Patent Description:
Combustion boilers, such as grate boilers and fluidized bed boilers are commonly utilized to generate steam which can be used for variety of purposes, such as for producing electricity and heat.

In a fluidized bed boiler, fuel and solid particulate bed material is introduced into a furnace. The bed material and fuel is fluidized by introducing fluidizing gas from a bottom portion of the furnace. Burning of fuel takes place in the furnace. In BFB combustion, fluidization gas is passed through the bed such that it forms bubbles in the bed. The fluidized bed can in a BFB be rather conveniently controlled by controlling the fluidization gas feed and fuel feed. In addition to fuel, certain additives such as aluminum silicates (such as, non-hydrated clay) and alkali alkaline earth metal carbonates and mixtures thereof (such as, limestone or calcium carbonate) may be added to the combustion to improve sorption of possible heavy metals, sulfur, and also to improve alkali sorption.

In CFB combustion, fluidization gas is passed through the bed material. Most bed particles will be entrained in the fluidization gas and they will be carried with flue gas. The particles are separated from the flue gas in at least one particle separator and circulated returning them back into the furnace. It is common to arrange a fluidized bed heat exchanger downstream the particle separator(s) to recover heat from the particles before they are returned into the furnace.

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

International application published under <CIT> of Improbed AB discloses a thermal load control method for a combustion boiler. In the method, the thermal load of a combustion boiler is reduced if monitored flue gas velocity in at least one location of the boiler exceeds a pre-determined maximum flue gas velocity limit. The flue gas velocity is computed from volume flow of flue gas divided by the cross-sectional area of the flue gas duct in the location just downstream the cyclone using an equation group.

Other methods are known from <CIT>, <CIT>, and from <NPL>.

A combustion boiler traditionally is designed for a given load that is the respective boiler maximum continuous rating (BMCR) of the boiler. This is sometimes called the design load level.

It is an objective of the invention to improve performance, profitability, and flexibility of the boiler, and also to improve control of the boiler load. This objective can be achieved with the combustion boiler control method according to claim <NUM> and with the combustion boiler according to claim <NUM>.

A further objective of the invention is to reduce complexity of control system of a combustion boiler. This objective can be met with a combustion boiler computation system according to claim <NUM>.

The dependent claims describe advantageous aspects of the combustion boiler control method, of the combustion boiler, and of the combustion boiler computation system.

The inventive combustion boiler control method comprises the steps of.

With the method, instead of having a fixed boiler maximum load, with the method of computing a flue gas factor and selecting its acceptance conditions suitable, it is possible to safely operate the combustion boiler at or closer to its current computational maximum boiler momentary load that at times may be higher than the fixed boiler maximum load would be. The current computational maximum boiler momentary load can be higher than the design load level. Therefore, the overall performance of the boiler may be improved and enabling increased power/heat production. Further, since the current computational maximum boiler momentary load may occasionally be smaller than the design load level, boiler wear resulting from exceeding the current computational maximum boiler momentary load may be better reduced. In other terms, the current computational maximum boiler momentary load can be considered as maximum allowable boiler load and/or preferable boiler load.

The present applicant has been able to obtain in the tests performed, in average, power output from a combustion boiler that exceeds the fixed boiler maximum load. The present applicant could in the tests demonstrate that for a combustion boiler the improvement potential may lie between <NUM>,<NUM> - <NUM>% which corresponds, for example, <NUM> to <NUM> MWth for a <NUM> MWth combustion boiler.

and further:
ii) monitored process data from both ia) and ib) is used in computation of the flue gas factor and when finding the numerical value for the current computational maximum boiler momentary load Qh,max.

Computation of heat duty of a heat exchanger is known for skilled person in the art and heat duty can be obtained, for instance, by using the following equation <MAT> wherein qm,fluid,i is the fluid flow in ith heat transfer surface, hfluid,in is the enthalpy of fluid entering to the ith heat transfer surface and hfluid,out is the enthalpy of fluid exiting from the ith heat transfer surface.

