TY  - EJOU
AU  - Zhu, Taotao 
AU  - Pang, Pai 
AU  - Wang, Yang 

TI  - Collaborative Optimization Strategy for Virtual Inertia Spatiotemporal Distribution Replenishment under Extreme Weather Events
T2  - Energy Engineering

PY  - 2026
VL  - 123
IS  - 5
SN  - 1546-0118

AB  - Frequent extreme weather events and the increasing popularity of renewable energy have exacerbated the frequency spatiotemporal imbalance in the new power system. To address these issues, this paper proposes a collaborative optimization strategy for virtual inertia spatiotemporal distribution replenishment, aiming to enhance nodal frequency stability through targeted virtual inertia allocation. This strategy integrates the nodal inertia characteristics with frequency response dynamics to establish a spatiotemporal quantitative model for evaluating the equivalent inertia distribution across nodes, thereby overcoming the limitations of conventional global inertia assessments. Furthermore, by implementing differentiated virtual inertia supplementation from renewable energy power plants and pre-deploying Modular Mobile Energy Storage Systems (MMESS), this collaborative optimization strategy achieves an average 11.4% reduction in the maximum nodal Rate-of-Change-of-Frequency (RoCoF) and a 4.9% decrease in total operating cost. Overall, the proposed strategy effectively mitigates the spatiotemporal frequency imbalance induced by multi-line faults at varying time intervals under extreme weather events, outperforming conventional inertia replenishment approaches. Finally, simulation results based on an improved IEEE 39-bus system demonstrate that the proposed optimization framework significantly enhances nodal frequency stability while minimizing associated costs.
KW  - Extreme weather events; virtual inertia spatiotemporal distribution; frequency spatial characteristics; nodal equivalent inertia; modular mobile energy storage systems

DO  - 10.32604/ee.2025.073516