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BLACK BOX APPROACH FOR IDENTIFICATION AND POLE PLACEMENT METHOD APPLIED TO THERMAL POWER PLANTS CONTROL Marina Hashim, ALSTOM, France E-mail : marina.hashim@power.alstom.com ABSTRACT This article deals with the control of sensitive loops belonging to the thermal process within a power plant. It is usually a pressure, a temperature, a level or a flow whose value has to be constant or to follow a profile, often with ramps and plateaus, anyway with slow variations. From one plant to the other, the provider of the different equipements involved in the same control loop changes, or even with the same provider, the design, the distance between elements, the installation, the materials vary. This is due to client’s desires concerning power, efficiency, use of the plant with the High Voltage Network or other industrial equipements such as refineries, aluminium factories, … The constraints of the site interfere as well. All this leads to differences between same type of processes from one plant to the other one, sometimes the architecture of the control loop is changed as well. In addition, when the power plant is linked to other industrial complexes, some new control loops appear. For example to control a steam flow to an aluminium factory to a constant value… As a consequence, it is difficult to have knowledge based models sufficient to tune by advance the controllers. Furthermore, the priority is given to on site tuning. The usual practise is to implement PID controllers and to let the tuning to commissioning people. Very often, no tools are used and the controllers are tuned in their PI form, thanks to several trials. Based on a will to improve the performances together with to provide a complete tool for identification and tuning, a digital controller of the RST form has been implemented in the ALSTOM POWER control and supervision system : the P320. The WINPIM and WINREG products of ADAPTECH are integrated in the P320 system in order to respectively identify the process and tune the controller. A “black box” approach is used. The effective application of this approach to the control of a 2x360 MW Thermal Power Plant at Luo Huang, China is presented.

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SUMMARY

1. Power Plant processes concerned and usual control practice with ALSTOM P320 control system ............... 3 1.1 Processes – Loops ......................................................................................................................................... 3 1.2 Closed loop control with ALSTOM P320..................................................................................................... 5 1.3 Choice of the RST Controller with a complete identification and tuning software....................................... 5 2. Black box approach for identification and pole placement method ............................................................... 6 2.1 Implementation ............................................................................................................................................. 6 2.2 On-site identification and tuning procedure.................................................................................................. 8 2.3 Validation on a superheater simulator........................................................................................................... 8 3. First on-site application : Luo Huang Thermal Power Plant 2 x 360 MW, China July-November 1998...... 10 3.1 Context – Architecture of the control with P320 – Loops chosen............................................................... 10 3.2 Results obtained – Comparison with a PID-controller................................................................................ 11 4. Conclusion .................................................................................................................................................... 19

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1. Power Plant processes concerned and usual control practice with ALSTOM P320 control system

1.1 Processes – Loops Processes The Thermal Power plants are of coal or fuel type, or combined cycle with gas turbines. The loops concerned in this article, are those of the water/steam cycle, or concerning the air intake, or the coal, the auxiliaries (fuel, demineralisation,…) They are « slow type » processes. (The gas or steam turbine governing loops are « quick processes » compared to these, and are not concerned by this article). The usual sampling time and working time for the controller is 300 ms which is highly sufficient to use PIDs which act as continuous-type controllers to the relatively slow processes. The response time is typically of a few seconds up to an hour, sometimes more. There are often dead-times, which can be of a few seconds or more, equivalent to a fifth of the response time for a typical example. The systems can generally be modelised around their operational point by a linear model with a transfer function of up to order 4, and with a delay. The major instabilities are due to integrators: the control of the level in the drum or in a tank for example. The processes that are classically the most difficult to tune are those of the desuperheating type. This corresponds to a temperature of hot steam or water controlled to a setpoint by one or more injection(s) of colder water before the temperature transmitter. Some heat exchangers (superheaters) can exist between the injection and the measurement of the temperature. These processes have a long time response (more than half an hour), a non-negligible delay and an order of 3 or 4 if identified with a linear model. This explains why they are tuned with difficulty and not significant results when a PID controller is used. Loops architectures The different loops are sometimes strongly linked. But monovariable controllers are used and tuned trying to isolate the most possible the containing loop. Some direct actions, functions of a variable controlled in another loop, are also often encountered. The processes are put in closed loop since the starting of the plant, far from their operating point. That is why the controllers have to be robust in order to control the process (with degraded performances) even far from the operating point. In some cases several controllers are computed for different operating zones. But even in these cases, the controllers have to be robust enough for the switching from one zone to the other one. In addition, at the very starting of the process, this one is rarely linear, but anyway put under automatic control by the operators of the power plant. Non-linearities always exist with more or less importance, the controllers have to cope with them. The architectures of the loops can be of the cascade type. Very often, the output of a controller has to act in split range on two different actuators.

