Peer-to-Peer Trading in Electricity Networks: An Overview
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Abstract (arXiv)
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.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). First posted on arXiv 19 Jan 2020.
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Citing papers per year: 2022: 1; 2023: 1; 2024: 1; 2025: 2; 2026: 1.
6 papers.
- 2022Prospect Theory-inspired Automated P2P Energy Trading with Q-learning-based Dynamic Pricingcited by 1
- 2024Peer-to-Peer Energy Trading of Solar and Energy Storage: A Networked Multiagent Reinforcement Learning Approachcited by 1
- 2023textite-Uber: A Crowdsourcing Platform for Electric Vehicle-based Ride- and Energy-sharingcited by 0
- 2025Peer-to-Peer Energy Trading in Dairy Farms using Multi-Agent Reinforcement Learningcited by 0
- 2025Truthful and Trustworthy IoT AI Agents via Immediate-Penalty Enforcement under Approximate VCG Mechanismscited by 0
- 2026Towards Serverless Semi-Decentralized Federated Learning with Heterogeneous Optimizerscited by 0
- 2026Towards Serverless Semi-Decentralized Federated Learning with Heterogeneous Optimizers4 Jun 2026
- 2025Truthful and Trustworthy IoT AI Agents via Immediate-Penalty Enforcement under Approximate VCG Mechanisms29 Nov 2025
- 2025Peer-to-Peer Energy Trading in Dairy Farms using Multi-Agent Reinforcement Learning28 Nov 2025
- 2024Peer-to-Peer Energy Trading of Solar and Energy Storage: A Networked Multiagent Reinforcement Learning Approach25 Jan 2024
- 2023textite-Uber: A Crowdsourcing Platform for Electric Vehicle-based Ride- and Energy-sharing31 Mar 2023
- 2022Prospect Theory-inspired Automated P2P Energy Trading with Q-learning-based Dynamic Pricing26 Aug 2022