Event-Triggered Data-Driven Load Frequency Control for Multiarea Power Systems

Bu, Xuhui; Yu, Wei; Cui, Lin; Hou, Zhongsheng; Chen, Zongyao

doi:10.1109/tii.2021.3130415

Cited by 48 publications

(22 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…With the rapid development of information technology in recent years [58][59][60][61][62][63], deep reinforcement learning is more and more used in prediction, identification and parameter optimization [64][65][66][67][68][69][70]. Combining the control methods based on mathematical model with the methods of artificial intelligence [71][72][73][74][75][76][77][78] to achieve better system performance is the next work to be carried out.…”

Section: Discussionmentioning

confidence: 99%

Output feedback based poles configuration for LDP systems with varying state and input dimensions

Gao

Han²,

Zhao

et al. 2022

IET Control Theory & Appl

View full text Add to dashboard Cite

The problem of pole configuration via periodic output feedback for linear discrete periodic systems with time-varying dimensions of states and input spaces is addressed. By some mathematical derivation, the considered problem can be reduced into solving a special Sylvester matrix equation from which the periodic output feedback gains can be separated and computed explicitly. Based on this, a detail parametric algorithm is presented, by which countless periodic output feedback gains can be generated by choosing different free parameter matrices. Furthermore, the proposed approach is used to achieve robustness performance and robust poles configuration algorithm is provided. Numerical examples are employed to illustrate the effectiveness of the proposed algorithms.

show abstract

Section: Discussionmentioning

confidence: 99%

Output feedback based poles configuration for LDP systems with varying state and input dimensions

Gao

Han²,

Zhao

et al. 2022

IET Control Theory & Appl

View full text Add to dashboard Cite

show abstract

“…This permits a two-way flow of real power between STAT-COM shunt output terminals and SSSC series output terminals. A series connected converter injects a voltage with convenient phase and phase angle [34]. A converter connected in parallel provides reactive power separately to the system.…”

Section: Modeling Of Unified Power Flow Controllermentioning

confidence: 99%

Two-area power system stability analysis by frequency controller with UPFC synchronization and energy storage systems by optimization approach

Kumaran

Rajesh

Kumaravel³

et al. 2023

IRASE

View full text Add to dashboard Cite

An optimization approach for two-area power system with Unified Power Flow Controller (UPFC) is proposed in this paper. The proposed method is the Atomic Orbital Search (AOS) approach. The proposed approach is applied to achieve full utilization of UPFC and keeps the parameters uncertain. The multivariable PI controller is utilized to control the system controller and eliminates the negative interaction of the controllers. The proposed approach combines the two subsystems by converting algebraic subsystem using differential approximation, which leads to a nonlinear system. The proposed approach provides efficient voltage regulation and quicker damping of inter-area mode oscillations. The proposed UPFC controller eliminates generator oscillation and fault condition, which guarantee the stability of the system as well as provides dynamic power flow control under the tie-line. At last, the proposed method is simulated on MATLAB platform and compared with existing methods. From this comparison, it is shown that the proposed approach provides less oscillation than the existing approach.

show abstract

“…Reference 6 investigates an integral sliding mode based MFAC approach to achieve a prescribed performance. References 7‐9 propose several event‐triggered MFAC methods to save control resources. A current sensorless control algorithm is developed by using MFAC 10 for a wound rotor synchronous machine.…”

Section: Introductionmentioning

confidence: 99%

Data‐driven set‐point tuning of model‐free adaptive control

Lin

Chi

Liu

et al. 2023

Intl J Robust & Nonlinear

Self Cite

View full text Add to dashboard Cite

Model-free adaptive control (MFAC) is an effective data-driven control method to deal with nonlinear and nonaffine systems. In this article, a data-driven set-point tuning (DDST) approach is proposed for MFAC to enhance its control performance. The proposed data-driven set-point tuning based MFAC (DDST-MFAC) system consists of two control loops. The inner control loop takes the MFAC as the feedback controller where a virtual reference error signal is adopted in the control input. The DDST in the outer loop is derived from an ideal nonlinear set-point tuning (NST) law, which exists in theory, to meet the control target. To realize the theoretically existing NST, a dynamic linearization (DL) technique is introduced. Virtually, the ideal NST law is independent of any controlled system, regardless linear or nonlinear, having an exact model or not. Since the nonlinear system considered in this work does not have any model information available to the designers, the parameter estimation law of the DDST is designed by using the DL method to transfer the original nonlinear system into a linear data model (LDM) with a projection algorithm to estimate the unknown parameters in the LDM. The convergence of tracking error is proved for a regulation scenario. Simulation study is provided to verify the theoretical results.

show abstract

Event-Triggered Data-Driven Load Frequency Control for Multiarea Power Systems

Cited by 48 publications

References 31 publications

Output feedback based poles configuration for LDP systems with varying state and input dimensions

Output feedback based poles configuration for LDP systems with varying state and input dimensions

Two-area power system stability analysis by frequency controller with UPFC synchronization and energy storage systems by optimization approach

Data‐driven set‐point tuning of model‐free adaptive control

Contact Info

Product

Resources

About