Method and device for online determining boiler efficiency target value during peak regulation of coal-fired unit

Abstract

The invention provides a method and device for online determining a boiler efficiency target value during peak regulation of a coal-fired unit, and relates to the field of energy efficiency improvement, and the method comprises the steps: determining an optimal boiler efficiency target value according to obtained real-time operation data and historical operation data; and if it is determined that the current boiler efficiency has the energy-saving potential, energy efficiency optimization adjustment is carried out according to the optimal target value of the boiler efficiency and the real-time operation data. According to the method, the optimal target value which the boiler efficiency should reach during peak-shaving low-load operation of the coal-fired unit can be rapidly determined on line, and the energy-saving potential of the unit is further increased.

Description

Technical Field

[0001] The present application relates to the field of energy efficiency improvement, and specifically to a method and device for online determining a boiler efficiency target value during peak load regulation of a coal-fired unit. Background Art

[0002] Coal-fired power generation units have taken on the new task of smoothing out the load fluctuations caused by the grid's absorption of new energy and ensuring the safe and stable operation of the grid. At present, in order to further improve the flexibility of thermal power operation and the ability to absorb new energy, the lower limit of unit output (minimum load rate) is constantly being refreshed. During peak load regulation, the operation of the unit deviates from the design value, the efficiency of the unit decreases, resulting in a significant increase in coal consumption for power supply, affecting the economic efficiency of the unit operation. In particular, some old domestic units did not consider the need for deep peak load regulation in the initial design and equipment selection. The types of coal used are very different from the designed types of coal, the quality is poor and there are many changes, and the operating pressure is even greater.

[0003] At present, the power supply coal consumption value is usually used to measure the energy efficiency of the unit, and the boiler thermal efficiency is one of the most important factors that determine the size of the power supply coal consumption. Boiler efficiency refers to the percentage of heat effectively utilized by the boiler and the heat brought into the furnace by the fuel, reflecting the degree of fuel utilization. On the one hand, during peak load regulation, the unit is often in a low-load operation state, the boiler efficiency is low, the amount of standard coal required to generate one kilowatt-hour of electricity increases, and the unit energy efficiency decreases. However, "whether the efficiency reduction is within a reasonable range", "whether the unit still has energy-saving potential", and "where is the key point of energy saving" are still issues that power generation companies need to study in depth and solve; on the other hand, during peak load regulation, how to improve the flexibility and rapid response load capacity of coal-fired units is another issue that power generation companies are most concerned about.

[0004] This section is intended to provide a background or context to the embodiments of the invention recited in the claims. No admission is made that the description herein is prior art by inclusion in this section. Summary of the invention

[0005] In response to the problems in the prior art, the present application provides a method and device for online determining the target value of boiler efficiency during peak-shaving of a coal-fired unit, which can realize online and rapid determination of the optimal target value that the boiler efficiency should reach when the coal-fired unit is operating at low load for peak-shaving, and further tap the energy-saving potential of the unit.

[0006] In order to solve the above technical problems, this application provides the following technical solutions:

[0007] In a first aspect, the present application provides a method for online determining a target value of boiler efficiency during peak load regulation of a coal-fired unit, comprising:

[0008] Determine the optimal target value of boiler efficiency based on the acquired real-time operation data and historical operation data;

[0009] If it is determined that the current boiler efficiency has energy-saving potential, energy efficiency optimization adjustment is performed according to the optimal target value of the boiler efficiency and the real-time operation data.

[0010] Furthermore, determining the optimal target value of boiler efficiency based on the acquired real-time operation data and historical operation data includes:

[0011] Performing cluster analysis on the real-time operation data and historical operation data to filter out normal operation data;

[0012] The optimal target value of boiler efficiency is determined using the normal operation data.

[0013] Further, the determining the optimal target value of boiler efficiency by using the normal operation data includes:

[0014] The total reduction in boiler efficiency is determined based on the increase in solid incomplete combustion loss caused by the change in coal type, the increase in smoke exhaust loss caused by the change in coal type, and the reduction in boiler efficiency caused by the change in air temperature;

[0015] The optimal target value of the boiler efficiency is determined according to the inherent value of the boiler efficiency under the current load and the total amount of the boiler efficiency decrease.

