WO2011055172A1

WO2011055172A1 - Method of monitoring and optimizing evaporator performance

Info

Publication number: WO2011055172A1
Application number: PCT/IB2010/001107
Authority: WO
Inventors: Senthilmurugan Subbiah; Tarun Prakash Mathur
Original assignee: Abb Research Ltd
Priority date: 2009-11-03
Filing date: 2010-05-13
Publication date: 2011-05-12

Abstract

Fouling of evaporators is a severe problem that results in reduced efficiency of operation of evaporators. Performing maintenance operations on evaporators is a necessary action to ensure continued availability of the evaporator for further use. However, scheduling of maintenance operations is not an easy task. In one aspect, the invention provides a method for operating an evaporator. The method comprises acquiring evaporator data that is selected from a group consisting of temperature, pressure, flow rate, density, viscosity and combinations thereof. The method of the invention then comprises estimating the fouling thickness value using fouling non-linear fouling rate model and the evaporator data. Fouling thickness value is an important measure of the performance of the evaporator. In yet another aspect, the invention provides a system for managing an evaporator.

Description

METHOD OF MONITORING AND OPTIMIZING EVAPORATOR PERFORMANCE

TECHNICAL FIELD The invention relates generally to a method of operating an evaporator and more specifically to estimating a fouling thickness value in an evaporator, and using the estimated fouling thickness value for affecting operations of the evaporator.

BACKGROUND

Evaporators are the equipment for the preferential volatilization of one component from a mixture comprising more than one component. This is done to obtain a concentrated liquor product from bottom and vapor mixture from top of the evaporator. Volatilization is achieved by the supplying of heat, typically from steam to the mixture comprising more than one component. Several types of evaporators are known for different application, each one having been designed to achieve increased productivity, decreased production costs, decreased energy consumption, speed of operation, and ease of operation.

The accumulation of unwanted material on solid surfaces is termed as fouling and it is one of the problems in an evaporator. Fouling refers to the accumulation of material on the walls of an evaporator. The accumulating material may be one of the components of the mixture. The reasons for the occurrence of fouling are manifold, and as noted by Al-Sofi (M.A.K. Al-Sofi, "Fouling phenomena in multi stage flash distillers", Desalination, V. 126 (1999), pp. 61-76), the mechanism of fouling is not very clear and has long been a subject of debate. However, it is quite well-established now that fouling decreases the efficiency of heat transfer, which results in poor energy efficiency, which manifests itself in different ways. For instance, it has been noted that fouling may lead to loss of production rate by 50 percent within a couple of weeks. To ensure maintenance of evaporator productivity, the fouled evaporator heating surface needs to be cleaned.

Several solutions have been proposed to overcome the deleterious effects of fouling. These issues related to fouling can be addressed either during design phase of the evaporator and the plant where the evaporators are installed or during operation of evaporator. For instance, Muller-Steinhagen notes that to compensate the loss of production, many evaporator plants have significant amount of excess heat transfer area, which consequently leads to high maintenance costs (Muller-Steinhagen, H., Fouling: the ultimate challenge for heat exchanger design, Proceedings of the 6th International Symposium on Transport Phenomena in Thermal Engineering II, 811-823 (1993).)· Alternately, US 4,269,030 provides for perturbation of circulation of the heating medium to improve the heat exchange during the operation of evaporator. But the perturbations in the heating medium disturb the evaporator process and affect its rate and quality of the product leaving the evaporator. The method does not take into account any information about the fouling inside the evaporator and thus may result in frequent and unnecessary perturbance to the evaporator process.

One of the most important aspects of the operation of an evaporator, or a plant comprising at least one evaporator, is to constantly monitor the performance of the evaporator and the plant. As noted already, fouling will cause the performance to decrease. However, despite decreased performance, an evaporator may still be used. Typically, the evaporator is shut down for maintenance purposes when the performance has reached a threshold value, such as energy efficiency has reached a minimum value.

The monitoring of performance is a reactive process in that the low efficiency values are observed and subsequently, the actions towards the performance of maintenance are taken. Efforts towards the prediction of when to perform the maintenance operations po^'se a great challenge. It can be understood that an estimation of fouling rate will help in the prediction of evaporator performance. The fouling rate can be estimated using first principle mathematical model of evaporator processes. This model can be used for optimizing production and maintenance schedule for the evaporator plant by minimizing the rate of fouling, which will result in increased overall production and reduced maintenance costs for the evaporator. The fouling rate models, such as linear fouling, falling-rate fouling and asymptotic fouling (for example Sanatgar, H. and E.F.C. Somerscales, Chem. Eng. Prog., December, 53-59 (1991)), are available in literature. However, these models are insufficient in that they differ significantly from experimental observations, especially in extreme conditions. US 4,766,553, US5,615,733 and US6,386,272 provide some mathematical models for the prediction of the fouling rate in an evaporator. However, these relationships are still linear between the fouling rate and the relevant parameters, such as temperature and fouling thickness. As the fouling rate varies non- linearly with temperature and fouling thickness, the linear relationships are valid only for a narrow range within the operating range of the evaporator and fail to accurately predict the actual fouling phenomenon beyond this applicable range. The operating range, here, means the range of values of parameters within which the evaporator is operated, and the parameters may be production rate and other process conditions such as pressure, temperature inside the evaporator, and the like. As the same evaporator can be operated at various operating conditions, the solution based on linear relationship cannot be applied at all the operating conditions. There is still a need in the art for a more relevant model for the prediction of fouling rate and fouling thickness in an evaporator, such that the performance of maintenance operations can be monitored more accurately, and maintenance operations may be scheduled in a more timely manner such that costs of production are kept low, while maintaining the overall plant and/or evaporator productivity and longevity.

