CN113757701A - Intelligent soot blowing control method and system based on multi-dimensional evaluation factor and storage medium - Google Patents
Intelligent soot blowing control method and system based on multi-dimensional evaluation factor and storage medium Download PDFInfo
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- CN113757701A CN113757701A CN202110777782.XA CN202110777782A CN113757701A CN 113757701 A CN113757701 A CN 113757701A CN 202110777782 A CN202110777782 A CN 202110777782A CN 113757701 A CN113757701 A CN 113757701A
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F23—COMBUSTION APPARATUS; COMBUSTION PROCESSES
- F23J—REMOVAL OR TREATMENT OF COMBUSTION PRODUCTS OR COMBUSTION RESIDUES; FLUES
- F23J1/00—Removing ash, clinker, or slag from combustion chambers
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F23—COMBUSTION APPARATUS; COMBUSTION PROCESSES
- F23J—REMOVAL OR TREATMENT OF COMBUSTION PRODUCTS OR COMBUSTION RESIDUES; FLUES
- F23J3/00—Removing solid residues from passages or chambers beyond the fire, e.g. from flues by soot blowers
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Abstract
The invention discloses an intelligent soot blowing control method, system and storage medium based on multidimensional evaluation factors.A plurality of boiler operation parameters reflecting the contamination degree of a heating surface corresponding to a soot blower and the influence of soot blowing on the safety and economy of boiler operation are selected as the evaluation factors of the selected soot blower, and the evaluation factors are respectively subjected to priority level grouping according to the magnitude of the influence of the evaluation factors on the safety of the boiler, the magnitude of the influence of the economy operation degree and the magnitude of the correlation degree between the evaluation factors and the contamination of the heating surface; judging whether the value of each evaluation factor is in a normal state range, counting the number of the evaluation factors of which the values are not in the normal state range in each group of priority levels, and judging whether a soot blower needs to perform soot blowing according to the number of the evaluation factors of which the values are not in the normal state range in each group of priority levels, thereby reducing the soot blowing steam loss of a power plant, reducing the blowing loss risk of a heating surface and improving the safety and the economy of the operation of a boiler.
Description
Technical Field
The invention relates to the field of intelligent control of coal-fired boiler equipment, in particular to an intelligent soot blowing control method and system based on a multi-dimensional evaluation factor and a storage medium.
Background
In the process of pulverized coal combustion of a boiler of a thermal power generating unit, due to deposition of incombustible minerals, different degrees of ash deposition and slag bonding can be generated on each heating surface. The heat transfer performance of the heating surface is reduced by the deposition and slagging of ash on the heating surface, and the heat transfer performance is a main reason for seriously influencing the boiler output and the boiler efficiency. Therefore, in the operation of the boiler, the soot blower is adopted to blow the heating surface in time, which is very important for the efficient and safe operation of the boiler.
The existing soot blowing control strategy of the boiler generally performs soot blowing according to a smoke flow sequence regularly based on an operation rule, which inevitably causes frequent or untimely soot blowing. Too frequent soot blowing not only wastes the steam investment cost of soot blowing, but also easily causes the blowing loss and thinning of the heating surface of the boiler, and increases the maintenance cost; the untimely soot blowing causes excessive soot deposition on a heating surface, reduces the heat transfer effect of the heating surface, causes the reduction of the economical efficiency of the unit, and more seriously causes steam temperature deviation and overtemperature of the pipe wall to influence the safe operation of the unit. And the sequential program control soot blowing according to the flue gas flow possibly causes the phenomena of over-temperature of a water cooling wall, over-low temperature or over-temperature of main steam and the like. In addition, there are many types of sootblowers, and the specific location and specific time at which the sootblowers of different types are applied also have different effects on the sootblowing effect and the boiler.
The soot blowing optimization system at the present stage evaluates the contamination degree of the heating surface by a common modeling method, but the related factors influencing soot blowing are more, the factors have volatility and coupling, and the established model is difficult to accurately reflect the actual contamination condition of the heating surface of the boiler. In addition, the influence of soot blowing on the boiler operation parameters is not considered in the method, and the boiler operation parameters deviate from the design values more in the soot blowing process or after soot blowing, so that the safe and economic operation of the boiler is influenced.
Therefore, the established soot blowing optimization scheme has poor effect due to the fact that the existing soot blowing optimization system cannot accurately evaluate the contamination degree of the heating surface and the influence of soot blowing on the safe and economic operation of the boiler, and the technical problem to be solved urgently by technical personnel in the field is solved, and it is very necessary to research the fine on-demand soot blowing based on the combination of the boiler operation parameter optimization and the heating surface cleanliness degree.
Disclosure of Invention
The invention provides an intelligent soot blowing control method, an intelligent soot blowing control system and a storage medium based on a multidimensional evaluation factor, which are used for solving the technical problem that the established soot blowing optimization scheme has poor effect because the existing soot blowing optimization system cannot accurately evaluate the contamination degree of a heating surface and the influence of soot blowing on the safe and economic operation of a boiler.
