引进可再生能源后电力系统的备用容量采购
——基于输电线路拥堵的技术与制度议题

As renewable energy penetration increases, the risk is expected to increase that reserves procured at the day-ahead stage may not be fully available when needed because of transmission congestion. Changes in renewable energy output forecasts after operational plans are established can affect transmission flows through reserve activation, with impacts depending on the location and direction of forecast errors and generator operating conditions. This paper examines how renewable energy forecast errors cause transmission congestion and introduces methods for identifying congestion-causing scenarios and evaluating overload probabilities using Monte Carlo simulation and optimal power flow calculations. Numerical simulations using a standard power system model show that congestion risk varies with renewable energy forecasts and generator operating conditions and can be reduced by procuring reserves at appropriate locations. The paper also discusses the institutional frameworks, data infrastructure, and computational methods needed to incorporate these findings into reserve procurement and revisions to generator commitment schedules.