METHOD OF OPERATING A HEAT RELEASING REACTOR, A HEAT RELEASING REACTOR, AND A COMPUTATION SYSTEM FOR A HEAT RELEASING REACTOR

Abstract

A method of operating a heat releasing reactor producing product gas. The method includes steps of (a) monitoring a current load of the reactor, (b) finding such a numerical value for a current computational maximum momentary load for which at least one product gas factor computed using currently monitored process data with a numerical model of the reactor fulfills an acceptance condition, and selecting the numerical value as the current computational maximum momentary load, (c) indicating the current computational maximum momentary load to the operator and/or, if the current load is (c1) less than the current computational maximum momentary load, (c1i) indicating the operator that the load may be increased, and/or (c1ii) automatically increasing the load, and/or (c2) greater than the current computational maximum momentary load, (c2i) indicating the operator that the load exceeds the current computational maximum boiler momentary load, and/or (c2ii) automatically reducing the boiler load.

Claims

1. A method of operating a heat releasing reactor producing a product gas, the method comprising the steps of: (a) monitoring a current load (Q.sub.h) of the reactor; (b) finding such a numerical value (Q.sub.h, candidate) for a current computational maximum momentary load (Q.sub.h, max) for which at least one product gas factor (df.sub.i) computed using currently monitored process data with a numerical model of the reactor fulfills an acceptance condition, and selecting the numerical value (Q.sub.h, candidate) as the current computational maximum momentary load (Q.sub.h,max); (c) indicating the current computational maximum momentary load (Q.sub.h,max) to an operator and/or, if the current load (Q.sub.h) is (c1) less than the current computational maximum momentary load (Q.sub.h,max): (c1i) indicating the operator that the load (Q.sub.h) may be increased, and/or (c1ii) automatically increasing the load (Q.sub.h), and/or (c2) greater than the current computational maximum momentary load (Q.sub.h,max): (c2i) indicating the operator that the load (Q.sub.h) exceeds the current computational maximum boiler momentary load, and/or (c2ii) automatically reducing the boiler load (Q.sub.h).

2. The method according to claim 1, wherein: (i) the currently monitored process data of the reactor includes: (ia) current product gas exit temperature (T.sub.G,exit,current) in a gas flow channel, and (ib) heat duty (Q.sub.fluid,i) for each heat transfer surface (i) in the product gas flow channel, and, further, wherein: (ii) monitored process data from both (ia) and (ib) is used in computation of the product gas factor and when finding the numerical value (Q.sub.h, candidate) for the current computational maximum momentary load (Q.sub.h,max).

3. The method according to claim 1, wherein the finding is performed such that, if the at least one product gas factor (df.sub.i) computed using currently monitored process data with a numerical model of the reactor fails to fulfill an acceptance condition, a next numerical value (Q.sub.h, candidate) is automatically selected.

4. The method according to claim 3, wherein the next numerical value (Q.sub.h, candidate) is selected iteratively.

5. The method according to claim 1, wherein the finding is carried out by performing the computational steps of: I: computing an estimate for product gas exit temperature (T.sub.G, exit) that results in a computational model when the load of the reactor corresponds to the numerical value (Q.sub.h, candidate); II: computing product gas mass flow (q.sub.m,productgas); III: computing a heat duty (Q.sub.fluid, i, candidate) for each heat transfer surface in the gas flow path using its current heat duty (Q.sub.fluid, i, current) that is corrected by using a numerical reactor model (Q.sub.fluid, i, candidate=Q.sub.fluid,i,current+S a.sub.j,I(Q.sub.fluid,max).sup.jS a.sub.j,i (Q.sub.fluid,current).sup.j); IV: using the computed heat duties (Q.sub.fluid, i, candidate) for each heat transfer surface in the product gas flow channel to compute product gas temperatures at each heat transfer surface (T.sub.G,in,i, T.sub.G,out,i; i=1, . . . , k) in the flue gas flow channel in the upstream direction of product gas flow, starting from the heat transfer surface 21.sub.k that is closest to the product gas exit using the estimate for the product gas exit temperature (T.sub.fluegas,out,k=T.sub.FG, exit); and V: computing the product gas factor (df.sub.i, i=1, . . . , k) for each heat transfer surface in the flue gas flow channel.

6. The method according to claim 5, wherein the flue gas factor includes or is: ${\mathrm{df}}_i={k_i\left(\frac{q_{m,G}}{{}_{\mathrm{productG},i}*A_{\mathrm{cross},i}}\right)}^n$ where k.sub.i is a non-zero parameter that may be chosen reactor-specifically, being a positive number, q.sub.m,productgas is product gas mass flow, n is a model parameter that may be chosen reactor-specifically, being a positive non-zero number, and p.sub.G,i is product gas density at i.sup.th heat transfer surface and A is a cross-sectional area of flue gas channel at i.sup.th heat transfer surface.

7. The method according to claim 6, wherein n is selected to be at least one of the following: (i) in the range of 0.9 to 1.1, for using computed product gas velocity; (ii) in the range of 2.9 to 3.5 for using computed product gas caused erosion; or (iii) in the range 1.8 to 2.2, for using pressure loss of the product gas flow.