BRIEF DESCRIPTION

In one aspect, the invention provides a method for operating an evaporator. The method comprises acquiring evaporator data. The evaporator data includes temperature, pressure, flow rate, density, viscosity, and combinations thereof. The method then involves estimating a fouling thickness value based on a non-linear fouling rate model and the evaporator data. Fouling thickness value of an evaporator is a measure of the performance of the evaporator. The method further comprises affecting operation of the evaporator based on the estimated fouling thickness value.

In another aspect, the invention provides a system for managing an evaporator. The system of the invention comprises a data acquisition module for acquiring evaporator data. The system also comprises an estimation module for estimating a fouling thickness value for the evaporator based on a non-linear rate of fouling model and the evaporator data. The system further comprises an affecting module for affecting operation of the evaporator based on the fouling thickness value. Affecting operation of the evaporator generally includes actions such as, but not limited to, scheduling maintenance, optimization of performance of the evaporator, estimation of performance parameters, and combinations thereof. DRAWINGS

These and other features, aspects, and advantages of the present invention will become better understood when the following detailed description is read with reference to the accompanying drawings in which like characters represent like parts throughout the drawings, wherein:

FIG. 1 is a flowchart representation of exemplary steps of a method of estimating a fouling thickness value for an evaporator; FIG. 2 is a flowchart representation of exemplary steps of a method of scheduling maintenance of a plant;

FIG. 3 is a block diagram representation of an exemplary embodiment of a tool for estimating a fouling thickness value for an evaporator according to one aspect of the invention;

FIG. 4 is a block diagram representation of an exemplary embodiment of a system for monitoring and optimizing the performance of an evaporator according to one aspect of the invention;

FIG. 5 is a block diagram representation of an exemplary embodiment of a system for scheduling maintenance of a plant according to one aspect of the invention; and

FIG. 6 is a graphical representation showing the relationship between the fouling rate and the fouling thickness in one exemplary embodiment.

DETAILED DESCRIPTION As used herein and in the claims, the singular forms "a," "an," and "the" include the plural reference unless the context clearly indicates otherwise.

As used herein, an evaporator is any device, equipment, apparatus, or an apparatus that is used for affecting evaporation. As used herein, evaporation means the removal of a volatile component from a mixture of a multiple components, wherein each of the components has a varying extent of volatility as determined by the corresponding boiling points. Generally, the mixture of components being supplied to the evaporator to be subjected to an evaporation may also be referred to as a liquor in the art. The mixture of components may be present as a simple admixture, a suspension, an emulsion, or a solution. In one exemplary embodiment, an aqueous solution having a solute dissolved in water may be concentrated by boiling off water in an evaporator to obtain solids. In another exemplary embodiment, an aqueous solution having a known concentration of a solute dissolved in known amount of water may be concentrated by the boiling of water in an evaporator to obtain a solution having higher solids content relative to the initial concentration. In another exemplary embodiment, an evaporator may be used to remove volatile organic solvents from organic solutions to obtain concentrated solution or for purifying the solute. In yet another exemplary embodiment, an evaporator is used to evaporate water vapor from salt water / sea water, the process is named as "desalination". Evaporator further is meant to encompass distillers, flash distillers, heat exchangers, and equipment used for selective preferential volatilization of one or more components from a mixture of components. Evaporator typically uses the process of heating the solution above the boiling point of the medium to be removed, thus enabling the removal of the medium. The medium may also be referred to as solvent medium, or simply the solvent in some instances. In some embodiments, instead of increasing the temperature, appropriate amount of vacuum may be applied to facilitate removal of volatile components. The amount of vacuum to be applied depends on the boiling point of the medium, and may be easily determined by one skilled in the art using the pressure- temperature nomograph.

Construction of evaporators is well-known to one skilled in the art. In one exemplary embodiment, a typical evaporator comprises a cold chamber that contains the mixture of components from which the medium needs to be volatilized, and a hot chamber into which a heating medium may be passed. The heating medium then comes in contact with the cold chamber which then results in the heating of the medium in cold chamber. The cold chamber is connected to a condenser that collects the volatilized medium that has been separated from the mixture of components. The hot chamber may be constructed in such a way that ensures the heating medium is circulated around so that the temperatures of the hot chamber and the cold chamber are maintained at a certain value. The cold chamber may further be built to facilitate the collection of the final product from within. Furthermore, the cold chamber may be connected to vacuum outlets to induce lower pressure inside the chamber. In many instances, the heating medium is steam. Variations of this construction of evaporators may also exist depending on the final application and usage. The production rate of the evaporator is defined based on the specific application, (e.g. in pulp mill chemical recovery section, amount of black liquor processed in evaporator per unit of time; in desalination, the amount of product water produced per unit of time, etc.)

In a plant comprising more than one evaporator, for example, multi-stage evaporators, all the evaporators are contained within a larger hot chamber. Through this hot chamber, the heating medium is passed through thus enabling the heating of the evaporators contained within. This manner of construction serves to save material, energy and hence, increase productivity while decreasing costs.

