1.State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources (North China Electric Power University), Beijing 102206, China;2.Chengxi Power Supply Branch of State Grid Tianjin Electric Power Company, Tianjin 300110, China

In the “Three North” regions of China, wind resources are abundant but system flexibility resources are scarce. During the heating period, the proportion of electric output of thermoelectric unit is high, occupying the space for wind power integration and posing severe challenges to the safe and economic operation of the system. To improve the economy of wind power accommodation, a collaborative robust planning method for electric and thermal flexibility resources considering reserve optimization is proposed. First, the peak shaving operation mechanism of promoting thermoelectric decoupling and its collaborative planning mechanism through various resources has been studied. On this basis, a min-max-min three-layer two-stage light robust planning model is established. The main problem aims to minimize the sum of the planned annual incremental investment cost, operation cost, and risk cost of insufficient reserve, optimizes all kinds of resource investment schemes and day-ahead deterministic optimal scheduling. Taking into account the uncertainty of wind power based on day-ahead scheduling results,the sub-problem minimizes the risk of insufficient reserve in the worst scenario, reschedule the equipment within days, searches for the worst scenario, and assesses the risk of insufficient reserve. The main problem and sub-problems are solved iteratively based on the column-and-constraint generation algorithm and the strong duality theory. Finally, the validity of the model is verified by a numerical example, and the robustness and risk of the model are analyzed.