Keywords
frequency; nodal inertia; inertia estimation; maximum likelihood identification
Abstract
In recent years, with the large-scale integration of power electronic interfaced power sources such as wind power and photovoltaics into the power grid, the overall inertia level of the power grid has decreased, and the nodal inertia has shown spatial distribution differences, significantly increasing the risk of system frequency instability. It is urgent to quickly evaluate the distribution of inertia in the power grid so that dispatch and operation personnel can timely formulate effective inertia control measures. Therefore, a method for estimating the power grid nodal inertia based on maximum likelihood identification is proposed. Firstly, by using frequency and active power measurement data, the autoregressive moving average model with exogenous inputs (ARMAX) for inertia estimation is constructed. Secondly, the unknown parameters in the ARMAX model are identified via the maximum likelihood identification method. Additionally, the transfer function of active power and frequency of the node and counter are employed to determine the estimated inertia and the required minimal measurement data length. Finally, the simulation test is conducted based on the improved CEPRI-36 node system to verify the effectiveness of the proposed method.
DOI
10.19781/j.issn.1673-9140.2025.02.003
First Page
21
Last Page
29
Recommended Citation
JIANG, Xinfan; LIU, Yonggang; SUN, Mingrui; WU, Jinbo; WANG, Jingwen; and WEN, Yunfeng
(2025)
"Method for power grid nodal inertia estimation based on maximum likelihood identification,"
Journal of Electric Power Science and Technology: Vol. 40:
Iss.
2, Article 3.
DOI: 10.19781/j.issn.1673-9140.2025.02.003
Available at:
https://jepst.researchcommons.org/journal/vol40/iss2/3