Method for operating a heat-radiating reactor, heat-radiating reactor, and calculation system for a heat-radiating reactor

Abstract

Methods have been proposed to improve the control of exothermic reactors. The method comprises: a) determining the current load (Q h ), b) monitoring at least one product gas coefficient (df i ) satisfies the tolerance conditions. h,max ) to the number (Q h,candidate ), and a numerical value (Q h,candidate ) to the current calculated maximum instantaneous load (Q h,max ) as the current calculated maximum instantaneous load (Q h、max ) to the operator, and / or the current load (Q h ) is c1) the current calculated maximum instantaneous load (Q h,max ) is smaller than c1i) load (Q h and / or c1ii) a step of indicating to the operator that the load (Q h ), and / or c2) automatically increasing the current calculated maximum instantaneous load (Q h,max ) is larger than c2i) load (Q h c2ii) indicating to the operator that the load (Q h ) automatically reducing

Description

[Technical Field]

[0001] The present invention relates to operating an exothermic reactor. [Background technology]

[0002] A common technical field in which exothermic reactors are used is in fired boilers, such as grate boilers, and fluidized bed boilers are typically utilized to generate steam, which can be used for a variety of purposes, such as the production of electricity and heat.

[0003] In a fluidized bed boiler, fuel and solid particulate bed material are introduced into the furnace. The bed material and fuel are fluidized by introducing a fluidizing gas from the bottom of the furnace. The fuel is burned in the furnace. In a BFB combustion, the fluidizing gas passes through the bed to form bubbles within the bed. In a BFB, the fluidized bed can be controlled fairly easily by controlling the fluidizing gas supply and the fuel supply. In addition to the fuel, certain additives may be added to the combustion, such as aluminum silicates (e.g., non-hydrated clays), alkali alkaline earth metal carbonates, and mixtures thereof (e.g., limestone or calcium carbonate), to enhance the sorption of possible heavy metals, sulfur, and also to enhance the sorption of alkali.

[0004] In a CFB, a fluidizing gas is passed through the bed material. Most of the bed particles become entrained in the fluidizing gas and are carried along with the exhaust gas. The particles are separated from the exhaust gas in at least one particle separator and circulated back into the furnace. A fluidized bed heat exchanger is typically located downstream of the particle separator to recover heat from the particles before they are returned to the furnace.

[0005] In all boilers, regardless of combustion technology, combustion conditions such as air and fuel mixing may not be ideal.

[0006] Improbed AB's published international application WO 2016 / 202640A1 discloses a method for controlling the heat load of a fired boiler, in which the heat load of the fired boiler is reduced if the flue gas velocity monitored at at least one location in the boiler exceeds a predetermined maximum flue gas velocity limit. The flue gas velocity is calculated using a set of equations by dividing the flue gas volumetric flow rate by the cross-sectional area of ​​the flue gas duct at a location immediately downstream of the cyclone.

[0007] Additionally, it is known that there are other processes that produce product gases, and the temperature of the product gases needs to be controlled, which may mean heating or cooling the gas and / or the process.

[0008] Exothermic reactors are designed for a given capacity, which is the reactor's respective boiler maximum continuous rating (MCR), sometimes called the design load level. Summary of the Invention [Problem to be solved by the invention]

[0009] The first object of the present invention is to improve the performance, profitability, and flexibility of heat-dissipating reactors and to improve the control of reactor loads. The second object of the present invention is to reduce the complexity of combustion boiler control systems. [Means for solving the problem]

[0010] The first object can be achieved by a method for operating a heat-dissipating reactor as set forth in claim 1 and a heat-dissipating reactor as set forth in claim 19. The second object can be achieved by a reactor calculation system as set forth in claim 24.

[0011] The dependent claims describe advantageous aspects of the method, the reactor and the computing system. [Effects of the Invention]

[0012] A method of operating an exothermic reactor to produce a product gas includes the following steps. a) Current load Q of the reactor h monitoring the b) finding a value for the current calculated maximum instantaneous load such that at least one product gas coefficient calculated using currently monitored process data including a numerical model of the reactor satisfies the tolerance condition, and identifying this value as the current calculated maximum instantaneous load Q h,max a step of selecting as c) Current calculated maximum instantaneous load Q h、max and / or the current load Q h but, c1) If it is smaller than the current calculated maximum instantaneous load, c1i) indicating to the operator that an increased load may occur; and / or c1ii) automatically increasing the load; and / or c2) If it is greater than the current calculated maximum instantaneous load, c2i) Load Q h indicating to the operator that the current calculated maximum instantaneous load is exceeded; and / or c2ii) Load Q h automatically reducing the

[0013] In this manner, rather than fixing the maximum load, by calculating the product gas coefficient and appropriately selecting the allowable conditions for the product gas coefficient, it is possible to safely operate the reactor at or near the reactor's current calculated maximum instantaneous load, which may sometimes be higher than the fixed maximum load. The current calculated maximum instantaneous load may be higher than the design load level. Therefore, the overall performance of the reactor can be improved, and power / heat production can be increased. Furthermore, because the current calculated maximum instantaneous load may be lower than the design load level, reactor wear due to exceeding the current calculated maximum instantaneous load can be better reduced. In other words, the current calculated maximum instantaneous load can be considered the maximum allowable load and / or the preferred load.

[0014] In tests carried out with boilers, the Applicant has been able to obtain, on average, a power output from the fired boiler that exceeds the fixed boiler maximum load. In tests, the Applicant has been able to demonstrate that for fired boilers, the improvement potential can be between 2.5 and 5%. This is the case for example with a 120 MW boiler. th In the case of combustion boilers, 3 to 6 MW th is equivalent to

[0015] In this method, it is preferable that: i) the currently monitored process data of the reactor, ia) the current product gas outlet temperature in the product gas flow path; ib) Heat duty for each heat transfer surface in the generated gas flow path and ii) The monitored process data from both steps ia) and ib) are used to calculate the product gas coefficient and the current calculated maximum instantaneous load Q h,max It is used when finding a numerical value for .

[0016] Calculating the heat load of a heat exchanger is known to those skilled in the art, and the heat load can be obtained, for example, by using the following formula: Qfluid,i =q m,fluid,i ×(h fluid,out -h fluid,in ) where q m,fluid,i is the fluid flow rate at the ith heat transfer surface, h fluid,in is the enthalpy of the fluid entering the ith heat transfer surface, h fluid,out is the enthalpy of the fluid leaving the ith heat transfer surface.

[0017] This discovery can be implemented such that if at least one product gas coefficient calculated using currently monitored process data, including a numerical model of the reactor, fails to meet the tolerance criteria, a next value is automatically selected. Preferably, the next value is selected iteratively. This can enable the use of computational library functions, specifically iterative solvers (such as Python's FSOLVE function, which solves the roots of a function).

[0018] This finding can be done by performing the following computational steps: - I: calculating an estimate of the boiler product gas outlet temperature, which results in a computational reactor model when the reactor heat load is matched to the numerical value; - II: calculating the product gas mass flow rate; - III: calculating the heat load of each heat transfer surface in the exhaust gas flow path using the current heat load corrected by using a numerical boiler model; - IV: Using the calculated heat load for each heat transfer surface in the product gas flow path, calculate the product gas temperature at each heat transfer surface, starting with the heat transfer surface in the product gas flow path closest to the product gas outlet in the upstream gas flow direction, using the estimated exhaust gas outlet temperature; - V: A process for calculating the gas generation coefficient for each heat transfer surface in the exhaust gas flow path.

