- Email: [email protected]
Simulation Support for Operator Control of the Wastewater Treatment Plant
Copyright © IFAC Computer Applications in Biotechnology. Garmisch-Panenkirchcn. Germany. 1995
SIMULATION SUPPORT FOR OPERATOR CONTROL OF THE W ASTEWATER TREATMENT PLANT
Mieczyslaw Metzger
Institute ofAutomatic Control Department ofAutomatic Control, Electronics and Computer Science Technical University of Silesia ul. Akademicka 16, PL 44100 Gliwice, Poland
Abstract: A problem of simulation support for operating control in the case of a sudden augmentation of cyanide concentration in the inlet flow of a big industrial wastewater treatment process is presented in the paper. An enhanced simulation support for operating process control that consists of two simulators is proposed in the paper. An application of the process simulator connected with the plant control system to continuously actualize process data is designed for an on-line operation aid. A stand-alone operator training simulator can be very helpful for additional off-line operator training on the base of process data stored for chosen past and anticipated process situations. Both simulators have been realized in practice as the LabWindows/CVI-based applications in the Windows environment. Keywords: Computer-aided supervisory control ; waste treatment; operating control; simulators; real-time simulation;
INTRODUCTION Over the last two decades a growing need has appeared for accurate real-time simulators of industrial processes. These simulators may be typically used for operator training and recently as an on-line operation aid, often connected with the actual process control system to continuously actualize process data. Both can be considered as an enhanced simulation support for operating control of a process. This kind of support may be very useful for operator control of processes in the case when a strong emergency can occur.
Several papers deal "ith the theoretical background for training simulators. System concepts for training systems development are discussed by Hays (1992). the problem of similarity for transfer of operator training is presented by Schumacher and Gentner (1988), while distributed acress control schemes for making the simulation experiments easier are presented by Metzger (1994a). Nowadays. the computational power required for real-time simulation and graphic visualization (necessary for training simulators) is available using even the standard PC/486 (see e.g. Ramesh and Sylla, 1990; Pimenta and Azevado, 1993 ; Metzger. 1992. 1994b).
The classical simulator applications are flight simulators and military training devices (see e.g. Rarnesh and Sylla, 1990; Krishnakumar et al., 1991; Cheok and Huang, 1992). An application of the industrial process simulation to better operating of processes was presented by Naess et al. (1993), while an experimental tool for the investigations of opc;rator control behavior of slow responding d)narnic water-alcohol distillation process was discussed by lelsma and Bijlstra (1990).
One of the most important dangers for wastewater treatment process is a possibility of a sudden toxic substance appearance (for example cyanide) in the inlet flow. The biological activated sludge process is the most important part of the installation for the industrial wastewater treatment process. When the toxic substance reaches the biological part of installation, the activated biomass may be destroyed. In a big wastewater treatment plant the biological part is situated behind some other mechanical and
269
chemical pans of the plant. so the contaminated wastewater appears with some delay and the process operator has some time-interval for appropriate decision making. There are five big retention basins in the considered installation. The contaminated \\astewater may be stored in a retention basin, it may be diluted by non poisonous water stored in another basin, or may be by-passed. The appropriate decision must be made by the process operator. An application of the process connected simulator as an on-line operation aid for an appropriate decision choice has been presented by Metzger (1994d). In the fast-mode (with scaled time) the simulator can be used many times to check the implications of the operating changes before the emergency in the realworld plant will occur. The emergency importance causes that the on-line operating aid may be insufficient for the operator control. Hence, the simulation support will be enhanced with an operator training simulator.
CONSIDERED PROCESS AND MATIIEMATICAL MODEL Figure 1 shows the industrial \\astewater treatment process that is considered in this work. It is one of the parts of a big cokery at Silesia. The plant includes conventional primary and secondary treatment processes. The primar), treatment "1 " includes mechanical treatment, primary clarification, chemical treatment and flotation. The primarily cleared \\astewater is pumped through the 400 m long pipeline system (1 or 2 parallel pipelines) to the secondary treatment process. At its input there are an equalization basin "2" and rapid mixer "3" with additional inlet flow of the municipal \\astewater. The most important parts of secondary treatment process are conventional biological activated sludge process "4" and multifunction chemical reactors "5" .