[0016] Furthermore, if it is determined that the current boiler efficiency has energy-saving potential, energy efficiency optimization adjustment is performed according to the optimal target value of the boiler efficiency and the real-time operation data, including:

[0017] Determining whether the current boiler efficiency is less than the optimal target value of boiler efficiency;

[0018] If so, determining that the current boiler efficiency has energy saving potential;

[0019] An energy efficiency optimization adjustment strategy is determined according to the measurement point values ​​in the real-time operation data and the corresponding design values ​​to perform energy efficiency optimization adjustment.

[0020] In a second aspect, the present application provides a device for online determining a target value of boiler efficiency during peak load regulation of a coal-fired unit, comprising:

[0021] An optimal target determination unit, used to determine the optimal target value of boiler efficiency based on the acquired real-time operation data and historical operation data;

[0022] The energy efficiency optimization and adjustment unit is used to optimize and adjust the energy efficiency according to the optimal target value of the boiler efficiency and the real-time operation data if it is determined that the current boiler efficiency has energy-saving potential.

[0023] Furthermore, the optimal target determination unit includes:

[0024] A normal data screening module is used to perform cluster analysis on the real-time operation data and historical operation data to screen normal operation data;

[0025] The optimal target determination module is used to determine the optimal target value of the boiler efficiency by using the normal operation data.

[0026] Furthermore, the optimal target determination module includes:

[0027] A total reduction determination module is used to determine the total reduction in boiler efficiency based on the increase in solid incomplete combustion loss caused by the change in coal type, the increase in smoke exhaust loss caused by the change in coal type, and the reduction in boiler efficiency caused by the change in air temperature;

[0028] The optimal efficiency determination module is used to determine the optimal target value of the boiler efficiency according to the inherent value of the boiler efficiency under the current load and the total amount of the boiler efficiency reduction.

[0029] Furthermore, the energy efficiency optimization and adjustment unit includes:

[0030] An efficiency comparison module, used to determine whether the current boiler efficiency is less than the optimal target value of the boiler efficiency;

[0031] An energy-saving potential judgment module, used for judging that the current boiler efficiency has energy-saving potential;

[0032] The tuning strategy determination module is used to determine the energy efficiency optimization adjustment strategy according to the measurement point values ​​in the real-time operation data and the corresponding design values, so as to perform energy efficiency optimization adjustment.

[0033] In a third aspect, the present application provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the steps of a method for online determining a target value of boiler efficiency during peak load regulation of the coal-fired unit are implemented.

[0034] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of a method for online determining a target value of boiler efficiency during peak load regulation of the coal-fired unit.

[0035] In a fifth aspect, the present application provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the steps of a method for online determining a target value of boiler efficiency during peak load regulation of the coal-fired unit.

[0036] In response to the problems in the prior art, the method and device for online determining the target value of boiler efficiency during peak-shaving of coal-fired units provided in the present application can online determine the optimal target value that the boiler efficiency should reach when the coal-fired unit is operating at low load during peak-shaving, and then deeply analyze the reasons for the decline in boiler efficiency and determine the specific strategies for energy-saving upgrades and optimization transformation of the unit, further tapping the energy-saving potential of the unit, which is of great significance for reducing operating costs and improving the operating stability of the unit. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0038] Figure 1 This is a flow chart of a method for online determining a boiler efficiency target value during peak load regulation of a coal-fired unit in an embodiment of the present application;

[0039] Figure 2 This is one of the flow charts for determining the optimal target value of boiler efficiency in an embodiment of the present application;

[0040] Figure 3 This is the second flow chart for determining the optimal target value of boiler efficiency in an embodiment of the present application;

[0041] Figure 4 A flow chart of energy efficiency optimization adjustment in an embodiment of the present application;

[0042] Figure 5 This is a structural diagram of a device for online determining a boiler efficiency target value during peak load regulation of a coal-fired unit in an embodiment of the present application;

[0043] Figure 6 This is a structural diagram of the optimal target determination unit in an embodiment of the present application;

[0044] Figure 7 This is a structural diagram of the optimal target determination module in an embodiment of the present application;

