P2P Energy Transaction Platform to Minimize Uncertainty of Behind-the-Meter Distributed Generations and Energy Cost of Participants

As decarbonization policies emerge around the world, research on cost-effective renewable energy is increasingly emphasized, but the uncertainty inherent in renewable energy disrupts the operation of power systems. Considering these issues, this paper presents a peer-to-peer (P2P) transaction platform that minimizes the cost of each transaction participant while considering photovoltaic (PV) generation uncertainty using stochastic programming. First, in the proposed algorithm, P2P energy transactions are conducted between prosumers who own PV and consumers. Then, prosumers purchase uncertainty demand response (UDR) capacity from consumers to counter the uncertainty of their PV. The performance of the proposed platform is verified through a case study using MATLAB 2021b Academic, Optimization Tool toolbox, and Matpower toolbox to demonstrate the economic feasibility by comparing the operating costs of participants and the power flow of Point of common coupling (PCC) with and without UDR transaction. The case studies show that the prosumers reduce the cost damage caused by the PV generation forecast error through the day-ahead UDR transaction, and the consumers reduce operating cost by bidding additional capacity in the UDR transaction that was not matched in the P2P transaction. In addition, the result of the power flow analysis indicates that the subject grid operates closer to day-ahead scheduling when the UDR transactions and implementations are performed.