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The output of a controller is also very often limited by a constant, or by the output of another controller.

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1.2 Closed loop control with ALSTOM P320 The architecture of the different elements used for control will be detailed later with the application of the Luo Huang Power Plant. The closed loop control program is computed periodically within the « regulation task ». The usual regulation task period is 300 ms. The programmation is made thanks to « functional blocks », which are chained, to each other in order to form the program. The standard PID controller, which can be used in any loop architecture, is one of these « functional blocks ». The management of the automatic to manual and manual to automatic switches is made outside the controller functional block. The commissioning people make the tuning of the closed loop controllers on site.

1.3 Choice of the RST Controller with a complete identification and tuning software. The choice of integrating an RST-controller with its tuning tools into the ALSTOM P320 control system was made for the following reasons: 1. Some processes, as already seen, the desuperheating control for example, necessitate a

controller of an order sufficient (3 or 4) 2. A non negligible dead time have to be modelised and must not disturb the controller 3. The black box approach for the identification is interesting as it is the normal approach

when using PID controllers, and due to the diversity of the processes to control 4. In general, an improvement of the performances was desired 5. A complete tool was wanted : for identification and design of the controller, with detailed

diagrams and margins for robustness analysis and possibility of simulation 6. The controller was to run inside the P320 multifunction controller, and as a consequence

to be a “functional block” as the PID controller is in the P320 system. The communication with the tuning tools was to be low cost in implementation

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2. Black box approach for identification and pole placement method

2.1 Implementation The RST controller program runs on the P320 multifunction controller. It is a “functional block” (a sub-program) that can be isolated. The RST structure which is a canonical structure of a digital controller is the following one : (refer to “The RST digital controller design and applications” I. D. Landau Control Engineering Practice 6 (1998) 155-165)

Bm

Am

+-

1

S

D.A.C.+

ZOHPlant A.D.C.

R

r ( t )T

DISCRETIZED PLANT

Fig 1 Where Bm/Am is a tracking reference model and the polynomials R, S, T have the following form :

nRnR

110

1 qr...qrr)q(R −−− +++=

nSnS

110

1 qs...qss)q(S −−− +++=

nTnT

110

1 qt...qtt)q(T −−− +++= All the initialisations of the RST functional block and limitations are computed outside the functional block and communicate with the RST controller thanks to input variables of the block.

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The implementation is similar to the one of the PID controller functional block. The tunable parameters and the management of the excitation for identification differ. A sub program allowing to add a centered pseudo random binary sequence (PRBS) of small magnitude (maximum 10% of the total scale of the actuator command) is integrated in the functional block of the RST controller :

FUNCTIONAL BLOCK

D.A.C.+

Z.O.HPlant A.D.C.

+ +

P.R.B.S.

R.S.T CONTROLLER

MEASURE

REFERENCE(SET POINT)

INITIALISATION

COMMAND

uCOMMAND

Fig 2 The PRBS is added to the command which can be a constant value (“initialisation command”) in case of an open loop identification, or the output of the RST controller (“command u”) in case of a closed loop identification. The controller can be used with the same dynamic for tracking and disturbances rejection, in that case, only R and S are used. When a tracking with a different dynamic is wanted, Bm, Am and T are also used. The RST controller and the PRBS work at a time period multiple of the regulation task period. The under sampling is done in the functional block. The time period depends on the response time of the plant. (In order to obtain 5 to 20 samples on the rising time of the plant in open loop, and a time delay as close as possible to a multiple of this period) On the same personal computer, the different tools for identification, tuning, on-line loading of the tuning parameters, and on-line observation are installed : CONTROSET software (Alstom) for on-line observation, record and loading into the

P320 multifunction controller WINPIM software (Adaptech) for identification, based on a CONTROSET input/output

record WINREG software (Adaptech) for the RST controller design and simulation

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2.2 On-site identification and tuning procedure Since the use of a digital RST controller was an innovation, there was no library of tuning parameters sets available for power plants, so the open loop excitation was considered. First, a step on the command, around the operating point gives the following information : . dead time if any . rising time to reach 90% of its final value . Static gain Then the RST controller working period is chosen : a multiple of the regulation task period, as close as possible to an under multiple of the dead time, and to obtain 5 to 20 samples on the rising time. The second stage is the identification with a PRBS :

1. The PRBS working time is classically chosen equal to the RST-controller period. In order to identify the static gain, the longer crenel (whose lasting is : order x PRBS period) must be comparable with the rise time of the process. If the RST-controller period is too short, a multiple of it can be used for the PRBS period. However, if this results in a too long excitation time, the PRBS period is kept equal to the RST controller one, and the static gain will be modified on the model found, if necessary.