8. The method according to claim 7, wherein the value for n is changed over time.

9. The method according to claim 7, wherein the value for n is determined from a group of reactors comprising at least two separate reactors using operational data monitored for each of the reactors.

10. The method according to claim 5, wherein, in the computation in step (I), the flue gas exit temperature is substantially estimated by an equation: $T_{G,\mathrm{exit}}=a_0+{{\mathrm{Sa}}_j\left(Q_{h,\mathrm{candidate}}\right)}^j$ or its first, second, third, or higher degree approximation, and wherein the respective coefficients (a.sub.0, a.sub.1, a.sub.2, . . . ) have been obtained beforehand by fitting after measuring product gas exit temperature (T.sub.G, exit) values for a number of discrete reactor load (Qh) values.

11. The method according to claim 5, wherein, in step (II), computation of product gas mass flow utilizes mass flow (q.sub.m,G,m) of product gas components m.

12. The method according to claim 5, wherein, in step (II), the computation of product gas mass flow includes using reactant parameters.

13. The method according to claim 1, wherein the step (b) is performed remotely to the reactor.

14. The method according to claim 1, wherein the step (b) is performed locally at the reactor site.

15. The method according to claim 1, wherein any of the currently monitored process data and/or current load is obtained from real-time measurements, treated by filtering, treated by averaging, computing trends, or any combination of these.

16. The method according to claim 1, wherein the acceptance condition includes a hysteresis condition, requiring a predefined minimum change before changing the current computational maximum momentary load (Q.sub.h,max).

17. The method according to claim 1, wherein the acceptance condition includes comparing the computed at least one product gas factor (df.sub.i) against a respective design value, and wherein, in the method, the numerical value (Q.sub.h, candidate) is rejected if the design value is exceeded.

18. The method according to claim 1, wherein the reactor is a circulating fluidized bed (CFB) or a bubbling fluidized bed (BFB) reactor, and the step (b) is carried out for the heat transfer surfaces in at least one of the reactor, and the product gas channel.

19. A heat releasing reactor comprising: a reactor chamber and associated passes defining a product gas flow path and having a number of heat transfer surfaces; measurement instrumentation to monitor current load (Q.sub.h) of the heat releasing reactor; further measurement instrumentation, such as sensors, to currently monitor process data; and a control system configured to carry out the method of operating the heat releasing reactor according to claim 1.

20. The heat releasing reactor (10) according to claim 19, wherein the control system comprises (CS) an edge server (203) that is configured to process real-time measurement results for at least one of currently monitored process data and current load, by filtering, averaging, and/or computing trends.

21. The heat releasing reactor according to claim 19, wherein the control system is configured to carry out the method step (b) to determine the current computational maximum momentary load (Q.sub.h,max) locally.

22. The heat releasing reactor according to claim 19, wherein the control system is configured to send data to a remote computing system that is configured to carry out the method step (b) and to return the current computational maximum momentary load (Q.sub.h,max) to the control system.

23. The heat releasing reactor according to claim 22, wherein the edge server is configured to reduce an amount of measurement data that is passed to the remote computing system.

24. A reactor computation system comprising: a group of reactors, according to claim 19, each reactor comprising a control system (DCS), comprising an edge server system that is configured to process the real-time measurement results for at least one of currently monitored process data and current load, by performing at least one of filtering, averaging, and computing trends, and to send the processed real-time measurement results to a remote computing system; a remote computing system that is configured to receive data processed from real-time measurement results and to compute data using a numerical model for each of the reactors, and to return computation results for each of the reactors; and, further, wherein the control system is configured to adapt its function based on the computation results.

25. The reactor computation system according to claim 24, wherein the computing system is configured to find such a numerical value (Q.sub.h, candidate) for a current computational maximum momentary load (Q.sub.h,max) for which at least one product gas factor (df.sub.i) computed using currently monitored process data with a numerical model of the reactor that fulfills an acceptance condition, and selecting the numerical value (Q.sub.h, candidate) as the current computational maximum momentary load (Q.sub.h,max).

26. The reactor computation system according to claim 24, wherein the reactor computation system is configured to calibrate a numerical model for a heat releasing reactor using processed measurement data for the heat releasing reactor.

27. The reactor computation system according to claim 24, wherein the reactor computation system is configured to calibrate a numerical model for a heat releasing reactor using processed measurement data also collected from other heat releasing reactors.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0088] The reactor and its control method are explained in more detail below in the context of the embodiments shown in the appended drawings in FIG. 1 to 9, of which:

[0089] FIG. 1 illustrates a CFB boiler;

[0090] FIG. 2 illustrates a BFB boiler;

[0091] FIG. 3 illustrates the flow of measurement data from sensors;

[0092] FIG. 4 is a flow diagram illustrating a first method for finding the current computational maximum boiler momentary load Q.sub.h, max;

[0093] FIG. 5 is a flow diagram illustrating a second method for finding the current computational maximum boiler momentary load Q.sub.h, max;

[0094] FIG. 6 illustrates how the current computational maximum boiler momentary load Q.sub.h, max can be presented to the boiler operator;

[0095] FIG. 7 shows boiler momentary load Q.sub.h and computed current computational maximum boiler momentary load Q.sub.h, max, as well as the effect of using the method according to the invention during a test period;

[0096] FIG. 8 a closer look at the data of FIG. 7, showing boiler momentary load Q.sub.h computed current computational maximum boiler momentary load Q.sub.h, max where the effect of using the method according to the invention during the 10 day test period is better visible; and

[0097] FIG. 9 illustrates another heat releasing reactor according to an embodiment of the invention.