Five retention basins "a" - "e" have been very useful for reliable operating control. During periods of heavy rainfall, the clear water is stored in a basin for possible future dilution of the strongly contaminated \\astewater, and vice versa the strongly contaminated \\astewater may be stored in a basin for future treatment or may be by passed through a basin as well. One of the most important dangers for the considered process is a possibility of a sudden augmentation of cyanide concentration ciII in the inlet flow. In the normal working point of the 3 = 400 m3 I h, CUI = 40 g 1m ) the process concentration of the cyanide before the biological 3 part of the plant is about c. =37 g I m and after secondary treatment this value decreases to 3 3 eR = 6 glm • The value of c~ = 50 g 1m can be accepted in the normal working point of the process, while the value of = 80 g I 3 should be treated as a critical value for the biological part of the process. The bigger values may destroy the active biomass in the biological part of the plant. To counteract this emergency the appropriate control decision must be made by the process operator. The simulation of the process may be very useful for computer aided support.
(V;
c:
m
The mathematical model for simulation of this very complicated process must consider only this mathematical description that is essential for simulation purpose. Hence, in this case only the cyanide concentration transport through installation is considered and finally the particular process units are considered as well stirred lumped parameter systems (ordinary state differential equations). Including the discretized advective equation as the mathematical description of the time-delay (Metzger, 1994c) introduced by the pipeline, the whole mathematical model of the process consists of 29 stiff nonlinear state differential equations. Nevertheless, the computing time of its numerical solution on the standard PC-486 is very short.
ON-LINE AND STAND-ALONE SIMULATORS
a)
b)
c)
cl)
e)
v~ ~----~~------Jl-L-----~~----~-L--I~
Fig. 1. Considered industrial \\astewater treatment process
270
Design of process simulators deals strictly with problems of the real-time simulation. The two most important features of the real-time simulation experiments (in relation to the conventional simulation experiments in the batch mode) are as follows. a) the simulation results are strictly connected with the real-time synchronization (for scaled real-time as well), but they should be independent of the time used for calculations, b) in any communication point (in which the inputoutput communication with the operator takes place) the operator can change the operating actions during simulation investigations.
As mentioned in the introduction, the enhanced simulation support for operating supervisory control of the considered wastewater treatment process should consist of two simulators. The process connected simulator for an on-line operator decision aid is presented in the Fig. 2. The process is controlled by the supervisory control and data acquisition (SCADA) system. The operator exerts his control actions from the SCADA operating console. Some chosen data necessary to initiate simulation running are continuously collected from the SCADA system. Hence, the operator in any time (especially when some process emergency occurs) can check his control actions on the base of the actual process situation. For several most important emergency situations (e.g. for changes of the cyanide concentration in the inlet flow) the operator should be prepared by the training on the stand-alone training simulator (Fig. 3). This simulator is based on the same mathematical model of the process as the process connected simulator, but initial conditions are taken from the data stored for chosen past and anticipated process situations (e.g. for several different fills of retention basins). Programming a real-time training simulator is difficult because (apart from classical process simulation) the real-time realization should be taken into consideration. This includes real-time synchronization of numerical calculations and especially continuous
Real-wor1d process
I. ,I I~==MathematIca=oI=the=~=1 =modeI===~ I
0aIII 8IOted for 8I1tiapeted aItuMow 01 the ~
I
R.l-tlme SImulatIOn and visualization
Fig. 3. Stand-alone operator training simulator. detection of events (operator actions). The new LabWindows/CVI (LW/CV!) instrumentation and visualization programming tool from National Instruments is also very useful for designing of realtime simulators. This tool links the power of full ANSI-C language with graphical flexibility in the Microsoft Windows em;ronment. The LW /CVI offers a large amount of ready-te-use functions of controls (as knobs. slides and switches) as well as graphs. charts and indicators for building a real-time interactive operator interface. The numerical calculations for simulation of the process (29 stiff nonlinear state equations) have been programmed in C which IS incorporated in the LW ICVI . The simulation program is controlled by the operator graphical interface - the same for both simulators (see Fig2 and Fig.3) . The main program COnsists 10 the process loop in which the LW /CVI orgaruzes the real-time processing (that is. the realtime synchronization. the continuous detection of events. the simulation calculations. and the visualization)
Conltnu"",.ty actualized proceu data Mathemaltcal model 01 the process
Real-time SImulation
Fig. 4 shows chosen (verified experimentally) simulation results . The response of the cyanide concentration c. after step increasing of the inlet cyanide concentration c'" =40+80 1(/) g/ml is presented in the Fig. 4a. This result shows that after 8 hours the biomass may be destroyed (without any operator reaction). The results of the appropriate operator control are shown in the Fig. 4b. This flow control consists of the step increasing of the rate to the empty basin "c", and of the step increasing of the V~ flow rate from the basin "b" with previously stored clear water. During the interval of 24 h the biomass is out of danger now.