In order to solve the technical problems, the technical scheme provided by the invention is as follows:
an intelligent soot blowing control method based on a multi-dimensional evaluation factor comprises the following steps:
selecting a plurality of boiler operation parameters as evaluation factors for selecting the soot blowers according to expert experience and mechanism analysis, wherein the plurality of boiler operation parameters reflect the contamination degree of the heating surfaces corresponding to the soot blowers and the influence of soot blowing on the safety and economy of boiler operation;
according to the influence of each evaluation factor on the safety of the boiler, the influence of the economic operation degree and the correlation degree between the evaluation factor and the contamination of the heating surface, priority level grouping is respectively carried out on each evaluation factor;
judging whether the value of each evaluation factor is in a normal state range, counting the number of the evaluation factors of which the values are not in the normal state range in each group of priority levels, judging whether the soot blower is required to blow soot according to the number of the evaluation factors of which the values are not in the normal state range in each group of priority levels, and if so, starting the soot blower to blow soot.
Preferably, when the soot blower is a short hearth soot blower, the evaluation factor includes: the method comprises the following steps of (1) furnace outlet smoke temperature, water wall temperature, superheat degree, superheater desuperheating water quantity, screen wall temperature, high wall temperature, main steam temperature, reheated steam temperature, denitration system inlet smoke temperature and exhaust gas temperature;
when the soot blower is a screen-over soot blower, the evaluation factors include: the method comprises the following steps of (1) furnace outlet smoke temperature, screen passing inlet and outlet working medium temperature rise, superheater desuperheating water quantity, flue gas baffle opening, screen passing wall temperature deviation, screen passing wall temperature maximum value, screen passing flue gas side differential pressure, main steam temperature, reheated steam temperature, denitration system inlet smoke temperature and exhaust gas temperature;
when the soot blower is above the soot blower, the evaluation factors include: the temperature of the working medium is higher than the temperature rise of the inlet working medium and the outlet working medium, the temperature reduction water quantity of the superheater, the opening degree of a flue gas baffle, the deviation of the temperature of the superheater, the maximum value of the temperature of the superheater, the pressure difference of the side of the superheater, the temperature of main steam, the temperature of reheated steam, the inlet flue gas temperature of a denitration system and the exhaust gas temperature;
when the soot blower is a high soot blower, the evaluation factors include: temperature rise of working media at a high re-inlet and outlet, opening degree of a flue gas baffle, temperature reduction water quantity of a reheater, high re-wall temperature deviation, maximum value of high re-wall temperature, high re-flue gas side differential pressure, main steam temperature, reheated steam temperature, inlet smoke temperature of a denitration system and exhaust gas temperature;
when the soot blower is a low over-blow soot blower, the evaluation factors include: low excess outlet pipe wall temperature, low excess inlet working medium temperature, low excess outlet flue gas temperature, air preheater inlet flue gas temperature, low excess side flue gas resistance, denitration system inlet flue gas temperature, smoke exhaust temperature and draught fan current;
when the soot blower is a low reblowing soot blower, the evaluation factors include: low reentry outlet pipe wall temperature, low reentry, outlet working medium temperature, low reentry, outlet flue gas temperature, air preheater inlet flue gas temperature, low reentry side flue gas resistance, denitration system inlet flue gas temperature, smoke exhaust temperature and draught fan current;
when the soot blower is an economizer soot blower, the evaluation factors include: the temperature of working media at the inlet and the outlet of the economizer, the temperature of flue gas at the inlet of the air preheater, the resistance of the flue gas of the economizer, the temperature of flue gas at the inlet of a denitration system, the temperature of flue gas discharged and the current of an induced draft fan;
when the soot blower is an air preheater soot blower group, the evaluation factors comprise: the method comprises the steps of measuring the temperature of inlet flue gas of the air preheater, the temperature of outlet flue gas of the air preheater, the side resistance of the flue gas of the air preheater, the side resistance of primary air of the air preheater, the side resistance of secondary air of the air preheater and the current of a draught fan.
Preferably, the method for priority level grouping of the evaluation factors according to the influence of the evaluation factors on the safety of the boiler, the influence of the economic operation degree and the correlation degree with the contamination of the heating surface comprises the following steps:
for each evaluation factor the following steps are performed:
analyzing the influence of the evaluation factor on the safety of the boiler, comparing the influence of the evaluation factor on the safety of the boiler with a preset first safety influence threshold, and if the influence of the evaluation factor on the safety of the boiler is greater than the preset first safety influence threshold, judging the evaluation factor as a first priority layer;
if the influence value of the evaluation factor on the boiler safety is smaller than a preset first safety influence threshold value and larger than a preset second safety influence threshold value, wherein the first safety influence threshold value is larger than the second safety influence threshold value and meets any one of the following conditions, the evaluation factor is judged to be a second priority level:
the influence value of the evaluation factor on the economic operation degree exceeds a preset economic influence threshold value;
the correlation degree value between the evaluation factor and the heating surface contamination exceeds a preset heating surface contamination degree threshold value;
if the influence value of the evaluation factor on the boiler safety is smaller than a preset second safety influence threshold value or the following conditions are met, judging that the evaluation factor is a third priority level:
the influence value of the evaluation factor on the economic operation degree does not exceed a preset economic influence threshold value;
the correlation degree value between the evaluation factor and the heating surface contamination does not exceed a preset heating surface contamination degree threshold value.