[0019] Using this technique, the condition of each heat transfer surface (herein "heat transfer surface" means a heat exchanger, heat exchanger tube, heat exchanger tube bundle, heat exchanger package, and / or heat exchanger configuration group) in the product gas flow path can be numerically estimated using the product gas coefficients when the reactor heat load matches the numerical value. Therefore, it is now possible to test whether a specific numerical value that is a candidate for the current calculated maximum instantaneous load will produce an acceptable condition for the heat transfer surface.

[0020] According to one embodiment of the present invention, in step III), the numerical reactor model is fluid,i,candidate =Q fluid,i,current +Σα j,i (Q h,candidate ) j -Σα j,i (Q h,current ) j It is a model of the form:

[0021] parameter (α j,i ) can be fitted manually by a human or automatically by a computer using historical data. Automatic updates of the parameters may occur, for example, monthly. AI and neural network-based algorithms can be used in the automatic updates.

[0022] In particular, when applied to a fuel-fired boiler, unlike the method disclosed in WO 2016 / 202640 A1, the present invention makes it possible to predict the current maximum boiler load that is mathematically allowable without reaching a limit at the current boiler load, while, even more importantly, it makes it possible to reach a limit without exceeding the current boiler load that is mathematically allowable.

[0023] Preferably, the gas production factor includes or is less than or equal to: df i =k i (q m,productgas / (ρ productgas,i ×A cross,i )) n where: k i is a non-zero parameter, preferably a positive (non-zero) number, that may be selected in particular for a combustion boiler; q m,productgas is the mass flow rate of the product gas, n is a model parameter, preferably a positive (non-zero) number, that can be specifically selected for the reactor; ρ productgas,i is the density of the product gas at the ith heat transfer surface, A cross,i is the cross-sectional area of ​​the gas flow passage at the ith heat transfer surface.

[0024] This selection of functional form for the product gas coefficient is particularly advantageous because it allows the product gas coefficient to be very flexible and easily adapted to suit various reactor operating needs, such as based on the current reactant conditions being used in the reactor. i) The model parameter n is particularly advantageous because it can be selected to be at least one of the following: in the range of 0.9 to 1.1, preferably about 1.0, when using calculated product gas rates; ii) When using a calculated product gas that causes corrosion, the range is 2.9 to 3.5, preferably between 3.2 and 3.35; or iii) The pressure drop of the product gas flow, if used, is in the range of 1.8 to 2.2, preferably about 2.0.

[0025] The value of n can be changed over time. This is advantageous if the reactor is a fluidized bed reactor because the exhaust gas flow conditions at the heat transfer surfaces can change over time due to fouling, ash agglomeration, or reactant or bed conditions. The product gas coefficient can therefore be shifted over time to better reflect actual process conditions.

[0026] According to one embodiment of the present invention, when n=2 and the generated gas coefficient represents the pressure loss, the generated gas coefficient df iand the maximum value of the gas production coefficient df max,i The comparison with can be performed for each heat transfer surface. The acceptable condition, according to one embodiment, is substantially df i =df max,i is.

[0027] According to one embodiment of the present invention, when n=2 and the production gas coefficient represents the pressure loss, the exhaust gas coefficient df i The sum of dp tot =Σdf i and the predetermined gas production coefficient df max,i or the given product gas coefficient simply represents the total pressure drop, and thus the comparison represents a comparison of the total pressure drop between the reactor and the stack. The permissive condition, according to one embodiment, is substantially dp tot =dp max,tot is.

[0028] The gas production factor, according to one embodiment of the present invention, represents the particle deposition factor and can be written in the following form: df i =k ph C(d)q m_fa v p n where k ph is the particle hardness coefficient, C(d) is the particle diameter function, q m_fa is the particle mass flow rate, v p is the particle velocity, and n is a power exponent (0, 3 to 4). A given gas production coefficient represents the maximum particle deposition value in this case. The particle deposition coefficient can also be adjusted based on particle characteristics (softness, etc.).

[0029] The reactor, according to certain embodiments of the present invention, is a fluidized bed (FB) reactor, such as an FB boiler or an FB gasifier, and the product gas coefficient represents the ash deposition coefficient and can be written in the following form: df i =k ph C(d)q m_fa v pn where k ph is the particle hardness coefficient, C(d) is the particle diameter function, q m_fa is the mass flow rate of fly ash, v p is the particle velocity, and n is a power exponent (0, 3-4). A given exhaust gas coefficient represents the maximum ash deposition value in such cases. The ash deposition coefficient can also be adjusted based on the ash characteristics (softness, etc.).

[0030] The permissive condition, according to one embodiment of the present invention, is substantially df i =df max,i However, in a practical situation, the acceptable conditions can be defined as follows: df max,i -δ <df i ≦df max,i where δ>0 and depends on numerical precision and / or method. max,i -δ <df i ≦df max,i means that at least one product gas coefficient calculated using currently monitored process data, including a numerical model of the reactor, satisfies the tolerance condition, and in such a case, the maximum allowable load is found, and therefore the value Q h,candidate However, the maximum instantaneous load Q h,max is selected as.

[0031] The admissibility condition, according to one embodiment of the present invention, is substantially Σ(df i )=Σ(df max,i ), but in a practical situation, the tolerance condition can be defined using the sum of Σ(df max,i )-δ<Σ(df i )≦Σ(df max,i ) where δ>0 and depends on the numerical precision and / or method. Σ(df max,i )-δ<Σ(df i )≦Σ(df max,i) means that at least one product gas coefficient calculated using currently monitored process data, including a numerical model of the boiler, satisfies the allowable condition, and in such a case, the maximum allowable load is found, and therefore the value Q h,candidate However, the maximum instantaneous load Q h,max According to one embodiment, the summation index i is over all of the heat transfer surface. According to another aspect of the invention, the summation index i is over only a portion of the heat transfer surface, preferably within the product gas channel.

[0032] It is particularly useful if the value of n is determined using monitored operational data for each of the reactors from a reactor population containing at least two separate reactors. Using a larger number of reactors (two, three, four, etc.) results in a larger data set; therefore, more operational data is monitored. This can produce better results and may be particularly advantageous in situations where interpolation and / or extrapolation of experimental data is used in the determination.

[0033] The product gas outlet temperature can be substantially estimated in the calculation of step I) by the following formula: T G,exit =α0+Σα i Q i h,candidate Alternatively, it is preferable to estimate the coefficient α using a first-, second-, third-, or higher-order approximation of the above equation. The coefficient α can be obtained by fitting after measuring the product gas outlet value for several individual reactor load values. This data can be collected over time and updated as needed, such as periodically. Alternatively or additionally, this data can be collected when performing one or more calibrations of the reactor.

[0034] The coefficient (α) can be applied manually by a human or automatically by a computer using historical data. Automatic updates of the coefficients may be performed, for example, once a month. AI and neural network-based algorithms can be used for the automatic updates.

