential customers, the energy management system is formulated as a double cooperative game. That is, the interaction among the residential users is formulated as a cooperative game, where the players are the customers and the strategies are the daily schedules of their household appliances; and the interaction among the utility companies is also formulated as a cooperative game, where the players are the suppliers and the strategies are the proportions of the daily total energy they provide for the customers. Without loss of generality, the bidirectional energy trading in the double cooperative game is formulated by allowing plug-in electric vehicles (PEVs) to discharge and sell energy back. Two distributed algorithms will be provided to realize the global optimal performance in terms of minimizing the energy costs, which can be guaranteed at the Nash equilibriums of the formulated cooperative games. Finally, simulation results illustrated that the proposed double cooperative game can benefit both the utility companies and residential users significantly.

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“…However, there was no consideration of the amount of required energy demand, so the required energy level was not guaranteed. Similar to [27], the work of Alshehri [28] is the closest to this study. The authors added the minimum required energy demand as a constraint in the model of [27].…”

Section: Introductionmentioning

confidence: 67%

“…Similar to [27], the work of Alshehri [28] is the closest to this study. The authors added the minimum required energy demand as a constraint in the model of [27]. However, there was no consideration of a power loss penalty between multiple suppliers and consumers.…”

Section: Introductionmentioning

confidence: 67%

“…Here, because it is assumed that each supplier serves enrolled consumers, pricing competition among multiple suppliers was not considered. Maharjan et al [27] applied the Stackelberg game theory and developed a distributed algorithm to find optimal strategies for multiple suppliers and consumers. In their study, each consumer attempted to maximize the logarithmic satisfaction function according to procured energy within pre-defined budgets.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Evaluation of Demand-Side Management over Pricing Competition of Multiple Suppliers Having Heterogeneous Energy Sources

2017

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Abstract:This study investigates a demand-side management problem in which multiple suppliers compete with each other to maximize their own revenue. We consider that suppliers have heterogeneous energy sources and individually set the unit price of each energy source. Then, consumers that share a net utility react to the suppliers' decisions on prices by deciding the amount of energy to request, or how to split the consumers' aggregated demand over multiple suppliers. In this case, the consumers need to consider the power loss and the price to pay for procuring electricity. We analyze the economic benefits of such a pricing competition among suppliers (e.g., a demand-side management that considers consumers' reaction). This is achieved by designing a hierarchical decision-making scheme as a multileader-multifollower Stackelberg game. We show that the behaviors of both consumers and suppliers based on well-designed utility functions converge to a unique equilibrium solution. This allows them to maximize the payoff from all participating consumers and suppliers. Accordingly, closed-form expressions are provided for the corresponding strategies of the consumers and the suppliers. Finally, we provide numerical examples to illustrate the effectiveness of the solutions. This game-theoretic study provides an example of incentives and insight for demand-side management in future power grids.

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Dependable Demand Response Management in the Smart Grid: A Stackelberg Game Approach

Cited by 690 publications

References 19 publications

The Fog Computing Paradigm: Scenarios and Security Issues

The Fog Computing Paradigm: Scenarios and Security Issues

Autonomous Household Energy Management Based on a Double Cooperative Game Approach in the Smart Grid

Evaluation of Demand-Side Management over Pricing Competition of Multiple Suppliers Having Heterogeneous Energy Sources

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