Preferably, the evaluation factors are respectively subjected to priority level grouping according to the influence of the evaluation factors on the safety of the boiler, the influence of the economic operation degree and the correlation degree between the evaluation factors and the contamination of the heating surface, and the following steps are implemented by searching the following table:
evaluation factor grading table for each soot blower group
Preferably, the determining whether the value of each evaluation factor is within the normal state range specifically includes the following steps:
for each evaluation factor the following steps are performed:
acquiring historical data of the category evaluation factors, calculating the mean value and standard deviation of the historical data, and calculating the value range of the normal value of the category evaluation factors as an evaluation standard Y by the following formula:
Y＝μ±xσ；
mu is the average value of the historical data distribution of the category evaluation factors, sigma is the standard deviation of the historical data distribution of the category evaluation factors, and x is the soot blower optimization saturation factor and is determined according to the unit condition;
and comparing the value of the evaluation factor with the evaluation criterion Y, if the value of the evaluation factor is within the evaluation criterion Y, judging that the evaluation factor is within the normal state range, and if the value of the evaluation factor is not within the evaluation criterion Y, judging that the value of the evaluation factor is not within the normal state range.
Preferably, the value of the evaluation criterion is not greater than the alarm value of the corresponding evaluation factor, the value of the evaluation criterion is within the operation safety margin of the corresponding evaluation factor, and the deviation of the normal operation average value of the corresponding evaluation factor is considered.
Preferably, the method for judging whether the soot blowing of the soot blower is needed or not according to the number of the evaluation factors which are in the priority levels of each group and have values not in the normal state range comprises the following steps:
calculating a comprehensive evaluation value of the evaluation factors according to the following formula:
S＝an(in)+bn(jn)+cn(kn)；
where S is a comprehensive evaluation value, a is a weight of the first priority level, and n (i)n) The number of evaluation factors in the first priority level, the values of which are not in the normal state values; b is the weight of the second priority level, n (j)n) The number of evaluation factors in the second priority level, the values of which are not in the normal state values; c is the weight of the third priority level, n (k)n) The number of evaluation factors in the third priority level, the value of which is not in the normal state value, wherein a is more than b and more than c, and 0 is more than a, 0 is more than b, and 0 is more than c;
and comparing the comprehensive evaluation value with a preset evaluation threshold, judging that the soot blower is required to blow soot when the comprehensive evaluation value is greater than the preset evaluation threshold, and judging that the soot blower is not required to blow soot when the comprehensive evaluation value is less than or equal to the preset evaluation threshold.
Preferably, the evaluation criterion Y value may be updated in a rolling manner according to historical data of a previous period of time to adapt to changes of different coal types, the length of the period of time may be determined according to the actual situation of the unit, the update range of the evaluation criterion Y value may be adjusted, and the updated Y value is Y-Y0+λ(Yn-Y0) Wherein Y is0For the evaluation criteria before update, YnThe evaluation criterion is calculated for historical data n days before updating, and the lambda is the evaluation criterion updating amplitude factor and the preferred value rangeThe circumference is 0.1-1.0.
A computer system comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the steps of the method being performed when the computer program is executed by the processor.
A computer storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the above method.
The invention has the following beneficial effects:
1. according to the intelligent soot blowing control method, system and storage medium based on the multidimensional evaluation factor, a plurality of boiler operation parameters are selected as the evaluation factor for selecting the soot blower, and the boiler operation parameters reflect the contamination degree of the heating surface corresponding to the soot blower and the influence of soot blowing on the safety and economy of boiler operation; according to the influence of each evaluation factor on the safety of the boiler, the influence of the economic operation degree and the correlation degree between the evaluation factor and the contamination of the heating surface, priority level grouping is respectively carried out on each evaluation factor; judging whether the value of each evaluation factor is in a normal state range, counting the number of the evaluation factors of which the values are not in the normal state range in each group of priority levels, and judging whether the soot blowing of the soot blower is needed according to the number of the evaluation factors of which the values are not in the normal state range in each group of priority levels. The invention can accurately judge the degree of contamination of the heating surface corresponding to the selected soot blower and the influence of soot blowing on the safety and the economy of boiler operation, and determine whether to adopt the soot blower to perform soot blowing according to the judged influence, thereby reducing the soot blowing steam loss of a power plant, reducing the blowing loss risk of the heating surface, reducing the overhauling and maintenance of soot blowing equipment and the labor amount of soot blowing, and improving the safety and the economy of boiler operation.