2. The order of the PRBS is chosen between 2 and 10. The higher it is, the more frequencies the PRBS contains. A classical choice is 7, but it is not always possible : the duration time of the PRBS is PRBS

n T)12( − , so PRBST127 for an order of 7. 3. The magnitude of the P.R.B.S. is of less than +/- 5 % in order not to disturb the

plant too much. Once the PRBS’ parameters chosen, the PRBS is added to the constant command, corresponding to the operating point. With fast process we can send two consecutive PRBS. With the CONTROSET tool, the inputs/outputs of the plant corresponding to the PRBS excitation are observed and recorded. The resulting record is read in WINPIM, and, thanks to a recursive identification method, a discretized model at the RST-controller period is found. The step response of the model is compared to the plant’s one . If necessary, the static gain is adjusted. Then with WINREG, several controllers are designed on the model, with different performances. After off-line simulation and robustness analysis, the parameters are sent thanks to CONTROSET which reads a WINREG controller-file. The parameters are sent on-line : all the parameters within the same regulation task cycle. As the different parameters sets correspond to a tuning on the same plant, the change from one tuning to the other one can be done on line and without opening the loop. The ultimate stage is the check of the controller performances on the plant.

2.3 Validation on a superheater simulator The first tests were made without the inputs/outputs cards (CE2000 field controller) : the program with the RST-controller was runing on a P320 multifunction controller, and the

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inputs/outputs cards together with a desuperheating plant were simulated thanks to the Alstom CONTROSET tool. The model used was a mechanical knowing model. As these tests were satisfying, the next stage was to insert the CE2000 inputs/outputs cards. To achieve this, the tests were performed on a desuperheating continuous simulator connected to the sampling cards. Mr. Klaus Moellmann from our german team was at the origin of this test platform. The architecture of the loop was a cascade one(two stages of water injection). The results using the RST-controller and the whole identification and tuning tools were still satisfying, so the next stage was to test the system with a real plant.

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3. First on-site application : Luo Huang Thermal Power Plant 2 x 360 MW, China July-November 1998.

3.1 Context – Architecture of the control with P320 – Loops chosen Context The Luo Huang 3-4 Power Plant project was the construction and commissioning of two new units of 360 MW each. These 2 units come in addition to the two already existing units in the Sichuan province in China. The tests were performed during the commissioning of the unit 3 in 1998. This unit is coal fired, composed of a boiler, a steam turbine and a condensing/feedwater heating plant. The controlled circulation type boiler is equipped with drum, superheaters and reheaters. Coal is supplied indirectly and burnt by 36 pulverized coal burners. The boiler is composed of : 2 rotating air heaters, 2 primary air fans, 2 forced draught fans, 2 induced draught fans, 2 steam preheaters, 2 electrostatic precipitators. Architecture of the control with P320

Fig 3 Luo Huang Power Plant – Architecture of the P320 control system The power plant is controlled from a decentralized control room thanks to the CENTRALOG operator workstations.

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At the moment, the CONTROSET observing tool was on the same workstation than the CENTRALOG. Modifications and loading of the programs into the controller are made from the engineer workstation. The program runs on the P320 redundant multifunction controller. The inputs/outputs come and are sent through the CE2000 field controller. The identification and tuning tools WINPIM and WINREG were not integrated at that moment, they were running on a portable PC. The communication of the CONTROSET records was made thanks to floppy disks. As the Luo Huang CONTROSET version was not integrating the whole identification and tuning tools, the RST-controllers were programmed in parallel with PID controllers. The commissioning people were tuning the PID controllers the standard way. The RST-controllers tuning was achieved during spare time, as they were not to stay on the installation. A boolean variable permitted (only in open loop, manual mode) to switch from the PID to the RST in parallel. As the RST-controller was not working at the sampling period (300 ms) but at multiple of it, a digital anti-aliasing filter was inserted before the RST-controller functional block in which the under sampling was computed. Loops chosen During these 5 months of tests, the disponibility of the closed loop elements (actuators, transmitters, steam/water…) was the preponderant criterium for the choice of a loop. In addition, a desuperheating plant was preferred, because of the usual problems encountered in tuning this system. The RST-controller was computed in parallel with a PID controller in two closed loops : 1. The control of the steam temperature at the steam air preheater inlet by actuation on a

spraywater control valve (“FPA” system). This is a desuperheating type plant. 2. The primary air pressure control by actuation in parallel on the two primary air fan inlet

vanes.

3.2 Results obtained – Comparison with a PID-controller Steam air preheater inlet temperature control The steam air preheater heats the air intake thanks to steam coming from the turbine. The preheating steam temperature is controlled to a variable setpoint, equal to 10°C above the saturated steam temperature. In order to achieve this control, the steam is desuperheated thanks to a spray water control valve.