[0098] The same reference numerals refer to same technical features in all figures.

DETAILED DESCRIPTION

[0099] FIG. 1 shows a combustion boiler 10 operating as a heat releasing reactor producing heat in a form of a circulating fluidized bed reactor CFB. The CFB reactor may be used as a combustor/steam generator, a carbon capture reactor using (calciner and/or carbonator), as well as a waste material gasifier. In the following description, the CFB reactor is referred particularly as a circulating fluidized bed (CFB) boiler and comprises a furnace 12 that has tube walls 13 connected to water-steam circuit of the combustion boiler 10. Water is fed from water tank (not shown) to economizer and from the economizer via a steam drum to evaporative heat transfer surfaces such as the tube walls 13 and then guided via the steam drum to superheaters and then to a turbine. Flue gas channel may be provided with an economizer and/or superheater/s.

[0100] Fluidization gas (such as, air and/or oxygen-containing gas) is fed from fluidization gas supply 153 to below the grate (the grate not shown in FIG. 1) via a windbox (not shown), wherefrom the primary fluidization air enters into the furnace through nozzles (not shown) (to fluidize the bed), and secondary fluidization gas feed 152 (to feed oxygen containing gas to control combustion). The effect is that the bed materials will be fluidized and also oxygen required for the combustion is provided into the furnace 12. Further, fuel is fed into the furnace 12 via the fuel feed 22. The combustion can be adjusted by controlling the fuel feed 22 (such as, by reducing or increasing fuel feed), and by controlling the fluidization gas feed (such as, by reducing or increasing amount of oxygen supply into the furnace 12). Fuel can be fed together with additives, in particular with such additives that act as alkali sorbents, such as CaCO.sub.3 and/or clay for example. In addition, or alternatively, NOx reduction agents, such as ammonia or urea can be fed into the combustion zone of the furnace 12, or above the combustion zone of the furnace 12.

[0101] Bed material is also fed into the furnace, which bed material may comprise sand, limestone, and/or clay, that, in particular, may comprise kaolin. One effect of the bed and, generally, of the combustion, is that, in the water-steam circuit, water and steam is heated in the tube walls 13 and water is converted to steam.

[0102] Ash may fall to the bottom of the furnace 12 and be removed via an ash chute (omitted from FIG. 1 for the sake of clarity) and part of the ash, so-called fly ash, will be carried along with the flue gas.

[0103] Combustion products, such as flue gas, unburnt fuel and bed material proceed from the furnace 12 to a particle separator 17 that may comprise a vortex finder 103. The particle separator 17 separates flue gases from solids. Especially, in larger combustion boilers 10, there may be more than one (two, three, . . . ) separators 17, preferably, arranged in parallel to each other.

[0104] Solids separated by the separator 17 pass through a loop seal 160 that preferably is located at the bottom of the separator 17. Then, the solids pass to fluidized bed heat exchanger (FBHE) 100 that is also a heat transfer surface so that the FBHE 100 collects heat from the solids to further heat the steam in the water-steam circuit. The chamber in which the FBHE 100 is located may be fluidized and the FBHE 100 itself comprises heat transfer tubes or other kinds of heat transfer surfaces. FBHE 100 may be arranged as a reheater or as a superheater. From the FBHE outlet 101, steam is passed into a high-pressure turbine (if the FBHE 100 is a superheater) or a medium-pressure turbine (if the FBHE 100 is a reheater). For the sake of clarity, the turbines are not illustrated in FIG. 1. The solids may be returned from the FBHE 100 via a return channel 102 into the furnace 12. Especially, in larger combustion boilers 10, there may be more than one (two, three, . . . ) loop seals 160 and FBHE 100, and return channels 102, preferably, arranged in parallel to each other, such that for each separator 17, there will be respective loop seal 160, FBHE 100 and return channel 102. In practice, some of the FBHE 100 may be arranged as superheaters while some others may be arranged as reheaters.

[0105] The flue gases are passed from the separator 17 to horizontal pass 15 and from there further to backpass 16 (that, preferably, may be a vertical pass) and from there via flue gas conduit 18 to stack 19.