The finding may be performed such that, if the at least one flue gas factor computed using currently monitored process data with a numerical model of the boiler fails to fulfill an acceptance condition, a next numerical value is automatically selected. Preferably, the next numerical value is selected iteratively. This may enable the use of computational library functions, and, in particular of an iterative solver (such as, Python FSOLVE function which solves roots of function).

The finding may be carried out with performing the computational steps of:.

With this approach, the situation of each heat transfer surface (here and hereinafter, "heat transfer surface" means a heat exchanger, a heat exchanger tube, heat exchanger tube bundle, heat exchanger packages and/or a constructive group of heat exchangers, such as economizer) in the flue gas flow channel can be estimated numerically with the flue gas factor in the situation where the thermal load of the boiler corresponds to the numerical value. Preferably, the term "heat transfer surface" means a constructive group of heat exchangers, such as economizer. So, we can now test whether a given numerical value that is a candidate for a current computational maximum boiler momentary load would produce an acceptable situation at the heat transfer surface.

According to an embodiment of the invention, in step III) the numerical boiler model is of the form Qfluid, i, candidate = Qfluid, i, current + Σαj, i (Qh, candidate)j - Σparj,i (Qh, current)j.

The fitting of the parameters (parj,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.

On one hand, this enables predicting the maximum computational allowable current boiler momentary load without going to the limit with the current boiler load, in contrast to the method disclosed in <CIT>, and on the other hand, and even more importantly, enables going to the limit without exceeding the maximum computational allowable current boiler momentary load.

Preferably, the flue gas factor includes or is: <MAT> where.

This is particularly convenient since choosing this functional form for the flue gas factor, it becomes very flexible and can be easily adapted to suit different combustion boiler needs, such as, based on the conditions in the current fuel.

Particularly advantageously, the model parameter n may be selected to include at least one of the following:.

The value for n may be changed over time. This is advantageous for the reason that the flue gas flow conditions at the heat transfer surfaces may change over time, such as because of slagging, ash agglomeration or fuel or bed conditions. Thus, the flue gas factor may be shifted over time, to better reflect the actual boiler situation.

According to an embodiment of the invention, when n=<NUM> and flue gas factor represents a pressure loss, the comparison between the flue gas factor dfi and a predetermined maximum value for the flue gas factor dfmax,i can be carried out for each heat transfer surface. According to an embodiment the acceptance condition is substantially dfi= dfmax i.

According to an embodiment of the invention, when n=<NUM> and flue gas factor represents a pressure loss, the comparison can be done between the sum of the flue gas factors dfi <MAT> and sum of the predetermined flue gas factors dfmax, i or simply predetermined flue gas factor represents total pressure drop and hence the comparison represents the comparison of total pressure drops between the furnace and stack. According to an embodiment the acceptance condition is substantially dptot= dpmax,tot.

According to an embodiment of the invention, the flue gas factor represents an ash loading factor and can be written in the form <MAT> where kph is particle hardness factor, C(d) is particle diameter function, qm_fa is fly ash mass flow rate, vp is particle velocity and n is exponent (<NUM>,<NUM> - <NUM>). In such case, the predetermined flue gas factor represents maximum ash loading value. It can also be adjustable based on the ash properties (softness, etc.).

According to an embodiment of the invention, the acceptance condition is substantially dfi = dfmax,i but in practical circumstances the acceptance condition can be defined as <MAT> wherein δ><NUM> and depends on the numerical accuracy and/or method. When dfmax, i - δ < dfi ≤ dfmax, i, it means that at least one flue gas factor computed using currently monitored process data with a numerical model of the boiler fulfills the acceptance condition and in such a case maximum allowable boiler load has been found and so the numerical value Qh, candidate is selected as the current computational maximum boiler momentary load Qh, max.

