Two-Stage Chance-Constrained Stochastic Thermal Unit Commitment for Optimal Provision of Virtual Inertia in Wind-Storage Systems

The frequency security problem becomes a critical concern in power systems when the system inertia is lowered due to the high penetration of renewable energy sources (RESs). A wind-storage system (WSS) controlled by power electronics can provide the virtual inertia to guarantee the fast frequency response after a disturbance. However, the provision of virtual inertia might be affected by the variability of wind power generation. To address this concern, we propose a two-stage chance-constrained stochastic optimization (TSCCSO) model to find the optimal thermal unit commitment (i.e., economic operation) and the optimal placement of virtual inertia (i.e., frequency stability) in a power grid using representative power system operation scenarios. An enhanced bilinear Benders decomposition method is employed with strong valid cuts to effectively solve the proposed optimization model. Numerical results on a practical power system show the effectiveness of the proposed model and solution method.

Automated summary

This paper proposes a two-stage chance-constrained stochastic optimization (TSCCSO) model to find the optimal thermal unit commitment and the optimal placement of virtual inertia in a power grid, addressing the frequency security problem in power systems with high penetration of RESs. The model utilizes representative power system operation scenarios and an enhanced bilinear Benders decomposition method to effectively solve the optimization problem, with numerical results demonstrating the effectiveness of the proposed approach in a practical power system.