[0106] The backpass 16 comprises a number of heat transfer surfaces 21.sub.i(where i=1, 2, 3, . . . , k, where k is the number of heat transfer surfaces). In FIG. 1, heat transfer surfaces 21.sub.1, 21.sub.2, 21.sub.3, . . . , 21.sub.k-1, 21.sub.k are illustrated. Heat transfer surface 21.sub.k depicts air preheater. Heat transfer surfaces 21.sub.k-1, 21.sub.2 depict superheaters and heat transfer surfaces 21.sub.1, 21.sub.3 depict reheaters. The actual number of different heat transfer surfaces in each of these components, for example, may be selected for each combustion boiler differently according to actual needs. And there may be further components as well, comprising a heat transfer surface 21.

[0107] Flue gas exiting the last heat transfer surface 21.sub.k will be in flue gas exit temperature T.sub.G, exit. This temperature is measured with temperature sensor 20.sub.k.

[0108] According to one aspect, the temperatures before and after each heat transfer surface 21.sub.i (T.sub.G,in,i, T.sub.G,in,i+1, respectively) can be measured with respective temperature sensors 20.sub.i (where i=1, 2, 3, . . . , k1, k).

[0109] According to another aspect, and, preferably, these temperatures however do not necessarily need to be measured. It will suffice to know the flue gas exit temperature T.sub.G, exit. The temperatures before and after each preceding heat transfer surface 21.sub.1 (T.sub.G,in,i, T.sub.G,in,i+1) can be obtained numerically. This will be explained further below.

[0110] A combustion boiler 10 is equipped with a plurality of sensors and computer units. Actually, one middle-size (100 to 150 MW.sub.th) combustion boiler 10 may produce one hundred million measurement results/day, which needs 25 GB of storage space. FIGS. 1, 2, and 3 illustrate some of the sensors and computer units. Examples of the sensors are combustion gas (usually combustion air) volume flow sensors 30 (for measuring primary and secondary fluidizing gas feeds), fuel feed sensors 650 and temperature sensors 20.sub.i (i=1, 2, . . . , k), a temperature sensor in FBHE and pressure sensor 116 in the return channel 102 (both only in a CFB boiler), and sensors 40 in the furnace 12.

[0111] Process data may be collected from the sensors by distributed control system (DCS) 201. The data collection may most conveniently be arranged over a field bus 290, for example. DCS 201 may have a display/monitor 202 for displaying operational status information to the operator. An EDGE server 203 may process measurement data from the obtained from sensors, such as, filter and smooth it. There may be a local storage 204 for storing data.

[0112] The DCS 201, display/monitor 202, EDGE server 203, local storage 204 may be in combustion boiler network 280 (local storage 204, preferably, directly connected to the EDGE server). The combustion boiler network 280 is preferably separate from the field bus 290 that is used to communicate measurement results from the sensors to the DCS 201 and/or the EDGE server 203. Between the DCS 201 and EDGE server 203 there may be an open platform communications server 210 (cf. FIG. 3) to make the systems better interoperable.

[0113] Combustion boiler network 280 may be in connection with the internet 200, preferably, via a gateway 290. In this situation, measurement results may be transferred from the combustion boiler network 280 to a cloud service, such as process intelligence system 205 located in a computation cloud 206. The applicant currently operates a cloud service running an analysis platform. The cloud service may be operated on a virtualized server environment, such as on Microsoft Azure, which is a virtualized, easily scalable environment for distributed computing and cloud storage for data. Other cloud computing services may be suitable for running the analysis platform too. Further, instead of a cloud computing service, or in addition thereto, a local or remote server can be used for running the analysis platform.

[0114] FIG. 2 illustrates a heat releasing reactor which is a combustion boiler 10 that is a bubbling fluidized bed (BFB) boiler. The BFB boiler differs from the CFB boiler in that the fluidized bed is not a circulating bed but a bubbling bed. Thus, there may not be a need for the separator 17, loop seal 160, FBHE 100 and return channel 102.

[0115] There is normally at least one superheater 14 located in the furnace 12, preferably, on top of the furnace 12. Superheater 14 inlet 141 is preferably the steam drum or from another superheater and the outlet 142 is to high pressure turbine.

[0116] FIG. 4 illustrates the method of operating a heat releasing reactor producing product gas: [0117] (a) the current load Q.sub.h of reactor 10 (such a combustion boiler, gasification reactor, liquid air energy storage, hydration reactor) is monitored in step K1 (in the method illustrated in FIG. 4, also product gas exit temperature T.sub.G, exit is monitored and heat duty Q.sub.fluid,i to heat transfer fluid for each heat transfer surface 21i in the gas flow channel 16; [0118] (b) a numerical value Q.sub.h, candidate is selected (step K3), after which heat duties at heat transfer surfaces 21.sub.i are computed and gas temperatures in relation to Q.sub.h, candidate. The numerical value Q.sub.h, candidate is then used to compute (step K7) at least one product gas factor df.sub.i (may be referred to as flue gas factor in connection with combustion process)using currently monitored process data with a numerical model of the reactor fulfills an acceptance condition (which is tested in step K9), and selecting the numerical value Q.sub.h, candidate as the current computational maximum momentary load Q.sub.h, max of the reactor 10(step K11); and [0119] (c) the current computational maximum momentary load Q.sub.h, max is indicated to the operator (such as, by displaying on the monitor/screen 202) and/or, if the current load Q.sub.h is: [0120] (c1) less than the computational maximum momentary load Q.sub.h,max: [0121] (c1i) indicating the operator that the boiler load Q.sub.h may be increased; and/or [0122] (c1ii) automatically increasing the load Q.sub.h of the reactor, and/or [0123] (c2) greater than the computational maximum momentary load Q.sub.h,max; [0124] (c2i) indicating the operator that the load Q.sub.h exceeds the maximum momentary load; and/or [0125] (c2ii) automatically reducing the reactor load Q.sub.h.

