A New Risk-Based Decentralized Model for Peer-to-Peer Energy Trading Among Smart Homes

Smart homes could have a significant impact on supplying the demand of both household consumers and the smart grid. Household consumers can trade energy via peer-to-peer (P2P) energy trading to reduce their costs. In other words, each of them can participate in the smart grid as a prosumer that can both produce and consume energy. On the other hand, more participation of smart homes in the demand-side management (DSM) program could help electricity decentralization. Also, energy storage systems (ESSs) and distributed energy resources (DERs) can lead to further decentralization of a smart microgrid. The production of renewable energy resources, such as photovoltaic (PV) systems, is associated with uncertainty. ESSs could be used as a reserve for PV systems. This paper presents a new risk-based model for P2P energy management of smart homes that consists of a PV system and EES and participates in the DSM program. The risk associated with the uncertainties of PVs’ production and market prices has been modeled by conditional value-at-risk (CVaR). The mixed integer non-linear programming (MINLP) model of the problem has been solved by COUENNE in GAMS software. Numerical results show that the expected cost of all resources and the related risk is reduced by the proposed decision-making model for smart homes.