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Programmed trajectory motion control for synchronous generators
- Source :
- International Journal of Electrical Power & Energy Systems. 119:105884
- Publication Year :
- 2020
- Publisher :
- Elsevier BV, 2020.
-
Abstract
- The paper presents the concept of adaptive control in electrical power systems, based on programmed trajectory motion of synchronous generators. The feasibility of the method is tested in a range of simulation experiments. The key feature of the technique is the use of a simple reference model which defines the dynamics of the controlled parameters. As a result, the voltage vector angle, velocity and acceleration are delivered to the exact, rather than approximate, target values in a predictable, coordinated, robust and efficient manner. Compared to other adaptive methods, such as model predictive control, the technique makes a more efficient use of computational resources, which makes it particularly beneficial if implemented at lower levels of control system hierarchy. It also shows a promising level of robustness against disturbances during the control process. We envisage that the most relevant practical applications are the stabilization and synchronization of small to medium size synchronous machines connected to distribution grid, and management (corrective control and resynchronization) of islanded sub-systems, such as microgrids. Simulations also indicate relatively short control time and improved stability against perturbations. With a proper choice of reference model, the need for bi-polar control action does not arise and the target values are achieved by uni-polar action only. Both the stabilization and the synchronization tasks are accomplished by means of one control algorithm, which improves the quality of control, especially in post-emergency operating conditions. The time-domain modeling results reported in the paper were obtained from software-based simulators.
- Subjects :
- Adaptive control
business.industry
Computer science
020209 energy
020208 electrical & electronic engineering
Energy Engineering and Power Technology
02 engineering and technology
Motion control
Electric power system
Model predictive control
Control theory
Robustness (computer science)
Distributed generation
Control system
0202 electrical engineering, electronic engineering, information engineering
Electrical and Electronic Engineering
business
Reference model
Subjects
Details
- ISSN :
- 01420615
- Volume :
- 119
- Database :
- OpenAIRE
- Journal :
- International Journal of Electrical Power & Energy Systems
- Accession number :
- edsair.doi...........0bf724d277a4378763933b8b82bd75c8