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This paper addresses the critical challenges of renewable energy integration and regional power balance in smart grids, which have become increasingly complex with the rapid growth of distributed energy resources. It proposes a novel three-layer scheduling framework with a dynamic peer-to-peer (P2P) trading mechanism to address these challenges. The framework incorporates a preliminary local supply–demand balance considering renewable energy, followed by an inter-regional P2P trading layer and, ultimately, flexible resource deployment for final balance adjustment. The proposed dynamic continuous P2P trading mechanism enables regions to autonomously switch roles between buyer and seller based on their internal energy status and preferences, facilitating efficient trading while protecting regional privacy. The model features an innovative price update mechanism that initially leverages historical trading data and dynamically adjusts prices to maximize trading success rates. To address the heterogeneity of regional resources and varying energy demands, the framework implements a flexible trading strategy that allows for differentiated transaction volumes and prices. The effectiveness of the proposed framework is validated through simulation experiments using k-means clustered typical daily data from four regions in Northeast China. The results demonstrate that the proposed approach successfully promotes renewable energy utilization, reduces the operational costs of flexible resources, and achieves an efficient inter-regional energy balance while maintaining regional autonomy and information privacy. [ABSTRACT FROM AUTHOR]

The rapid growth of distributed renewable energy penetration is promoting the evolution of the energy system toward decentralization and decentralized and digitized smart grids. This study was based on energy blockchain, and developed a dual-biding mechanism based on the real-time energy surplus and demand in the local smart grid, which is expected to enable reliable, affordable, and clean energy supply in smart communities. In the proposed system, economic benefits could be achieved by replacing fossil-fuel-based electricity with the high penetration of affordable solar PV electricity. The reduction of energy surplus realized by distributed energy production and P2P energy trading, within the smart grid results in less transmission loss and lower requirements for costly upgrading of existing grids. By adopting energy blockchain and smart contract technologies, energy secure trading with a low risk of privacy leakage could be accommodated. The prototype is examined through a case study, and the feasibility and efficiency of the proposed mechanism are further validated by scenario analysis. [ABSTRACT FROM AUTHOR]

Peer-to-peer (P2P) trading is seen as a viable solution to handle the growing number of distributed energy resources in distribution networks. However, when dealing with large-scale consumers, there are several challenges that must be addressed. One of these challenges is limited communication capabilities. Additionally, prosumers may have specific preferences when it comes to trading. Both can result in serious asynchrony in peer-to-peer trading, potentially impacting the effectiveness of negotiations and hindering convergence before the market closes. This paper introduces a connection-aware P2P trading algorithm designed for extensive prosumer trading. The algorithm facilitates asynchronous trading while respecting prosumer's autonomy in trading peer selection, an often overlooked aspect in traditional models. In addition, to optimize the use of limited connection opportunities, a smart trading peer connection selection strategy is developed to guide consumers to communicate strategically to accelerate convergence. A theoretical convergence guarantee is provided for the connection-aware P2P trading algorithm, which further details how smart selection strategies enhance convergence efficiency. Numerical studies are carried out to validate the effectiveness of the connection-aware algorithm and the performance of smart selection strategies in reducing the overall convergence time. [Display omitted] • Develop the connection-aware P2P trading algorithm to address the asynchrony challenge in P2P trading. • Propose smart selection strategies within the context of connection limits in P2P trading. • Provide theoretical guarantees on the convergence of the connection-aware P2P trading algorithm. [ABSTRACT FROM AUTHOR]

Peer-to-peer (P2P) energy trading refers to a type of decentralized transaction, where the energy from distributed energy resources is directly traded between peers. A key challenge in peer-to-peer energy trading is designing a safe, efficient, and transparent trading model and operating mechanism. In this study, we consider a P2P trading environment based on blockchain technology, where prosumers can submit bids or offers without knowing the reports of others. We propose an Arrow-d'Aspremont-Gerard-Varet (AGV)-based mechanism to encourage prosumers to submit their real reserve price and determine the P2P transaction price. We demonstrate that the AGV mechanism can achieve Bayesian incentive compatibility and budget balance. Kernel density estimation (KDE) is used to derive the prior distribution from the historical bid/offer information of the agents. Case studies are carried out to analyze and evaluate the proposed mechanism. Simulation results verify the effectiveness of the proposed mechanism in guiding agents to report the true reserve price while maximizing social welfare. Moreover, we discuss the advantages of budget balance for decentralized trading by comparing the Vickrey-Clarke-Groves (VCG) and AGV mechanisms. [ABSTRACT FROM AUTHOR]

