Optimising Demand and Bid Matching in a Peer-to-Peer Energy Trading Model

Meinke, Robin-Joshua, Sun, Hongjian and Jiang, Jing (2020) Optimising Demand and Bid Matching in a Peer-to-Peer Energy Trading Model. In: ICC 2020 - 2020 IEEE International Conference on Communications (ICC). IEEE, Piscataway, pp. 1-6. ISBN 9781728150901, 9781728150895

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Abstract

This paper addresses Peer-to-Peer energy trading as one of the new market paradigms for the post-subsidy operation of distributed renewable energy sources in local energy networks. The owners of such facilities become prosumers and now play an active role in the local energy supply by trading electricity among each other. This paper proposes: 1). an internal pricing model among peers by using the supplydemand ratio; 2). a peer self-optimisation method for promoting self-consumption of renewable energy; and 3). a peer to peer optimisation method that matches prosumer peers by reducing the distances of their energy trading. The case study validates the effectiveness of the proposed Peer-to-Peer trading method with real data. The main improvements revealed are significant economic benefits for the community and prosumers, i.e., a lower exchange of electricity with the utility grid by increasing the self-consumption in the community, and a reduction of peak demand hours due to local energy trading.

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