2. In the preferred scheme, the soot blowing optimization, the boiler operation parameter optimization and the heating surface cleaning degree are combined by using a big data self-defined algorithm to carry out multi-dimensional evaluation, so that the fine soot blowing according to the requirement is realized.
3. In a preferred scheme, the evaluation criterion Y in the invention is updated in a rolling manner according to the historical data of the previous n days, so that a self-learning function is realized, and the change of different coal types is adapted.
4. In a preferred scheme, the multidimensional evaluation factors of each heating surface are divided into different levels according to the degree of influencing the safe and economic operation of the boiler and the degree of association between the contamination condition of the heating surface and the evaluation factors, and different judgment conditions are adopted in different levels to realize the priority ranking and differentiation of the evaluation factors, so that the influence of soot blowing of a soot blower on the operation state of the boiler can be evaluated more accurately.
In addition to the objects, features and advantages described above, other objects, features and advantages of the present invention are also provided. The present invention will be described in further detail below with reference to the accompanying drawings.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the invention and, together with the description, serve to explain the invention and not to limit the invention. In the drawings:
FIG. 1 is a flow chart of an intelligent soot blowing control method based on a multi-dimensional evaluation factor according to the present invention;
fig. 2 is a flow chart of an intelligent soot blowing control method based on a multi-dimensional evaluation factor in the preferred embodiment of the present invention.
Detailed Description
The embodiments of the invention will be described in detail below with reference to the drawings, but the invention can be implemented in many different ways as defined and covered by the claims.
The first embodiment is as follows:
as shown in fig. 1, the present embodiment discloses an intelligent soot blowing control method based on a multidimensional evaluation factor, which includes the following steps:
selecting a plurality of boiler operation parameters as evaluation factors for selecting the soot blowers according to expert experience and mechanism analysis, wherein the plurality of boiler operation parameters reflect the influence of areas corresponding to the soot blowers and ash layers of corresponding types on the safety and economic operation degree of the boiler and the correlation degree of the contamination of the corresponding heated surfaces;
according to the influence of each evaluation factor on the safety of the boiler, the influence of the economic operation degree and the correlation degree between the evaluation factor and the contamination of the heating surface, priority level grouping is respectively carried out on each evaluation factor;
judging whether the value of each evaluation factor is in a normal state range, counting the number of the evaluation factors of which the values are not in the normal state range in each group of priority levels, judging whether the soot blower is required to blow soot according to the number of the evaluation factors of which the values are not in the normal state range in each group of priority levels, and if so, starting the soot blower to blow soot.
Furthermore, in the present embodiment, a computer system is also disclosed, which comprises a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method when executing the computer program.
Furthermore, in the present embodiment, a computer storage medium is also disclosed, on which a computer program is stored, which when executed by a processor implements the steps in the above method.
According to the intelligent soot blowing control method, system and storage medium based on the multidimensional evaluation factor, a plurality of boiler operation parameters are selected as the evaluation factor for selecting the soot blower, and the boiler operation parameters reflect the contamination degree of the heating surface corresponding to the soot blower and the influence of soot blowing on the safety and economy of boiler operation; according to the influence of each evaluation factor on the safety of the boiler, the influence of the economic operation degree and the correlation degree between the evaluation factor and the contamination of the heating surface, priority level grouping is respectively carried out on each evaluation factor; judging whether the value of each evaluation factor is in a normal state range, counting the number of the evaluation factors of which the values are not in the normal state range in each group of priority levels, and judging whether the soot blowing of the soot blower is needed according to the number of the evaluation factors of which the values are not in the normal state range in each group of priority levels. The invention can accurately judge the degree of contamination of the heating surface corresponding to the selected soot blower and the influence of soot blowing on the safety and the economy of boiler operation, and determine whether to adopt the soot blower to perform soot blowing according to the judged influence, thereby reducing the soot blowing steam loss of a power plant, reducing the blowing loss risk of the heating surface, reducing the overhauling and maintenance of soot blowing equipment and the labor amount of soot blowing, and improving the safety and the economy of boiler operation.
Example two:
the second embodiment is the preferred embodiment of the first embodiment, and the difference between the first embodiment and the second embodiment is that the specific steps of the intelligent soot blowing control method based on the multidimensional evaluation factor are refined, and the method comprises the following steps:
soot blowers in different positions are used for removing soot on heating surfaces of different areas of a boiler, and different boiler operation parameters can directly or indirectly reflect soot contamination degrees of different heating surfaces and safe and economic operation conditions of the boiler before and after soot blowing, so if the soot contamination degrees of the heating surfaces are accurately judged, the safe and economic operation conditions of the boiler before and after soot blowing of the soot blowers are ensured, the soot blowers are controlled to finely and efficiently perform soot blowing as required, and the boiler operation parameter group corresponding to the soot blowers is accurately selected.
