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Co-Design of Distributed Model-Based Control and Event-Triggering Scheme for Load Frequency Regulation in Smart Grids
- Source :
- IEEE Transactions on Systems, Man, and Cybernetics: Systems. 50:3311-3319
- Publication Year :
- 2020
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2020.
-
Abstract
- In this paper, one new distributed load frequency regulation approach is proposed for smart power system operation under two specific practical constraints, including the limited communication resource and speed droop parametric uncertainty. To address these two constraints, the co-design of event-triggering communication scheme and distributed model-based controller is studied. Instead of using zero-order holders, the proposed model-based scheme is able to extend the maximum allowable time interval and thus reduce communication bandwidth usage. In the meantime, the proposed co-design scheme is able to get the model-based control parameters and event-triggering condition metrics simultaneously. This can loosen the conservation in the choice of control gains and event-triggering parameters faced by existing approaches where the control gains are fixed in prior. Comparisons on the multiple-area system confirm that this designed load frequency regulation method significantly reduces the number of required data transmissions without sacrificing the dynamic performance of the frequency and tie-line power. It is also shown that the proposed approach has great robustness to speed droop coefficient uncertainty.
- Subjects :
- 0209 industrial biotechnology
Computer science
Distributed element model
020208 electrical & electronic engineering
Automatic frequency control
02 engineering and technology
Computer Science Applications
Power (physics)
Human-Computer Interaction
020901 industrial engineering & automation
Smart grid
Control and Systems Engineering
Robustness (computer science)
Control theory
Frequency regulation
0202 electrical engineering, electronic engineering, information engineering
Voltage droop
Electrical and Electronic Engineering
Software
Parametric statistics
Subjects
Details
- ISSN :
- 21682232 and 21682216
- Volume :
- 50
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Systems, Man, and Cybernetics: Systems
- Accession number :
- edsair.doi...........0282ec1ae9c2a9a3b76583c4835933bf