Aggregation frequency response modeling with applications to East China power grid

Zhimeng Zhu; Siyuan Wu; Chuan Qin

doi:10.1117/12.2674947

2 May 2023 Aggregation frequency response modeling with applications to East China power grid

Zhimeng Zhu, Siyuan Wu, Chuan Qin

Proceedings Volume 12642, Second International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2023); 1264202 (2023) https://doi.org/10.1117/12.2674947
Event: Second International Conference on Electronic Information Engineering, Big Data and Computer Technology (EIBDCT 2023), 2023, Xishuangbanna, China

Abstract

In the receiving-end power grid, the proportion of external power supplies and large-scale renewable power generations has increased rapidly, which not only increases the unbalanced power impact of the system, but also weakens the frequency support capability of the system. Therefore, frequency security becomes a bottleneck of the receiving-end power grid, and system frequency response modeling becomes a key concern. In this paper, an aggregation modeling method is presented to build the system frequency response model (SFR). Two types of the SFR model structures are proposed. The first one considers the dynamics of the governors and prime movers of both the thermal and hydro units, which is suitable for the simulation and analysis of the system frequency behaviour following small power disturbances. The second one additionally considers the boiler dynamics of the thermal units, which is suitable for the simulation following large power disturbances. The parameter aggregation method for the SFR model are also proposed. The aggregation SFR model is built based on the detailed model of the east China power grid. The results show that the proposed method can achieve satisfactory performance owing to its accuracy and efficiency.

Citation Download Citation

Zhimeng Zhu, Siyuan Wu, and Chuan Qin "Aggregation frequency response modeling with applications to East China power grid", Proc. SPIE 12642, Second International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2023), 1264202 (2 May 2023); https://doi.org/10.1117/12.2674947

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