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Abstract
The nature of the processes taking place in a nuclear power plant (NPP) steam turbine is the reason why their modeling is very difficult, especially when the model is intended to be used for on-line optimal model based process control over a wide range of operating conditions, caused by changing electrical power demand e.g. when combined heat and power mode of work is utilized. The paper presents three nonlinear models of NPP steam turbine, which are: the static model, and two dynamic versions, detailed and simplified. As the input variables, the models use the valve opening degree and the steam flow properties: mass flow rate, pressure and temperature. The models enable to get access to many internal variables describing process within the turbine. They can be treated as the output or state variables. In order to verify and validate the models, data from the WWER-440/213 reactor and the 4 CK 465 turbine were utilized as the benchmark. The performed simulations have shown good accordance of the static and dynamic models with the benchmark data in steady state conditions. The dynamic models also demonstrated good behavior in transient conditions. The models were analyzed in terms of computational load and accuracy over a wide range of varying inputs and for different numerical calculation parameters, especially time step values. It was found that the detailed dynamic model, due to its complexity and the resultant long calculation time, is not applicable in advanced control methods, e.g. model predictive control. However, the introduced simplifications significantly decreased the computational load, which enables to use the simplified model for on-line control.
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Details
- Category:
- Articles
- Type:
- artykuł w czasopiśmie wyróżnionym w JCR
- Published in:
-
APPLIED MATHEMATICAL MODELLING
no. 48,
pages 491 - 515,
ISSN: 0307-904X - Language:
- English
- Publication year:
- 2017
- Bibliographic description:
- Kulkowski K., Grochowski M., Duzinkiewicz K., Kobylarz A.: Nuclear Power Plant Steam Turbine - Modeling for Model Based Control Purposes// APPLIED MATHEMATICAL MODELLING. -Vol. 48, (2017), s.491-515
- DOI:
- Digital Object Identifier (open in new tab) 10.1016/j.apm.2017.04.008
- Verified by:
- Gdańsk University of Technology
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