According to an embodiment of the invention, the acceptance condition is substantially Σ (dfi) = Σ (dfmax, i) but in practical circumstances the acceptance condition can be defined as utilizing the following sums <MAT> wherein δ><NUM> and depends on the numeric accuracy and/or method. When Σ (dfmax,i) - δ < Σ (dfi) ≤ Σ (dfmax,i), it means that at least one flue gas factor computed using currently monitored process data with a numerical model of the boiler fulfills the acceptance condition and in such a case maximum allowable boiler load has been found and so the numerical value Qh, candidate is selected as the current computational maximum boiler momentary load Qh, max. According to an embodiment the summation index i goes over all of the heat transfer surfaces. According to another aspect of the invention, the summation index i goes over only a part of the heat transfer surfaces, preferably in a flue gas channel.

It may be particularly useful if the value for n is determined from a group of boilers comprising at least two separate boilers using operational data monitored for each of the boilers. Using a larger number of boilers (two, three, four,. ) gives a larger data set. Hence, there will be more operational data monitored. This may produce better results, which may be especially good in a situation where the determination uses interpolation and/or extrapolation of experimental data.

For the computation in step I), the flue gas exit temperature may be substantially estimated by equation <MAT> or preferably its first, second, or third (or higher) degree approximation. The coefficients α may be obtained by fitting after measuring flue gas exit values for a number of discrete steam load values. This data may be collected over time and refreshed from time to time, such as, periodically. Alternatively, or in addition, it may be collected in one or more calibration runs of the combustion boiler.

The fitting of the coefficients (α) can be done manually by human or automatically by computer utilizing historical data. Automatic update of the coefficients may be done e.g. once per month. AI and neural network based algorithms can be utilized in automatic update.

According to an embodiment of the invention, in step I), the flue gas exit temperature may be substantially estimated by utilizing artificial intelligence tools. According to another embodiment of the invention, in step I), the flue gas exit temperature may be substantially estimated by utilizing neural network.

According to an embodiment of the invention, in step I), the flue gas exit temperature may be estimated by equation <MAT> wherein α<NUM>, α<NUM> and α<NUM> can be predefined constants. Alternatively or in addition, the fitting of the coefficients (α) can be done manually by human or automatically by computer utilizing historical data.

Automatic update of the coefficients may be done e.g. once per month. AI and neural network based algorithms can be utilized in automatic update.

According to an embodiment of the invention, α<NUM> term may be solved based on the current state values <MAT> wherein Tboiler,exit,current represents measured flue gas exit temperature.

According to an embodiment of the invention, in step II), the flue gas mass flow is computed using boiler mass and energy balance equations.

In step II), the computation of flue gas mass flow may include taking into account mass flow of components CO<NUM>, H<NUM>O, N<NUM>, SO<NUM>, O<NUM>. The concentration of these components can be measured reliably with rather simple equipment.

In step II), the component values may include fuel parameters. This enables reflecting changes in the fuel properties or/or in the kind of fuel that is used in the combustion boiler. For example, for fuels that tend to cause more erosion, the acceptance condition may be stricter, while a more relaxed acceptance condition may be used for fuels that tend to cause less erosion.

The step b) may be performed remotely to the combustion boiler, preferably in a cloud-based computation service. This helps to simplify the maintenance of the combustion boiler, since the remote computation equipment, such as configured to run the cloud-based computation service, can be maintained separately from the combustion boiler. The computational software updates, for example, can thus be performed centrally at one or a few locations, instead of updating software at each combustion boiler.

Alternatively, the step b) may be performed locally at the combustion boiler, preferably at an edge server. This may speed up the computation since no data needs to be transferred to a remote computation location.

Any of the currently monitored process data and/or current load may be obtained from real-time measurements. Instead of this, or in addition to it, the currently monitored process data and/or current load may be treated by filtering, treated by averaging, computing trends or any combination of these. This helps to avoid noise or outlier measurements to impact the outcome of the computation, and thus facilitates to increase stability of the current computational maximum boiler momentary load.