[0035] According to one embodiment of the present invention, the product gas outlet temperature can be substantially estimated in step I) by utilizing an artificial intelligence tool. According to another embodiment of the present invention, the product gas outlet temperature can be substantially estimated in step I) by utilizing a neural network.

[0036] The product gas outlet temperature can be estimated in step I) according to one embodiment of the present invention by the following formula: T G,exit =α0+α1×Q h,candidate +α2×Q h,candidate 2 where α0, α1, and α2 can be predefined constants. Alternatively or additionally, the coefficients (α) can be fitted manually by a human or automatically by a computer using historical data. Automatic updating of the coefficients may be performed, for example, once a month. AI and neural network-based algorithms can be used for the automatic updating.

[0037] According to one embodiment of the present invention, the α 0 term can be solved based on the current state values. α0=T G,exit,current -α1×Q h,current -α2×Q h,current 2 where T G,exit,current represents the measured product gas outlet temperature.

[0038] The product gas mass flow rate is calculated in step II) according to one embodiment of the present invention using the reactor mass and energy balance equations.

[0039] In step II), the calculation of the product gas mass flow rate may include taking into account the gas-specific mass flow rates of the components of the product gas. In the case of a combustion process, these components include CO2, H2O, N2, SO2, and O2. The concentrations of these components can be reliably measured using fairly simple equipment.

[0040] In step II), the component values ​​can include reactant parameters, which can reflect changes in reactant properties. For example, for reactants that tend to cause more corrosion, tighter tolerances can be used, while for reactants that tend to cause less corrosion, leaner tolerances can be used.

[0041] Step b) may be performed remotely relative to the reactor, preferably in a cloud-based computing service. This helps simplify maintenance of the combustion boiler, since a remote computing device, such as one configured to run the cloud-based computing service, can be maintained separately from the combustion boiler. Updates to the computing software, for example, can thereby be performed centrally in one or a few locations, rather than updating the software at each reactor.

[0042] Step b) may alternatively be performed locally at the reactor site, preferably by an edge server, which may speed up the computation as data does not need to be transferred to a remote computation location.

[0043] Either the currently monitored process data and / or the current load may be obtained by real-time measurement. Alternatively, or in addition, the currently monitored process data and / or the current load may be processed by filtering, averaging, calculating trends, or any combination thereof. This helps to avoid noisy or outlier measurements that affect the calculation results, thereby facilitating increased stability of the currently calculated maximum instantaneous load.

[0044] The tolerance condition may include a hysteresis condition that requires a predetermined minimum change before changing the current calculated maximum boiler instantaneous load, which is preferable because it can increase the stability of the current calculated maximum instantaneous load and help avoid excessive fluctuations in the current calculated maximum instantaneous load.

[0045] The applicant has discovered that it is also useful if the fired boiler is a circulating fluidized bed (CFB) or bubbling fluidized bed (BFB) boiler, or more generally a CFB and BFB reactor, and step b) is carried out on the heat transfer surface of the fluidized bed reactor.

[0046] Step b) is, according to one embodiment, carried out on a heat transfer surface located between the reactor and the chimney.

[0047] The exothermic reactor comprises: - a reactor chamber and associated passages defining a product gas flow path and comprising several heat transfer surfaces; - Measuring equipment, monitoring the current load of the exothermic reactor, - separate measuring devices to monitor current process data, as well as - a control system configured to perform the method for operating an exothermic reactor.

[0048] The exothermic reactor, according to one embodiment, comprises a reactor chamber and associated passages that define a gas flow path and include several heat transfer surfaces within the gas flow path.

[0049] Such an exothermic reactor allows for improved aspects of reactor control, the advantages of which are the same as those of the method of operating an exothermic reactor.

[0050] The control system may include an edge server that may be configured to process real-time measurements of currently monitored process data and / or current loads, i.e., by filtering, averaging, and / or calculating trends. The edge server may facilitate reducing the amount of currently monitored process data. This may be particularly useful in light of the fact that in certain installations, there may be 60-90 gigabytes of monitored process data each day.

[0051] The control system may be configured to perform step b) of the method to locally determine the current calculated maximum instantaneous load, which may facilitate rapid decision making at the reactor as less or no data may need to be transferred from the reactor.

[0052] Alternatively or additionally, the control system may be configured to transmit the data to a remote, preferably cloud-based, computing system that may be configured to perform step b) of the method and return the current calculated maximum boiler instantaneous load to the control system. This makes it easier to simplify the reactors and to update the computing system. Updates can be performed centrally in this situation, rather than in each and every reactor.

[0053] The edge server can be configured to reduce the amount of measurement data passed to the remote computing system. In this way, a smaller bandwidth may be sufficient for data transfer. This can be particularly useful considering the fact that in certain installations, there may be 60-90 gigabytes of monitored process data each day.

[0054] The reactor calculation system comprises: - a group of reactors comprising a reactor control system, each reactor comprising an edge server system configured to process real-time measurements of currently monitored process data and / or current loads by filtering, averaging, and / or calculating trends, and to transmit the processed real-time measurements to a remote computing system; - a remote computing system, preferably a cloud-based computing system, configured to receive processed data from the real-time measurements, calculate the data for each of the reactors using a numerical reactor model, and return the calculated results to the respective reactor.

[0055] In the reactor calculation system, the control system is further configured to adapt the function of the reactor control system based on the calculation results.

[0056] The advantage of this configuration is that it reduces the need for computing devices in the reactor, while still allowing efficient and fast computational results to be obtained from a remote computing system.

[0057] The computing system may be configured to find a numerical value or current calculated maximum instantaneous load for which at least one product gas coefficient calculated using currently monitored process data including a numerical model of the reactor satisfies an acceptable condition, and select this numerical value as the current calculated maximum instantaneous load, which essentially allows the method of the present invention to be used in a distributed environment.

[0058] The reactor calculation system may be configured to use the processed measurement data of the reactor to calibrate a numerical model of the reactor, such as a product gas coefficient numerical model, making it easier to remotely adapt or calibrate the numerical model of reactor control.

[0059] The reactor calculation system may be configured to use collected and processed measurement data from other reactors to adapt or calibrate the numerical model of the reactor, allowing more collected data to be used to adjust the numerical model of reactor control.

[0060] The present invention is applicable for use in a variety of processes and reactors involving heat production and heat recovery.

[0061] The present invention is applicable for use with thermochemical reactors to control the load of the thermochemical reactor, which is the rate at which energy is charged and discharged from the reactor.

[0062] The present invention is further applicable for use with waste gasifiers that control the heat generated during the thermochemical destruction of waste while producing gases that can be further synthesized in subsequent synthesis processes to make fuels and chemicals.

[0063] The present invention is further applicable for use with so-called carbon capture processes, such as controlling the load of a loop carbon capture reactor (e.g., a calcium loop reactor) for additional heat production while capturing CO from a gas stream.