During the operation of an evaporator, several parameters are monitored and/or controlled. Such parameters, also referred to as evaporator data, include, but not limited to, rate of flow of heating medium, rate of flow of the liquor, viscosity of liquor, volume of liquor, temperature of the cold chamber, temperature of the hot chamber, heating medium pressure, pressure inside the cold chamber, surface area of the liquor, density of the liquor, and the like. The monitoring of the parameters may be conducted by at least one operator present at the evaporator facility. Alternately, the monitoring of the parameters may be achieved through some automated means, such as a computer controlled monitoring unit. Furthermore, a combination of at least one operators and an automated means may be used for monitoring the parameters. Similarly, controlling the parameters may be effected by at least one operator or through automated means. In an exemplary embodiment, the temperature of the heating medium is monitored based on which the flow rate of the heating medium is controlled to ensure better operation of the evaporator. During the operation of an evaporator, one of the common occurrences in an evaporator is fouling. As used herein, fouling refers to the accumulation of material on the inside walls of the cold chamber of an evaporator. In many embodiments, the accumulating material may be the solute or the remaining components from the initial mixture. Fouling may also be known as, depending on the context and situation, deposit formation, encrustation, crudding, deposition, scaling, scale formation, slagging, and sludge formation. Fouling results in inefficient operation of the whole evaporation process. Inefficient operation of evaporator may result due to inefficient heat transfer between the hot chamber and the cold chamber. The extent of inefficiency of the evaporation depends on several parameters. Fouling thickness value is one such parameter, and as used herein, means the thickness of the accumulation layer on the inside wall of the cold chamber. The invention provides a method for operating an evaporator. Referring to the drawings, Fig. 1 shows the method of the invention, depicted by the numeral 10, in a flow chart form. The method involves acquiring evaporator data, as depicted by numeral 12 in Fig. 1. Evaporator data, as used herein, refers to the data that is measured to assess the performance of the evaporator. Such data may include parameters such as, but not limited to, temperature, pressure, flow rate, density, viscosity, and combinations thereof. Temperature may refer to the measured temperature of the heating medium at the point of inlet to the hot chamber. In other embodiments, temperature may refer to the average of the measured temperature of the heating medium at one or more points inside the cold chamber. In yet other embodiments, temperature may refer to the measured temperature of the heating medium at the outlet from the hot chamber. In further embodiments, temperature may refer to the temperature measured inside the cold chamber that comprises the mixture of one or more components. Similarly, pressure may refer to the measured inlet pressure of the heating medium or the measured outlet pressure of the heating medium or measured outlet vapor pressure at cold chamber. Flow rate may refer to the rate of flow of the heating medium into the hot chamber or liquor flow rate to cold chamber. Density and viscosity may refer to the measured values of the physical parameters of the mixture of the components in the cold chamber. Measured as used herein, is also meant to include not only measured values but also estimated values through some other calculation means. Techniques for measurement of such data are quite well-known in the art. The exact type of data that is used in the invention depends on the construction of the evaporator and the equipment available on hand to an operator on-site. In some embodiments, the method of the invention involves acquiring combinations of evaporator data. Such combinations may include, for example, but not limited to, inlet heating medium temperature and outlet heating medium temperature; inlet heating medium temperature and outlet heating medium pressure; outlet heating medium temperature, outlet heating medium pressure and viscosity of the mixture of components; and the like. In one specific embodiment, the evaporator data that is acquired is the inlet pressure of the heating medium. Acquiring, as used herein, may include, besides measured values of the evaporator data, estimated values, values obtained from simulations, user inputted values based on past experience or other sources, user modified input based on past experience or available data, etc. In some instances, a combination of steps is used, for example, taking into account measured values and simulated values and averaging them out may be used to mean the acquiring evaporator data.

In the exemplary embodiment a fouling thickness value is estimated using a non-linear fouling rate model as indicated by step 14 in Fig. 1. The non-linear rate of fouling model is a mathematical relationship between a rate of fouling and the fouling thickness value. The rate of fouling provides an estimate of the extent of fouling over a given period of time. It has been empirically seen that when rate of fouling is plotted against fouling thickness value, fouling rate first increases with fouling thickness, then reaches a peak value and then starts decreasing. A typical relationship between rate of fouling and the fouling thickness value is shown graphically in Fig. 6. The graph in Fig. 6 shows that the fouling rate increases initially and then decreases with increasing fouling thickness. Without being bound to any theory, Schreier et al. have explained this observation as occurring due to two opposing phenomena, namely, deposition rate and removal rate of the deposits on the wall of the evaporator (Schreier P. J.R and Fryer P J. "Heat Exchanger Fouling: A model study of the scale up of laboratory data", Chemical Engineering Science, Vol 50, No. 8, ppl311-1321, 1995.) Therefore, one peak is observed in the relationship between fouling rate and fouling thickness. Further, it can be observed from Fig. 6 that rate of fouling reaches asymptotic values as fouling thickness values increases.

