Paper Info
Title
Impact of signal transmission delays on power system damping control using heuristic dynamic programming
Abstract
In this paper, the impact of signal transmission delays on static VAR compensator (SVC) based power system damping control using reinforcement learning is investigated. The SVC is used to damp low-frequency oscillation between interconnected power systems under fault conditions, where measured signals from remote areas are first collected and then transmitted to the controller as the inputs. Inevitable signal transmission delays are introduced into such design that will degrade the dynamic performance of SVC and in the worst case, cause system instability. The adopted reinforcement learning algorithm, called goal representation heuristic dynamic programming (GrHDP), is employed to design the SVC controller. Impact of signal transmission delays on the adopted controller is investigated with fully transient model based time-domain simulation in Matlab/Simulink environment. The simulation results on a four-machine two-area benchmark system with SVC demonstrate the effectiveness of the adopted algorithm on damping control and the impact of signal transmission delays.
Year
DOI
Venue
2014
10.1109/CIASG.2014.7011567
CIASG
Keywords
Field
DocType
signal transmission delays,power system damping control,svc controller,learning (artificial intelligence),static var compensators,heuristic programming,low-frequency oscillation,power system interconnection,matlab environment,power transmission control,simulink environment,time-domain simulation,goal representation heuristic dynamic programming,dynamic programming,reinforcement learning algorithm,damping,static var compensator,benchmark testing,control systems
Transmission (telecommunications),Control theory,MATLAB,Control theory,Electric power system,Static VAR compensator,Engineering,Control system,Benchmark (computing),Reinforcement learning
Conference
Citations 
PageRank 
References 
1
0.36
11
Authors
5
Name
Order
Citations
PageRank
Yufei Tang120322.83
Xiangnan Zhong234616.35
Zhen Ni352533.47
Jun Yan417913.72
Haibo He53653213.96