[0126] In the method, the currently monitored process data of the reactor may include (a) current product gas exit temperature T.sub.G,exit in a gas flow channel and (b) heat duty Q.sub.fluid,i for each heat transfer surface 21.sub.1 in the gas flow channel 16.

[0127] Further, in the method monitored process data from both (a) and (b) may be used in computation of the product gas factor df.sub.i and when finding the numerical value Q.sub.h, candidate for the current computational maximum momentary load Q.sub.h,max.

[0128] The finding is performed such that, if the at least one product gas factor df.sub.i computed using currently monitored process data with a numerical model of the reactor that fails to fulfill an acceptance condition, a next numerical value Q.sub.h, candidate is automatically selected. The automatic selection is preferably done iteratively.

[0129] As a specific example, the finding may be carried out with performing the computational steps of: [0130] I: computing an estimate for product gas exit temperature T.sub.G, exit that results in a computational model when the thermal load of the reactor corresponds to the numerical value Q.sub.h, candidate; [0131] II: computing gas mass flow q.sub.m,fluegas; [0132] III: computing a heat duty Q.sub.fluid, i, candidate for each heat transfer surface 21.sub.1 in the flue gas flow channel (back pass 16) using its current heat duty Q.sub.fluid, i, current that is corrected by using a numerical boiler model Q.sub.fluid, i, candidate=Q.sub.fluid,i,current+.sub.j,i(Q.sub.h,candidate).sup.j.sub.j,i(Q.sub.h,current).sup.j; [0133] IV: using the computed heat duties Q.sub.fluid, i, candidate for each heat transfer surface 21.sub.i in the gas flow channel 16 to compute gas temperatures at each heat transfer surface (T.sub.G,in,i, T.sub.G,out,i; i=1, . . . , k) in the gas flow channel 16 in the upstream direction of gas flow, starting from the heat transfer surface 21.sub.k that is closest to the flue gas exit i.e. using the estimate for the gas exit temperature T.sub.G,out,m=T.sub.G, exit; and [0134] V: computing a product gas factor df.sub.i, i=1, . . . , k for each heat transfer surface 21.sub.i in the flue gas flow channel (back pass 16).

[0135] The fitting of the parameters (a.sub.j,i) can be done manually by human or automatically by computer utilizing historical data. Automatic update of the parameters may be done, e.g., once per month. AI and neural network-based algorithms can be utilized in automatic update.

[0136] Step (II) may include computing product gas mass flow q.sub.m,G,m for selected flue gas components.

[0137] The gas temperatures at each heat transfer surface can be computed, for instance:

[00011]$T_{G,\mathrm{in},i}=T_{G,\mathrm{out},i}+\frac{Q_{\mathrm{fluid},i}}{q_{m,G}*c_p}$

wherein T.sub.G,in,i is the flue gas temperature at the inlet of ith heat transfer surface, c.sub.p is specific heat capacity, and T.sub.G,out,i is the flue gas temperature at the outlet of ith heat transfer surface. The flue gas temperatures could be determined with artificial intelligence tools. The flue gas temperatures could be determined with neural network.

[0138] Preferably, the product gas factor df.sub.i includes or is:

[00012]${\mathrm{df}}_i={k_i\left(q_{m,G}/\left({}_{G,I}{A}_{\mathrm{cross},i}\right)\right)}^n$ [0139] where k.sub.i is a predetermined non-zero parameter that may be chosen combustion-boiler specifically, preferably positive (non-zero) number, [0140] q.sub.m,G is a flue gas mass flow, [0141] n is a positive number (which may be selected as a natural number, rational number, real number, or even as complex number), [0142] p.sub.G,i is flue gas density obtainable from flue gas temperature T.sub.G, in, i at i.sup.th heat transfer surface 21.sub.i and A is a cross section of flue gas channel at i.sup.th heat transfer surface 21.sub.i. [0143] (i) Advantageously, n may be selected to include at least one of the following: in the range of 0.9 to 1.1, preferably equivalent or about 1.0, for using computed gas velocity; [0144] (ii) in the range of 2.9 to 3.5, preferably between 3.2 and 3.35, for using computed gas caused erosion; or [0145] (iii) in the range of 1.8 to 2.2, preferably equivalent or about 2.0, for using pressure loss.

[0146] The value for n may be changed over time. In particular, the value for n may be determined from a group of reactors, the group comprising at least two separate reactors 10, such that using operational data monitored for each of the reactors 10 is used in the determination.