[0045] Figure 8 This is a structural diagram of the energy efficiency optimization and adjustment unit in the embodiment of the present application;

[0046] Fig. 9 A schematic diagram of the structure of an electronic device in an embodiment of the present application;

[0047] Fig.10 This is a schematic diagram of a process for online determination of a boiler efficiency target value during peak load regulation of a coal-fired unit in an embodiment of the present application;

[0048] Fig.11 It is a schematic diagram of a boiler efficiency fitting curve in an embodiment of the present application;

[0049] Fig.12 Schematic diagram of flue gas temperature change in an embodiment of the present application. DETAILED DESCRIPTION

[0050] To make the purpose, technical solution and advantages of the embodiments of the present invention more clear, the embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings. Here, the exemplary embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0051] The information collected in the technical solution of this application is information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of relevant data comply with the relevant laws, regulations and standards of relevant countries and regions, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0052] Provide users with corresponding operation entrances for them to choose to agree or reject the automated decision-making results; if the user chooses to reject, the expert decision-making process will be entered.

[0053] In one embodiment, see Figure 1 In order to quickly determine the optimal target value of boiler efficiency that should be achieved when the coal-fired unit is running at low load during peak load regulation online, and further tap the energy-saving potential of the unit, the present application provides a method for determining the target value of boiler efficiency online during peak load regulation of a coal-fired unit, including:

[0054] S101: Determine an optimal target value of boiler efficiency based on the acquired real-time operation data and historical operation data;

[0055] S102: If it is determined that the current boiler efficiency has energy-saving potential, energy efficiency optimization adjustment is performed according to the optimal target value of the boiler efficiency and the real-time operation data.

[0056] It is understood that the specific implementation process of the method for online determination of boiler efficiency target value during peak load regulation of coal-fired units can be found in Fig.10 As shown. First, obtain real-time operation data and historical operation data, and then filter out normal operation data as the basic data for determining the optimal target value of boiler efficiency. On this basis, based on the optimal target value of boiler efficiency, determine whether the current boiler efficiency has energy-saving potential, and then optimize and adjust energy efficiency according to the optimal target value of boiler efficiency and real-time operation data.

[0057] Taking a 1000MW supercritical wet-cooled coal-fired unit as an example, during peak load regulation, the unit load rate drops to 35%, at which time the boiler efficiency is 87.02%.

[0058] 1. Retrieve real-time data: retrieve real-time operation data of coal-fired power plant units;

[0059] 2. Retrieve historical data: retrieve the historical data of the coal-fired power plant units under the load within 1 hour;

[0060] 3. Abnormal data judgment: put the real-time operation data in the historical data, and use the density-based cluster analysis method (BSCAN algorithm) to determine whether the real-time data is abnormal data. If the data is normal, proceed to the next step;

[0061] 4. Fit the boiler efficiency values ​​under at least three loads of the unit pre-commissioning acceptance test into a curve, and obtain the curve formula. The inherent value of the boiler efficiency under the current load is 93.35% through online calculation. Fig.11 shown.

[0062] According to the industry standard DL / T1929-2018, the total boiler efficiency reduction is 3.98%. According to formula (1), the optimal target value of boiler fuel efficiency under the current peak load should be 89.37%.

[0063] 5. Compare the optimal target value of boiler efficiency with the current test boiler efficiency. The current boiler efficiency is 87.02% < the optimal target value of boiler efficiency 87.02%. It is judged that there is energy saving potential and further operation is required:

[0064] a. Carry out measuring point detection: Accurate measuring points;

[0065] Comparison of main steam flow measurement point, boiler coal measurement point, primary air volume measurement point, secondary air volume measurement point, primary air temperature measurement point at air preheater inlet, secondary air temperature measurement point at air preheater inlet, primary fan inlet air temperature measurement point, blower inlet air temperature measurement point, primary fan outlet air temperature measurement point, blower outlet air temperature measurement point with design values:

[0066] if Accurate measuring points;

[0067] b. Check the boiler insulation layer to make sure it is not damaged;

[0068] c. Make operation optimization adjustments:

[0069] Compare the measured value of the outlet flue gas temperature with the design value:

[0070] Take the design values ​​of the outlet flue gas temperature at three loads of 100%, 75%, and 50%, and fit them into a curve according to the load to obtain the curve formula. Fig.12 As shown. According to the curve formula, the design value of the outlet flue gas temperature under the peak load is calculated online to be 100.6℃;

[0071] The measured value of the outlet flue gas temperature is 96.2℃, which is lower than the design value of the outlet flue gas temperature. So proceed directly to the next step.

