SCADA simulation
1. Introduction
The requests of simulation model of hydraulic power plants (HPP) are, to assure large transient stability program simulation, isolated system operation, system restoration after brake up, load rejection, load acceptance, water hammer dynamics and optimal speed control. In this paper linear models are used for simulation of hydraulic plants for which Robust control law was designed. Comparison with non-linear models are made which are required where speed and power changes are large, such as in islanding, load rejection and system restoration studies although there are great diffi culties designing good governor of hydraulic turbines, because the hydraulic turbine is highly non-linear device which characteristics vary signifi cantly with the unpredictable load on the unit. Such nonlinearities make the governor design a nontrivial task because governors designed for one operating condition may not work at all under other conditions.
Because of that robust control law is designed, allowing the system hydraulic turbine-governor to work satisfactory at all working conditions, not only around working point. The signifi cance of robust control design is to show how to overcome some of limitations of conventional governor design methods.
In the end, a SCADA program for simulation of proposed control is created. This program is create using NI Lookout and simulates the work of a real plant and gives visualisation of the step response. The acquisition
of data is not provided from a real system but from virtual graphical objects and expressions which are developed from previously made simulations in Matlab.
2. Design of optimal robust control law
To design an optimal governor which is capable of providing stability and performance for the turbine operating under a wide range of load conditions, robust control
methodology should be utilized.
By robustness it is presumed the ability of the governor to provide satisfactory stability and optimal performance to the hydro turbine over a wide range of operating conditions. The optimality refers to minimisation of properly designed cost function in the control system.
In the process of design most important is to model nonlinear behaviour of the turbine and use that model for robust control design. The design approach has following steps:
Abstract
There are great diffi culties designing good governor of hydraulic
turbines, because the hydraulic turbine is highly non-linear device which characteristics vary signifi cantly with the unpredictable load on the unit. In this paper linear models are used for simulation of hydraulic plants for which Robust control law was designed, allowing the system hydraulic turbine-governor to work satisfactory at all working conditions, not only around working point. Comparisons with non-linear models are also made. In the end, a SCADA program for simulation of proposed control is created. This program is create using NI Lookout and simulates the work of a real plant and gives visualization of the step response.
Key words: Hydraulic turbine, Monitoring, Plant Control, Robust Control, simulation.
Projektiranje Robustnog upravljanja hidro turbine i SCADA simulacija Hidro Elektricne Centrale
Kada se dizajnira upravljanje hidroturbina, javljaju se velike poteskoce zbog toga sto hidroturbina je nelinearna postrojka i njene karakteristike variraju u velikoj meri sa nepredvidivim opterecenjem mreze. U ovom clanku prezentovani su linearni modeli za simuliranje hidropostojke i procedura projektiranja robustnog upravljanja, koje omogucava zadovoljavajuce ponasanje hidropostrojke u svim radnim uslovima, ne samo u izabranoj radnoj tacki. Uporedna analiza sa nelinearnim modelima je uradjena. Na kraju kreirana je SCADA aplikacija za simuliranje predlozenog upravljanja.
Izvedena je pomocu NI Lookout aplikacije i simulira rad realne hidropostojke i vizuelizira nekoliko vaznih parametara.
Ključne reci: Hidroturbina, Monitoring, Upravljanje, Hidropostrojka, Robusno upravljanje.
modelling the turbine nonlinearities using uncertainty model principle, synthesis of optimal robust control by taking into account uncertainties, perform model reduction of the resulting controller for easy
implementation and verifying design by time-domain simulations. The power of the turbine is a function of the wicket gate opening
c
, water head h and rotation speed of the turbine ω. Also the water fl owq
is a function of the wicket gate openingc
, water head h and rotation speed of the turbine ω, which is shown in equation 1 [6]:(1)
for given operating condition equation 1 can be linearized as partial derivatives which depends from the operating conditions of the turbine, and from the load of the unit.
Their values are obtained from model acceptance measurements for some representative operating conditions of the system. To investigate how extensive model varies with the system operating conditions, Bode plots of the entire system are shown in fi gure 2, for three representative conditions, and for linear model from equation 1.
From fi gure 2 easily can be noticed that the frequency responses of the four transfer functions are very similar even though their parametric models are different.