The acceptance condition may include a hysteresis condition, requiring a predefined minimum change before changing the current computational maximum boiler momentary load. This may increase the stability of the current computational maximum boiler momentary load, preferably helping to avoid changing the current computational maximum boiler momentary load up and down within a short period of time.

Even though the method can be utilized in any sort of combustion boiler, the present applicant finds it particularly useful if the combustion boiler is a circulating fluidized bed (CFB) or a bubbling fluidized bed (BFB) boiler, and the step b) is carried out for the combustion boiler heat transfer surfaces. The method is particularly convenient for CFB or BFB boilers.

According to an embodiment the step b) is carried out for the combustion boiler heat transfer surfaces between a furnace and stack.

An inventive combustion boiler comprises:.

According to an embodiment combustion boiler comprises a furnace and associated passes defining a flue gas flow path a flue gas flow path and having a number of heat transfer surfaces in the flue gas flow path.

Such a combustion boiler, the boiler control can be improved. The advantages are same as the advantages of the method.

The control system may comprise an edge server which 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. The edge server will facilitate cutting down the amount of currently monitored process data. In certain installations this may be particularly useful especially in view of the fact that there may be <NUM> to <NUM> gigabytes of monitored process data each day.

The control system may be configured to carry out the method step b) to determine the current computational maximum boiler momentary load locally. This facilitates to have fast decision making at the combustion boiler since less or no data may need to be transferred from the combustion boiler system.

Alternatively, or in addition, the control system may be configured to send data to a remote, preferably cloud-based, computing system which may be configured to carry out the method step b) and return the current computational maximum boiler momentary load to the control system. This facilitates to have a combustion boiler simpler and makes updating the computing system easier. The updating can in this situation be performed centrally and not at each and every combustion boiler.

The edge server may be configured to reduce amount of measurement data that is passed to the remote computing system. In this manner, a smaller bandwidth for transferring data may suffice. In certain installations this may be particularly useful especially in view of the fact that there may be <NUM> to <NUM> gigabytes of monitored process data each day.

An inventive combustion boiler computation system comprises.

Further, in the inventive combustion boiler computation system, the boiler control system is configured to adapt its function based on the computation results.

The advantage for this arrangement is that the need of computation devices at the combustion boiler can be reduced, still obtaining effective and fast computation results from the remote computing system.

The inventive computing system is configured to find such a numerical value or a current computational maximum boiler momentary load for which at least one flue gas factor computed using currently monitored process data with a numerical model of the boiler that fulfills an acceptance condition and selecting the numerical value as the current computational maximum boiler momentary load. This basically enables using the method of the invention also in a distributed environment. The boiler computation system may be configured to adapt or calibrate a numerical model, such as, the flue gas factor numerical model, for a boiler using processed measurement data for the boiler. This makes it easier to remotely adapt or calibrate the numerical model for boiler control.

The boiler computation system may be configured to adapt or calibrate a numerical model for a boiler using processed measurement data collected also from other boilers. This enables using a larger collection of data to adjust the numerical model for boiler control.

The combustion boiler and its control method are explained in more detail below in the context of the embodiments shown in the appended drawings in FIG <NUM> to <NUM>, of which:.

Same reference numerals refer to same technical features in all FIG.

<FIG> shows a combustion boiler <NUM> that is a CFB boiler and comprises a furnace <NUM> that has tube walls <NUM> connected to water-steam circuit of the combustion boiler <NUM>. 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 <NUM> and then guided via the steam drum to superheaters and then to a turbine. Flue gas channel may be provided with economizer and/or superheater/s.

Fluidization gas (such as, air and/or oxygen-containing gas) is fed from fluidization gas supply <NUM> to below the grate (the grate not shown in <FIG>) 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 <NUM> (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 <NUM>. Further, fuel is fed into the furnace <NUM> via the fuel feed <NUM>. The combustion can be adjusted by controlling the fuel feed <NUM> (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 <NUM>). Fuel can be fed together with additives, in particular with such additives that act as alkali sorbents, such as CaCO<NUM> and/or clay for example. In addition or alternatively, NOx reduction agents, such as ammonium or urea can be fed into the combustion zone of the furnace <NUM>, or above the combustion zone of the furnace <NUM>.