To accommodate these observations of the relationship between the rate of fouling and the fouling thickness value, the invention provides a non-linear fouling rate model which is a mathematical relationship equating the rate of fouling and at least one evaporator data through the use of at least one parameter, wherein the relationship between the rate of fouling and the at least one evaporator data is non-linear in nature that is capable of predicting the rate of fouling in an accurate manner across the entire range of operation. The relationship may generally be represented as follows:

*-'<''> 1

dt_f

— - is fouling rate

wherein dt

t_f = fouling thickness

The fouling rate model that most suitably fits the given observation of a single peak value for the rate of fouling for increasing fouling thickness value would be a second order function in fouling thickness generally represented as shown in equation 2:

Any higher order functions such as a third order function will result in more than one peak value for rate of fouling, which would be inconsistent with the observations.

However, a simple second order relationship would be inadequate as such a relationship would also accommodate negative values for rate of fouling, which is not observed in practice. Also, second order relationships do not result in asymptotic behavior, which is also generally observed in practice. An exponential relationship will generally be able to capture the observed behavior, which includes a single peak value and asymptotic values. Thus, in order to capture the asymptotic behavior observed in practical situations, the non-linear fouling rate model of the invention is an exponential relationship between rate of fouling and fouling thickness values, which function may generally be represented as shown in equation 3: ^- = k * exp(b *t_f -a *tf² + c) 3 wherein 'k', 'a', 'b' and 'c' are fouling thickness parameters.

In order to get a positive value of fouling thickness at the peak, the coefficient of t_f and t_f ² , namely 'b' and 'a' respectively should be of opposite signs. Consequently, the non-linear fouling rate model of the invention includes the positive sign before the fouling thickness parameter 'b', but a negative sign before the fouling thickness parameter 'a', wherein the absolute values of the fouling thickness parameters 'a' and 'b' are positive. The non-linear fouling rate model of the invention as described in equation 3 will fit the observed fouling phenomenon of the rate of fouling decreasing with increasing fouling thickness values, which includes a parabolic curve with only one peak value and asymptotic behavior of rate of fouling with increasing fouling thickness values.

In one exemplary embodiment, the non-linear fouling rate model as used herein is represented by the followin

4 where, ε- fouling rate coefficient, t_r fouling thickness value, ¾ and K₂ - fouling thickness parameters, _T - coefficient of fouling temperature parameter, Z_s- mass fraction of solids in the mixture of one or more components, Tr temperature of the mixture of one or more components in the cold chamber at heat transfer surface, A- Area of heat transfer, p- initial density of the mixture of the one or more components. Equation 4 is a specific embodiment of the general non-linear fouling rate model represented by equation 1.

In one exemplary embodiment that provides the use of this non-linear fouling rate model, for a given evaporator having known fouling thickness values t_f and rate of fouling dt_f dt , the parameters ε, _T, Ki and K₂ are estimated. This may be done after a statistically sufficient number of data points for the given evaporator have been obtained. This may subsequently also be validated over a few runs for the given evaporator by the calculation of rate of fouling and ensuring the calculated values match the measured values. Then during operation of the given evaporator, the values of Z_s, Ti, A, and p are measured and input into the equation. The rate of fouling may be calculated for a given evaporator based on the previous measurements. It must be noted that the rate of fouling may vary with several parameters, such as time of operation, extent of operation, amount of volatile components evaporated, density of mixture of components, viscosity of mixture of components, and the like. But with enough data points and careful monitoring of the evaporator, an accurate value may be obtained by one skilled in the art. The fouling thickness is obtained by solving non-linear fouling rate model equation given above as indicated at step 16 in Fig. 1.

In a similar manner any other mathematical relationship equating the rate of fouling and at least one evaporator data through the use of at least one parameter, wherein the relationship between the rate of fouling and the at least one evaporator data is non-linear in nature that is capable of predicting the rate of fouling in an accurate manner across the entire range of operation may be used in this invention. Other types of non-linear relationships between fouling thickness value and rate of fouling that can accurately simulate the observed relationship between fouling thickness value and rate of fouling of an evaporator may be sigmoid function, logarithmic functions, and the like.

Further, variations to the non-linear fouling rate model described herein are also considered to be part of the non-linear fouling rate model of the invention. Thus, for example, a second derivative of the fouling thickness value with respect to time, which may also be viewed as the rate of change of rate of fouling with time, and which is mathematically equivalent to the first derivative of the right hand sife of equation 3, and the specific manifestations of equation 3, such as equation 4, is also included within the invention. Similarly, in another illustrative embodiment, an integrated function of equation 3 is considered to be within the scope of the invention.

The values of the fouling thickness parameters of the equation can be calculated using observed plant data, which may include the peak value of rate of fouling at a given fouling thickness value. Further, the slope of the curve associated with the observed relationship between the rate of fouling and the fouling thickness values, based on the real evaporator plant data, is used to obtain the values of the fouling thickness parameters.

All existing theories in this regard known to those skilled in the art are generally based on an assumption that the rate of fouling and fouling thickness value are related in a linear manner. However, some empirical measurements have shown that the relationship between rate of fouling and fouling thickness value varies substantially from linearity. The non-linear fouling rate model provided in the invention is very useful in that it takes into account the non-linearity of the relationship between the rate of fouling and the fouling thickness value. Hence, the values for rate of fouling, or fouling thickness values may be predicted with a greater degree of accuracy than based on theories known before.

