Optimizing Fairness in Peer-to-Peer Energy Systems for Effective Duck Curve Management

The integration of renewable energy sources, particularly solar, has introduced challenges such as the duck curve phenomenon in energy grids, characterized by midday surplus and evening peaks in demand. This paper proposes an optimization model for peer-to-peer (P2P) energy trading systems aimed at mitigating the duck curve while ensuring fair energy distribution among participants. The model formulates an objective function that minimizes deviations from a target load profile, emphasizing both load flattening and equitable energy sharing. Constraints include energy balance equations, storage limits, and trading bounds, ensuring operational feasibility. MATLAB simulations demonstrate the effectiveness of the proposed approach in achieving significant reductions in peak loads and promoting fairness in energy transactions. By optimizing energy trades based on participant preferences and system-wide objectives, the proposed approach seeks to enhance grid stability and efficiency in decentralized energy markets.