[0072] The quantitative verification value of carbon content in ash is compared with the quantitative verification value of carbon content in ash when the boiler efficiency is highest when burning the same type of coal recently (at the same time, the quantitative verification value of carbon content in ash when the boiler efficiency is highest recently must not exceed the value required by the power plant regulations): it is found that the quantitative verification value of carbon content in ash is greater than the quantitative verification value of carbon content in ash when the boiler efficiency is highest recently, the coal powder particle size matches the current combustion equipment, and the temperature measuring points of the boiler heating surface are detected to be uneven, so the boiler combustion is optimized and adjusted to optimize the air-coal ratio and improve the degree of coal burnout.

[0073] Compare the fly ash carbon content verification value with the fly ash carbon content verification value when the boiler efficiency is the highest when the same type of coal is burned recently. If the fly ash carbon content verification value is ≤ the fly ash carbon content verification value when the boiler efficiency is the highest recently, proceed to the next step;

[0074] The main steam temperature was tested and found to be 593℃<design value 600℃. On the premise of ensuring that the heating surface does not overheat, the main steam temperature was increased as much as possible to make it as close to the design value as possible;

[0075] After testing the reheat steam temperature, it was found that the reheat steam temperature was 596℃<design value and 600℃<design value. Therefore, the reheat steam temperature was increased as much as possible while ensuring that the heating surface did not overheat.

[0076] Through the above steps, the boiler efficiency is increased to 88.63%.

[0077] From the above description, it can be seen that the method for online determining the target value of boiler efficiency during peak-shaving of coal-fired units provided in the present application can online determine the optimal target value that the boiler efficiency should reach when the coal-fired unit is operating at low load during peak-shaving, and then deeply analyze the reasons for the decline in boiler efficiency and determine the specific strategies for energy-saving upgrades and optimization transformation of the unit, further tapping the energy-saving potential of the unit, which is of great significance for reducing operating costs and improving the operating stability of the unit.

[0078] In one embodiment, see Figure 2 , the step of determining the optimal target value of boiler efficiency based on the acquired real-time operation data and historical operation data includes:

[0079] S201: performing cluster analysis on the real-time operation data and historical operation data to filter out normal operation data;

[0080] S202: Determine the optimal target value of the boiler efficiency using the normal operation data.

[0081] Specifically, see Figure 3 , the use of the normal operation data to determine the optimal target value of boiler efficiency includes: S301: determining the total amount of boiler efficiency reduction based on the increase in solid incomplete combustion loss caused by changes in coal types, the increase in smoke exhaust loss caused by changes in coal types, and the decrease in boiler efficiency caused by changes in air temperature; S302: determining the optimal target value of boiler efficiency based on the inherent value of boiler efficiency under the current load and the total amount of boiler efficiency reduction.

[0082] It can be understood that in this embodiment, abnormal data judgment is first performed: the real-time operation data is placed in the historical data, and the density-based cluster analysis method (BSCAN algorithm) is used to determine whether the real-time data is abnormal data; if the data is abnormal data, the calculation is stopped and "Data abnormality alarm!" is displayed; if the data is normal, the next step is performed. The above method can be used to screen out normal operation data and participate in the determination of the optimal target value of boiler fuel efficiency. The specific method is as follows:

[0083]

[0084] in:

[0085] η B,pt ——The inherent value of boiler efficiency under the current load. The method of obtaining it is: take the boiler efficiency values ​​under at least three loads of the unit acceptance test before commissioning and input them into the system. Take the load r as the independent variable, and the boiler efficiency value η B,pt is the dependent variable, and the relationship between the two is η B,pt =a+br+cr 2 , the system is based on η under three loads B,pt The linear regression method can be used to obtain the regression coefficients a, b, and c, from which the formula for the change of boiler efficiency with load can be obtained. The boiler efficiency under the current load can be calculated online through the formula;

[0086] Δη B ——Total reduction in boiler efficiency;

[0087] Δq 4,f,cr ——Increase in solid incomplete combustion loss caused by coal type change, calculated according to industry standard DL / T1929-2018, %;

[0088] Δq 2,f,cr——The increase in smoke exhaust loss caused by the change in coal type is calculated according to the industry standard DL / T1929-2018, %;

[0089] Δq 2,a,cr ——The reduction in boiler efficiency caused by changes in air temperature is calculated according to the industry standard DL / T1929-2018, %.

