Dynamic performance and sensitivity of grid-connected hydropower station under uncertain disturbance Article Swipe
Y Liu
,
Wencheng Guo
,
Runxi Cao
,
Z Chen
,
Linling Wang
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1088/1755-1315/1079/1/012113
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1088/1755-1315/1079/1/012113
The grid-connected operating condition of hydropower station is a common operation mode to provide electric energy for the load side. This paper investigates the dynamic performance and sensitivity of grid-connected hydropower station (GCHS) under uncertain disturbance. Firstly, the nonlinear uncertain model of GCHS under uncertain disturbance is established. Then, the dynamic performance of GCHS is studied when the governor parameters change under certain step disturbance, periodic disturbance and uncertain random disturbance, respectively. Finally, based on the sensitivity index of the uncertain output obtained from the extended Fourier amplitude sensitivity test method, the sensitivity of the uncertain random disturbance at different input positions is studied. The results indicate that the GCHS under periodic disturbances or random disturbances have more complex dynamic performance than that under certain step disturbance. Under periodic disturbance, the forced oscillations and high frequency resonances are generated in dynamic response of GCHS. Under the uncertain random disturbance, the system of GCHS always presents random oscillation. The state variables q H , z, qP , y , x s , x t , and δ of GCHS are the most sensitive to uncertain disturbances, which are introduced at the generator or surge tank. The uncertain disturbances have significant interaction on the dynamic response of GCHS.
Related Topics
Concepts
Disturbance (geology)
Control theory (sociology)
Sensitivity (control systems)
Oscillation (cell signaling)
Nonlinear system
Disturbance voltage
Hydropower
Grid
Computer science
Mathematics
Engineering
AC power
Control (management)
Physics
Voltage
Geology
Paleontology
Biology
Voltage optimisation
Genetics
Electronic engineering
Geometry
Quantum mechanics
Electrical engineering
Artificial intelligence
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1088/1755-1315/1079/1/012113
- https://iopscience.iop.org/article/10.1088/1755-1315/1079/1/012113/pdf
- OA Status
- diamond
- References
- 7
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4306252954
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4306252954Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1088/1755-1315/1079/1/012113Digital Object Identifier
- Title
-
Dynamic performance and sensitivity of grid-connected hydropower station under uncertain disturbanceWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-09-01Full publication date if available
- Authors
-
Y Liu, Wencheng Guo, Runxi Cao, Z Chen, Linling WangList of authors in order
- Landing page
-
https://doi.org/10.1088/1755-1315/1079/1/012113Publisher landing page
- PDF URL
-
https://iopscience.iop.org/article/10.1088/1755-1315/1079/1/012113/pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
-
https://iopscience.iop.org/article/10.1088/1755-1315/1079/1/012113/pdfDirect OA link when available
- Concepts
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Disturbance (geology), Control theory (sociology), Sensitivity (control systems), Oscillation (cell signaling), Nonlinear system, Disturbance voltage, Hydropower, Grid, Computer science, Mathematics, Engineering, AC power, Control (management), Physics, Voltage, Geology, Paleontology, Biology, Voltage optimisation, Genetics, Electronic engineering, Geometry, Quantum mechanics, Electrical engineering, Artificial intelligenceTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
-
7Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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