A CVaR-Based Peer-to-Peer Energy Trading Model for Local Energy Communities with Electric Vehicles and Hydrogen Systems

Peer-to-peer (P2P) energy trading is a way for Local Energy Communities (LECs) to use more regional energy sources instead of relying on the grid. By allowing prosumers to trade surplus green electricity, this method saves costs and supports decarbonization. But there are concerns about renewable energy fluctuations affecting system reliability and costs. This research tackles these through uncertainty modeling, P2P trading, and Conditional Value at Risk (CVaR) risk management. We explored four scenarios: no variability; only P 2 P trading without uncertainties; uncertainty causing a 0.2% rise in grid use; P 2 P reducing grid load by 7.5% and emissions by 13.8%, and CVaR further cutting grid dependence by 1.4% and emissions by 3%. Results indicate P2P trading plus CVaRbased management optimizes energy allocation, minimizes dependence on the grid, and ensures robust systems, thus being sustainable and cost-effective for LECs.