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Keywords

new energy; interval optimization; inertia assessment; inertia prediction; interval number

Abstract

The large-scale grid connection of new energy leads to the continuous compression of the start-up capacity of synchronous power sources, and the system faces the risk of low-inertia operation. Existing deterministic inertia trend assessment methods ignore the time-varying impact of random new energy fluctuations on unit commitment, which may lead to the misjudgment of inertia adequacy. In this regard, an analysis method for power system inertia intervals is proposed to realize a panoramic portrayal of inertia boundaries by coupling the uncertainty of new energy output. First, a confidence interval is constructed based on probability modeling of wind and solar power prediction errors. Then, an operational constraint system involving unit start-stop, new energy fluctuation, virtual inertia, and power flow security is established. An interval possibility transformation is adopted to convert the uncertain optimization problem into a deterministic inertia extreme value search model, and a multi-time-scale rotational kinetic energy optimization framework is constructed. After the trigger, the quantitative assessment of the trends of system inertia intervals and the risk early warning for the inertia situation are realized. Finally, a simulation analysis and validation are conducted taking a provincial power grid with a high proportion of new energy in China as an example. The results show that the proposed method well quantifies the inertia intervals under the fluctuation of new energy output, providing a decision-making basis for early warnings during periods of weak inertia.

DOI

10.19781/j.issn.1673-9140.2026.02.015

First Page

167

Last Page

177

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