In some embodiments, the evaporator data used for the estimation of fouling thickness value is pressure. Pressure, as mentioned herein, could mean inlet heating medium pressure, outlet heating medium pressure, and so on. In some cases, pressure is measured evaporator data through the use of appropriate instruments. In other instances, pressure is estimated by the conversion of measured evaporator data. In one exemplary embodiment wherein the heating medium is steam, the hot chamber of the evaporator is saturated with steam and the measured evaporator data is temperature, the measured evaporator data may be converted to pressure using an appropriate formula, as shown in equation 5:

wherein P = steam Pressure and T_s = steam temperature.

The method of the invention also provides for affecting operation of the evaporator, depicted by numeral 16 in Fig. 1. Affecting operation of an evaporator, as used herein, means performing appropriate operations on the evaporator as demanded by a given situation, which situation is governed by the estimated fouling thickness value. Operations may include, for example, monitoring performance parameters, scheduling maintenance, performing maintenance on the evaporator, optimization of performance of the evaporator, estimation of performance parameters, and the like, and combinations thereof. Affecting operations of the evaporator may be a direct operation on the evaporator, or may be indirectly conveyed through the use of an intermediate step or an intermediate unit.

It may be easily understood that the as the fouling thickness value increases, the performance of the evaporator will decrease. Performance of an evaporator may generally be understood as the optimum utilization of resources, maximum productivity, production capacity, and the like. Performance of an evaporator may be evaluated through the estimation of performance parameters. Such performance parameters may include projected fouling thickness value, heat transfer coefficient, steam economy, maintenance schedule timing, maintenance cost, operation costs, rate of flow of steam, rate of flow of liquor, and the like, and combinations thereof. In one exemplary embodiment wherein the performance parameter is steam economy, the mathematical relationship generally used to measure the steam economy, defined as the quantity of water evaporated per unit of steam supplied, is given in equation 6:

Steam Economy = ^Amount °f ^water evaporated ₌ F,„(l - Z,„) -F_oul (l - Z_oul ) ₆

Amount of steam sup plied G

wherein

F_in = Flow rate of inlet liquor to be evaporated (expressed in kilograms per second or kg/s) Z_jn = mass fraction of solute in the inlet liquor

Z_out = mass fraction of solute in outlet product liquor stream

F_out = Flow rate of outlet product liquor stream (kg/s)

G = Flow rate of steam entering the evaporator plant (kg/s) Any or all of the inputs for the right hand side of the equation 6 can be estimated using the fouling thickness value estimated using the non-linear fouling rate model of the invention. Thus, the steam economy that is estimated based on the non-linear fouling rate model is used as the performance parameters of a given evaporator. Similarly, other given performance parameters may be estimated using the fouling thickness value, which in turn is estimated using the non-linear fouling rate model of the invention.

Projected fouling thickness value may be a simple extension of available fouling thickness values to obtain a future predicted value. Projections of existing fouling thickness values to obtain projected fouling thickness values may be obtained using suitable techniques known in the art, such as simulations, graphs, user or operator's experience, expert consultation and the like.

The heat transfer coefficient value is a measure of the transfer of heat from the heating medium in the hot chamber to the mixture of one or more components in the cold chamber. One skilled in the art will appreciate that the greater the fouling thickness value, the less efficient the heat transfer will be, and consequently, the heat transfer coefficient value will reflect this. Thus, in one embodiment, the invention provides a method for monitoring a performance of an evaporator using the heat transfer coefficient value.

The monitoring of the performance parameters may be conducted by at least one operator present at the evaporator facility. Alternately, the monitoring of the performance parameters may be achieved through some automated means, such as a computer controlled monitoring unit. Further, a combination of at least one operators and an automated means may be used for monitoring the performance parameters.

In an alternate embodiment, the performance parameters may be estimated through the appropriate use of mathematical relationships relating the monitored parameters and the performance parameters. More accurate estimation of fouling thickness values for an evaporator results in more accurate estimations of the performance parameters of the evaporator. Once a better estimate of the performance parameters is made, then the performance of the evaporator may be optimized better through the appropriate control of the parameters. As an example, when during the operation of the evaporator, the temperature of steam is found to decrease, and the non-linear fouling rate model shows a particular fouling thickness value, the flow rate of the liquor may be adjusted to provide better heating of the liquor, so as to ensure more efficient of the evaporator. The optimization of performance of an evaporator may be achieved by controlling the parameters by at least one operator or through automated means, or a combination thereof.

In another embodiment, the fouling thickness value is used to estimate cost of operating the evaporator. As one skilled in the art may appreciate, when the fouling thickness value increases, the heat transfer coefficient is affected, which may lead to appropriate adjustment of the operating conditions, such as increased steam flow rate, decreased liquor flow rate, higher pressure, greater vacuum, and the like. Each of the steps described will result in increased cost of operation, and thus, it is highly advantageous to optimize the same. Using the more accurately estimated fouling thickness value, such costs may be better optimized.