V;
Fig. 2. Process connected simulator
271
training simulator can be very useful for teaching students in the operator control and decision making.
c,.[gIm'j 111
80
Acknowledgment: This work was supported by the Committee of Scientific Research (KEN).
a)
50 37
REFERENCES 0
20
c,. (gIm')
51
I (h)
b)
37
10 2 1.711
20
I)
HIm) t--p~-----.,
•
20
I (h)
20
I (h)
I
Fig. 4. Simulation responses after step increase of the inlet cyanide concentration, a) without any operator action, b) with appropriate operator control
CONCLUDING REMARKS
A problem of simulation support for operating control in the case of a sudden augmentation of cyanide concentration in the inlet flow of a big industrial wastewater treatment process has been presented in the paper. An enhanced simulation support for operating process control that consists of two simulators has been proposed in the paper. An application of the process simulator connected with the plant control system to continuously actualize process data is designed for the on-line operation aid. The stand-alone operator training simulator can be very helpful for additional off-line operator training on the base of process data stored for chosen past and anticipated process situations. Both si~ulators have been realized in practice as the in the LabWindows/CVI-based applications Windows environment. Besides, the operator
272
Cheok. K.C. and N. Huang (1992). Real-time simulation and animation for dynamic control systems. Simulation. 59, No 4, pp. 246-252. Hays, T. (1992). Systems concepts for training systems development. Trans. IEEE on Syst. Man and Cybernetics. 22, No 2. pp. 258-266. Jelsma, O. and lP. Bijlstra (1990). Process: Program for research on operator control in an experimental simulated setting. Trans. IEEE on Syst. Man and Cybernetics. 20, pp.1221-1228. Krishnalrumar, K.S., D. Sawal, lE. Bailey and JA Dohme (1991). A simulator-based automated helicopter hover trainer-synthesis and verification. Trans.lEEE/SMC 21. pp. 961-969. Metzger, M. (1992). Real-time simulation of the biological activated sludge process. In: Computer Simulation in Biology. Ecology and MediCine 1992, (Ed. M. Kotva). pp. 92-96. Simulation Council, Inc., San Diego. Metzger, M. (1994a). A new concept of industrial process simulation - cybernetic approach using distributed access control schemes. Systems Ana(vsis. Model.. Simulation. 15, pp. 185-202. Metzger, M. (1 994b). Fast-mode real-time simulation of a biological process. In: Modelling and Simulation ESM94 (Ed. A Guash and RM.Huber), pp. 753-755. Simulation Councils. Inc., San Diego. Metzger, M. (l994c). Modelling and simulation of time-de)ay element via advective equation. In: Modelling and Simulation ESM94 (Ed. A Guash and RM.Huber), pp. 756-759. Simulation Councils. Inc .. San Diego. Metzger, M. (1994d). Fast-mode real-time simulator for the wastewater treatment process. Water Science Technology, 30, No. 4, pp. 191-197. Naess, L., A Mjaavatten, and lO. Li (1993). Using dynamic process simulation from conception to nonnal operation of process plants. Computers chem. Engng. 17, No 516, pp. 585-600. Pimento, P.C.C., and S. Feyo de Az.evado (1993). Real-time dynamic simulation of non-linear MIMO systems. Computers chem. Engng. 17 (supplement). pp. S343-S348. Ramesh, R and C. Sylla (1990). A framework for the optimal design of instructor/operator stations in flight simulators. Trans. IEEE on Syst. Man and Cybernetics. 20, pp. 571-581. Schumacher, RM. and D. Gentner (1988). Transfer of training as analogical mapping. Trans. IEEE on Syst. Man and Cybernetics. 18, pp. 592-600.
