Towards the detailed modeling of deregulated electricity markets comprising Smart prosumers and peer to peer energy trading

Smart Grid concept has promoted the use of distributed generation in an era of continuously increasing renewable energy generation. Peer-to-Peer electricity trading is a means for smart grid to achieve it. Consumption-side is able to directly trade electricity and enhance power system flexibility. However, the sto-chastic behavior of prosumers and renewable generation introduces great complexity that needs to be addressed through careful modeling. This paper proposes a hierarchical electricity trading scheme that models residential, commercial and industrial prosumers, energy storage, renewable energy sources, and centralized generation in a fully transactive smart environment. To model the above, a hierarchical MAS of three auctioning layers is developed. A novel modeling of residential activity and optimal constrained end-user energy scheduling are developed. Moreover, a parallel peer-to-peer electricity market that uses the Discriminatory k-DA matching mechanism and enhanced price calculation through fuzzy logic is developed. A novel case study of a hybrid Day-Ahead market is presented, using the proposed trading scheme that yields less expensive electrical power system operation. The proposed detailed model incorporates multiple end-user types and multi-layer scalable energy systems and sets the foundation for holistic energy market modeling.