Typically, maintenance of an evaporator involves shutting down the facility, opening the evaporator, removing the fouling deposits by following appropriate procedures, washing the fouling deposits off, drying the evaporator if necessary, and closing it to get the evaporator ready for subsequent operation. It has been empirically determined that it is practical to perform such maintenance operations only when the fouling thickness value reaches a certain range of threshold values. Performing the maintenance operations earlier would not be very efficient in that it may affect product costs, while performing the maintenance operations later may result in greater cleaning costs, or in some instances, cleaning the fouling deposits may become impossible resulting in high replacement costs. Thus, the non-linear fouling rate model provided in the invention that is used in the method of the invention finds tremendous use in the accurate estimation of fouling thickness value and perform more timely scheduling of maintenance operation of an evaporator. The maintenance schedule timing is a performance parameter, wherein the evaporator data and the fouling thickness value are used to estimate the time taken to reach a certain value for a given parameter, such as a threshold value of a fouling thickness value, and based on this, a maintenance schedule timing in appropriate units, such as hours or days is generated. As stated herein, performance of maintenance incurs a certain cost. It can be inferred by one skilled in the art that the fouling thickness value has a direct impact on the amount of cleaning materials used, the time taken to clean, and so on; and hence, the fouling thickness value has a direct impact on the maintenance costs. Thus, in one embodiment, maintenance costs of the evaporator is a performance parameter also.

In one embodiment, the invention provides for performing the maintenance of the evaporator based on the fouling thickness value estimated using the non-linear fouling rate model. As one skilled in the art would also appreciate, the method of the invention is capable of being applicable to a plant that comprises more than one evaporator. In the situation wherein there are more than one evaporator, the same method may be applied to the optimum operation of the entire plant instead of a single evaporator, by taking into account the performance of each individual evaporator, and combining the data to calculate the performance parameters of the whole plant as such, and accordingly monitor performance parameters of the plant, estimate performance parameters of the plant, optimize performance of the plant, schedule maintenance of the plant, perform maintenance of the plant, and combinations thereof. In another aspect, the invention provides a method of scheduling and optimizing the maintenance of a plant and the method ensures that the previously mentioned constraints are met, wherein the plant comprises at least one evaporator, the method being depicted by numeral 20 in Fig. 2. The maintenance of the plant may be scheduled within a certain time horizon, for example within 4 months, or within 2 years, and so on. The method comprises estimating a fouling thickness value for each evaporator using the non-linear fouling rate model provided herein, and an evaporator data, which is depicted by numeral 16 in Fig. 2. The fouling thickness value is then used to estimate the cost of performing maintenance on each evaporator, which is shown by numeral 22 in Fig. 2. The cost may include the cost of tools required, cleaning materials and equipment, labor involved, costs associated with downtime of the evaporator, costs associated with wear and tear of the tools, cleaning equipment and the evaporator, and the like. Further, this cost can be called as objective function value for scheduling optimization.

The estimated cost of performing maintenance on each evaporator is then used to calculate a cost of performing maintenance on the plant. This is shown by the numeral 24 in Fig. 2. The cost of performing maintenance on the plant may be simple summation of the costs of performing maintenance on all the evaporators. Alternately, the costs may also include some extra costs associated with the plant. Once the costs of performing maintenance on the plant have been estimated, the exact time of performing maintenance of the plant may be scheduled. The maintenance schedule can thus be planned where the maintenance cost (objective function value) is minimum and certain constrains are met. The scheduling of maintenance of plant is depicted by numeral 26 in Fig. 2.

As stated herein, the non-linear fouling rate model provides for a more accurate estimation, and even prediction, of fouling thickness value. This greater accuracy will result in a more accurate estimation of cost of performing maintenance on each evaporator, which will further result in a more accurate estimation of cost of performing maintenance on the plant. Furthermore, since the non-linear fouling rate model can provide for a more accurate prediction of the fouling thickness values, the estimation of costs of performing maintenance on each evaporator, and consequently, on the plant, at a future date will also be fairly accurate. Thus, with more accurate data available on hand, better maintenance schedules can be generated for the plant that optimizes the longevity of the plant and equipments, raw materials used, costs of production, costs of downtime, and other such operational parameters.

The method further provides as indicated at step 28, optimizing the maintenance cost of the evaporator plant during a certain time horizon (e.g. 4 months, 2 years horizon etc.). During scheduling calculations for minimization maintenance costs and certain constraints are met, these include but are not limited to, demand side constraints, for example in a pulp mill chemical recovery section the downstream process includes a recovery boiler that demands a certain flow of concentrated liquid from evaporators to be fed to it. In another example where the plant is the desalination plant, it is the demand of water from customer that needs to be met. The calculation of maintenance schedule ensures that these demands are always met. Similarly, there may be supply side constraints as well that need to met while scheduling maintenance. The supply side constraints include but are not limited to for example, in pulp plants, the availability of the black liquor to be processed poses a constraint on the evaporator. Similarly, in a desalination plant, the availability of feed water from pretreatment process is the constraint.

Another constraint to be met while scheduling maintenance is related to the fouling thickness. The fouling thickness at maintenance should be less than the threshold value of the fouling as described earlier. This is important because if the maintenance is delayed, one allows the fouling thickness to build up which decreases the steam economy of the evaporators during its operation. Also, the cost of chemicals and energy required to clean the fouled surfaces is increased due to delay in the maintenance. On the other hand, if maintenance is done before required, it results in loss of production and the plant may not be able to meet the demand from the customers or the downstream processes.

Thus the method of the invention calculates the optimum schedule for maintenance by considering the trade-off between the different costs (loss of production cost, chemical and energy costs, operational cost due to decrease in steam economy etc.).