SIMULATION SUPPORT FOR OPERATOR CONTROL OF THE W ASTEWATER TREATMENT PLANT
Mieczyslaw Metzger
Institute ofAutomatic Control Department ofAutomatic Control, Electronics and Computer Science Technical University of Silesia ul. Akademicka 16, PL 44100 Gliwice, Poland
Abstract: A problem of simulation support for operating control in the case of a sudden augmentation of cyanide concentration in the inlet flow of a big industrial wastewater treatment process is presented in the paper. An enhanced simulation support for operating process control that consists of two simulators is proposed in the paper. An application of the process simulator connected with the plant control system to continuously actualize process data is designed for an on-line operation aid. A stand-alone operator training simulator can be very helpful for additional off-line operator training on the base of process data stored for chosen past and anticipated process situations. Both simulators have been realized in practice as the LabWindows/CVI-based applications in the Windows environment. Keywords: Computer-aided supervisory control ; waste treatment; operating control; simulators; real-time simulation;
INTRODUCTION Over the last two decades a growing need has appeared for accurate real-time simulators of industrial processes. These simulators may be typically used for operator training and recently as an on-line operation aid, often connected with the actual process control system to continuously actualize process data. Both can be considered as an enhanced simulation support for operating control of a process. This kind of support may be very useful for operator control of processes in the case when a strong emergency can occur.
Several papers deal "ith the theoretical background for training simulators. System concepts for training systems development are discussed by Hays (1992). the problem of similarity for transfer of operator training is presented by Schumacher and Gentner (1988), while distributed acress control schemes for making the simulation experiments easier are presented by Metzger (1994a). Nowadays. the computational power required for real-time simulation and graphic visualization (necessary for training simulators) is available using even the standard PC/486 (see e.g. Ramesh and Sylla, 1990; Pimenta and Azevado, 1993 ; Metzger. 1992. 1994b).
The classical simulator applications are flight simulators and military training devices (see e.g. Rarnesh and Sylla, 1990; Krishnakumar et al., 1991; Cheok and Huang, 1992). An application of the industrial process simulation to better operating of processes was presented by Naess et al. (1993), while an experimental tool for the investigations of opc;rator control behavior of slow responding d)narnic water-alcohol distillation process was discussed by lelsma and Bijlstra (1990).
One of the most important dangers for wastewater treatment process is a possibility of a sudden toxic substance appearance (for example cyanide) in the inlet flow. The biological activated sludge process is the most important part of the installation for the industrial wastewater treatment process. When the toxic substance reaches the biological part of installation, the activated biomass may be destroyed. In a big wastewater treatment plant the biological part is situated behind some other mechanical and
269
chemical pans of the plant. so the contaminated wastewater appears with some delay and the process operator has some time-interval for appropriate decision making. There are five big retention basins in the considered installation. The contaminated \\astewater may be stored in a retention basin, it may be diluted by non poisonous water stored in another basin, or may be by-passed. The appropriate decision must be made by the process operator. An application of the process connected simulator as an on-line operation aid for an appropriate decision choice has been presented by Metzger (1994d). In the fast-mode (with scaled time) the simulator can be used many times to check the implications of the operating changes before the emergency in the realworld plant will occur. The emergency importance causes that the on-line operating aid may be insufficient for the operator control. Hence, the simulation support will be enhanced with an operator training simulator.
CONSIDERED PROCESS AND MATIIEMATICAL MODEL Figure 1 shows the industrial \\astewater treatment process that is considered in this work. It is one of the parts of a big cokery at Silesia. The plant includes conventional primary and secondary treatment processes. The primar), treatment "1 " includes mechanical treatment, primary clarification, chemical treatment and flotation. The primarily cleared \\astewater is pumped through the 400 m long pipeline system (1 or 2 parallel pipelines) to the secondary treatment process. At its input there are an equalization basin "2" and rapid mixer "3" with additional inlet flow of the municipal \\astewater. The most important parts of secondary treatment process are conventional biological activated sludge process "4" and multifunction chemical reactors "5" .
