Flexible Aggressiveness Probabilistic Optimisation (Fapo) Bidding for Peer-to-Peer Electricity Trading

Abstract

The maximisation of renewable energy generation is critical for net zero as- piring countries around the globe. Local Energy Markets (LEMs) facilitate the seamless incorporation of energy from distributed renewable energy re- sources (DERs) into the electricity network, serving as market platforms for trading locally-generated renewable energy between prosumers in residential communities. However, LEMs’ essential role in DER integration is not suffi- cient to encourage participation. Prosumers are most likely to join a LEM if financial incentives are offered as well. To address this, we present the Flex- ible Aggressiveness Probabilistic Optimisation (FAPO) bidding strategy for trading of electricity within a LEM aimed at the maximisation of participa- tion incentive, which is formulated as an optimisation problem aiming at the maximisation of prosumers’ individual utilities. The FAPO methodology is applied in a simplified LEM simulation environment and the results from its implementation are compared to those utilising two other well-established bidding strategies: Zero Intelligence (ZI) and a version of Adaptive Ag- gressiveness (AA). Results indicated that FAPO bidding achieved a wider range of clearing prices compared to both AA and ZI, thereby incentivising greater prosumer participation. Consequently, FAPO is proven to be an en- gaging bidding methodology likely to attract more prosumers to partake in LEMs. This is critical for the successful acceptance, uptake and eventually, widespread application of this financial market type, which is key for the smooth integration of DERs in the network.

Keywords: peer-to-peer (P2P), Local Energy Market, power trading, bidding strategy, Optimization, flexibility