The decentralization of power generation driven by the rise in the adoption of distributed energy resources paves the way for a new paradigm in grid operations. P2P energy trading is beneficial to the grid as well as the connected peers. A blockchain-based smart contract is well suited to transparently facilitate trades between energy consumers and producers without the services of intermediaries. In this paper, Ethereum-based smart contracts that facilitate double energy auction and spinning reserve trading are developed with Solidity, compiled, and deployed within the Remix IDE. Willing energy sellers/buyers submit offers/bids to a contract that implements the double auction procedure. In order to fulfil energy supply obligations, sellers are also able to purchase spinning reserves via another smart contract. The smart contracts' effectiveness in performing the auction procedure and making payments is confirmed using an energy/reserve market scenario. The proposed scheme encourages further adoption of distributed energy resources and participation in local P2P energy trading. [ABSTRACT FROM AUTHOR]

• A strategy for distributed Peer-to-Peer (P2P) energy trading was proposed. • A quantification strategy for flexible resources was proposed. • A pricing strategy with privacy and intelligence was proposed. • The impact of renewable energy uncertainty on bidding decisions was considered. • The strategy protects privacy, improves benefits, and enhances local energy balance. With the widespread application of distributed power generation, traditional energy consumers are becoming active prosumers. Giving full play to the role of the electricity market in resource allocation, peer-to-peer (P2P) energy trading between multiple prosumers and consumers helps increase the revenue of electricity sales and reduce the cost of electricity consumption. The participation of flexible resources in P2P energy trading achieves local power complementarity, improves benefits, and reduces the operating pressure of lines. To ensure the benefits of prosumers and stimulate their enthusiasm, it is necessary to propose an effective trading strategy to fully allow flexible resources to participate in P2P energy trading. Therefore, this paper establishes a P2P energy market based on the continuous double auction (CDA) mechanism. Based on the model predictive control (MPC) theory, we propose a minimum cost rolling optimization model to optimize the bidding quantity of flexible resources. Moreover, the Automatic Learning (AL) pricing strategy with privacy and learning is proposed. The AL bidding price strategy enables interactive learning among prosumers. In addition, the influence of bidding price on bidding quantity during the trading process is also considered. Furthermore, this paper considers the impact of renewable energy source (RES) uncertainty on the bidding decisions of prosumers. Finally, the effectiveness of the proposed strategy is verified by the simulation results of cases. The simulation results demonstrate that the proposed strategy can improve the benefits for prosumers, enhance the local balance ability, achieve price learning, and increase the transaction rate. [ABSTRACT FROM AUTHOR]

Distributed peer-to-peer (P2P) energy trading can promote the localized balancing of power supply and demand, improve grid utilization efficiency, and ensure fairness. Shared energy storage (SES) enables users to withdraw electrical energy from shared batteries. This paper proposes a P2P energy trading model combined with SES and studies a cooperative surplus distribution mechanism based on the asymmetric Nash bargaining (ANB) theory. First, a cooperative model is established for enabling cooperation among sellers and buyers in a P2P energy trading system, offering a cooperative surplus due to cooperation. Secondly, by using the Asymmetric Nash Bargaining theory, a profit distribution model for the participants is constructed to ensure that the cooperation surplus can be fairly distributed among buyers and sellers. Finally, case studies are presented to verify the effectiveness of the proposed model. The simulation results show that the proposed cooperative method can improve the benefits of each entity and the overall benefits of the cooperative alliance. The proposed profit distribution model can reflect the difference in the contributions of sellers and buyers in the P2P energy trading system and fairly distribute the cooperation surplus. Furthermore, SES can improve the overall economics of DGs and consumers. • A cooperative game model of P2P energy trading combined with SES is established. • ANB theory is introduced to distribute cooperative surplus. • The bargaining power is measured by the marginal contribution and the CVaR. • Fairness index is applied to study the fairness of the method. [ABSTRACT FROM AUTHOR]

