TY - JOUR
T1 - Online Realization of an Ambient Signal-Based Load Modeling Algorithm and Its Application in Field Measurement Data
AU - Wang, Ying
AU - Lu, Chao
AU - Wu, Peixuan
AU - Zhang, Xinran
AU - Su, Yinsheng
AU - Xiong, Chunhui
AU - Zhao, Biao
N1 - Publisher Copyright:
© 1982-2012 IEEE.
PY - 2022/7/1
Y1 - 2022/7/1
N2 - With the development of synchrophasor measurement techniques, ambient signal-based load modeling is recently proposed to track the time-varying characteristics of power loads. On this basis, the hardware realization of this approach, which includes the local load modeling devices and the data center, is proposed and tested with the field measurement data from China Southern Power Grid. In this way, practical load model parameters can be identified from field measurement data both online and offline by the hardware system. To begin with, the hardware system, which is the first realization of an ambient signal-based load modeling algorithm, offers sufficient field measurements for load modeling. Then, the identification results of the field measurements verify the effectiveness of the ambient signal-based load modeling algorithm. Besides, the identified load model parameters for different substations during different times demonstrate the time-varying and the distributed characteristics of power loads.
AB - With the development of synchrophasor measurement techniques, ambient signal-based load modeling is recently proposed to track the time-varying characteristics of power loads. On this basis, the hardware realization of this approach, which includes the local load modeling devices and the data center, is proposed and tested with the field measurement data from China Southern Power Grid. In this way, practical load model parameters can be identified from field measurement data both online and offline by the hardware system. To begin with, the hardware system, which is the first realization of an ambient signal-based load modeling algorithm, offers sufficient field measurements for load modeling. Then, the identification results of the field measurements verify the effectiveness of the ambient signal-based load modeling algorithm. Besides, the identified load model parameters for different substations during different times demonstrate the time-varying and the distributed characteristics of power loads.
KW - Ambient signal
KW - field measurement data
KW - hardware realization
KW - load modeling
UR - https://www.scopus.com/pages/publications/85124803352
U2 - 10.1109/TIE.2021.3102428
DO - 10.1109/TIE.2021.3102428
M3 - 文章
AN - SCOPUS:85124803352
SN - 0278-0046
VL - 69
SP - 7451
EP - 7460
JO - IEEE Transactions on Industrial Electronics
JF - IEEE Transactions on Industrial Electronics
IS - 7
ER -