[0147] In the computation in step (I), the computational value for gas exit temperature T.sub.G, exit under any chosen numerical value Q.sub.h,candidate for boiler load can be estimated by equation:

[00013]$T_{G,\mathrm{exit}}={}_0+{{}_j\left(Q_{h,\mathrm{candidate}}\right)}^j$

or, preferably, its first, second, third or higher degree approximation. The coefficients a.sub.0, a.sub.1, a.sub.2, . . . have been obtained beforehand by fitting after measuring flue gas exit temperature T.sub.G, exit values for a number of discrete reactor load Q.sub.h values.

[0148] In step (II), the computation of the components q.sub.m,G,m in case the process in the reactor is combustion of fuel preferably includes at least some, most preferably, all of the following: m=CO.sub.2, H.sub.2O, N.sub.2, SO.sub.2, O.sub.2 so as to determine gas mass flow. In other words, in step (IV) of the computation, as q.sub.m,G,m values some or all of q.sub.m,G,CO2, q.sub.m,G,H2O, q.sub.m,G,N2,q.sub.m,G,SO2,q.sub.m,G,O2 may be used. They are preferably measured in gas conduit 18 or in stack 19, for which reason suitable sensors are installed in the gas passage. In step (II), the component values may further include reactant (such as fuel of alkali oxide, like CaO) parameters.

[0149] In case of the reactor is for combustion process the product gas, i.e., flue gas mass flow may be based on computation of sums of flue gas component mass flows q.sub.m,G,m which are calculated based on fuel analysis (proximate and ultimate analysis of fuel), combustion air flow and/or recirculation gas flow according to boiler mass and energy balance calculation.

[0150] Preferably, the flue gas mass flow may be computed:

[00014]$q_{m,G}=.Math.q_{m,G,i}$

i.e., for example, the sums of the following flue gas mass flow components CO.sub.2, H.sub.2O, N.sub.2, SO.sub.2 and O.sub.2:

[00015]$q_{m,G,\mathrm{CO}2}=x_{C,\mathrm{fuel}}*\frac{M_{\mathrm{CO}2}}{M_C}*q_{m,\mathrm{fuel}}{q}_{m,G,H2O}=0.5*x_{H,\mathrm{fuel}}*\frac{M_{H2O}}{M_H}*q_{m,\mathrm{fuel}}+x_{H2O,\mathrm{fuel}}*q_{m,\mathrm{fuel}}+x_{\mathrm{moist},\mathrm{air}}*q_{m,\mathrm{air}}{q}_{m,G}=0.5*x_{N,\mathrm{fuel}}*q_{m,\mathrm{fuel}}+x_{N2,\mathrm{air}}*q_{m,\mathrm{air}}{q}_{m,G,\mathrm{SO}2}=x_{S,\mathrm{fuel}}*\frac{M_{\mathrm{SO}2}}{M_S}*q_{m,\mathrm{fuel}}{q}_{m,G,O2}=x_{O2,\mathrm{air}}*q_{m,\mathrm{air}}-q_{m,G,\mathrm{CO}2}*\frac{M_{O2}}{M_{\mathrm{CO}2}}-0.25*x_{H,\mathrm{fuel}}*\frac{M_{H2O}}{M_H}*q_{m,\mathrm{fuel}}-q_{m,G,\mathrm{SO}2}*\frac{M_{O2}}{M_{\mathrm{SO}2}}$

where, for instance, x.sub.C,fuel represents carbon in fuel, i.e., first subscript denotes component and second subscript is either fuel or combustion air referred, q.sub.m,fuel is a fuel flow, q.sub.m,air is combustion air flow and M.sub.x denotes molar mass. Advantageously, fuel properties as utilized in flue gas mass flow components and combustion air properties. Fuel moisture may be measured or calculated.

[0151] According to another embodiment of the invention, when the reactor is a thermochemical reactor, particularly, based on CaO/Ca(OH).sub.2 hydration/dehydration reaction, the flow of H.sub.2O (steam) and air as fluidization gas are the mass flows in the step (II), the computation mass flows of which the components are computed making use of hydration and dehydration reactions.

[0152] According to another embodiment of the invention, when the reactor is a waste material gasifier the gas flow determination may be provided in a same manner as in the case of the combustion process, but the gas composition may be different including also CO and H.sub.2 and some minor gasification products.

[0153] According to another embodiment of the invention, when the reactor is a so called carbon capture reactor, a fluidized be carbonator and calciner are connected with each other suitably. The reactor configured to reduce particularly CO.sub.2 from a gas to be cleaned (carbonator)by reaction with CaO and producing substantially pure CO.sub.2 (calciner) by calcination of CaCO.sub.3. The gas flow determination may be provided in a same manner as in the case of the combustion process, considering that fuel is being burned in a calciner, including gas flow of oxygen and the gas to be cleaned.

[0154] The step (b) may be performed remotely to the combustion boiler, such as, in the process intelligence system 205. Alternatively, the step (b) may be performed locally at the combustion boiler, preferably, at the EDGE server 203.

[0155] Any of the currently monitored process data and/or current load may be obtained from real-time measurements, treated by filtering, treated by averaging, computing trends or any combination of these.