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 <NUM> and water is converted to steam.

Ash may fall to the bottom of the furnace <NUM> and be removed via an ash chute (omitted from <FIG> for the sake of clarity) and part of the ash, so-called fly ash, will be carried along flue gas.

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

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

The flue gases are passed from the separator <NUM> to horizontal pass <NUM> and from there further to backpass <NUM> (that preferably may be a vertical pass) and from there via flue gas conduit <NUM> to stack <NUM>.

The backpass <NUM> comprises a number of heat transfer surfaces <NUM>i (where i = <NUM>, <NUM>, <NUM>,. , k, where k is the number of heat transfer surfaces). In <FIG>, heat transfer surfaces <NUM><NUM>, <NUM><NUM>, <NUM><NUM>,. , <NUM>k-<NUM>, <NUM>k are illustrated. Heat transfer surface <NUM>k depicts air preheater. Heat transfer surfaces <NUM>k-<NUM>, <NUM><NUM> depict superheaters and heat transfer surfaces <NUM><NUM>, <NUM><NUM> 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 <NUM>.

Flue gas exiting the last heat transfer surface <NUM>k will be in flue gas exit temperature TFG, exit. This temperature is measured with temperature sensor <NUM>k.

According to one aspect, the temperatures before and after each heat transfer surface <NUM>i (TFG,in,i, TFG,in,i+<NUM>, respectively) can be measured with respective temperature sensors <NUM>i (where i = <NUM>, <NUM>, <NUM>,. , k-<NUM>, k).

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 TFG, exit. The temperatures before and after each preceding heat transfer surface <NUM>i (TFG,in,i, TFG,in,i+<NUM>) can be obtained numerically. This will be explained further below.

A combustion boiler <NUM> is equipped with a plurality of sensors and computer units. Actually, one middle-size (<NUM> - <NUM> MWth) combustion boiler <NUM> may produce <NUM> million measurement results / day, which needs <NUM> GB of storage space. <FIG>, <FIG> and <FIG> illustrate some of the sensors and computer units. Examples of sensors are combustion gas (usually combustion air) volume flow sensors <NUM> (for measuring primary and secondary fluidizing gas feeds), fuel feed sensors <NUM> and temperature sensors <NUM>i (i = <NUM>, <NUM>,. , k), temperature sensor in FBHE and pressure sensor <NUM> in the return channel <NUM> (both only in a CFB boiler), and sensors <NUM> in the furnace <NUM>.

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

The DCS <NUM>, display/monitor <NUM>, EDGE server <NUM>, local storage <NUM> may be in combustion boiler network <NUM> (local storage <NUM> preferably directly connected to the EDGE server). The combustion boiler network <NUM> is preferably separate from the field bus <NUM> that is used to communicate measurement results from the sensors to the DCS <NUM> and/or the EDGE server <NUM>. Between the DCS <NUM> and EDGE server <NUM> there may be an open platform communications server <NUM> (cf. <FIG>) to make the systems better interoperable.

Combustion boiler network <NUM> may be in connection with the internet <NUM>, preferably via a gateway <NUM>. In this situation, measurement results may be transferred from the combustion boiler network <NUM> to a cloud service, such as process intelligence system <NUM> located in a computation cloud <NUM>. 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.

<FIG> illustrates a combustion boiler <NUM> that is a BFB boiler. BFB boiler differs from CFB boiler in that the fluidized bed is not a circulating bed but a bubbling bed. Thus, there is no need for the separator <NUM>, loop seal <NUM>, FBHE <NUM> and return channel <NUM>.

There is normally at least one superheater <NUM> located in the furnace <NUM>, preferably on top of the furnace <NUM>. Superheater <NUM> inlet <NUM> is preferably the steam drum or from another superheater and the outlet <NUM> is to high pressure turbine.

