电压降
自动频率控制
控制理论(社会学)
电力系统
计算机科学
电力系统仿真
数学优化
控制(管理)
功率(物理)
工程类
数学
电压
电信
物理
量子力学
人工智能
电气工程
分压器
作者
Likai Liu,Zechun Hu,Yilin Wen,Yuxin Ma
出处
期刊:IEEE Transactions on Power Systems
[Institute of Electrical and Electronics Engineers]
日期:2024-01-01
卷期号:39 (1): 2080-2092
被引量:4
标识
DOI:10.1109/tpwrs.2023.3252502
摘要
The high penetration of converter-based renewable energy sources has brought challenges to the power system frequency control. It is essential to consider the frequency security constraints and frequency control reserve requirements in unit commitment (UC). First, a novel extreme learning machine-based method is proposed to approximate the highly nonlinear frequency nadir constraint (FNC) by a set of linear constraints. Second, considering the variation of the frequency insecurity risk under the changing operational condition, we propose to optimize the primary frequency control (PFC) droop gains and reserve capacities in the UC model to provide diverse control efforts in different risk levels adaptively. Third, a secondary frequency control (SFC) reserve capacity quantification method is proposed by combining the Copula theory and distributionally robust optimization technique. The UC simulation is conducted on the IEEE 118-bus system to test the proposed optimal PFC droop gain strategy and SFC reserve capacity quantification method. Simulation results show that the proposed optimal PFC droop gain strategy is better than the traditional fixed PFC droop gain setting on economic efficiency and operational flexibility. Besides, the SFC reserve capacity calculated by the proposed method is more appropriate than the actual SFC reserve capacity in the historical operation.
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