[0156] The acceptance condition may include a hysteresis condition, requiring a predefined minimum change before changing the current computational maximum boiler momentary load Q.sub.h,max.

[0157] The acceptance condition preferably includes comparing the computed at least one flue gas factor df.sub.i against a respective maximum value df.sub.max,i. The maximum value df.sub.max,i is a preset value and preferably boiler specific. The numerical value Q.sub.h, candidate is rejected if the maximum value df.sub.max,i is exceeded.

[0158] In the combustion boiler 10, the furnace 12 and associated passes (horizontal pass 15 and back pass 16) define a flue gas flow path. The furnace 12 and the passes 15, 16 have a number of heat transfer surfaces 21.sub.1 in the flue gas flow path. The combustion boiler 10 also has measurement instrumentation to monitor current load Q.sub.h of the combustion boiler, and further measurement instrumentation to currently monitor process data.

[0159] The control system (DCS 201, and EDGE server 203, or DCS 201 remote process intelligence system 205, possibly under the participation of the EDGE server 203) is configured to carry out the boiler control method.

[0160] The EDGE server 203 may be configured to process the real-time measurement results for currently monitored process data and/or current load, namely by filtering, averaging, and/or computing trends.

[0161] The control system may be configured to carry out the method step (b) to determine the current computational maximum boiler momentary load Q.sub.h,max locally at the combustion boiler 10, and/or to send data to a remote, preferably cloud-based (such as, computation cloud 206), computing system (such as, process intelligence system 205) which is configured to carry out the method step (b) and return the current computational maximum boiler momentary load Q.sub.h,max to the control system. The control system may then use the display/monitor to indicate the information, such as in method step (c), to the boiler operator, such as, by displaying the information.

[0162] The EDGE server 203 may be configured to reduce amount of measurement data that is passed to the remote computing system.

[0163] A combustion boiler computation system comprises a group of combustion boilers 10, each combustion boiler 10 comprising a boiler control system (CS) comprising an EDGE server (203) system that is configured to process the real-time measurement results for currently monitored process data and/or current load, namely, by filtering, averaging, and/or computing trends, and to send the processed real-time measurement results to a remote computing system. The remote computing system is, preferably, a cloud-based computing system, configured to receive data processed from real time measurement results and to compute data using a numerical boiler model for each of the combustion boilers 10, and to return computation results for each of the combustion boilers 10. The boiler control system may be configured to adapt its function based on the computation results.

[0164] The computing system is, preferably, configured to find such a numerical value Q.sub.h, candidate for a current computational maximum boiler momentary load Q.sub.h,max for which at least one flue gas factor df.sub.i computed using currently monitored process data with a numerical model of the boiler that fulfills an acceptance condition, and selecting the numerical value Q.sub.h, candidate as the current computational maximum boiler momentary load Q.sub.h,max.

[0165] The boiler computation system may be configured to adapt or to calibrate a numerical model for a boiler using processed measurement data for the combustion boiler 10. Alternatively, or in addition, the boiler computation system may be configured to adapt or calibrate a numerical model for a combustion boiler 10 using processed measurement data collected also from other combustion boilers 10.

[0166] FIG. 5 shows a modification of the method shown in FIG. 4. Steps L1, L3, L7, L9 are the same as steps K1, K3, K9, K11, respectively, but, in step L5, the product gas factors df.sub.i can be directly computed for all heat transfer surfaces 20.sub.i: if the temperatures T.sub.G,in,i are measured using the respective temperature sensors 21.sub.i, the back-calculation will not be necessary and thus the step K7 can be omitted in the method illustrated in FIG. 5.

[0167] FIG. 6 shows in step N1 the use of possible inputs to the numerical boiler model. In step N3 the Q.sub.h,max is computed numerically using the boiler model, and in step N5, the estimated maximum load Qh,max is presented to boiler operator via a specific user interface (UI), preferably, via display/monitor 202.

[0168] FIG. 7 shows boiler momentary load Q.sub.h and computed current computational maximum boiler momentary load Q.sub.h, max, as well as the effect of using the method according to the invention during a test period. During the ten day test period, the 120 MW.sub.th boiler power obtained in average a three to six MW.sub.th higher load as outside the test period. FIG. 8 illustrates the 10 day test period in more detail.

[0169] In other words, in the control method applied to a boiler, the current computational maximum boiler momentary load Q.sub.h,max of the combustion boiler is estimated using a numerical model using determined boiler's operating parameters. The current boiler load Q.sub.h is computed using steam circuit measurement data.

[0170] Then, if the boiler load Q.sub.h is smaller than the current computational maximum boiler momentary load Q.sub.h,max, it is (i) indicated to the boiler operator that the boiler load may be increased, and/or (ii) the boiler load is automatically increased. Alternatively or in addition, if the boiler load Q.sub.h is larger than the boiler maximum momentary load Q.sub.h,max, it is (i) indicated to the boiler operator that the boiler load exceeds the boiler maximum momentary load, and/or (ii) the boiler load is automatically reduced.

