Peer-to-Peer Electricity Trading in Microgrids with Renewable Sources and Uncertainty Modeling Using IGDT

Microgrids are known as the main components of energy networks because they can accommodate a large share of renewable energy sources. Peer-to-peer energy trading is one of the most effective ways to implement decentralized patterns in the electricity market. In peer-to-peer trades, each actor negotiates directly with a set of partners without any intermediaries. Peer-to-peer energy exchange methods allow direct energy exchange between producers and consumers. This study tested the peer-to-peer trading method on networks consisting of 4 microgrids. Existing microgrids have different generating sources, such as solar energy, wind turbines, and microturbines, each of which is modeled separately. Moreover, in order to reduce the uncertainty in the production of renewable sources, a battery storage system has been used in this network. Also, to encourage microgrids to use renewable resources, cut-off costs have been considered by these resources. This research uses the constrained optimization method and GAMS software with a Baron solver to optimize the problem. In the end, the uncertainty of producing renewable resources for different modes is examined using the information gap decision theory method. The available results show the power distribution between microgrids and other network components based on the objective function and existing constraints.