[0064] The reactor and reactor control method are described in more detail below in connection with the embodiments shown in the accompanying drawings of FIGS. [Brief explanation of the drawings]

[0065] [Figure 1] FIG. 1 is a diagram showing a CFB boiler. [Figure 2] FIG. 1 is a diagram showing a BFB boiler. [Figure 3] FIG. 2 is a diagram showing the flow of measurement data from a sensor. [Figure 4] 1 is a flow chart illustrating a first method for finding the current calculated maximum boiler instantaneous load Qh,max. [Figure 5]10 is a flow chart illustrating a second method for finding the current calculated maximum boiler instantaneous load Qh,max. [Figure 6] FIG. 10 illustrates how the current calculated maximum boiler instantaneous load Qh,max can be presented to the boiler operator. [Figure 7] 1 is a graph showing the boiler instantaneous load Qh and the calculated current maximum calculated boiler instantaneous load Qh, max, and the effect of using the method according to the invention during a test period. [Figure 8] Looking more closely at the data in Figure 7, the effect of using the method of the present invention becomes more apparent. Figure 7 is a graph showing the boiler instantaneous load Qh, the calculated current maximum calculated boiler instantaneous load Qh,max during the 10-day test period. [Figure 9] FIG. 2 illustrates another exothermic reactor according to one embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0066] In all figures, the same reference numbers refer to the same technical features.

[0067] FIG. 1 shows a combustion boiler 10 operating as a heat-generating heat-dissipating reactor in the form of a circulating fluidized bed reactor (CFB). The CFB reactor can be used as a combustor / steam generator, a carbon capture reactor using a calciner and / or carbonator, as well as a waste gasifier. The CFB reactor, specifically referred to in the following description as a circulating fluidized bed (CFB) boiler, comprises a furnace 12 with a tube wall 13 connected to the steam circuit of the combustion boiler 10. Water is supplied from a water tank (not shown) to an economizer, from which it is supplied via a steam drum to an evaporative heat transfer surface such as the tube wall 13, and then conducted via the steam drum to a superheater and then to a turbine. The exhaust gas channel may be provided with an economizer and / or a superheater.

[0068] Fluidizing gas (such as air and / or oxygen-containing gas) is supplied from a fluidizing gas supply 153 through a wind box (not shown) below the grate (the grate is not shown in FIG. 1 ). Primary fluidizing air enters the furnace from below the grate through a nozzle (not shown) (for fluidizing the bed) and a secondary fluidizing gas supply 152 (which supplies oxygen-containing gas to control combustion). As a result, the bed medium is fluidized and oxygen necessary for combustion is also supplied to the furnace 12. Furthermore, fuel is supplied to the furnace 12 via a fuel supply 22. Combustion can be adjusted by controlling the fuel supply 22 (e.g., by decreasing or increasing the fuel supply) and the fluidizing gas supply (e.g., by decreasing or increasing the amount of oxygen supplied to the furnace 12). The fuel can be supplied together with an additive, specifically, an additive that acts as an alkali sorbent, such as CaCO and / or clay. Additionally or alternatively, a NOx reducing agent such as ammonium or urea may be provided in or above the combustion zone of the furnace 12 .

[0069] A bed medium is also provided within the furnace and may include sand, limestone, and / or clay, the latter of which may specifically include kaolin. As a result of the bed, and generally of combustion, in the steam circuit, water and steam are heated within the tube walls 13, converting the water to steam.

[0070] The ash falls to the bottom of the furnace 12 and is removed via an ash chute (omitted from Figure 1 for clarity), and a portion of the ash, the so-called fly ash, is carried away with the exhaust gases.

[0071] Combustion products such as exhaust gas, unburned fuel, and bed media pass from the furnace 12 to a particle separator 17, which may include a vortex finder 103. The particle separator 17 separates the exhaust gas from the solids. Particularly in larger combustion boilers 10, there may be multiple (two, three, ...) separators 17, preferably arranged parallel to one another.

[0072] The solids separated by the separator 17 pass through a loop seal 160, preferably located at the bottom of the separator 17. The solids then proceed to a fluidized bed heat exchanger (FBHE) 100, which also serves as a heat transfer surface, whereby the FBHE 100 collects heat from the solids and further heats the steam in the steam circuit. The chamber within which the FBHE 100 is located can be fluidized, and the FBHE 100 itself comprises heat transfer tubes or other types of heat transfer surfaces. The FBHE 100 can be configured as a reheater or superheater. Steam is sent from the FBHE outlet 101 into a high-pressure turbine (if the FBHE 100 is a superheater) or an intermediate-pressure turbine (if the FBHE 100 is a reheater). For clarity, the turbines are not shown in FIG. 1. The solids can be returned from the FBHE 100 to the furnace 12 through a return channel 102. In particular, in larger combustion boilers 10, there may be multiple (two, three, etc.) loop seals 160 and FBHEs 100, and return channels 102, preferably arranged parallel to one another, so that there is a respective loop seal 160, FBHE 100, and return channel 102 for each separator 17. In practice, some of the FBHEs 100 may be arranged as superheaters and some may be arranged as reheaters.

[0073] From the separator 17 the flue gas is passed into a horizontal passage 15 from which it is passed further into a rear flue 16 (which may preferably be a vertical passage) from which it is passed through a flue gas conduit 18 to a chimney 19 .

[0074] The rear flue 16 is connected to several heat transfer surfaces 21 i (i=1, 2, 3, . . . , k, where k is the number of heat transfer surfaces). k-1 ,twenty one k The heat transfer surface 21 k indicates an air preheater. Heat transfer surface 21 k-1, 212 denote superheaters, and heat transfer surfaces 211, 213 denote reheaters. The actual number of different heat transfer surfaces in each of these components can be selected differently for each combustion boiler, for example, depending on the actual needs. Also, other components with heat transfer surfaces 21 may be present as well.

[0075] Last heat transfer surface 21 k The exhaust gas exiting from the G,exit This temperature is measured by the temperature sensor 20 k It is measured in

[0076] According to one embodiment, each heat transfer surface 21 i The temperatures before and after (T G,in,i , T G,in,i+1 ) are the temperature sensors 20 i (i=1, 2, 3, . . . , k-1, k).

[0077] However, in another embodiment, it is preferable that these temperatures do not necessarily need to be measured. G,exit It will be sufficient to know the above-mentioned heat transfer surfaces 21 i The temperature before and after (T G,in,i , T G,in,i+1 ) can be obtained numerically, as will be explained further below.

[0078] The combustion boiler 10 is equipped with a number of sensors and computer units. th ) A combustion boiler 10 may generate 100 million measurements per day, which requires 25 GB of storage space. Figures 1, 2, and 3 show some sensors and computer units. Example sensors include a combustion gas (usually combustion air) volumetric flow sensor 30 (to measure the primary and secondary fluidization gas supply), a fuel supply sensor 650, and a temperature sensor 20. i(i=1, 2, . . . , k), there is a temperature sensor in the FBHE and a pressure sensor 116 in the return channel 102 (both present only in CFB boilers), as well as a sensor 40 in the furnace 12 .

[0079] Process data may be collected from the sensors by a distributed control system (DCS) 201. The data collection may be most conveniently located, for example, via a fieldbus 290. The DCS 201 may include a display / monitor 202 for displaying operational status information to an operator. An edge server 203 may process, such as filtering and smoothing, the measurement data obtained from the sensors. There may be local storage 204 for storing the data.

[0080] The DCS 201, display / monitor 202, edge server 203, and local storage 204 may be within a combustion boiler / network 280 (with local storage 204 preferably connected directly to the edge server). The combustion boiler network 280 is preferably independent of the fieldbus 290 used to communicate measurements from sensors to the DCS 201 and / or edge server 203. There may be an open platform communication server 210 (see FIG. 3) between the DCS 201 and edge server 203 to further enhance system interoperability.