<FIG> illustrates the combustion boiler control method:.

The step b) is preferably carried out for the combustion boiler <NUM> heat transfer surfaces <NUM>i between furnace <NUM> and stack <NUM>.

In the method, the currently monitored process data of the boiler may include a) current flue gas exit temperature TFG,exit in a flue gas flow channel and b) heat duty Qfluid,i for each heat transfer surface <NUM>i in the flue gas flow channel (back pass <NUM>).

Further, in the method monitored process data from both a) and b) may be used in computation of the flue gas factor dfi and when finding the numerical value Qh, candidate for the current computational maximum boiler momentary load Qh max.

The finding is performed such that, if the at least one flue gas factor dfi computed using currently monitored process data with a numerical model of the boiler that fails to fulfill an acceptance condition, a next numerical value Qh, candidate is automatically selected. The automatic selection is preferably done iteratively.

As a specific example, the finding may be carried out with performing the computational steps of:.

Step II) may include computing flue gas mass flow qm,fluegas,m for selected flue gas components.

The flue gas temperatures at each heat transfer surface can be computed, for instance, <MAT> wherein Tfluegas,in,i is the flue gas temperature at the inlet of ith heat transfer surface, cp is specific heat capacity, and Tfluegas,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.

Preferably, the flue gas factor dfi includes or is: <MAT>.

Advantageously, n may be selected to include at least one of the following:.

The value for n may be changed over time. In particular, the value for n may be determined from a group of combustion boilers, the group comprising at least two separate combustion boilers <NUM>, such that using operational data monitored for each of the combustion boilers <NUM> is used in the determination.

In the computation in step I), the computational value for flue gas exit temperature TFG, exit under any chosen numerical value Qh, candidate for boiler load can be estimated by equation <MAT> or preferably its first, second, third or higher degree approximation. The coefficients α<NUM>, α<NUM>, α<NUM>,. have been obtained beforehand by fitting after measuring flue gas exit temperature TFG, exit values for a number of discrete boiler load Qsteam values.

In step II), the computation of the components qm,fluegas,m preferably includes at least some, most preferably all of the following: m = CO<NUM>, H<NUM>O, N<NUM>, SO<NUM>, O<NUM> so as to determine flue gas mass flow. In other words, in step IV) of the computation, as qm,fluegas,m values some or all of qm,fluegas,CO2, qm,fluegas,H20 , qm,fluegas,N2 , qm,fluegas,SO2 , qm,fluegas,O2 may be used. They are preferably measured in flue gas conduit <NUM> or in flute <NUM>, for which reason suitable sensors are installed in the flue gas passage. In step II), the component values may further include fuel parameters.

Flue gas mass flow may be based on computation of sums of flue gas component mass flows qm,fluegas,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.

Preferably, the flue gas mass flow may be computed: <MAT> i.e., for example, the sums of the following flue gas mass flow components CO<NUM>, H<NUM>O, N<NUM>, SO<NUM> and O<NUM>: <MAT> <MAT> <MAT> <MAT> <MAT> <MAT> where, for instance, xC,fuel represents carbon in fuel i.e. first subscript denotes component and second subscript is either fuel or combustion air referred, qm,fuel is a fuel flow, qm,air is combustion air flow and Mx 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.

The step b) may be performed remotely to the combustion boiler, such as, in the process intelligence system <NUM>. Alternatively, the step b) may be performed locally at the combustion boiler, preferably at the EDGE server <NUM>.

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.

The acceptance condition may include a hysteresis condition, requiring a predefined minimum change before changing the current computational maximum boiler momentary load Qh,max.

The acceptance condition preferably includes comparing the computed at least one flue gas factor dfi against a respective maximum value dfmax,i. The maximum value dfmax,i is a preset value and preferably boiler specific. The numerical value Qh, candidate is rejected if the maximum value dfmax,i is exceeded.

