Reserve Scheduling in the Congested Transmission Network Considering Wind Energy Forecast Errors

An increasing penetration of renewable energy has brought unprecedented uncertainty to today's grid, and properly scheduled reserve is a key to accommodate the intermittency and volatility of renewable energy. Although renewable energy forecast has been a popular area, there is limited study on forecast errors, and there lacks a study on how error distributions from different forecast models influence the scheduling of reserves, especially in congested networks. This study aims to propose a stochastic reserve optimization model that ensures the delivery of reserve in case of transmission congestion and ramping constraints and study the impact of wind forecast errors on reserve scheduling. The model was implemented on a modified RTS-96 test system and results show that the errors from different forecast models significantly influence the amount of scheduled reserves in a stochastic reserve optimization problem.