.png){kind=icon}
Return
Low-Complexity Distributed Predictive Automatic Generation Control With Guaranteed Properties
.png){kind=icon}
OA
AI
DOI：10.1109/TSG.2017.2705524.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
An automatic generation control scheme for multi-area power systems is presented, based on the technique of distributed model predictive control (MPC). Local area controllers solve nested MPC problems in order to regulate states to steady values, and reject the disturbances induced by tie-line interactions. The approach achieves guaranteed constraint satisfaction, recursive feasibility of the MPC problems and stability, while maintaining on-line complexity similar to conventional MPC. A rigorous off-line design methodology is given for selecting controller parameters, and is demonstrated on an example 4-area system.
Keywords:
Load frequency control
automatic generation control
model predictive control
distributed control
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
9.8
Papers:
5.7K
Citations:
4.3W
Organization
Cited Papers
Robust model predictive control of constrained linear systems with bounded disturbances.png)
AUTOMATICAOAAI
AUTOMATICAIF5.9
OAAIShareSaveImproved Accuracy of Tissue Glucose Measurement Using Low Magnification Optical Coherence Tomography
OAAI
OAAIShareSaveShareSaveShareSaveShareSaveDistributed predictive control: A non-cooperative algorithm with neighbor-to-neighbor communication for linear systemsAUTOMATICA
AUTOMATICAIF5.9
PREAI
ShareSaveShareSaveOptimized robust control invariance for linear discrete-time systems: Theoretical foundationsAUTOMATICA
AUTOMATICAIF5.9
PREAI
ShareSave
View more