In the inventive combustion boiler <NUM>, the furnace <NUM> and associated passes (horizontal pass <NUM> and back pass <NUM>) define a flue gas flow path. The furnace <NUM> and the passes <NUM>, <NUM> have a number of heat transfer surfaces <NUM>i in the flue gas flow path. The combustion boiler <NUM> also has measurement instrumentation to monitor current load Qh of the combustion boiler, and further measurement instrumentation to currently monitor process data.

The control system (DCS <NUM>, and EDGE server <NUM>, or DCS <NUM> remote process intelligence system <NUM>, possibly under the participation of the EDGE server <NUM>) is configured to carry out the inventive combustion boiler control method.

The EDGE server <NUM> 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. The control system may be configured to carry out the method step b) to determine the current computational maximum boiler momentary load Qh,max locally at the combustion boiler <NUM>, and/or to send data to a remote, preferably cloud-based (such as, computation cloud <NUM>), computing system (such as, process intelligence system <NUM>) which is configured to carry out the method step b) and return the current computational maximum boiler momentary load Qh,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.

The EDGE server <NUM> may be configured to reduce amount of measurement data that is passed to the remote computing system.

An inventive combustion boiler computation system comprises a group of combustion boilers <NUM>, comprising at least two separate inventive combustion boilers <NUM>, each combustion boiler <NUM> comprising a boiler control system (CS) comprising an EDGE server (<NUM>) system which 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 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 <NUM>, and to return computation results for each of the combustion boilers <NUM>. The boiler control system may be configured to adapt its function based on the computation results.

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

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

<FIG> shows a modification of the method shown in <FIG>. Steps L1, L3, L7, L9 are the same as steps K1, K3, K9, K11, respectively, but in step L5, the flue gas factors dfi can be directly computed for all heat transfer surfaces <NUM>i: if the temperatures Tes,in,i are measured using the respective temperature sensors <NUM>i, the back-calculation will not be necessary and thus the step K7 can be omitted in the method illustrated in <FIG>.

<FIG> shows in step N1 the use of possible inputs to the numerical boiler model. In step N3 the Qh,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 <NUM>.

<FIG> shows boiler momentary load Qh and computed current computational maximum boiler momentary load Qh, max, as well as the effect of using the method according to the invention during a test period. During the <NUM> day test period, the <NUM> MWth boiler power obtained in average a <NUM> to <NUM> MWth higher load as outside the test period. <FIG> illustrates the <NUM> day test period in more detail.

In other words, in the boiler control method, the current computational maximum boiler momentary load Qh,max of the combustion boiler is estimated using a numerical model using determined fluidized bed combustion boiler operating parameters. The current boiler load Qh is computed using steam circuit measurement data.

Then, if the boiler load Qh is smaller than the current computational maximum boiler momentary load Qh,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 Qh is larger than the boiler maximum momentary load Qh,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.

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 the appended claims.

Claim 1:
A combustion boiler control method, comprising the steps of:
a) monitoring the current load (Qh) of a combustion boiler;
b) finding such a numerical value (Qh, candidate) for a current computational maximum boiler momentary load (Qh, max) for which at least one flue gas factor (dfi) computed using currently monitored process data with a numerical model of the boiler fulfills an acceptance condition, and selecting the numerical value (Qh, candidate) as the current computational maximum boiler momentary load (Qh,max);
c) indicating the current computational maximum boiler momentary load (Qh,max) to the operator and/or, if the current load (Qh) is
c1) smaller than the current computational maximum boiler momentary load (Qh,max):
c1i) indicating the boiler operator that the boiler load (Qh) may be increased, and/or
c1ii) automatically increasing the boiler load (Qh),
and/or
c2) larger than the current computational maximum boiler momentary load (Qh,max):
c2i) indicating the boiler operator that the boiler load (Qh) exceeds the current computational maximum boiler momentary load, and/or
c2ii) automatically reducing the boiler load (Qh).