Five retention basins "a" - "e" have been very useful for reliable operating control. During periods of heavy rainfall, the clear water is stored in a basin for possible future dilution of the strongly contaminated \\astewater, and vice versa the strongly contaminated \\astewater may be stored in a basin for future treatment or may be by passed through a basin as well. One of the most important dangers for the considered process is a possibility of a sudden augmentation of cyanide concentration ciII in the inlet flow. In the normal working point of the 3 = 400 m3 I h, CUI = 40 g 1m ) the process concentration of the cyanide before the biological 3 part of the plant is about c. =37 g I m and after secondary treatment this value decreases to 3 3 eR = 6 glm • The value of c~ = 50 g 1m can be accepted in the normal working point of the process, while the value of = 80 g I 3 should be treated as a critical value for the biological part of the process. The bigger values may destroy the active biomass in the biological part of the plant. To counteract this emergency the appropriate control decision must be made by the process operator. The simulation of the process may be very useful for computer aided support.
(V;
c:
m
The mathematical model for simulation of this very complicated process must consider only this mathematical description that is essential for simulation purpose. Hence, in this case only the cyanide concentration transport through installation is considered and finally the particular process units are considered as well stirred lumped parameter systems (ordinary state differential equations). Including the discretized advective equation as the mathematical description of the time-delay (Metzger, 1994c) introduced by the pipeline, the whole mathematical model of the process consists of 29 stiff nonlinear state differential equations. Nevertheless, the computing time of its numerical solution on the standard PC-486 is very short.
ON-LINE AND STAND-ALONE SIMULATORS
a)
b)
c)
cl)
e)
v~ ~----~~------Jl-L-----~~----~-L--I~
Fig. 1. Considered industrial \\astewater treatment process
270
Design of process simulators deals strictly with problems of the real-time simulation. The two most important features of the real-time simulation experiments (in relation to the conventional simulation experiments in the batch mode) are as follows. a) the simulation results are strictly connected with the real-time synchronization (for scaled real-time as well), but they should be independent of the time used for calculations, b) in any communication point (in which the inputoutput communication with the operator takes place) the operator can change the operating actions during simulation investigations.
As mentioned in the introduction, the enhanced simulation support for operating supervisory control of the considered wastewater treatment process should consist of two simulators. The process connected simulator for an on-line operator decision aid is presented in the Fig. 2. The process is controlled by the supervisory control and data acquisition (SCADA) system. The operator exerts his control actions from the SCADA operating console. Some chosen data necessary to initiate simulation running are continuously collected from the SCADA system. Hence, the operator in any time (especially when some process emergency occurs) can check his control actions on the base of the actual process situation. For several most important emergency situations (e.g. for changes of the cyanide concentration in the inlet flow) the operator should be prepared by the training on the stand-alone training simulator (Fig. 3). This simulator is based on the same mathematical model of the process as the process connected simulator, but initial conditions are taken from the data stored for chosen past and anticipated process situations (e.g. for several different fills of retention basins). Programming a real-time training simulator is difficult because (apart from classical process simulation) the real-time realization should be taken into consideration. This includes real-time synchronization of numerical calculations and especially continuous
Real-wor1d process
I. ,I I~==MathematIca=oI=the=~=1 =modeI===~ I
0aIII 8IOted for 8I1tiapeted aItuMow 01 the ~
I
R.l-tlme SImulatIOn and visualization
Fig. 3. Stand-alone operator training simulator. detection of events (operator actions). The new LabWindows/CVI (LW/CV!) instrumentation and visualization programming tool from National Instruments is also very useful for designing of realtime simulators. This tool links the power of full ANSI-C language with graphical flexibility in the Microsoft Windows em;ronment. The LW /CVI offers a large amount of ready-te-use functions of controls (as knobs. slides and switches) as well as graphs. charts and indicators for building a real-time interactive operator interface. The numerical calculations for simulation of the process (29 stiff nonlinear state equations) have been programmed in C which IS incorporated in the LW ICVI . The simulation program is controlled by the operator graphical interface - the same for both simulators (see Fig2 and Fig.3) . The main program COnsists 10 the process loop in which the LW /CVI orgaruzes the real-time processing (that is. the realtime synchronization. the continuous detection of events. the simulation calculations. and the visualization)
Conltnu"",.ty actualized proceu data Mathemaltcal model 01 the process
Real-time SImulation
Fig. 4 shows chosen (verified experimentally) simulation results . The response of the cyanide concentration c. after step increasing of the inlet cyanide concentration c'" =40+80 1(/) g/ml is presented in the Fig. 4a. This result shows that after 8 hours the biomass may be destroyed (without any operator reaction). The results of the appropriate operator control are shown in the Fig. 4b. This flow control consists of the step increasing of the rate to the empty basin "c", and of the step increasing of the V~ flow rate from the basin "b" with previously stored clear water. During the interval of 24 h the biomass is out of danger now.