[0090] From the above description, it can be seen that the method for determining the target value of boiler efficiency online during peak load regulation of coal-fired units can determine the optimal target value of boiler efficiency based on the acquired real-time operation data and historical operation data.

[0091] In one embodiment, see Figure 4 If it is determined that the current boiler efficiency has energy-saving potential, energy efficiency optimization adjustment is performed according to the optimal target value of the boiler efficiency and the real-time operation data, including:

[0092] S401: Determine whether the current boiler efficiency is less than the optimal target value of boiler efficiency;

[0093] S402: If yes, determine that the current boiler efficiency has energy saving potential;

[0094] S403: Determine an energy efficiency optimization adjustment strategy according to the measurement point values ​​in the real-time operation data and the corresponding design values ​​to perform energy efficiency optimization adjustment.

[0095] It is understandable that the optimal target value of boiler efficiency is compared with the current test boiler efficiency to analyze the energy saving potential and energy efficiency improvement.

[0096] 1) If the current boiler efficiency is ≥ the optimal target value of boiler efficiency, it is judged that there is no energy-saving potential and no further operation is required;

[0097] 2) If the current boiler efficiency is less than the optimal target value of boiler efficiency, it is judged that there is energy saving potential and further operations are required, as follows:

[0098] a. Carry out measuring point detection:

[0099] Check whether the measuring points are accurate. Among them, the exhaust gas oxygen content measuring point, exhaust gas CO content measuring point (if there is no measuring point, directly take the test value), exhaust gas temperature measuring point, air preheater inlet gas temperature measuring point, air preheater inlet flue gas oxygen content measuring point, take the real-time data value and compare it with the measured data:

[0100] if It is judged that the measuring point is accurate and proceed directly to the next step;

[0101] if It is judged that the measuring point is inaccurate and needs to be inspected and calibrated; the main steam flow measurement point, boiler coal measurement point, primary air volume measurement point, secondary air volume measurement point, air preheater inlet primary air temperature measurement point, air preheater inlet secondary air temperature measurement point, primary fan inlet air temperature measurement point, blower inlet air temperature measurement point, primary fan outlet air temperature measurement point, blower outlet air temperature measurement point are compared with the design value:

[0102] if It is judged that the measuring point is accurate and proceed directly to the next step;

[0103] if It is judged that the measuring point is inaccurate and needs to be inspected and calibrated;

[0104] b. Detection of boiler insulation layer:

[0105] Take the real-time value of the boiler wall temperature measuring point. If the measuring point value is greater than or less than the wall temperature range value of the measuring point in the operating regulations, it is judged that "the boiler insulation layer is damaged" and needs to be repaired or reinforced. Otherwise, proceed directly to the next step; c. Carry out operation optimization and adjustment:

[0106] Under the condition that the measurement points are correct and the insulation layer is not damaged, determine the cause of low boiler efficiency and carry out maintenance and equipment optimization:

[0107] Compare the measured value of the outlet flue gas temperature with the design value:

[0108] Get the design value of the outlet flue gas temperature: Input the design values ​​of the outlet flue gas temperature under at least three loads into the system, taking the load r as the independent variable and the design value of the flue gas temperature t py,ds is the dependent variable, and the relationship between the two is t py,ds =a+br+cr 2 , the system is based on three loads t py,ds The linear regression method can be used to obtain the regression coefficients a, b, and c, from which the formula for the change of the design value of the flue gas temperature with the load can be obtained. The design value of the outlet flue gas temperature under the peak load can be calculated online according to the formula;

[0109] If the measured value of the outlet flue gas temperature = the designed value of the outlet flue gas temperature, proceed directly to the next step;

