Flocking-based decentralised double auction for P2P energy trading within neighbourhoods

Abstract

Renewable energy sources are highly unreliable and create unreliable energy surplus and energy demands. These energy surpluses and demands can be traded frequently within neighbourhoods. This paper presents a trading algorithm to trade unreliable renewable energy frequently within neighbourhoods. We considered the flocking behaviour of birds and distributed double auction, and developed a trading algorithm to perform peer-to-peer(P2P) energy trading within neighbourhoods. Peers are prosumers which can be energy co-operatives, micro-grids, electric vehicles, charging stations, etc. We implemented our flocking-based decentralised double auction algorithm in Java and tested using a residential PV data set from California state in the USA. Our mathematical analysis shows that the peers are converging to average positions of neighbourhoods while performing P2P trading. Our experimental results showed that the proposed algorithm has a higher success rate and faster convergence to the success rate than the centralised double auction and distributed double auction presented in the literature. Moreover, nodes are converging to neighbourhoods. This guarantees trading within neighbourhoods. Further, we have observed that successful trading reaches around 80%.