[0081] The combustion boiler network 280 may be connected to the Internet 200, preferably via a gateway 290. Measurement results, in this situation, may be transferred from the combustion boiler network 280 to a cloud service, such as a process intelligence system 205 located in a computational cloud 206. Applicant currently operates a cloud service that runs the analytics platform. The cloud service may be operated in a virtualized server environment, such as Microsoft® Azure®, which is a virtualized, easily scalable environment for distributed computing and cloud storage of data. Other cloud computing services may also be suitable for running the analytics platform. Furthermore, a local or remote server may be used to run the analytics platform instead of or in addition to the cloud computing service.

[0082] 2 shows a heat-dissipating reactor that is a bubbling fluidized bed (BFB) boiler, a fired boiler 10. BFB boilers differ from CFB boilers in that the fluidized bed is a bubbling bed rather than a circulating bed. Therefore, the separator 17, loop seal 160, FBHE 100, and return channel 102 may not be necessary.

[0083] Typically, there is at least one superheater 14 within the furnace 12, preferably in the upper portion of the furnace 12. The inlet 141 of the superheater 14 is from a steam drum or another superheater, and the outlet 142 is preferably to a high pressure turbine.

[0084] FIG. 4 illustrates a method of operating an exothermic reactor to produce a product gas. a) the current load Q of the reactor 10 (combustion boiler, gasification reactor, liquid air energy store, hydration reactor, etc.) h is monitored in step K1 (in the method shown in FIG. 4, the product gas outlet temperature T G,exit , and the heat transfer surface 21 in the gas flow path 16 i Heat load Q for each heat dissipation fluid fluid,i are also monitored. b) Number Q h,candidate is selected (step K3), and then the heat transfer surface 21 i Heat load at, and Q h,candidate The gas temperature is then calculated for the number Q h,candidate Using currently monitored process data, including a numerical model of the reactor, that meets the tolerance conditions (tested in step K9), at least one product gas coefficient df i (sometimes called the exhaust gas coefficient in relation to the combustion process) is calculated (step K7), and the value Q h,candidate is the current calculated maximum instantaneous load Q of the reactor 10. h,max (Step K11). c) Current calculated maximum instantaneous load Q h、max is shown to the operator (such as by displaying on the monitor / screen 202), and / or the current load Q h but, c1) Calculated maximum instantaneous load Q h,max If it is less than c1i) Boiler load Q h Indicate to the operator that there may be an increase in c1ii) Reactor load Q h automatically increases, and / or c2) Calculated maximum instantaneous load Q h,max If it is greater than c2i) Load Q h indicates to the operator that the maximum instantaneous load has been exceeded, and / or c2ii) Reactor load Q h is automatically reduced.

[0085] In this method, the currently monitored reactor process data includes: a) the current product gas outlet temperature T G,exit and b) the heat transfer surface 21 in the gas flow path 16. i per heat load Q fluid,i may be included.

[0086] The method further comprises: determining whether the monitored process data from both a) and b) is a product gas coefficient df i When calculating the maximum instantaneous load Q h,max For the number Q h,candidate It can be used when discovering

[0087] This finding is based on the calculation of at least one product gas coefficient, df, calculated using currently monitored process data including a numerical model of the reactor. i If the following number Q cannot satisfy the tolerance condition, h,candidate is automatically selected. The automatic selection is preferably performed iteratively.

[0088] This finding can be done, as an example, by performing the following calculation steps: - I: The reactor heat load is Q h,candidate The calculated model results in a product gas outlet temperature T that is consistent with G,exit calculating an estimate of - II: Gas mass flow rate q m,fluegas A process of calculating - III: Heat transfer surface 21 in the exhaust gas flow path (rear flue 16) i Heat load Q per fluid,i,candidate , the numerical boiler model, Q fluid,i,candidate =Q fluid,i,current +Σα j,i (Q h,candidate ) j -Σα j,i (Q h,current ) j The current heat load Q on the heat transfer surface, corrected by using fluid,i,current A process of calculating using - IV: Heat transfer surface 21 in gas flow path 16 i Calculated heat load Q per fluid,i,candidate The heat transfer surface 21 in the gas flow path 16 is closest to the exhaust gas outlet in the upstream direction of the gas flow. k From this, the estimated gas outlet temperature T G,out,m =T G,exit The gas temperature at each heat transfer surface (T G,in,i, T G,out,i , i=1,...,k). - V: Heat transfer surface 21 in the exhaust gas flow path (rear flue 16) i per unit gas production coefficient df i , i=1,···, k.

[0089] parameter (α j,i ) can be fitted manually by a human or automatically by a computer using historical data. Automatic parameter updates may be performed, for example, once a month. AI and neural network-based algorithms can be used for the automatic updates.

[0090] In step II), for the selected exhaust gas components, the product gas mass flow rate q m,G,m It may include calculating:

[0091] The gas temperature at each heat transfer surface can be calculated, for example, using the following formula:

[0092]

number

[0093] Preferably, the gas production factor includes or is less than or equal to: df i =k i (q m,G / (ρ G,I A cross,i )) n where k i is a predetermined non-zero parameter, preferably a positive (non-zero) number, that can be specifically selected for a combustion boiler; q m,G is the mass flow rate of the exhaust gas, n is a positive number (which may be chosen as a natural number, a rational number, a real number, or even a complex number), ρ G,i is the i-th heat transfer surface 21 i Exhaust gas temperature T G,in,i is the exhaust gas density obtained from A is the i-th heat transfer surface 21 i is the cross-sectional area of ​​the exhaust gas channel at

[0094] i) n can advantageously be chosen to be at least one of the following: in the range of 0.9 to 1.1, preferably equal to or about 1.0, when using calculated gas velocities; ii) When using a calculated corrosion-causing gas, the range is 2.9 to 3.5, preferably between 3.2 and 3.35; or iii) When pressure drop is used, it is in the range of 1.8 to 2.2, preferably equal to or about 2.0.

[0095] The value of n can be varied over time. The value of n can be specifically determined from a group of reactors, where the group includes at least two separate reactors 10, and thus the determination uses monitored operational data for each reactor 10.

[0096] In the calculation of step I), an arbitrary value Q selected for the boiler load h,candidate Under this condition, the gas outlet temperature T G,exit The calculated value of can be estimated by the following formula: T G,exit =α0+Σα j (Q h,candidate ) j Alternatively, it is preferable to estimate the above equation using a first-order, second-order, or third-order or higher approximation equation. The coefficients α0, α1, α2, ... are the individual reactor loads Q h The exhaust gas outlet temperature T G,exit The values ​​of are measured and then obtained in advance by fitting.

[0097] In step II), if the process in the reactor is the combustion of fuel, the component q is used to determine the mass flow rate of the gas. m,G,m It is preferred that the calculation of m = CO2, H2O, N2, SO2, O2 includes at least some, most preferably all of them. In other words, in step IV) of the calculation, q m,G,m As the value of q m,G,CO2 , q m,G,H20 , q m,G,N2 , q m,G,SO2 , q m,G,O2 may be used. These are preferably measured in the gas conduit 18 or chimney 19, for which purpose suitable sensors are installed in the gas passage. In step II), the component values ​​may further include parameters of the reactants (such as alkali oxide fuels, such as CaO).