[0110] If the measured value of the outlet flue gas temperature is greater than the designed value of the outlet flue gas temperature, then:

[0111] · Check the heating surface to see if |temperature measurement point value - design value| is less than or equal to the requirements of the regulations. If |temperature measurement point value - design value| is greater than the requirements of the regulations, it is judged as "there is dust accumulation, slagging or scaling on the inner wall of the water pipe", and it needs to be purged and removed. If there is scaling on the inner wall of the water pipe, the boiler water quality needs to be improved; if |temperature measurement point value - design value| is less than or equal to the requirements of the regulations, proceed to the next step;

[0112] Detect exhaust smoke oxygen content:

[0113] If the exhaust smoke oxygen content is ≤ the design value, proceed directly to the next step;

[0114] If the exhaust gas oxygen content is greater than the design value, check whether the air preheater leakage is within the specified range. If so, proceed to the next step; if it exceeds the range, it is necessary to carry out air leakage control;

[0115] · Detect the oxygen content of flue gas at the air preheater inlet:

[0116] If the inlet flue gas oxygen content is ≥ the design value, proceed directly to the next step;

[0117] If the oxygen content of the inlet flue gas is less than the design value, check whether the air preheater leakage is within the specified range. If so, proceed to the next step; if it exceeds the range, it is necessary to carry out air leakage control;

[0118] If the flue gas dew point temperature is less than the measured value of the outlet flue gas temperature and less than the designed value of the outlet flue gas temperature, proceed directly to the next step;

[0119] If the measured value of the outlet flue gas temperature is ≤ the flue gas dew point temperature, then

[0120] · Check whether there is dust accumulation inside the boiler. If not, proceed to the next step. If there is dust accumulation, it needs to be purged and removed. For old boilers, they can be upgraded if necessary.

[0121] · Check whether the exhaust pipe temperature is greater than or less than the exhaust pipe temperature range specified in the regulations. If it exceeds the specified range, it is judged as "blockage" and needs to be cleared; if it is within the specified range, proceed to the next step;

[0122] · Check whether the boiler water pressure is > or < the water pressure range specified in the regulations. If the water pressure is too high or too low, it is judged as "the boiler operating pressure needs to be adjusted to be within a reasonable range". If it is within a reasonable range, proceed to the next step;

[0123] Compare the carbon content of ash with the carbon content of ash recently tested when the boiler efficiency is the highest when the same type of coal is burned (at the same time, the carbon content of ash recently tested when the boiler efficiency is the highest must not exceed the value required by the power plant regulations):

[0124] If the carbon content of ash is less than or equal to the carbon content of ash when the boiler efficiency is the highest in the recent period, proceed to the next step;

[0125] If the carbon content in ash is greater than the carbon content in ash when the boiler efficiency is the highest in the recent period, it is necessary to:

[0126] · Check whether the coal powder particle size matches the current combustion equipment:

[0127] If the diameter of the pulverized coal particles meets the requirements of the regulations, it is judged as "matched", and the boiler combustion optimization adjustment is carried out to optimize the air-coal ratio and improve the degree of coal burnout;

[0128] If the diameter of the pulverized coal particles exceeds the requirements of the regulations, it is judged as "mismatched" and the pulverized coal particles are adjusted to the appropriate size by adjusting the operation of the coal mill;

[0129] Compare the carbon content of fly ash with the carbon content of fly ash when the boiler efficiency is the highest when the same type of coal is burned recently (at the same time, the carbon content of fly ash when the boiler efficiency is the highest recently must not exceed the value required by the power plant regulations):

[0130] If the carbon content in fly ash is less than or equal to the carbon content in fly ash when the boiler efficiency is the highest in the recent period, proceed to the next step;

[0131] If the carbon content of fly ash is greater than the carbon content of fly ash when the boiler efficiency is the highest in the recent period, it is necessary to carry out boiler combustion optimization adjustment, adjust the secondary air volume and negative pressure, and reduce the carbon content of fly ash;

[0132] Check whether there is uneven temperature at the boiler heating surface measurement points:

[0133] If the temperature value of the same layer | maximum temperature - minimum temperature | ≤ 3°C, it is judged as "temperature uniformity" and the next step is carried out; If the temperature value of the same layer | the highest temperature - the lowest temperature | > 3°C, it is judged as "uneven temperature" and combustion optimization adjustment is required. If necessary, upgrade and reconstruction are carried out to add water-cooled wall temperature measuring devices.