As shown in fig. 2, in this embodiment, an intelligent soot blowing control method based on a multidimensional evaluation factor is disclosed, which includes the following steps:
step 1: the boiler soot blowers are grouped, and the specific grouping mode can adopt the following modes: 1) short-time blowing of a hearth: first layer short blowing, second layer short blowing, third layer short blowing and fourth layer short blowing; 2) corner area of the folded flame: screen over, height over; 3) a vertical shaft flue: low-pass, low-recycle and coal economizer; 4) an air preheater soot blower.
The soot blowers in the soot blower group can be further grouped to realize the refined soot blowing of the heating surface area.
Step 2: and selecting the multidimensional evaluation factor of the soot blower group according to expert experience and mechanism analysis. The soot blower group multidimensional evaluation factors include, but are not limited to, the following parameters:
1) evaluation factors of furnace short-blow groups: the method comprises the following steps of (1) furnace outlet smoke temperature (screen bottom smoke temperature), water wall temperature, superheat degree, superheater desuperheating water quantity, screen wall temperature, high wall temperature, main steam temperature, reheated steam temperature, denitration system inlet smoke temperature and smoke exhaust temperature;
2) evaluation factor of ash blowing set: the method comprises the following steps of (1) furnace outlet smoke temperature (screen bottom smoke temperature), screen inlet and outlet working medium temperature rise, superheater desuperheating water quantity, smoke baffle opening, screen wall temperature deviation, screen wall temperature maximum value, screen smoke side differential pressure, main steam temperature, reheated steam temperature, denitration system inlet smoke temperature and smoke exhaust temperature;
3) exceeding the soot blower group evaluation factor: the temperature of the working medium is higher than the temperature rise of the inlet working medium and the outlet working medium, the temperature reduction water quantity of the superheater, the opening degree of a flue gas baffle, the deviation of the temperature of the superheater, the maximum value of the temperature of the superheater, the pressure difference of the side of the superheater, the temperature of main steam, the temperature of reheated steam, the inlet flue gas temperature of a denitration system and the exhaust gas temperature;
4) high reblowing ash group evaluation factor: temperature rise of working media at a high re-inlet and outlet, opening degree of a flue gas baffle, temperature reduction water quantity of a reheater, high re-wall temperature deviation, maximum value of high re-wall temperature, high re-flue gas side differential pressure, main steam temperature, reheated steam temperature, inlet smoke temperature of a denitration system and exhaust gas temperature;
5) low overflown ash group evaluation factor: low excess outlet pipe wall temperature, low excess inlet working medium temperature, low excess outlet flue gas temperature, air preheater inlet flue gas temperature, low excess side flue gas resistance, denitration system inlet flue gas temperature, smoke exhaust temperature and draught fan current;
6) low reblowing ash group evaluation factor: low reentry outlet pipe wall temperature, low reentry, outlet working medium temperature, low reentry, outlet flue gas temperature, air preheater inlet flue gas temperature, low reentry side flue gas resistance, denitration system inlet flue gas temperature, smoke exhaust temperature and draught fan current;
7) evaluation factors of a soot blower group of the economizer: the temperature of working media at the inlet and the outlet of the economizer, the temperature of flue gas at the inlet of the air preheater, the resistance of the flue gas of the economizer, the temperature of flue gas at the inlet of a denitration system, the temperature of flue gas discharged and the current of an induced draft fan;
8) evaluation factors of an air preheater soot blower group: the method comprises the steps of measuring the temperature of inlet flue gas of the air preheater, the temperature of outlet flue gas of the air preheater, the side resistance of the flue gas of the air preheater, the side resistance of primary air of the air preheater, the side resistance of secondary air of the air preheater and the current of a draught fan.
The evaluation factors of each soot blower group are divided into three levels according to the degree of influencing the safe and economic operation of the boiler and the degree of the correlation between the contamination of the heating surface and the evaluation factors, and are shown in the table 1. Table 1 is merely one preferred example of an evaluation factor ranking and is not intended to be limiting. Factors, other examples can be classified differently according to the actual situation of the unit.
TABLE 1 evaluation factor grading table for each soot blower group
And step 3: and establishing an evaluation standard. And the historical operation data distribution of each soot blower group evaluation factor under each unit load adopts Y ═ mu +/-x sigma as the evaluation standard under each load, mu is the average value of the historical data distribution of the category evaluation factor, sigma is the standard deviation of the historical data distribution of the category evaluation factor, and x is the soot blower optimization saturation factor, and the evaluation range is determined according to the unit condition and is 1.0-3.0.
When the wall temperature is used as the evaluation factor, the preferred evaluation criterion Y should be determined with reference to the alarm value of the wall temperature.