[0098] If the reactor is for a combustion process, the mass flow rate of the product gas, i.e., the exhaust gas, is calculated based on the fuel analysis (proximate and final fuel analysis), the combustion air flow rate, and / or the recirculation gas flow rate from the boiler mass and energy balance calculations. m,G,m The calculation may be based on the sum of

[0099] The mass flow rate of the exhaust gas may preferably be calculated by the following formula: q m,G =Σq m,G,i That is, for example, the sum of the following exhaust gas mass flow components CO2, H2O, N2, SO2, and O2.

[0100]

number

[0101] According to another embodiment of the invention, when the reactor is a thermochemical reactor, especially based on the CaO / Ca(OH) hydration / dehydration reaction, the flow rates of HO (vapor) and air as fluidizing gas are the mass flow rates in step II), and the calculation of the mass flow rates of the components is calculated using the hydration and dehydration reactions.

[0102] According to another embodiment of the present invention, when the reactor is a waste gasifier, the determination of the gas flow rate can be performed in the same manner as for a combustion process, but the gas composition may be different, including CO and H2, as well as some minor gasification products.

[0103] According to another embodiment of the invention, the reactor, when it is a so-called carbon capture reactor, comprises a fluidized bed carbonator and a calciner, suitably connected to each other. The reactor is configured to, inter alia, reduce CO from the gas to be purified by reaction with CaO (carbonator) and produce substantially pure CO by calcination of CaCO (calciner). The determination of the gas flow rates, including the oxygen and gas flow rates of the gas to be purified, taking into account that fuel is combusted in the calciner, can be carried out in the same way as for combustion processes.

[0104] Step b) may be performed remotely to the combustion boiler, such as in the process intelligence system 205. Step b) may alternatively be performed locally at the combustion boiler, preferably at the edge server 203.

[0105] Any currently monitored process data and / or current load may be obtained by real-time measurement, processed by filtering, averaging, calculating trends, or any combination thereof.

[0106] The allowable conditions include the current calculated maximum boiler instantaneous load Q h,max A hysteresis condition may be included that requires a predetermined minimum change before changing .

[0107] The permissible condition is that at least one calculated exhaust gas factor df i The maximum value df max,i Preferably, the method includes comparing the maximum value df max,i is a preset value, preferably a boiler-specific value. h,candidate is the maximum value df max,i If it exceeds, it is discarded.

[0108] In the combustion boiler 10, the furnace 12 and associated passages (horizontal passage 15 and rear flue 16) define a passage through which the exhaust gas flows. The furnace 12 and passages 15, 16 have several heat transfer surfaces 21 within the passage through which the exhaust gas flows. i The combustion boiler 10 is equipped with a current load Q of the combustion boiler. h and another measurement device for currently monitoring current process data.

[0109] The control system (DCS 201 and edge server 203, or possibly with the involvement of edge server 203, remote process intelligence system 205) is configured to execute the boiler control method.

[0110] The edge server 203 may be configured to process, i.e., by filtering, averaging, and / or trending, real-time measurements of currently monitored process data and / or current load.

[0111] The control system executes step b) of the method and calculates the current calculated maximum boiler instantaneous load Q of the combustion boiler 10. h,max locally determining and / or using the data to perform step b) of the method, and determining the current calculated maximum boiler instantaneous load Q h,maxto a remote, preferably cloud-based (such as compute cloud 206) computing system (such as process intelligence system 205) that is configured to return the information to the control system. The control system may then present the information to the boiler operator, such as by displaying the information using a display / monitor, as in step c) of the method.

[0112] The edge server 203 may be configured to reduce the amount of measurement data passed to the remote computing system.

[0113] The combustion boiler computing system comprises a group of combustion boilers 10, each of which comprises a boiler control system (CS) comprising an edge server (203) system configured to process, i.e., filter, average, and / or calculate trends, real-time measurements of currently monitored process data and / or current loads and transmit the processed real-time measurements to a remote computing system. The remote computing system is preferably a cloud-based computing system configured to receive the processed data from the real-time measurements, calculate data using a numerical boiler model for each of the combustion boilers 10, and return the calculation results to each of the boilers 10. The boiler control system may be configured to adapt its functionality based on the calculation results.

[0114] The computing system calculates at least one exhaust gas coefficient df using currently monitored process data, including a numerical model of the boiler. i The maximum boiler instantaneous load Q that satisfies the allowable conditions is calculated as follows: h,max The numerical value Q for h,candidate Discover the number Q h,candidate The current calculated maximum boiler instantaneous load Q h,max Preferably, the device is configured to select the

[0115] The boiler calculation system may be configured to use the processed measurement data of the combustion boiler 10 to adapt or calibrate a numerical model of the boiler. Alternatively, or additionally, the boiler calculation system may be configured to use processed measurement data collected from other combustion boilers 10 to adapt or calibrate a numerical model of the combustion boiler 10.

[0116] Figure 5 shows a modification of the method shown in Figure 4. Steps L1, L3, L7, and L9 are the same as steps K1, K3, K9, and K11, respectively, but step L5 involves removing all heat transfer surfaces 20 i Regarding the gas production coefficient df i can be calculated directly, i.e., T G,in,i , and each temperature sensor 21 i When the measurement is performed using the method shown in FIG. 5, step K7 can be omitted since back calculation is not necessary.

[0117] Figure 6 shows the available inputs to the numerical boiler model in step N1. h,max is calculated numerically using the boiler model and in step N5 the estimated maximum load Qh,max is presented to the boiler operator via a specific user interface (UI), preferably via a display / monitor 202.

[0118] Figure 7 shows the boiler instantaneous load Q h , and the calculated current maximum boiler instantaneous load Q h、max The results show the effect of using the method according to the present invention during the test period. th The boiler output was 3 to 6 MW on average during the test period. th Large loads were obtained. Figure 8 shows the 10-day test period in more detail.

[0119] In other words, the current calculated maximum boiler instantaneous load Q of the fired boiler is calculated using a numerical model that uses the determined boiler operating parameters in a manner that applies to the boiler. h,max The current boiler load Q is estimated. h is calculated using measured data from the steam circuit.

[0120] Next, the boiler load Q h is the current calculated maximum boiler instantaneous load Q h,max If the boiler load Q is less than 0.001, then: i) indicate to the boiler operator that the boiler load may be increased; and / or ii) automatically increase the boiler load. Alternatively or additionally, h is the boiler maximum instantaneous load Q h,max If the value is greater than 0.05, then: i) indicate to the boiler operator that the boiler load is exceeding the boiler maximum instantaneous load; and / or ii) automatically reduce the boiler load.

[0121] The present invention has been described above with reference to combustion processes in CFBs and BFBs. It will be apparent that the present invention is equally applicable to, for example, CFB and BFB gasifiers, where, instead of flue gas, a cooled product gas is formed for use as needed. Of course, in gasification applications, the product gas is not released to the atmosphere through a chimney, but is instead stored or delivered to a desired further processing facility.

[0122] The exothermic reactor may be, for example, a waste gasifier reactor or a carbon capture reactor.

