Mechanistic model for Francis turbines in OpenModelica

Vytvytskyi, Liubomyr; Lie, Bernt

doi:10.1016/j.ifacol.2018.03.018

Cited by 11 publications

(14 citation statements)

References 2 publications

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“…Our work on modelling the waterway and the Francis turbine for high head hydropower systems using the multiphysics tool OpenModelica [20], has been reported in [21][22][23]. Unit models have been developed for our in-house open-source Modelica [24] library-OpenHPL (Open Hydro Power Library is developed by the first author within his PhD study).…”

Section: Previous Workmentioning

confidence: 99%

“…Particular emphasis is put into describing the model geometry of the turbine outlet. Moreover, the turbine design algorithm developed in [23] is improved in this study with an analytical expression for the turbine loss coefficients. Both of these contributions try to answer the particular research question: "how suitable is OpenHPL for describing a real hydropower plant with minimal prior information, and how can model parameters be tuned to fit experimental data?…”

Section: Overview Of Papermentioning

confidence: 99%

“…Based on Equations (1) and (2), the simple turbine model is implemented in OpenHPL as the Turbine element. Our library also includes a mechanistic Francis turbine model that has been presented and described in detail in [23]. In [23], the mechanistic Francis turbine model is provided together with a design algorithm for all the needed turbine geometry parameters that are used in this model.…”

Section: Turbine Unitmentioning

confidence: 99%

“…Our library also includes a mechanistic Francis turbine model that has been presented and described in detail in [23]. In [23], the mechanistic Francis turbine model is provided together with a design algorithm for all the needed turbine geometry parameters that are used in this model. Input data for the design algorithm are the turbine nominal operational values that can be found in Table 2 of this study.…”

Section: Turbine Unitmentioning

confidence: 99%

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OpenHPL for Modelling the Trollheim Hydropower Plant

Vytvytskyi

Lie

2019

Energies

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An increase of tightly integrated, renewable energy sources with highly varying production leads to a greater need for flexible hydropower plants to “balance” the intermittent production from these sources. From a systems perspective, the intermittency aspect constitutes a disturbance, while the tight integration leads to a multivariable systems, both of which causes increased challenges for good control. This instigates the need for a model based analysis and synthesis tool which can describe dynamic phenomena, supports multiphysics problems, and allows for immediate use in advanced control analysis and design. Previously, an open source Hydro Power Library (OpenHPL) have been developed within the multiphysics Modelica eco-system which satisfies the above requirements: OpenHPL contains a set of model units relevant for hydropower systems, as well as examples of tools for analysis of these models for control purposes. Thus far, OpenHPL has been validated by comparison against other simulation tools. However, a real test of OpenHPL is to use it to describe a real hydropower plant using minimal plant information, to tune model parameters against experimental data, and to validate the model. As a case study, experimental data from the Trollheim hydropower plant in Norway have been made available, and used to test OpenHPL. By flow sheeting a hydropower model in OpenModelica using OpenHPL, the model can be simulated from within a script language (Python via the OMPython API, Julia via the OMJulia API) and further analyzed using analysis tools in the script language. Based on default model parameter suggestions from OpenHPL, least squares model fitting was carried out in Python, and the model was validated with good model fit. Important parts of the modelling phase were the development of a new friction model for the Francis turbine, and iterations on the description of the turbine outlet geometry. The results are complemented with a discussion of possible uses of the model.

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Section: Previous Workmentioning

confidence: 99%

Section: Overview Of Papermentioning

confidence: 99%

Section: Turbine Unitmentioning

confidence: 99%

Section: Turbine Unitmentioning

confidence: 99%

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OpenHPL for Modelling the Trollheim Hydropower Plant

Vytvytskyi

Lie

2019

Energies

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“…Thus, one of the most important challenges currently is enhancing the impact of renewable energy in existing power systems. Up to now, hydropower power generation is still the most effective large-scale method of electricity production [1][2][3][4][5][6]. The energy flows are centralized and can easily be controlled, and in addition, the kinetic energy of the conversion process can be directly converted into electrical energy without heat loss or any chemical processes.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Backstepping Nonsingular Fast Terminal Sliding Mode Control for Hydro-Turbine Governor Design

Lin

Bălaş

et al. 2019

Energies

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To investigate a typical large-scale nonlinear hydropower system (HS) with a stochastic water flow, a novel nonlinear adaptive control scheme, which is created by the combination of a backstepping strategy, nonsingular fast terminal sliding mode surface and command filter, is proposed for the hydro-turbine governor design of a HS to not only improve the transient stability of the HS but also increase the energy conversion efficiency and improve the reliability and availability of the electricity supply. In contrast to previous research based on ideal hydro-turbine models with accurate parameters, an adaptive backstepping nonsingular fast terminal sliding mode control (ABNFTSMC) with command filtered (CF) is proposed in which virtual control inputs and error compensations are applied to overcome distribution characteristics resulting from energy losses, while guaranteeing finite-time convergence. In addition, to avoid the requirement of analytic differentiation in Lyapunov stability, a command filter method is used to generate certain compensating signals and their derivatives. In this paper, the Nazi Gorge hydropower station in China is used as our verification model of a hydropower plant with monitored data, where energy losses and random water flow disturbances are considered. Simulation results illustrate that the proposed control strategy for a hydro-turbine governor can significantly increase the stability, reliability, and system performance of a HS even in the presence of uncertainties.

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