No Arabic abstract
Blockchain is increasingly being used as a distributed, anonymous, trustless framework for energy trading in smart grids. However, most of the existing solutions suffer from reliance on Trusted Third Parties (TTP), lack of privacy, and traffic and processing overheads. In our previous work, we have proposed a Secure Private Blockchain-based framework (SPB) for energy trading to address the aforementioned challenges. In this paper, we present a proof-on-concept implementation of SPB on the Ethereum private network to demonstrates SPBs applicability for energy trading. We benchmark SPBs performance against the relevant state-of-the-art. The implementation results demonstrate that SPB incurs lower overheads and monetary cost for end users to trade energy compared to existing solutions.
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.
Scalability and security problems of the centralized architecture models in cyberphysical systems have great potential to be solved by novel blockchain based distributed models.A decentralized energy trading system takes advantage of various sources and effectively coordinates the energy to ensure optimal utilization of the available resources. It achieves that goal by managing physical, social and business infrastructures using technologies such as Internet of Things (IoT), cloud computing and network systems. Addressing the importance of blockchain-enabled energy trading in the context of cyberphysical systems, this article provides a thorough overview of the P2P energy trading and the utilization of blockchain to enhance the efficiency and the overall performance including the degree of decentralization, scalability and the security of the systems. Three blockchain based energy trading models have been proposed to overcome the technical challenges and market barriers for better adoption of this disruptive technology.
We consider user-private information retrieval (UPIR), an interesting alternative to private information retrieval (PIR) introduced by Domingo-Ferrer et al. In UPIR, the database knows which records have been retrieved, but does not know the identity of the query issuer. The goal of UPIR is to disguise user profiles from the database. Domingo-Ferrer et al. focus on using a peer-to-peer community to construct a UPIR scheme, which we term P2P UPIR. In this paper, we establish a strengthened model for P2P UPIR and clarify the privacy goals of such schemes using standard terminology from the field of privacy research. In particular, we argue that any solution providing privacy against the database should attempt to minimize any corresponding loss of privacy against other users. We give an analysis of existing schemes, including a new attack by the database. Finally, we introduce and analyze two new protocols. Whereas previous work focuses on a special type of combinatorial design known as a configuration, our protocols make use of more general designs. This allows for flexibility in protocol set-up, allowing for a choice between having a dynamic scheme (in which users are permitted to enter and leave the system), or providing increased privacy against other users.
This paper studies social cooperation backed peer-to-peer energy trading technique by which prosumers can decide how they can use their batteries opportunistically for participating in the peer-to-peer trading. The objective is to achieve a solution in which the ultimate beneficiaries are the prosumers, i.e., a prosumer-centric solution. To do so, a coalition formation game is designed, which enables a prosumer to compare its benefit of participating in the peer-to-peer trading with and without using its battery and thus, allows the prosumer to form suitable social coalition groups with other similar prosumers in the network for conducting peer-to-peer trading. The properties of the formed coalitions are studied, and it is shown that 1) the coalition structure that stems from the social cooperation between participating prosumers at each time slot is both stable and optimal, and 2) the outcomes of the proposed peer- to-peer trading scheme is prosumer-centric. Case studies are conducted based on real household energy usage and solar generation data to highlight how the proposed scheme can benefit prosumers through exhibiting prosumer-centric properties.
Efforts to efficiently promote the participation of distributed energy resources in community microgrids require new approaches to energy markets and transactions in power systems. In this paper, we contribute to the promising approach of peer-to-peer (P2P) energy trading. We first formalize a centralized welfare maximization model of an economic dispatch with perfect information based on the value of consumption with zero marginal-cost energy. We characterize the optimal solution and corresponding price to serve as a reference for P2P approaches and show that the profit-maximizing strategy for individuals with storage in response to an optimal price is not unique. Second, we develop a novel P2P algorithm for negotiating energy trades based on iterative price and quantity offers that yields physically feasible and at least weakly Pareto-optimal outcomes. We prove that the P2P algorithm converges to the centralized solution in the case of two agents negotiating for a single period, demonstrate convergence for the multi-agent, multi-period case through a large set of random simulations, and analyze the effects of storage penetration on the solution.