Virtual Inertia Optimization Configuration for Virtual Power Plants Based on Node RoCoF Constraints

As the penetration of renewable energy in power systems continues to increase, the reduction of traditional rotational inertia poses significant challenges to frequency stability. This paper proposes a virtual inertia optimization method for Virtual Power Plants, based on node Rate of Change of Frequency constraints to contribute to the frequency stability of the power system. A bi-level optimization model is developed, considering the frequency dynamic response of both generator and load nodes. The upper-level problem aims at minimizing the VPP operator's cost while the lower-level problem aims at maximizing DERs profit under given price conditions The proposed method is validated through case studies on the IEEE 9-bus 3-generator system and solved by combined Particle Swarm Optimization and Gurobi solver. Results demonstrate that the method effectively enhances frequency support capability and achieves coordinated optimization of economic efficiency and system stability. This research provides theoretical insights and practical guidance for inertia allocation in highrenewable penetration power systems.