Increase in the deployment of Distributed Energy Resources (DERs) has triggered a new trend to redesign electricity markets as consumer-centric markets relying on Peer-to-Peer (P2P) approaches. In the P2P markets, players can directly negotiate under bilateral energy trading to match demand and supply. The trading scheme should be designed adequately to incentivise players to participate in the trading process actively. This paper proposes a decentralised P2P energy trading scheme for electricity markets with high penetration of DERs. A novel algorithm using primal-dual gradient method is described to clear the market in a fully decentralised manner without interaction of any central entity. Also, to incorporate technical constraints in the energy trading, line flow constraints are modelled in the bilateral energy trading to avoid overloaded or congested lines in the system. This market structure respects market players' preferences by allowing bilateral energy trading with product differentiation. The performance of the proposed method is evaluated using simulation studies, and it is found that market players can trade energy to maximise their welfare without violating line flow constraints. Also, compared with other similar methods for P2P trading, the proposed approach needs lower data exchange and has a faster convergence rate.

Massive deployment of distributed energy resources (DERs) along with innovations in information and communication technologies have changed the power system from a hierarchical structure to a more deregulated model by introducing new generations at lower levels. This change raises operational and market challenges. Local energy trading provides opportunities to manage these DERs by encouraging localised trading. The concept of local energy trading at the distribution level is widely broadcasted for implementation in the power system. In the design of electricity markets for local energy trading, a clear definition of market participants, their objective, and purpose of market clearing should be established. This design depends on the changing needs of the power system and can be performed from different viewpoints. Classification and organisation of the literature on potential designs for local energy trading can help researchers to develop their future steps properly. This study presents a comprehensive review on this topic and provides a systematic classification of the market players, market clearing objectives, and approaches. Several research works are analysed against different criteria, including scalability, overheads requirements, and network constraints management.

This paper presents a scalable mechanism for peer-to-peer (P2P) energy trading among prosumers in a smart grid. In the proposed mechanism, prosumers engage in a non-mediated negotiation with their peers to reach an agreement on the price and quantity of energy to be exchanged. Instead of concurrent bilateral negotiation between all peers with high overheads, an iterative peer matching process is employed to match peers for bilateral negotiation. The proposed negotiation algorithm enables prosumers to come to an agreement, given that they have no prior knowledge about the preference structure of their trading partners. A greediness factor is introduced to model the selfish behavior of prosumers in the negotiation process and to investigate its impact on the negotiation outcome. In order to recover the costs related to power losses, a transaction fee is applied to each transaction that enables the grid operator to recover incurred losses due to P2P trades. The case studies demonstrate that the proposed mechanism discourages greedy behavior of prosumers in the negotiation process as it does not increase their economic surplus. Also, it has an appropriate performance from the computation overheads and scalability perspectives.

This study proposes a hybrid energy trading scheme for peer‐to‐peer (P2P) energy trading in transactive energy markets. Market players can participate in different markets, including local markets, trading with neighbourhood areas, and traditional trading with the grid. In each local market, a community manager (CM) facilitates energy trading and negotiates with other CMs for neighbourhood trading. Based on the heterogeneous preferences of players of each community, each local market has a different price, which is different from market price for neighbourhood trading and trading with the grid. A distributed market clearing mechanism is presented that incorporates coordination among different markets. Also, a network utilisation charge function is defined to apply price signals to the market players to reflect network constraints in energy trading. These price signals are calculated based on the technical constraints in each market and are applied to the corresponding players based on their contribution to network constraints violation. Performance of the proposed trading scheme is evaluated against different market structures and through several case studies.

A local energy trading in microgrids is one of the emerging concepts in the area of distribution networks. A proper business model is required to manage local energy trading. The pricing mechanism is crucial because the agreed energy price determines the benefits of local energy trading. Designing a proper pricing mechanism with a specific objective considering the privacy of agents and respecting physical network constraints is a challenging task. This paper proposes a decentralized algorithm for local energy trading in microgrids with an integrated pricing mechanism considering welfare maximization and network voltage management through local information exchange among neighbors. The proposed algorithm guarantees that the energy transactions do not violate voltage constraints in a physical network and agents' privacy is preserved. A two-stage approach is proposed to achieve fast convergence and increase the practicability of the algorithm. The simulation results are presented to verify the effectiveness of the proposed approach.