It may be noted here that the method steps described herein need not be discreet steps and two or more steps may be combined in a single module during implementation. The following exemplary implementations are also to be understood in the same light and under implementation, two or more of the different components may be combined to provide a combined functionality. In another aspect, the invention provides a tool for estimating a fouling thickness value for an evaporator. The tool is illustrated in a diagrammatic representation in Fig. 3 by reference numeral 30. The tool comprises a receiver 32 for receiving evaporator data. The tool also comprises a calculator 34 for calculating the rate of fouling based on the non-linear fouling rate model provided in the invention. The tool comprises a first estimator 36 that is used to estimate the fouling thickness value for the evaporator. The tool follows the method of the invention as explained in reference with Fig. 1 and Fig. 2, to estimate the fouling thickness value using the non-linear fouling rate model provided in the invention to calculate the rate of fouling. As mentioned herein, the various parameters of the fouling rate model are determined based on a series of experiments with known, measured and/or estimated values for the rate of fouling and fouling thickness values. These values are then used to calculate the rate of fouling, which is then used to accurately estimate the fouling thickness value for a given evaporator. The tool further comprises a monitor, depicted by numeral 40 in Fig. 3, which monitors the performance of the evaporator based on the fouling thickness value. The tool may have some predetermined values inputted for the fouling thickness value, based on which the tool is capable of providing feedback to an operator regarding the performance of the evaporator. The monitor 40 will provide inputs to the scheduler 42 in the tool that may be used to schedule the maintenance operations.

The tool may further comprise a second estimator, depicted by numeral 38 in Fig. 3, that estimates the heat transfer coefficient value using the fouling thickness value. As mentioned in reference with Fig. 1 , the heat transfer coefficient and it's value has a direct relationship with the performance of the evaporator and hence it is one of the critical performance parameters. The tool then inputs the value from the second estimator to the monitor 40, whose output in turn is the input for the scheduler 42.

In yet another aspect, the invention provides a system for managing an evaporator, shown in Fig. 4 and depicted by numeral 44. The system comprises a data acquisition module 46 that is used to acquire evaporator data. Acquiring, as used herein, may include, besides measured values of the evaporator data, estimated values, values obtained from simulations, user inputted values based on past experience or other sources, user modified input based on past experience or available date, etc. In some instances, a combination of steps, for example, taking into account measured values and simulated values and averaging them out, may be used to mean the acquiring evaporator data. The system also comprises an estimation module 50 that is used to estimate a fouling thickness value based on the non-linear fouling rate model and the evaporator data.

The system of the invention further comprises an affecting module 52 that affects the operation of the evaporator based on the estimated fouling thickness value. As used herein, affecting operation of the evaporator includes scheduling maintenance, optimization of performance of the evaporator, estimation of performance parameters, and combinations thereof.

In yet another aspect, the invention provides a system for monitoring and optimizing the performance of the evaporator, depicted by the numeral 44 in Fig. 4. The system comprises a data acquisition module 46 for acquiring evaporator data. The evaporator data is then input into the tool 30 for estimating the fouling thickness value (as explained in reference with Fig. 3) that is capable of calculating a rate of fouling based on the non-linear fouling rate model provided by the invention. The fouling thickness value is used as a measure of performance of the evaporator.

The output module is capable of communicating performance monitoring parameters to an operator. Some exemplary performance monitoring parameters include, but not limited to, pressure of the heating medium at the inlet, outlet temperature, elapsed time since last performed maintenance, fouling thickness value, heat transfer coefficient value (also obtained by tool 30 as explained in reference with Fig. 3) and the like. The manner of communicating by the output module may include, among other ways, displaying the actual values in a digital or analog manner, flashing a color-coded light, sounding an alarm, and the like. The system of the invention may also comprise a controller module that controls the above mentioned one or more performance monitoring parameters, such as pressure, temperature, and the like. In one specific embodiment, the performance monitoring parameters includes input pressure of a heating medium, for example steam. Steam pressure is an important parameter to improve the performance of the evaporator.

The system 44 further includes a performance optimization module for optimizing one or more performance indices for the evaporator, for example steam economy. The performance optimization module calculates optimum steam pressure for the evaporator or for each stage of the multi-effect evaporator by maximizing the steam economy. The performance optimization module also undertakes to meet the performance optimization constrains like the production rate of the evaporator; the quality of product from the evaporator; and the threshold values of the fouling thickness as described herein. The system may also comprise a monitoring module that monitors the performance of the evaporator, which may be recorded or displayed. The performance of the evaporator can be monitored over a period of time, and the data obtained and/or recorded therein may be used to perform scheduling of performance of maintenance operations.

In alternate embodiments, the system itself comprises a maintenance module 58 that can schedule maintenance of the evaporator. In situations where the performance of maintenance operations is conducive for automation, the maintenance module may automatically activate the performance of maintenance operations in the evaporator. In other situations, the maintenance module may provide appropriate messages to one or more operators associated with the evaporator regarding the performance of maintenance operations schedule. The maintenance module is also configured to optimize the maintenance cost of the evaporator plant during a certain time horizon (e.g. 4 months, 2 years horizon etc.). The maintenance module calculates maintenance costs and provides an optimized maintenance schedule while taking into account certain constraints such as demand side constraints and supply side constraints as mentioned herein before. The maintenance module also ensures that the fouling thickness at maintenance is less than the threshold value of the fouling as described earlier. The maintenance module thus provides an optimum maintenance schedule for the evaporator.

