1,824 research outputs found
Lightweight Blockchain Framework for Location-aware Peer-to-Peer Energy Trading
Peer-to-Peer (P2P) energy trading can facilitate integration of a large
number of small-scale producers and consumers into energy markets.
Decentralized management of these new market participants is challenging in
terms of market settlement, participant reputation and consideration of grid
constraints. This paper proposes a blockchain-enabled framework for P2P energy
trading among producer and consumer agents in a smart grid. A fully
decentralized market settlement mechanism is designed, which does not rely on a
centralized entity to settle the market and encourages producers and consumers
to negotiate on energy trading with their nearby agents truthfully. To this
end, the electrical distance of agents is considered in the pricing mechanism
to encourage agents to trade with their neighboring agents. In addition, a
reputation factor is considered for each agent, reflecting its past performance
in delivering the committed energy. Before starting the negotiation, agents
select their trading partners based on their preferences over the reputation
and proximity of the trading partners. An Anonymous Proof of Location (A-PoL)
algorithm is proposed that allows agents to prove their location without
revealing their real identity. The practicality of the proposed framework is
illustrated through several case studies, and its security and privacy are
analyzed in detail
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Diffusion of shared goods in consumer coalitions. An agent-based model
This paper focuses on the process of coalition formation conditioning the common decision to adopt a shared good, which cannot be afforded by an average single consumer and whose use cannot be exhausted by any single consumer. An agent based model is developed to study the interplay between these two processes: coalition formation and diffusion of shared goods. Coalition formation is modelled in an evolutionary game theoretic setting, while adoption uses elements from both the Bass and the threshold models. Coalitions formation sets the conditions for adoption, while diffusion influences the consequent formation of coalitions. Results show that both coalitions and diffusion are subject to network effects and have an impact on the information flow though the population of consumers. Large coalitions are preferred over small ones since individual cost is lower, although it increases if higher quantities are purchased collectively. The paper concludes by connecting the model conceptualisation to the on-going discussion of diffusion of sustainable goods, discussing related policy implications
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Incentive Mechanisms in Peer-to-Peer Networks â A Systematic Literature Review
Centralized networks inevitably exhibit single points of failure that malicious actors regularly target. Decentralized networks are more resilient if numerous participants contribute to the networkâs functionality. Most decentralized networks employ incentive mechanisms to coordinate the participation and cooperation of peers and thereby ensure the functionality and security of the network. This article systematically reviews incentive mechanisms for decentralized networks and networked systems by covering 165 prior literature reviews and 178 primary research papers published between 1993 and October 2022. Of the considered sources, we analyze 11 literature reviews and 105 primary research papers in detail by categorizing and comparing the distinctive properties of the presented incentive mechanisms. The reviewed incentive mechanisms establish fairness and reward participation and cooperative behavior. We review work that substitutes central authority through independent and subjective mechanisms run in isolation at each participating peer and work that applies multiparty computation. We use monetary, reputation, and service rewards as categories to differentiate the implementations and evaluate each incentive mechanismâs data management, attack resistance, and contribution model. Further, we highlight research gaps and deficiencies in reproducibility and comparability. Finally, we summarize our assessments and provide recommendations to apply incentive mechanisms to decentralized networks that share computational resources
Dynamic constrained coalition formation among electric vehicles
Background: The use of electric vehicles (EVs) and vehicle-to-grid (V2G) technologies have been advocated as an efficient way to reduce the intermittency of renewable energy sources in smart grids. However, operating on V2G sessions in a cost-effective way is not a trivial task for EVs. The formation of coalitions among EVs has been proposed to tackle this problem. Methods: In this paper we introduce Dynamic Constrained Coalition Formation (DCCF), which is a distributed heuristic-based method for constrained coalition structure generation (CSG) in dynamic environments. In our approach, coalitions are formed observing constraints imposed by the grid. To this end, EV agents negotiate the formation of feasible coalitions among themselves. Results: Based on experiments, we show that DCCF is efficient to provide good solutions in a fast way. DCCF provides solutions whose quality approaches 98% of the optimum. In dynamically changing scenarios, DCCF also shows good results, keeping the agents payoff stable along time. Conclusions: Essentially, DCCFâs main advantage over traditional CSG algorithms is that its computational effort is very lower. On the other hand, unlike traditional algorithms, DCCF is suitable only for constraint-based problems
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