When the main steam temperature and the reheat steam temperature are used as evaluation factors, the preferable evaluation criterion Y is determined by referring to the alarm value of the steam temperature.
When the inlet flue gas temperature of the denitration system is used as an evaluation factor, the preferable evaluation criterion Y is determined by referring to the upper limit value of the allowable operation flue gas temperature of the denitration system.
When the inlet smoke temperature of the air preheater is used as an evaluation factor, the preferable evaluation criterion Y is determined by referring to the upper limit value of the allowable operation smoke temperature of the air preheater.
And 4, step 4: and acquiring real-time operation data, and judging whether to trigger set evaluation conditions. Judging factor i of each leveln、jn、knWhether the value of the evaluation criterion Y is reached, a first priority evaluation factor inIn which n factors reachThe evaluation criterion Y value was n (i)n) Second priority evaluation factor jnN factors of the evaluation criteria Y value n (j)n) Third priority evaluation factor knThe weight of the soot blowing influenced by n factors reaching the evaluation standard Y value is n (k)n) Calculating the total number S ═ an (i) of evaluation factors of each layer reaching the value of each evaluation criterion Yn)+bn(jn)+cn(kn) Wherein a, b and c are weight factors of each level, wherein a is more than b and more than c, 0 is more than a, 0 is more than b, and 0 is more than c.
And comparing the comprehensive evaluation value with a preset evaluation threshold, judging that the soot blower is required to blow soot when the comprehensive evaluation value is greater than the preset evaluation threshold, and judging that the soot blower is not required to blow soot when the comprehensive evaluation value is less than or equal to the preset evaluation threshold. If the evaluation threshold value is w, a is more than w,2b is more than w, and 3c is more than w;
in this embodiment, w is 0.7, and when S >0.7, it is considered that the soot blowing condition is triggered.
According to the above rule, the weighting factors a, b, and c of each level are preferably set to 1, 0.5, and 0.3, respectively, but not limited thereto, and other weighting values may be given according to the unit situation. The specific number of the evaluation factors of each priority level reaching the corresponding evaluation criterion Y and whether the soot blowing condition is triggered are shown in table 2.
TABLE 2 summary table of conditions of triggered soot blowing
And 5: when the evaluation conditions are set in a triggering mode, the corresponding soot blower groups perform soot blowing.
Step 6: the judgment standard is updated in a rolling mode by adopting the operation data of a previous period of time every day, the period of time can be determined according to the actual condition of the unit, and the preferable value range is 1.0-10.0 days.
The updating amplitude of the evaluation criterion Y value can be adjusted, and the updated Y value is Y-Y0+λ(Yn-Y0) Wherein Y is0For the evaluation criteria before update, YnThe evaluation criterion is calculated for historical data n days before updating, lambda is an evaluation criterion updating amplitude factor, and the preferred value range is 0.1-1.0.
When the coal quality of the boiler is changed frequently, the evaluation standard updating amplitude factor is preferably selected to be larger to adapt to the coal quality change. When the quality of the coal fed into the boiler is stable for a long time, the evaluation standard updating amplitude factor is preferably selected to be a smaller value so as to reduce the amplitude of the fluctuation of the evaluation standard.
And each evaluation factor is judged in real time to meet the real-time soot blowing requirement according to the requirement. And after the soot blowing action of a certain soot blower group, judging the evaluation factor of the soot blower group after 1 hour.
If the soot blowing is performed once by the soot blower groups which do not trigger the soot blowing condition for 3 consecutive days, the soot blowing is not effectively performed due to the fact that the partial soot blower groups have less influence on the evaluation factor. Especially, soot blowers at the slope of the folded flame angle are required to regularly blow soot, so that the condition that the combustion stability in the furnace is influenced and even the non-abnormal stop of a unit is caused due to the fact that the soot blowers at the folded flame angle collapse ash is avoided.