These similarities in frequency domain suggest that can be selected single transfer function as the nominal transfer function of the system, and represent other transfer functions as variations around this nominal transfer function as model uncertainties. The advantage of this approach is that the optimal robust controller can be easily designed for
the entire system operating range.
The relative modelling errors among the transfer functions are:
(2) The nominal transfer function should be the one that gives the overall smallest modelling error, which is the linear transfer function. The uncertainty bound can be represented as unstructured multiplicative uncertainty:
(3) The system model with the
uncertainty bound is:
(4) The relative modelling errors using nominal transfer function are shown in fi gure 3
The robust control system strategy is to design controller based on the nominal system transfer function with the defi ned maximum uncertainty bound, so that the desired performance is achieved for all system models. This controller can be designed using mixed sensitivity optimisation techniques.
For robust stability analysis, the controller should be chosen such that the following inequality is satisfi ed:
(5) which is known as the Small Gain Theorem [6].
In robust controller design, the design specifi cations are usually converted to appropriate weighting functions. These weighting functions are then combined with the closed loop system transfer function. Three weighting functions have been used in the design process. The robust controller design can be formulated as the following minimisation problem, also known as the Mixed Sensitivity Optimal H∞ design:
(6) In the process of design of the controller equation 8 means to fi nd a stable controller so that the Fig. 1 - Block diagram of hydro prime mover and control
Fig. 2 - Bode plots of transfer functions
maximum value of three weighted functions is minimised, and the equation 3 is satisfi ed. The key problem in any Mixed Sensitivity
H∞ design is how to choose appropriate weighting functions, such that the closed loop system
meets the design specifi cations.
One of the unique features in the optimisation given in equation 4 is that the resulting cost function always turns out to be fl at over the frequency band of interest
The solution to the optimisation problem in equation 6 can be
For model reduction it is used Shur BST-REM model reduction, which provide analytic bound on the worst approximation error in terms of twice the sum of the singular values of the eliminated dynamics. The reduced order controller is:
(8) The frequency response of full order and reduced order controller is compared in fi gure 4.
3. Scada application for simulation made in lookout
The SCADA application for control of the hydropower plant is made in Lookout and has form of enclosed logical parts of the process displayed on individual control panels used for supervisory control, so that the operator can see the whole part of the process. There are around 10 control panels presenting the main processes in HPP: The main control panel, control panels of separate units, the hydraulic aggregate control panel and etc. Control structure of the SCADA application is in pyramidal form. On the top there is so called Main Panel, which conveys the basic information to the operator in normal operation conditions. From this panel the operator can go further to the panels which represent particular power units. Main structure of SCADA application is shown in Fig.
9 [2]
3.1 Connecting of control objects with expressions and developing output signals One has to have in mind that this SCADA application for simulation does not have contact with real system (Fig. 5). All parts of real system which is here represented are presented with virtual objects.
Objects between themselves are connected with expressions but everything functions according to real algorithms. Objects that produce control (output) signals can be: potentiometers, switches, push buttons. Those signals represent inputs in expressions which produce visual output in different forms:
numerical (with numbers), logical (with graphical objects) or textual (textual message). In this way we make programming [5].
Fig. 3 - Uncertainty bound
(7) obtained by solving two algebraic Riccati equations, using MATLAB.
The order of the resulting controller is equal to that of the system and three weighting functions, in this case of eight order (4+2+1+1=8), given in equation 7
Fig. 4 - Comparison of full and reduced order controllers
The controller is obviously too complicated for a reliable implementation in practice. Because of that must be obtained reduced order model, which involves
approximation of a high order system by a low one, and because of that the resulting controller is sub-optimal.
3.2. Main panel
The main panel of the SCADA application represents the top of the SCADA application and it is a starting panel for particular
panels representing particular power units and their respective processes.
The main panel is shown in Fig. 6.
With the help of pushbutton objects on the left side we can select a particular unit, and go further into the controlled process to see details of the selected unit. In this panel are shown also basic values which are important for the running the particular unit and the operator can control the power by increasing or decreasing its value, or can stop any of the power units.
From the main panel, SCADA application branches out to fi ve fundamental branches of the process shown in the Fig. 9.