It will be appreciated by those skilled in the art that the above system for monitoring and optimizing the performance of the evaporator, described herein above can be tailored to provide maintenance system for an entire plant that includes one or more evaporators. Fig. 5 is a block diagram illustration of such a plant maintenance system 60 that includes the system for monitoring and optimizing the performance of the evaporator 44. In the case of the plant having more than one evaporators, it may be understood to one skilled in the art that each individual evaporator may comprise a data acquisition module, or alternately, all the evaporators feed evaporator data into a single data acquisition module, or some evaporators may have their own individual data acquisition module and a group of evaporators may have a single data acquisition module. In all these situations, when more than one data acquisition module is present, all of them are collectively referred to as data acquisition module.

The plant maintenance system 60 may additionally include a first cost estimating module 62 that is capable of estimating a cost of performing maintenance on each evaporator based on the calculated values from the system 44. The maintenance system 60 also comprises a second cost estimating module 64 for estimating a cost of performing maintenance on the entire plant. The cost of performing maintenance on the plant may be simple summation of the costs of performing maintenance on all the evaporators. Alternately, the costs may also include some extra costs associated with the plant. Once the costs of performing maintenance on the plant have been estimated, the exact time of performing maintenance of the plant may be scheduled. The plant system 60 further comprises a plant maintenance scheduling module 66 for scheduling maintenance of the plant based on the cost of performing maintenance on the plant. The system of the invention gives better maintenance schedules for the plant that optimizes the performance of the evaporators, longevity of the plant and equipments, raw materials used, costs of production, costs of downtime, and other such operational parameters.

EXAMPLES

Case 1

Values of parameters

AT, = 0.0001 m

K₂ = 0.0001 m

K_T = 273.15 K

Α= 00 m²

-]

The graph associated with this equation is shown in Fig. 6, and depicted by the numeral 68. The graph is between the rate of fouling and fouling thickness value. As can be seen, the graph is non-linear in nature.

For the graphs shown in Figs. 6, X-axis is the fouling thickness which is represented by t_f in the

dt_f equations above, and Y-axis of the graph is the fouling rate which is represented by—— . The

dt graph is plotted using the equation defined above. The graphs represent the non linear behavior of fouling rate with the fouling thickness. Initially, the fouling rate increases with the increase in fouling thickness. After reaching a peak value, the fouling rate starts decreasing with the fouling thickness. The linear models currently used in prior art systems do not capture the fouling phenomenon as accurately as the non-linear model of the invention that advantageously captures a non linear relationship between fouling rate and fouling thickness. The linear model will either represent the increasing or decreasing relationship only. This invention provides an alternate and a more accurate model over the existing prior art for the prediction of rate of fouling and for the estimation of fouling thickness values, which manifests in the better scheduling of maintenance operations of an evaporator. This is critical in the general upkeep to maintain high productivities while simultaneously maintaining low costs. While only certain features of the invention have been illustrated and described herein, many modifications and changes will occur to those skilled in the art. It is, therefore, to be understood that the appended claims are intended to cover all such modifications and changes as fall within the true spirit of the invention.

Claims

WE CLAIM:

1. A method ( 10) for operating an evaporator, the method comprising:

acquiring evaporator data (12), the evaporator data being selected from a group consisting of temperature, pressure, flow rate, density, viscosity, or combinations thereof;

estimating a fouling thickness value (14) based on a non-linear fouling rate model and the evaporator data;

affecting operation of the evaporator (16) based on the estimated fouling thickness value.

2. The method as claimed in Claim 1, wherein affecting operation of the evaporator is selected from the group consisting of monitoring of performance parameters, estimation of performance parameters, optimization of performance of the evaporator, scheduling maintenance, performing maintenance, or combinations thereof.

3. The method as claimed in Claim 2, wherein the performance parameters is selected from the group consisting of projected fouling thickness value, heat transfer coefficient, steam economy, maintenance schedule timing, maintenance cost, operation costs, rate of flow of steam, rate of flow of liquor, or combinations thereof.

4. The method as claimed in Claim 1 , wherein the affecting operation of the evaporator is affected directly or indirectly.

5. The method as claimed in Claim 1, wherein the acquiring of evaporator data is through one of measurement, simulation, estimation, user input of evaporator data, user modified input of evaporator data, or combinations thereof.

6. The method as claimed in Claim 1 , wherein the non-linear fouling rate model is based on fouling thickness value, rate of fouling, temperature, pressure, or combinations thereof.

7. A system (44) for managing an evaporator, the system comprising:

a data acquisition module (46) for acquiring evaporator data;

an estimation module (50) for estimating a fouling thickness value based on a non-linear fouling model and the evaporator data; and

an affecting module (52) for affecting operation of the evaporator based on the fouling thickness value; wherein the affecting operation of the evaporator is selected from the group consisting of scheduling maintenance, optimization of performance of the evaporator, estimation of performance parameters, monitoring of performance, performing maintenance, or combinations thereof.

8. The system as claimed in Claim 7, wherein the acquiring of evaporator data is through one of measurement, simulation, estimation, user input of evaporator data, user modified input of evaporator data, or combinations thereof.

9. A plant that uses the system as claimed in Claim 7.

10. A plant that comprises the system as claimed in Claim 7.