Peer-to-peer trading is a next-generation energy management technique that economically benefits proactive consumers (prosumers) transacting their energy as goods and services. At the same time, peer-to-peer energy trading is also expected to help the grid by reducing peak demand, lowering reserve requirements, and curtailing network loss. However, large-scale deployment of peer-to-peer trading in electricity networks poses a number of challenges in modeling transactions in both the virtual and physical layers of the network. As such, this article provides a comprehensive review of the state-of-the-art in research on peer-to-peer energy trading techniques. By doing so, we provide an overview of the key features of peer-to-peer trading and its benefits of relevance to the grid and prosumers. Then, we systematically classify the existing research in terms of the challenges that the studies address in the virtual and the physical layers. We then further identify and discuss those technical approaches that have been extensively used to address the challenges in peer-to-peer transactions. Finally, the paper is concluded with potential future research directions.

Peer-to-Peer Trading in Electricity Networks: An Overview

Bridging data-driven and model-based approaches for process fault diagnosis and health monitoring: A review of researches and future challenges

Incipient fault detection with smoothing techniques in statistical process monitoring

A coalition formation game framework for peer-to-peer energy trading

We consider a network of prosumers involved in peer-to-peer energy exchanges, with differentiation price preferences on the trades with their neighbors, and we analyze two market designs: (i) a centralized market, used as a benchmark, where a global market operator optimizes the flows (trades) between the nodes, local demand and flexibility activation to maximize the system overall social welfare; (ii) a distributed peer-to-peer market design where prosumers in local energy communities optimize selfishly their trades, demand, and flexibility activation. We first characterizethe solution of the peer-to-peer market as a Variational Equilibrium and prove that the set of Variational Equilibria coincides with the set of social welfare optimal solutions of market design (i). We give several results that help understanding the structure of the trades at an equilibriumor at the optimum. We characterize the impact of preferences on the network line congestion and renewable energy waste under both designs. We provide a reduced example for which we give the set of all possible generalized equilibria, which enables to give an approximation of the price ofanarchy. We provide a more realistic example which relies on the IEEE 14-bus network, for which we can simulate the trades under different preference prices. Our analysis shows in particular that the preferences have a large impact on the structure of the trades, but that one equilibrium(variational) is optimal.

Peer-to-Peer Electricity Market Analysis: From Variational to Generalized Nash Equilibrium

An improved weighted recursive PCA algorithm for adaptive fault detection

Empowering end-use consumers of electricity to aggregate for demand-side participation

Optimal operation of a system of charging hubs and a fleet of shared autonomous electric vehicles

A Nash-bargaining model for trading of electricity between aggregations of peers

A bilevel conic optimization model for routing and charging of EV fleets serving long distance delivery networks

Kevin A. Melendez

Papers

An improved weighted recursive PCA algorithm for adaptive fault detection

Empowering end-use consumers of electricity to aggregate for demand-side participation

Optimal operation of a system of charging hubs and a fleet of shared autonomous electric vehicles

A Nash-bargaining model for trading of electricity between aggregations of peers

A bilevel conic optimization model for routing and charging of EV fleets serving long distance delivery networks