In summary, in the intelligent soot blowing control method, system and storage medium based on the multidimensional evaluation factor, a plurality of boiler operation parameters are selected as the evaluation factors for selecting the soot blower, and the boiler operation parameters reflect the contamination degree of the heating surface corresponding to the soot blower and the influence of soot blowing on the safety and economy of boiler operation; according to the influence of each evaluation factor on the safety of the boiler, the influence of the economic operation degree and the correlation degree between the evaluation factor and the contamination of the heating surface, priority level grouping is respectively carried out on each evaluation factor; judging whether the value of each evaluation factor is in a normal state range, counting the number of the evaluation factors of which the values are not in the normal state range in each group of priority levels, and judging whether the soot blowing of the soot blower is needed according to the number of the evaluation factors of which the values are not in the normal state range in each group of priority levels. The invention can accurately judge the degree of contamination of the heating surface corresponding to the selected soot blower and the influence of soot blowing on the safety and the economy of boiler operation, and determine whether to adopt the soot blower to perform soot blowing according to the judged influence, thereby reducing the soot blowing steam loss of a power plant, reducing the blowing loss risk of the heating surface, reducing the overhauling and maintenance of soot blowing equipment and the labor amount of soot blowing, and improving the safety and the economy of boiler operation.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. An intelligent soot blowing control method based on a multi-dimensional evaluation factor is characterized by comprising the following steps:
selecting a plurality of boiler operation parameters as evaluation factors for selecting the soot blowers according to expert experience and mechanism analysis, wherein the plurality of boiler operation parameters reflect the contamination degree of the heating surfaces corresponding to the soot blowers and the influence of soot blowing on the safety and economy of boiler operation;
according to the influence of each evaluation factor on the safety of the boiler, the influence of the economic operation degree and the correlation degree between the evaluation factor and the contamination of the heating surface, priority level grouping is respectively carried out on each evaluation factor;
judging whether the value of each evaluation factor is in a normal state range, counting the number of the evaluation factors of which the values are not in the normal state range in each group of priority levels, judging whether the soot blower is required to blow soot according to the number of the evaluation factors of which the values are not in the normal state range in each group of priority levels, and if so, starting the soot blower to blow soot.
2. The intelligent soot blowing control method based on multi-dimensional evaluation factors as claimed in claim 1, wherein when the soot blower is a furnace short soot blower, the evaluation factors comprise: the method comprises the following steps of (1) furnace outlet smoke temperature, water wall temperature, superheat degree, superheater desuperheating water quantity, screen wall temperature, high wall temperature, main steam temperature, reheated steam temperature, denitration system inlet smoke temperature and exhaust gas temperature;
when the soot blower is a screen-over soot blower, the evaluation factor includes: the method comprises the following steps of (1) furnace outlet smoke temperature, screen passing inlet and outlet working medium temperature rise, superheater desuperheating water quantity, flue gas baffle opening, screen passing wall temperature deviation, screen passing wall temperature maximum value, screen passing flue gas side differential pressure, main steam temperature, reheated steam temperature, denitration system inlet smoke temperature and exhaust gas temperature;
when the soot blower is a high-pressure soot blower, the evaluation factor includes: the temperature of the working medium is higher than the temperature rise of the inlet working medium and the outlet working medium, the temperature reduction water quantity of the superheater, the opening degree of a flue gas baffle, the deviation of the temperature of the superheater, the maximum value of the temperature of the superheater, the pressure difference of the side of the superheater, the temperature of main steam, the temperature of reheated steam, the inlet flue gas temperature of a denitration system and the exhaust gas temperature;
when the soot blower is a high sootblower, the evaluation factor includes: temperature rise of working media at a high re-inlet and outlet, opening degree of a flue gas baffle, temperature reduction water quantity of a reheater, high re-wall temperature deviation, maximum value of high re-wall temperature, high re-flue gas side differential pressure, main steam temperature, reheated steam temperature, inlet smoke temperature of a denitration system and exhaust gas temperature;
when the soot blower is a low-pass soot blower, the evaluation factor includes: low excess outlet pipe wall temperature, low excess inlet working medium temperature, low excess outlet flue gas temperature, air preheater inlet flue gas temperature, low excess side flue gas resistance, denitration system inlet flue gas temperature, smoke exhaust temperature and draught fan current;
when the soot blower is a low reorderer blower, the evaluation factor includes: low reentry outlet pipe wall temperature, low reentry, outlet working medium temperature, low reentry, outlet flue gas temperature, air preheater inlet flue gas temperature, low reentry side flue gas resistance, denitration system inlet flue gas temperature, smoke exhaust temperature and draught fan current;
when the soot blower is an economizer soot blower, the evaluation factor includes: the temperature of working media at the inlet and the outlet of the economizer, the temperature of flue gas at the inlet of the air preheater, the resistance of the flue gas of the economizer, the temperature of flue gas at the inlet of a denitration system, the temperature of flue gas discharged and the current of an induced draft fan;
when the soot blower is an air preheater soot blower group, the evaluation factor comprises: the method comprises the steps of measuring the temperature of inlet flue gas of the air preheater, the temperature of outlet flue gas of the air preheater, the side resistance of the flue gas of the air preheater, the side resistance of primary air of the air preheater, the side resistance of secondary air of the air preheater and the current of a draught fan.