V;
Fig. 2. Process connected simulator
271
training simulator can be very useful for teaching students in the operator control and decision making.
c,.[gIm'j 111
80
Acknowledgment: This work was supported by the Committee of Scientific Research (KEN).
a)
50 37
REFERENCES 0
20
c,. (gIm')
51
I (h)
b)
37
10 2 1.711
20
I)
HIm) t--p~-----.,
•
20
I (h)
20
I (h)
I
Fig. 4. Simulation responses after step increase of the inlet cyanide concentration, a) without any operator action, b) with appropriate operator control
CONCLUDING REMARKS
A problem of simulation support for operating control in the case of a sudden augmentation of cyanide concentration in the inlet flow of a big industrial wastewater treatment process has been presented in the paper. An enhanced simulation support for operating process control that consists of two simulators has been proposed in the paper. An application of the process simulator connected with the plant control system to continuously actualize process data is designed for the on-line operation aid. The stand-alone operator training simulator can be very helpful for additional off-line operator training on the base of process data stored for chosen past and anticipated process situations. Both si~ulators have been realized in practice as the in the LabWindows/CVI-based applications Windows environment. Besides, the operator
272
Cheok. K.C. and N. Huang (1992). Real-time simulation and animation for dynamic control systems. Simulation. 59, No 4, pp. 246-252. Hays, T. (1992). Systems concepts for training systems development. Trans. IEEE on Syst. Man and Cybernetics. 22, No 2. pp. 258-266. Jelsma, O. and lP. Bijlstra (1990). Process: Program for research on operator control in an experimental simulated setting. Trans. IEEE on Syst. Man and Cybernetics. 20, pp.1221-1228. Krishnalrumar, K.S., D. Sawal, lE. Bailey and JA Dohme (1991). A simulator-based automated helicopter hover trainer-synthesis and verification. Trans.lEEE/SMC 21. pp. 961-969. Metzger, M. (1992). Real-time simulation of the biological activated sludge process. In: Computer Simulation in Biology. Ecology and MediCine 1992, (Ed. M. Kotva). pp. 92-96. Simulation Council, Inc., San Diego. Metzger, M. (1994a). A new concept of industrial process simulation - cybernetic approach using distributed access control schemes. Systems Ana(vsis. Model.. Simulation. 15, pp. 185-202. Metzger, M. (1 994b). Fast-mode real-time simulation of a biological process. In: Modelling and Simulation ESM94 (Ed. A Guash and RM.Huber), pp. 753-755. Simulation Councils. Inc., San Diego. Metzger, M. (l994c). Modelling and simulation of time-de)ay element via advective equation. In: Modelling and Simulation ESM94 (Ed. A Guash and RM.Huber), pp. 756-759. Simulation Councils. Inc .. San Diego. Metzger, M. (1994d). Fast-mode real-time simulator for the wastewater treatment process. Water Science Technology, 30, No. 4, pp. 191-197. Naess, L., A Mjaavatten, and lO. Li (1993). Using dynamic process simulation from conception to nonnal operation of process plants. Computers chem. Engng. 17, No 516, pp. 585-600. Pimento, P.C.C., and S. Feyo de Az.evado (1993). Real-time dynamic simulation of non-linear MIMO systems. Computers chem. Engng. 17 (supplement). pp. S343-S348. Ramesh, R and C. Sylla (1990). A framework for the optimal design of instructor/operator stations in flight simulators. Trans. IEEE on Syst. Man and Cybernetics. 20, pp. 571-581. Schumacher, RM. and D. Gentner (1988). Transfer of training as analogical mapping. Trans. IEEE on Syst. Man and Cybernetics. 18, pp. 592-600.