[0123] The process requires at least the following controllable input streams 22, 23 to a suitably located reactor 10: Thermochemical reactor, CaO (generally alkali metal oxide) hydration i. Adding reactants such as CaO to the hydration reactor ii. H2O (steam) injection iii. Ca(OH)2 dehydration reactor iv. Air injection Waste Gasifier Reactor i. The corresponding input flow similar to the combustion process ii. CO and H2, and some minor gasification products

[0124] According to another embodiment of the invention, when the reactor is a so-called carbon capture reactor, it comprises a fluidized bed carbonator and a calciner, suitably connected to each other, which may be arranged in a CFB reactor, as shown in Figure 1. The reactor is configured to, inter alia, reduce CO from the gas to be purified by reaction with CaO (carbonator) and produce substantially pure CO by calcination of CaCO (calciner). The determination of the gas flow rates, including the gas flow rates of oxygen and of the gas to be purified, taking into account that fuel is combusted in the calciner, can be carried out in the same way as for combustion processes.

[0125] 9 shows an exothermic reactor 10 according to one embodiment of the present invention. The exothermic reactor may be, for example, a thermochemical reactor, such as a CaO (generally an alkali metal oxide) hydration reactor. The reactor 10 comprises a reactor chamber 12 surrounded by a wall 13, which may optionally be a cooled wall connected to a fluid circuit that extracts heat from the process carried out in the reactor chamber, depending on the actual application.

[0126] Reactants are fed into reaction chamber 12 via reactant inlet 22. The reaction can be regulated by controlling reactant feed inlet 22 and generally by controlling process variables related to the heat release process of reactor 10.

[0127] The reaction products, which may generally be referred to as product gas, flow from the reactor chamber 12 into a gas passage 16. The reactor 10 may also be provided with an outlet 22' into the reactor chamber 12 for at least partially reacted solid material. The gas passage is described here as a vertical passage, but may similarly be variously designed, such as horizontal. From the product gas passage, the product gas is conducted to further processing section 19, which may comprise a simple reservoir or gas delivery piping.

[0128] The product gas flow path 16 has several heat transfer surfaces 21 i (I=1, 2, 3, . . . , k, where k is the number of heat transfer surfaces). k-1 ,twenty one k The actual number of various heat transfer surfaces in each of these components can be selected differently for each reactor 10, for example, depending on the actual needs.

[0129] Last heat transfer surface 21 k The product gas exiting from the G,exit This temperature is measured by the temperature sensor 20 k It is measured in

[0130] According to one embodiment, each heat transfer surface 21 i The temperatures before and after (T G,in,I , T G,in,i+1 ) are the temperature sensors 20 i (I=1, 2, 3, . . . , k-1, k).

[0131] However, in another embodiment, it is preferable that these temperatures do not necessarily need to be measured. G,exit It will be sufficient to know the above-mentioned heat transfer surfaces 21 i The temperature before and after (T G,in,I , T FG,in,i+1 ) can be obtained numerically, as will be explained further below.

[0132] The reactor 10 is equipped with multiple sensors 40 and computer units, only some of which are shown for clarity. For example, depending on the current actual application of the reactor 10, there may be a sensor 40 for determining the rate of flow of reactants into the reactor 10, a sensor 40 indicating the temperature at one or more locations within the reactor 10, and a sensor 40 indicating the pressure within the reactor.

[0133] Process data may be collected from sensors by a distributed control system (DCS) 201, similar to that disclosed in connection with Figure 1, except that the combustion boiler network is, of course, instead a heat dissipation network and operates in a corresponding manner.

[0134] It is obvious to those skilled in the art that with the advancement of technology, the basic idea of ​​the present invention can be implemented in many ways. The present invention and its embodiments are therefore not limited to the examples and samples described above, but can be modified within the scope of the claims and their legal equivalents.

[0135] In addition to or instead of using the specific empirical formulas mentioned above, it is possible to utilize artificial intelligence tools and / or neural networks in the numerical model calculations.

[0136] In the following claims and in the foregoing description of the invention, unless the context otherwise requires, either by express wording or necessary implication, the word "comprise" or variations such as "comprises" or "comprising" are used in the inclusive sense, i.e., used to specify the presence of stated features but not to exclude the presence or addition of other features in various embodiments of the invention.

Claims

1. 1. A method of operating an exothermic reactor to produce a product gas, comprising: a) the current load of the exothermic reactor (Q ｈ ) monitoring the b) at least one product gas coefficient (df) calculated by a numerical model of the exothermic reactor using currently monitored process data; ｉ ) is the maximum instantaneous load (Q ｈ，ｍａｘ ) to the numerical value (Q ｈ，ｃａｎｄｉｄａｔｅ ), and finding the value (Q ｈ，ｃａｎｄｉｄａｔｅ ) to the current calculated maximum instantaneous load (Q ｈ，ｍａｘ ) as c) The current calculated maximum instantaneous load (Q ｈ，ｍａｘ ) to the operator, and / or ｈ )but, c1) The current calculated maximum instantaneous load (Q ｈ，ｍａｘ ), c1i) the load (Q ｈ and / or c1ii) the load (Q ｈ ) automatically increasing the and / or c2) The current calculated maximum instantaneous load (Q ｈ，ｍａｘ ), c2i) the load (Q ｈ ) exceeds the current calculated maximum instantaneous load, and / or c2ii) the load (Q ｈ ) automatically reducing A method comprising:

2. i) the currently monitored process data of the exothermic reactor, ia) The current product gas outlet temperature (T Ｇ，ｅｘｉｔ，ｃｕｒｒｅｎｔ )and, ib) The heat load (Q) for each heat transfer surface (i) in the generated gas flow path ｆｌｕｉｄ，ｉ )and and ii) monitored process data from both ia) and ib) is used in calculating the product gas coefficient, and the current calculated maximum instantaneous load (Q ｈ，ｍａｘ ) to the numerical value (Q ｈ，ｃａｎｄｉｄａｔｅ ) is used when discovering The method of claim 1.

3. The at least one product gas coefficient (df ｉ ) does not satisfy the acceptance condition, the discovery is ｈ，ｃａｎｄｉｄａｔｅ 3. The method of claim 1, wherein the method is performed so that the first and second selections are automatically selected.

4. The next numerical value (Q ｈ，ｃａｎｄｉｄａｔｅ 4. The method of claim 3, wherein:

5. The discovery - I: The load of the exothermic reactor is the value (Q ｈ，ｃａｎｄｉｄａｔｅ ) coincides with the product gas outlet temperature (T Ｇ，ｅｘｉｔ ) calculating an estimate of II: When the load of the exothermic reactor matches the value (Q h,candidate ), use the reactor mass and energy balance equation to determine the product gas mass flow rate (q ｍ，ｐｒｏｄｕｃｔｇａｓ ) -III: Heat load (Q) per heat transfer surface in the gas flow path ｆｌｕｉｄ，ｉ，ｃａｎｄｉｄａｔｅ ) to (Q ｆｌｕｉｄ，ｉ，ｃａｎｄｉｄａｔｅ =Q ｆｌｕｉｄ，ｉ，ｃｕｒｒｅｎｔ +Σα ｊ，ｉ (Q ｆｌｕｉｄ，ｍａｘ ) ｊ -Σα ｊ，ｉ (Q ｆｌｕｉｄ，ｃｕｒｒｅｎｔ ) ｊ ) the current heat load (Q ｆｌｕｉｄ，ｉ，ｃｕｒｒｅｎｔ ) calculating using - IV: The calculated heat load (Q ｆｌｕｉｄ，ｉ，ｃａｎｄｉｄａｔｅ ) is used, and the heat transfer surface 21 in the product gas flow passage is closest to the product gas outlet in the upstream direction of the product gas flow. ｋ From the above, the produced gas outlet temperature (T ｆｌｕｅｇａｓ，ｏｕｔ，ｋ The product gas temperature (T boiler, exit) at each heat transfer surface is calculated using the estimated values ​​of Ｇ，ｉｎ，ｉ , T Ｇ，ｏｕｔ，ｉ , i=1, ..., k), - V: the generated gas coefficient (df ｉ , i=1, . . . , k) The method according to any one of claims 1 to 4, which is carried out by performing the following steps.