1. Identification of the discrete time plant model The chosen period time was 30 seconds. The input used was a PRBS of magnitude +/- 5%, and generated by a shift register with N=7 and a period of 30 seconds. The record was done thanks to CONTROSET and sent in WINPIM for identification. The following recursive identification methods had been used : Output Error with fixed Compensator and Output error with extended Prediction Model. For validation of the identified models, the cross correlation between the predicted output and the output error as well as the whiteness test on the prediction error have been used. During the different phases of commissioning, the plant had evolved. In August 1998, the commissioning phase was in the steam blowing phase. The aim of this operation is

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to clean the superheated, cold reheat and reheat steam circuits, driving out oxides, scale and foreign bodies (welding scraps, bevelling chips,etc…). The steam is blowed at high speed through the pipes and discharged to the atmosphere.

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During this phase, a model with the following poles and zeros had been found :

fig 4 poles and zeros of the model of the steam air preheater temperature during the steam blowing phase Later, in November 98, with the unit 3 synchronised at half load (180 MW), the model found was quite different :

fig 5 poles and zeros of the half load model of the steam air preheater temperature

2. Controller design The pole placement method was used. The disturbances rejection was the main point. At 180 MW, the following performances were specified for the two dominant poles : pulsation w0 = 0,014 rad/s (rise time in closed loop equal to the one in open loop = 210 s), damping ξ = 0,8. The robustness margins are : modulus margin = 0,552; gain margin =2,23; phase margin =71,2° and delay margin = 56 s for a sampling period of 30 s.

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The simulation of the step response of the control system is shown fig. 4

fig 6 Simulation of a the steam air preheater RST-controller in closed loop Then the following results were obtained on the plant in closed loop (fig. 6) and compared to the closed loop with the PID-controller (fig. 7)

fig 7 Steam air preheater in closed loop with a RST-controller

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fig. 8 Steam air preheater in closed loop with a PID-controller A step of 10 Celcius degrees is made on the set point in the both cases. The rise time is divided by two with the RST controller.

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Fig. 9 and 10 show the plant in closed loop with respectively the PID controller and the RST controller. The observation (lasting 2 hours) shows that the RST-controller keeps the steam temperature closer to the set point. In addition, the spray water valve command is smoother in the RST-controller case which is an important point for a power plant actuator.

fig 9 Steam air preheater desuperheating in closed loop with a PID

fig 10 Steam air preheater desuperheating in closed loop with a RST

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Primary air pressure control The primary air is generated by two fans and used to transfer the pulverized coal from the storage bunkers to the burners. The set point of the primary air pressure is adjustable from the control room. The control loop acts in parallel on the two primary air fan inlet vanes’actuators.

1 Identification of the discrete time plant model The open loop rise time is about 16 seconds, so the period time chosen is 3 seconds. A PRBS of a magnitude of +/-5%, N=7 and a period of 3 seconds (fig 11) is generated.

fig 11 Primary air pressure record for identification

In WINPIM, the procedure is the same one than for the steam air preheater inlet temperature. The model found has got the following poles and zeros :

fig 12 Primary air pressure model poles and zeros

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2 Controller design The following performances were specified with the pole placement method : W0 = 0,25 rad/s (closed loop rising time of 12 s), and ξ=0,7. The corresponding robustness margins are : modulus margin = 0,619; gain margin =2,741; phase margin =63.8° and delay margin = 13.13 s for a sampling period of 3 s. This RST-controller was compared to the PID in parallel : the rejection of the disturbances is quicker and better . Fig 13 and 14,a similar disturbance (the speed of the forced draught fans change from low to high) acts on the closed loop. The primary air pressure rises to 4.55 kPA with the PID compared to 4.7 kPa for the RST but the disturbance is rejected in 40 seconds compared to 2mn 30 s with the PID. Fig 15 shows the closed loop with the RST submitted to a huge disturbance : the extinction of 5 burners at the same time followed by a total extinction and a boiler trip.

fig 13 Primary air pressure in closed loop with a RST controller

fig 14 Primary air pressure in closed loop with a PID controller

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fig 15 Primary air pressure in closed loop with a RST controller submitted to 5 burners extinction followed by a boiler trip

4. Conclusion After the tests on Luo Huang, the tools were integrated on the same PC. In addition Man/Machine interfaces were created to facilitate the procedure. Later on, thanks to complementary tests on simulators, the anti-aliasing filter was withdrawn : it was in fact not necessary and it was disturbing the identification and the control. The whole system has been applied to the Condor project in the Arabic Emirates, which is a combined cycle and has already been commissioned. Other actual projects are using the RST-controllers. The open-loop adaptation of the controller parameters has been implemented because some processes are changing with the load. The closed loop identification is a perspective which will be very interesting when we will have libraries of RST-controller parameters for Power Plants.