A Shadow Price-Guided Computational Framework for Congestion-Aware Transmission Expansion Planning

Transmission expansion planning (TEP) for renewable-rich power systems requires a computational workflow that links investment decisions with chronological operations and nodal economic signals. This study presents a shadow price-guided framework integrating hourly DC optimal power flow, multi-hour candidate screening, mixed-integer TEP, SCUC–SCED evaluation, and leave-one-line-out line value evaluation. Renewable curtailment is represented explicitly at renewable generators and is separated from involuntary load shedding. The SP-WCI candidate score aggregates 24 hourly flow–price difference products using congestion surplus weights. On a 101-bus reduced system, the automatically selected eight-line plan lowers average LMP from 597.33 to 259.98 CNY/MWh (56.5%), load shedding from 21,159.0 to 0.0 MWh (100.0%), and unused renewable/hydro availability from 117,882.9 to 50,398.7 MWh (57.2%). Comparison with weighted overload and rule-based screening uses the same candidate budget, while the random benchmark is summarized over ten independent seeds. Sensitivity tests show how the fixed plan responds to alternative load-shedding penalties. The complete screening–optimization–verification chain is additionally executed natively on the full-order 796-bus system, confirming that the framework scales to full network data while delineating the limits of the reduced surrogate. The results are interpreted as evidence from a stressed representative day case rather than as a general estimate of commercial project returns.