Open Access

ARTICLE

Collaborative Optimization Strategy for Virtual Inertia Spatiotemporal Distribution Replenishment under Extreme Weather Events

Taotao Zhu, Pai Pang, Yang Wang^*

School of Electrical and Information Engineering, Jiangsu University, Zhenjiang, 212013, China

* Corresponding Author: Yang Wang. Email:

Energy Engineering 2026, 123(5), 14 https://doi.org/10.32604/ee.2025.073516

Received 19 September 2025; Accepted 10 November 2025; Issue published 27 April 2026

Abstract

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.

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Keywords

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