6. The gas production coefficient comprises or is: [Equation 1] Here, k ｉ is a non-zero parameter that is a positive number and can be selected specifically for the exothermic reactor; q ｍ，ｐｒｏｄｕｃｔｇａｓ is the mass flow rate of the product gas, n is a model parameter that is a positive non-zero number that can be chosen specific to the exothermic reactor; ρ Ｇ，ｉ 6. The method of claim 5, wherein ℓ is the product gas density at the i-th heat transfer surface and A is the cross-sectional area of ​​the product gas channel at the i-th heat transfer surface.

7. n is i) in the range of 0.9 to 1.1 when taking into account the calculated product gas velocity; ii) in the range of 2.9 to 3.5 when taking into account corrosion caused by calculated product gases; or iii) In the case where the pressure loss of the produced gas flow is taken into consideration, the range is 1.8 to 2.

2. The method of claim 6 , wherein the selected value is at least one of:

8. The method of claim 7 , wherein the value of n is varied over time.

9. 9. The method of claim 7 or 8, wherein the value of n is determined from a group of exothermic reactors including at least two separate exothermic reactors using monitored operational data for each of the exothermic reactors.

10. In the calculation of step I), the product gas outlet temperature is substantially T Ｇ，ｅｘｉｔ =a ０ +Sa ｊ (Q) ｈ，ｃａｎｄｉｄａｔｅ ) ｊ Alternatively, the coefficients (α ０ , α １ , α ２ , ...) are the product gas outlet temperatures (T Ｇ，ｅｘｉｔ 10. The method according to claim 5, wherein the value of (a) is measured, and then a predetermined function is fitted to the measured value, and the value of (b) is previously obtained by the fitted function.

11. In step II), the mass flow rate of the produced gas is calculated by using the mass flow rate (q ｍ，Ｇ，ｍ 11. The method according to claim 5, wherein

12. 12. The method of any one of claims 5 to 11, wherein in step II) the calculation of product gas mass flow rate includes using reactant parameters.

13. 13. The method of any one of claims 1 to 12, wherein step b) is performed remotely with respect to the exothermic reactor.

14. 12. The method of any one of claims 1 to 11, wherein step b) is carried out locally at the site of the exothermic reactor.

15. wherein the currently monitored process data and / or current load are both obtained by real-time measurement, processed by filtering, processed by averaging, calculating trends, or any combination thereof; The method according to any one of claims 1 to 14.

16. The allowable conditions include the current calculated maximum instantaneous load (Q ｈ，ｍａｘ 16. The method of any one of claims 1 to 15, including a hysteresis condition that requires a predetermined minimum change in the at least one product gas coefficient (df i ) before changing the at least one product gas coefficient (df i ).

17. The permissive condition is determined based on the calculated at least one gas production coefficient (df ｉ ) to their respective design values, ｈ，ｃａｎｄｉｄａｔｅ 17. The method according to claim 1, wherein the amount of the molten metal is discarded if the amount of the molten metal exceeds the design value.

18. 18. The method of any one of claims 1 to 17, wherein the exothermic reactor is a circulating fluidized bed (CFB) reactor or a bubbling fluidized bed (BFB) reactor, and step b) is carried out on the heat transfer surfaces in the exothermic reactor and / or in the product gas channels.

19. The method of claim 1, wherein the heat-dissipating reactor is a combustion boiler, a gasification reactor, a liquid air energy storage reactor, a hydration reactor, or a carbon capture reactor.

20. - Defines the product gas flow path and has several heat transfer surfaces (21 ｉ a reactor chamber (12) and associated passages (15, 16) comprising: - the current load (Q) of the exothermic reactor (10) ｈ ) and a measuring device for monitoring the - sensors (20, 20) that monitor current process data ｉ , 30, 40, 116, 165, 650) and another measuring device, a control system (CS 201, 203, 205) configured to implement the method for operating the exothermic reactor according to any one of claims 1 to 18; A heat-dissipating reactor comprising:

21. 21. The exothermic reactor (10) of claim 20, wherein the control system (CS) comprises an edge server (203) configured to process real-time measurements of currently monitored process data and / or current loads by filtering, averaging, and / or calculating trends.

22. The control system executes step b) of the method to calculate the current calculated maximum instantaneous load (Q ｈ，ｍａｘ 22. The exothermic reactor of claim 20 or 21, configured to locally determine

23. The control system executes step b) of the method to calculate the current calculated maximum instantaneous load (Q ｈ，ｍａｘ 22. The exothermic reactor of claim 20 or 21, configured to transmit data to a remote computing system configured to return a signal to the control system.

24. The control system is configured to transmit data to a remote computing system configured to perform step b) of the method and return the current calculated maximum instantaneous load (Q h,max ) to the control system; 22. The exothermic reactor of claim 21, wherein the edge server is configured to reduce the amount of process data passed to the remote computing system.

25. A group of exothermic reactors (10) according to any one of claims 20 to 24, each comprising a control system (DCS) comprising an edge server (203) system configured to process the real-time measurements of currently monitored process data and / or current load by filtering, averaging and / or calculating trends and to transmit the processed real-time measurements to a remote computing system (205), a remote computing system (205) configured to receive processed data from the real-time measurements, calculate the data for each of said exothermic reactors (10) using a numerical model, and return the calculation results to each of said exothermic reactors (10); A reactor calculation system comprising: The exothermic reactor calculation system, wherein the control system is configured to adapt the function of the exothermic reactor based on the calculation results.

26. The remote computing system calculates at least one product gas coefficient (df ｉ ) is the maximum instantaneous load (Q ｈ，ｍａｘ ) to the numerical value (Q ｈ，ｃａｎｄｉｄａｔｅ ) and find the value (Q ｈ，ｃａｎｄｉｄａｔｅ ) to the current calculated maximum instantaneous load (Q ｈ，ｍａｘ ) as the 26. The exothermic reactor calculation system of claim 25.

27. 27. The radiative reactor calculation system of claim 25 or 26, wherein the radiative reactor calculation system is configured to calibrate a numerical model of the radiative reactor (10) using processed measurement data of the radiative reactor (10).

28. The radiative reactor calculation system according to any one of claims 25 to 27, wherein the radiative reactor calculation system is configured to calibrate a numerical model of the radiative reactor (10) using processed measurement data also collected from other radiative reactors (10).

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