• Microgrid and blockchain alone and together enable collective energy communities. • Microgrid as local aggregator of control and communication with regulated grid. • Blockchain as interactive aggregator of large-scale framework and service in trust. • Survey on co-creation of microgrid-blockchain in research, applications and pilots. • Future trends are analyzed on microgrid-blockchain innovation in energy transition. Decarbonisation of energy sector is crucial to deliver the future net zero energy system with promoting and facilitating the large-scale electrification of end-user sectors. It is necessary to provide sustainable, cost-effective, resilient and scalable energy solutions to exploit the power of citizens to contribute to the clean energy transition, increasing the flexibility of the overall energy system. Energy community, as the new actor, create an integrated pan energy market by bringing together the local consumers and energy market players. However, diversity of energy community brings huge challenges in integration of decentralized renewables with regulated framework, interaction of decentralized marketplaces, as well as interoperability of the cross-border energy sectors with privacy, security and incentives. This paper intends to provide an in-depth investigation on the role of microgrid and blockchain, alone and together, in facilitating the energy community as the "enabling framework" to boost the potential solutions of electrification in the transportation, building, and industrial sectors, as well as rural/remote areas and islands towards a networking green ecosystem. This paper serves as a comprehensive reference to understand the modern microgrid on its control and communication technology with integration of blockchain services in promoting the techno-socio-economic innovations for the restructuring of the sustainable energy supply chain. [ABSTRACT FROM AUTHOR]

Peer-to-peer (P2P) energy trading is gaining attention as a technology to effectively handle already existing distributed energy resources (DER). In order to manage a large number of DER, it is necessary to increase the number of P2P energy trading participants. For that, designing incentives for participants to engage in P2P energy trading is important. This paper describes a user-centric cooperative mechanism that enhances user participation in P2P energy trading. The key components of this incentive for participants to engage in P2P energy trading are described and evaluated in this study. The goal of the proposal is to make it possible to conduct economic transactions while reflecting the preferences of the traders in the ordering process, making it possible to conduct transactions with minimal effort. As a case study, the Higashi-Fuji demonstration experiment conducted in Japan verified the proposed mechanism. In this experiment, 19 households and 9 plugin hybrid vehicles (PHV) were evaluated. As a result, the study confirmed that prosumers were able to sell their surplus electricity, and consumers were able to preferentially purchase renewable energy when it was available. In addition, those trades were made economically. All trades were made automatically, and this efficiency allowed the users to continue using the P2P energy trading. [ABSTRACT FROM AUTHOR]

• Presents a two-stage optimisation for design and operation of community microgrids. • Third-party based investment planning of community distributed energy resources. • Local energy market is developed to allow participation of multiple stakeholders. • The energy management system facilitates peer-to-peer optimal energy trading. • Urban and remote communities reduce annual bills by 17.75%. In this article, a new business model considering multiple stakeholders is proposed to develop a framework for third-party investment and future flexible retail electricity market in community microgrids. The proposed two-stage optimisation platform generates opportunities for multiple stakeholders to invest in the design of community microgrids, comprising multiple and different distributed energy resources such as renewable generation units, battery energy storage systems, and micro diesel engines, to minimize daily operational costs of the system. To proliferate the prosumers in retail energy markets as per the Office of Gas and Electricity Markets, United Kingdom, a peer-to-peer energy trading and energy management scheme is also proposed. The optimal sizing of urban and remote community microgrids are determined in stage-1, followed by their optimal operations to minimise the daily operating cost of the community system in stage-2. An improved version of the genetic algorithm is employed to optimise decision variables in both the stages. Different cases are investigated which show the tremendous potential of revenue generation for all stakeholders while effectively optimizing techno-economic operations of microgrids. [ABSTRACT FROM AUTHOR]