Secure and Robust Demand Response Using Stackelberg Game Model and Energy Blockchain

Samadi, Mikhak; Ruj, Sushmita; Schriemer, Henry; Erol-Kantarci, Melike

doi:10.3390/s23208352

Cited by 3 publications

(1 citation statement)

References 62 publications

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“…Focusing on mathematical analysis of interactive multi-agent decision-making processes, game theory has gained increasing acknowledgement as a classic tool in areas [ 8 , 9 ] including wireless networks, Blockchains [ 10 ], Robots, and so on [ 11 ]. The game-playing process can be significantly influenced by the player’s cognition regarding the possibilities of different choices and the suitability of these choices, since a player makes his/her choices based on such a cognition.…”

Section: Introductionmentioning

confidence: 99%

Playing Extensive Games with Learning of Opponent’s Cognition

Liu,

Cong,

Yao

et al. 2024

Sensors

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Decision-making is a basic component of agents’ (e.g., intelligent sensors) behaviors, in which one’s cognition plays a crucial role in the process and outcome. Extensive games, a class of interactive decision-making scenarios, have been studied in diverse fields. Recently, a model of extensive games was proposed in which agent cognition of the structure of the underlying game and the quality of the game situations are encoded by artificial neural networks. This model refines the classic model of extensive games, and the corresponding equilibrium concept—cognitive perfect equilibrium (CPE)—differs from the classic subgame perfect equilibrium, since CPE takes agent cognition into consideration. However, this model neglects the consideration that game-playing processes are greatly affected by agents’ cognition of their opponents. To this end, in this work, we go one step further by proposing a framework in which agents’ cognition of their opponents is incorporated. A method is presented for evaluating opponents’ cognition about the game being played, and thus, an algorithm designed for playing such games is analyzed. The resulting equilibrium concept is defined as adversarial cognition equilibrium (ACE). By means of a running example, we demonstrate that the ACE is more realistic than the CPE, since it involves learning about opponents’ cognition. Further results are presented regarding the computational complexity, soundness, and completeness of the game-solving algorithm and the existence of the equilibrium solution. This model suggests the possibility of enhancing an agent’s strategic ability by evaluating opponents’ cognition.

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Section: Introductionmentioning

confidence: 99%

Playing Extensive Games with Learning of Opponent’s Cognition

Liu,

Cong,

Yao

et al. 2024

Sensors

View full text Add to dashboard Cite

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Stackelberg game strategy for demand response in electrolytic aluminum enterprise considering user response willingness

Li,

Pan,

Chen

et al. 2024

Journal of Renewable and Sustainable Energy

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In the context of demand response (DR), formulating rational electricity pricing (EP) and electricity pricing subsidy (EPS) strategies is crucial for the power grid when dealing with a high electricity user (EU), particularly an electrolytic aluminum enterprise (EAE) in an industrial park (IP). In addition, it is difficult to assess the response effectiveness of EU. This paper proposes a method to assess demand response willingness (DRW) by introducing indicators such as demand response economy and demand response potential, while taking into account carbon emission deviation. Then, the EPS is formulated based on the result of the DRW assessment. Second, this paper establishes a two-layer electricity supplier (ES)-EAE game model, in which the ES operates as the leader and EAE operates as the follower. The model takes into account the fluctuation and deviation of loads, constructs utility functions for both the leader and follower, selects dynamic EP scenarios at different time scales, and employs a large-scale global optimization particle swarm algorithm based on cooperative evolution for solving. Finally, the model's effectiveness is validated under three electricity pricing strategies: peak-valley pricing, critical peak pricing (CPP), and real-time pricing (RTP). According to the result of simulations, under the RTP strategy, the DRW of EAE has increased by 12.5% compared to the CPP strategy, and the DR load has increased by 82%. Additionally, there has been some reduction in costs of electricity consumption. This indicates that the ES can effectively guide the EU to reduce peak loads through EP, and the EU can also achieve a reasonable reduction in electricity costs.

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Review of Authentication, Blockchain, Driver ID Systems, Economic Aspects, and Communication Technologies in DWC for EVs in Smart Cities Applications

Rajamanickam,

Vishnuram,

Abraham

et al. 2024

Smart Cities

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The rapid advancement and adoption of electric vehicles (EVs) necessitate innovative solutions to address integration challenges in modern charging infrastructure. Dynamic wireless charging (DWC) is an innovative solution for powering electric vehicles (EVs) using multiple magnetic transmitters installed beneath the road and a receiver located on the underside of the EV. Dynamic charging offers a solution to the issue of range anxiety by allowing EVs to charge while in motion, thereby reducing the need for frequent stops. This manuscript reviews several pivotal areas critical to the future of EV DWC technology such as authentication techniques, blockchain applications, driver identification systems, economic aspects, and emerging communication technologies. Ensuring secure access to this charging infrastructure requires fast, lightweight authentication systems. Similarly, blockchain technology plays a critical role in enhancing the Internet of Vehicles (IoV) architecture by decentralizing and securing vehicular networks, thus improving privacy, security, and efficiency. Driver identification systems, crucial for EV safety and comfort, are analyzed. Additionally, the economic feasibility and impact of DWC are evaluated, providing essential insights into its potential effects on the EV ecosystem. The paper also emphasizes the need for quick and lightweight authentication systems to ensure secure access to DWC infrastructure and discusses how blockchain technology enhances the efficiency, security, and privacy of IoV networks. The importance of driver identification systems for comfort and safety is evaluated, and an economic study confirms the viability and potential benefits of DWC for the EV ecosystem.

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Secure and Robust Demand Response Using Stackelberg Game Model and Energy Blockchain

Cited by 3 publications

References 62 publications

Playing Extensive Games with Learning of Opponent’s Cognition

Playing Extensive Games with Learning of Opponent’s Cognition

Stackelberg game strategy for demand response in electrolytic aluminum enterprise considering user response willingness

Review of Authentication, Blockchain, Driver ID Systems, Economic Aspects, and Communication Technologies in DWC for EVs in Smart Cities Applications

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