3.3. Control structure of units The whole software is made in Macedonian language and Cyrillic letters.
Particular parts of the process are represented with graphical objects in order to help the operator in everyday use of the SCADA application. Objects with their animations and changes of the graphical states show operating states of some important parts of that unit. If there is need to go further in the process than that can be done with pressing the buttons which activate particular panels, and the operator can see controls of that particular level. From here he can turn on or off the unit or change the way of how it works, from automatic to manual.
Every operator has his user name and password with which it is set
the number of control actions he can make. In this way it is possible to improve security and to defi ne who has responsibility to switch off/on some particular parts. In Fig. 7 we can see control structure of the unit.
3.4. Hydraulic aggregate of the turbine controller
When we choose the button Turbine Controller from the control panel of the unit we can enter the control panel of the turbine controller and monitor and control its work (Fig.
8). For example when we begin the process of starting the unit we can clearly see which elements are under pressure, which valves are open/close, if they are open/close on time, if they follow the defi ned order … in other words we can see if the controller function according to the defi ned operating algorithms.
Controls can be made with pushing control buttons, for example from this panel we can close the turbine valve and immediately stop the work of the plant. The change of the status of particular elements is notice with colors: for turning on the solenoid of the proportional valves, for turning on some switch, for pipe and elements under pressure – they are marked with red color, and opposite for turned off they are marked with green color, or with blue color for the pipes which are not under pressure. With arrows are marked moving directions for the servomotors. To make the work of the operator as simple and easy as possible, for particular elements and positions which are most important, in addition to the colors and arrows the program gives announcements to the operator in textual form and sometimes suggests decisions for the problems. For example, there are announcements for the position of the turbine valve: Closed TV- when the valve is closed, Opening of TV- when the turbine valve is in phase of opening, Open TV- when the turbine valve is open. If some of these phases are not completed in an adequate time period, the operator will be alarmed.
4. Conclusion
The advantages of nonlinear mathematical model versus linear mathematical model become apparent when both models are subjected to large excursions in turbine loading, but nonlinear model although good, not always satisfi es all demands for specifi c Fig. 5 - Input and output signals in a SCADA program for
simulation
Fig. 6 - Main panel of the SCADA application for simulation
Fig. 7 - Control panel of the unit 1
turbine. A governor control system for a hydraulic turbine generating unit has been designed using optimal robust control techniques.
The signifi cance of the work is to show in a systematic manner how robust control theory can be used to overcome some of limitations of the conventional governor design methods. On the basis of dates from MATLAB simulations SCADA application have been made which incorporates dependence expressions of step responses of the unit with proposed robust control law. SCADA
application simulates the work of the hydropower plant. This
program also gives opportunity to see the operation of a real plant because it incorporates real algorithms: start up and shut down algorithms.
[3] E. De Jaeger, et a.l: Hydro turbine model for system dynamic studies, IEEE
Transactions on Power Systems, Vol.9, No 4, pp. 1709-1715, 1994.
[4] O.H. Souza Jr. et al.: Study of hydraulic transients in hydropower plants through simulation of nonlinear model of penstock and hydraulic turbine model, IEEE Transactions on Power Systems, Vol.14, No 4, pp 1269-1273, 1999
[5] National Instruments: Lookout developer’s manual, 2001 [6] J. Jiang: Design of an Optimal
Robust Governor for Hydraulic Fig. 8 - Control panel of the turbine controller hydraulic
aggregate
Fig. 9 - Control structure of the SCADA application for unit 1
5. References
[1] IEEE working group report:
Hydraulic turbine and turbine control models for system dynamic studies, IEEE
Transactions on Power Systems, Vol.7, No. 1, pp. 167-179, 1992.
[2] L. N. Hannett et al: Field tests to validate Hydro turbine-governor model structure and parameters, IEEE Transactions on Power Systems, Vol.9, No 4, pp. 1744-1750, 1994.
Turbine Generating Units, IEEE Transactions on Energy Conversion, Vol.10, No 1, pp.
188-194, 1995.
[7] Bruno Strah i Ognjen Kuljacha:
Nova turbinska regulacija na HE Miljacka, Brodarski institute, Zagreb
V.prof.dr Valentino Stojkovski, Prof.dr Zvonimir Kostić, Prof.dr Aleksandar Nošpal
Univerzitet Sv. Kiril i Metodij, Masinski fakultet, Skopje, R.Makedonija UDC: 621.221.011.004