Grid-Forming Inverter Enabled Virtual Power Plants With Inertia Support Capability

Modern energy systems are experiencing the transition towards renewable-powered ones. Some conventional thermal units based on synchronous machines are gradually decommissioned and replaced by power electronics interfaced renewables. Thus, the lack of natural inertia and governor damping, which are the features of synchronous machines, raises significant concern about system frequency stability, including the faster rate of change and lower nadir point of frequency. Meanwhile, with the rapid development of communication and Internet of Things technologies, distributed energy resources can be aggregated as a virtual power plant to help balance real-time electricity demand and supply. However, the capability of utilizing the whole virtual power plant to provide adjustable inertia support has not been explored yet. In this paper, we propose a framework of the synchronous virtual power plant based on grid-forming inverter interfaced distributed energy resources. By coordinating the parameter settings of grid-forming inverters, the virtual power plant provides inertia support. Also, we design an online learning-based parameter settings method that makes the inertia of the virtual power plant adjustable. A case study in IEEE 34 nodes system illustrates the effectiveness of the proposed method.

Automated summary

Modern energy systems are transitioning to renewable-powered ones, replacing conventional thermal units with power electronics interfaced renewables. This transition raises concerns about system frequency stability due to the lack of natural inertia and governor damping. Additionally, the aggregation of distributed energy resources as a virtual power plant has the potential to balance real-time electricity demand and supply. However, utilizing the virtual power plant for adjustable inertia support has not been explored. This paper proposes a framework for a synchronous virtual power plant based on grid-forming inverter interfaced distributed energy resources, demonstrating its effectiveness through a case study in the IEEE 34 nodes system.