[0171] Above the invention has been explained referring to a combustion process in CFB and BFB. It is clear that the invention is applicable to, for example, in CFB and BFB gasifiers as well, where, instead of flue gas, a cooled product gas is formed for use as desired. Naturally, in a gasification application the product gas is stored or delivered to a desired further processing instead of admitting to atmosphere through a stack.

[0172] The heat releasing reactor may also be, for example, a waste material gasifier reactor, or a carbon capture reactor.

[0173] The process requires controllable input flows (22, 23) arranged at suitable locations into the reactor 10, at least as follows.

[0174] Thermochemical reactor, CaO (generally alkali metal oxides) hydration: [0175] i. Reactant input, such as CaO, hydration reactor, [0176] ii. H.sub.2O (steam) input, [0177] iii. Ca(OH).sub.2 dehydration reactor, and [0178] iv. Air input.
Waste gasifier reactor: [0179] i. Corresponding input flows as in combustion process, and [0180] ii. CO and H.sub.2 and some minor gasification products.

[0181] According to another embodiment of the invention, when the reactor is a so-called carbon capture reactor, including a fluidized bed carbonator and calciner connected with each other suitably, which may be arranged in a CFB reactor as shown in the FIG. 1. The reactor configured to reduce particularly CO.sub.2 from a gas to be cleaned (carbonator)by reaction with CaO and producing substantially pure CO.sub.2 (calciner) by calcination of CaCO.sub.3. The gas flow determination may be provided in a same manner as in a case of the combustion process, considering that fuel is being burned in a calciner, including gas flow of oxygen and the gas to be cleaned.

[0182] FIG. 9 depicts a heat releasing reactor 10 according to an embodiment of the invention. The heat releasing reactor may be for example thermochemical reactor, such as CaO (generally alkali metal oxides) hydration reactor. The reactor 10 comprises a reactor chamber 12 that is enclosed by walls 13, which may be optionally cooled walls connected to fluid circuit for extracting heat from process practiced in the reactor chamberdepending on the practical application.

[0183] Reactant is fed into the reaction chamber 12 via a reactant inlet 22. The reaction can be adjusted by controlling the reactant feed inlet 22, and, generally, by controlling the process variables which relate the heat releasing process of the reactor 10.

[0184] Reaction products, which may generally be referred to as product gas, flows from the reactor chamber 12 to a gas flow channel 16. The reactor 10 may be also provided with an outlet 22 for solid material which has at least partially reacted in the reactor chamber 12. It is described here as a vertical pass, but it may as well be differently designed, such as horizontally. From the product gas flow channel, the product gas is led to further processing 19, which may comprise simple storage, or a gas delivery pipework.

[0185] The product gas flow channel 16 comprises a number of heat transfer surfaces 21.sub.i (where I=1, 2, 3, . . . , k, where k is the number of heat transfer surfaces). In FIG. 9, heat transfer surfaces 21.sub.1, 21.sub.2, 21.sub.3, . . . , 21.sub.k-1, 21.sub.k are illustrated. The actual number of different heat transfer surfaces in each of these components, for example, may be selected for each reactor 10 differently according to actual needs.

[0186] Product gas exiting the last heat transfer surface 21k will be in exit temperature T.sub.G, exit. This temperature is measured with temperature sensor 20.sub.k.

[0187] According to one aspect, the temperatures before and after each heat transfer surface 21.sub.i (T.sub.G,in,i, T.sub.G,in,i+1, respectively) can be measured with respective temperature sensors 20.sub.i (where I=1, 2, 3, . . . , k1, k).

[0188] According to another aspect, and, preferably, these temperatures however do not necessarily need to be measured. It will suffice to know the flue gas exit temperature T.sub.G, exit. The temperatures before and after each preceding heat transfer surface 21.sub.i (T.sub.G,in,i, T.sub.FG,in,i+1) can be obtained numerically. This will be explained further below.

[0189] The reactor 10 is equipped with a plurality of sensors 40, and computer units, and only some of the sensors and computer units are presented for sake of clarity. For example, there may be sensors 40 for determining flow rate of a reactants into the reactor 10, sensor 40 indicating temperature at one or more locations in the reactor 10, sensors 40 for indicating pressure in the reactor, depending on the actual practical application of the reactor 10.

[0190] Process data may be collected from the sensors by distributed control system (DCS) 201. This is similar to that disclosed in connection with the FIG. 1, of course the combustion boiler network is instead a heat releasing network, operating in corresponding manner.

[0191] It is obvious to the skilled person that, along with the technical progress, the basic idea of the invention can be implemented in many ways. The invention and its embodiments are thus not limited to the examples and samples described above but they may vary within the contents of patent claims and their legal equivalents.

[0192] In addition, or instead of using above mentioned specific empirical equations, it is possible to utilize artificial intelligence tools and/or neural network in the numerical model computations.

[0193] In the claims that follow and in the preceding description of the invention, except where the context requires otherwise due to express language or necessary implication, the word comprise or variations such as comprises or comprising is used in an inclusive sense, i.e., to specify the presence of the stated feature, but not to preclude the presence or addition of further features in various embodiments of the invention.