3. The intelligent soot blowing control method based on multi-dimensional evaluation factors as claimed in claim 1, wherein the evaluation factors are grouped in a priority level according to the influence of the evaluation factors on the safety of the boiler, the influence of the economic operation degree and the correlation degree with the contamination of the heating surface, and the method comprises the following steps:
for each evaluation factor the following steps are performed:
analyzing the influence of the evaluation factor on the safety of the boiler, comparing the influence of the evaluation factor on the safety of the boiler with a preset first safety influence threshold, and if the influence of the evaluation factor on the safety of the boiler is greater than the preset first safety influence threshold, judging that the evaluation factor is a first priority layer;
if the influence value of the evaluation factor on the boiler safety is smaller than a preset first safety influence threshold value and larger than a preset second safety influence threshold value, wherein the first safety influence threshold value is larger than the second safety influence threshold value and meets any one of the following conditions, the evaluation factor is judged to be in a second priority level:
the influence value of the evaluation factor on the economic operation degree exceeds a preset economic influence threshold value;
the correlation degree value between the evaluation factor and the heating surface contamination exceeds a preset heating surface contamination degree threshold value;
if the influence value of the evaluation factor on the boiler safety is smaller than a preset second safety influence threshold value or the following conditions are met, judging that the evaluation factor is a third priority level:
the influence value of the evaluation factor on the economic operation degree does not exceed a preset economic influence threshold value;
the correlation degree value between the evaluation factor and the heating surface contamination does not exceed a preset heating surface contamination degree threshold value.
4. The intelligent soot blowing control method based on multi-dimensional evaluation factors as claimed in claim 2, wherein the evaluation factors are grouped in priority levels according to the degree of the boiler safety influence, the economic operation degree influence and the correlation degree with the contamination of the heating surface, and the method is implemented by looking up the following table:
evaluation factor grading table for each soot blower group
5. The intelligent soot blowing control method based on the multidimensional evaluation factors as claimed in claim 1, wherein judging whether the value of each evaluation factor is within a normal state range specifically comprises the following steps:
for each evaluation factor the following steps are performed:
acquiring historical data of the category evaluation factors, calculating the mean value and standard deviation of the historical data, and calculating the value range of the normal value of the category evaluation factors as an evaluation standard Y through the following formula:
Y＝μ±xσ；
wherein mu is the average value of the historical data distribution of the category evaluation factor, sigma is the standard deviation of the historical data distribution of the category evaluation factor, and x is the soot blower optimization saturation factor, and is determined according to the unit condition;
and comparing the value of the evaluation factor with the evaluation criterion Y, if the value of the evaluation factor is within the evaluation criterion Y, judging that the evaluation factor is within a normal state range, and if the value of the evaluation factor is not within the evaluation criterion Y, judging that the value of the evaluation factor is not within the normal state range.
6. The intelligent soot blowing control method based on the multi-dimensional evaluation factors as claimed in claim 5, wherein the value of the evaluation criterion is not greater than the alarm value of the corresponding evaluation factor, the value of the evaluation criterion is within the operation safety margin of the corresponding evaluation factor, and the deviation of the normal operation average value of the corresponding evaluation factor is considered.
7. The intelligent soot blowing control method based on the multidimensional evaluation factor as claimed in claim 1, wherein judging whether the soot blower needs to perform soot blowing according to the number of the evaluation factors with the values not within the normal state range in each group of priority levels comprises the following steps:
calculating a comprehensive evaluation value of the evaluation factors according to the following formula:
S＝an(in)+bn(jn)+cn(kn)；
where S is a comprehensive evaluation value, a is a weight of the first priority level, and n (i)n) The number of evaluation factors in the first priority level, the values of which are not in the normal state values; b is the weight of the second priority level, n (j)n) The number of evaluation factors in the second priority level, the values of which are not in the normal state values; c is the weight of the third priority level, n (k)n) The number of evaluation factors in the third priority level, the value of which is not in the normal state value, wherein a is more than b and more than c, and 0 is more than a, 0 is more than b, and 0 is more than c;
and comparing the comprehensive evaluation value with a preset evaluation threshold, judging that the soot blower is required to blow soot when the comprehensive evaluation value is greater than the preset evaluation threshold, and judging that the soot blower is not required to blow soot when the comprehensive evaluation value is less than or equal to the preset evaluation threshold.
8. The intelligent soot blowing control method based on multi-dimensional evaluation factors as claimed in claim 5, wherein the evaluation criterion Y value is updated in a rolling manner according to historical data of a previous period of timeThe evaluation criterion Y value updating range can be adjusted to adapt to the change of different coal types, the time period is determined according to the actual situation of the unit, and the updated Y value is Y-Y0+λ(Yn-Y0) Wherein Y is0For the evaluation criteria before update, YnAnd calculating an evaluation standard for historical data n days before updating, wherein lambda is an evaluation standard updating amplitude factor and has a value range of 0.1-1.0.
9. A computer system comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method of any of the preceding claims 1 to 8 are carried out by the processor when the computer program is executed by the processor.
10. A computer storage medium having a computer program stored thereon, wherein the program is adapted to perform the steps of the method of any one of claims 1 to 8 when executed by a processor.
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| PCT/CN2021/128298 WO2023279601A1 (en) | 2021-07-09 | 2021-11-03 | Intelligent soot blowing control method based on multi-dimensional evaluation factors, and system and storage medium |
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