TY - JOUR
T1 - A Data-Driven Method for Online Gain Scheduling of Distributed Secondary Controller in Time-Delayed Microgrids
AU - Xia, Yang
AU - Xu, Yan
AU - Wang, Yu
AU - Yao, Weitao
AU - Mondal, Suman
AU - Dasgupta, Souvik
AU - Gupta, Amit K.
AU - Gupta, Gaurav M.
N1 - Publisher Copyright:
© 1969-2012 IEEE.
PY - 2024/5/1
Y1 - 2024/5/1
N2 - Secondary control of a microgrid is to restore the frequency/voltage and share power among different units. However, due to time-delay issues in secondary control loops, system instability may happen. To solve this problem, a data-driven approach is proposed for scheduling the control gains to ensure the stability of the microgrid. By utilizing real-time measured current as input, the proposed method can appropriately adjust the control gain setting for the distributed secondary control to achieve a stable operation even under various time-delay scenarios. First, a time-delayed small-signal model is developed for microgrid stability analysis. Based on the damping ratio calculated from the small-signal model, a constrained soft actor-critic (SAC) algorithm is designed to learn an optimal policy of gain scheduling, which can improve the safety and efficiency of learning. Finally, case studies are carried out to validate that the proposed method can provide an optimal gain scheduling policy, which enhances the stability of microgrids during real-time operation.
AB - Secondary control of a microgrid is to restore the frequency/voltage and share power among different units. However, due to time-delay issues in secondary control loops, system instability may happen. To solve this problem, a data-driven approach is proposed for scheduling the control gains to ensure the stability of the microgrid. By utilizing real-time measured current as input, the proposed method can appropriately adjust the control gain setting for the distributed secondary control to achieve a stable operation even under various time-delay scenarios. First, a time-delayed small-signal model is developed for microgrid stability analysis. Based on the damping ratio calculated from the small-signal model, a constrained soft actor-critic (SAC) algorithm is designed to learn an optimal policy of gain scheduling, which can improve the safety and efficiency of learning. Finally, case studies are carried out to validate that the proposed method can provide an optimal gain scheduling policy, which enhances the stability of microgrids during real-time operation.
KW - Microgrid secondary control
KW - constrained soft actor-critic
KW - data-driven gain scheduling
KW - time-delayed small-signal model
UR - http://www.scopus.com/inward/record.url?scp=85174846993&partnerID=8YFLogxK
U2 - 10.1109/TPWRS.2023.3323790
DO - 10.1109/TPWRS.2023.3323790
M3 - Article
AN - SCOPUS:85174846993
SN - 0885-8950
VL - 39
SP - 5036
EP - 5049
JO - IEEE Transactions on Power Systems
JF - IEEE Transactions on Power Systems
IS - 3
ER -