A Peer-to-Peer energy trading market model based on time-driven prospect theory in a smart and sustainable energy community

Abstract Human is the main decision-maker in a Peer-to-Peer (P2P) energy trading problem. Modeling a decision maker’s monetary mental view in P2P experiences is a crucial issue. An end-user that participates in P2P trading is faced with a set of probable scenarios. Decision weight factors assigned by end-users to the scenarios considering risk-aversion attitude are to be implemented in P2P trading. To this end, applying the prospect theory is proposed in this paper. Referring to some psychological studies, it is assumed that the value of prospected income for a P2P problem tends to be reduced based upon the time. In this regard, we modify the prospect theory considering time discount impact in the value function while it is applied to the proposed P2P trading model. The results show that the proposed method can increase the satisfaction of end-users with a minor negative impact on expected profit. Moreover, the important role of the mental time discount effect on the P2P energy trading problem is verified by the obtained results.