Risk-Embedded Security Pricing Mechanism for Transmission Grid Congestion Mitigation

With the accelerated development of new power systems, the large-scale integration of high-penetration flexible loads, such as electric vehicles (EVs), under locational marginal pricing (LMP) frameworks has intensified grid security risks. Existing deterministic pricing models fail to quantify the impact of transmission capacity insufficiency during extreme events on electricity prices and lack risk early-warning capabilities. This paper proposes a risk-coupled security pricing mechanism by establishing a DC optimal power flow (DCOPF) model incorporating transmission congestion risks. The model optimizes generator outputs to minimize total system generation costs, determines nodal security prices using Lagrange multipliers and power transfer distribution factors (PTDFs), and innovatively introduces a risk early-warning component that integrates line failure probability and incident severity. Case studies demonstrate that security pricing mechanism effectively guides load distribution through price signals, achieves efficient congestion management, and ensures safe and stable grid operation.