[0134] Detection of main steam temperature:

[0135] If the main steam temperature is ≥ the design value, proceed to the next step;

[0136] If the main steam temperature is less than the design value, the main steam temperature should be raised as much as possible to make it as close to the design value as possible while ensuring that the heating surface does not overheat.

[0137] Detection of reheat steam temperature:

[0138] If the reheat steam temperature is ≥ the design value, proceed to the next step;

[0139] If the reheat steam temperature is less than the design value, the reheat steam temperature should be raised as much as possible to make it as close to the design value as possible while ensuring that the heating surface does not overheat. If necessary, upgrades can be made to increase the heating surface and implement flue gas recirculation modifications.

[0140] From the above description, it can be seen that the method of determining the boiler efficiency target value online during peak load regulation of coal-fired units can determine whether the current boiler efficiency has energy-saving potential, and optimize the energy efficiency according to the optimal target value of the boiler efficiency and real-time operation data.

[0141] Based on the same inventive concept, the embodiment of the present application also provides a device for determining the target value of boiler efficiency online during peak shaving of a coal-fired unit, which can be used to implement the method described in the above embodiment, as described in the following embodiment. Since the principle of solving the problem by the device for determining the target value of boiler efficiency online during peak shaving of a coal-fired unit is similar to the method for determining the target value of boiler efficiency online during peak shaving of a coal-fired unit, the implementation of the device for determining the target value of boiler efficiency online during peak shaving of a coal-fired unit can refer to the implementation of the method based on software performance benchmark determination, and the repetitions will not be repeated. As used below, the terms "unit" or "module" can be a combination of software and / or hardware that implements predetermined functions. Although the system described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceived.

[0142] In one embodiment, see Figure 5 In order to quickly determine the optimal target value of boiler efficiency that should be achieved when the coal-fired unit is running at low load during peak load regulation online, and further tap the energy-saving potential of the unit, the present application provides a device for determining the target value of boiler efficiency online during peak load regulation of a coal-fired unit, comprising:

[0143] The optimal target determination unit 501 is used to determine the optimal target value of boiler efficiency according to the acquired real-time operation data and historical operation data;

[0144] The energy efficiency optimization and adjustment unit 502 is used to optimize and adjust the energy efficiency according to the optimal target value of the boiler efficiency and the real-time operation data if it is determined that the current boiler efficiency has energy-saving potential.

[0145] In one embodiment, see Figure 6 , the optimal target determination unit 501 comprises:

[0146] A normal data screening module 601 is used to perform cluster analysis on the real-time operation data and the historical operation data to screen normal operation data;

[0147] The optimal target determination module 602 is used to determine the optimal target value of the boiler efficiency by using the normal operation data.

[0148] In one embodiment, see Figure 7 , the optimal target determination module 602 includes:

[0149] The total reduction determination module 701 is used to determine the total reduction of boiler efficiency according to the increase of solid incomplete combustion loss caused by the change of coal type, the increase of smoke exhaust loss caused by the change of coal type and the reduction of boiler efficiency caused by the change of air temperature;

[0150] The optimal efficiency determination module 702 is used to determine the optimal target value of the boiler efficiency according to the inherent value of the boiler efficiency under the current load and the total amount of the boiler efficiency reduction.

[0151] In one embodiment, see Figure 8 , the energy efficiency optimization and adjustment unit 502 includes:

[0152] The efficiency comparison module 801 is used to determine whether the current boiler efficiency is less than the optimal target value of the boiler efficiency;

[0153] Energy saving potential determination module 802, for determining that the current boiler efficiency has energy saving potential;

[0154] The tuning strategy determination module 803 is used to determine the energy efficiency optimization adjustment strategy according to the measurement point values ​​in the real-time operation data and the corresponding design values, so as to perform energy efficiency optimization adjustment.

[0155] From the hardware level, in order to realize online rapid determination of the optimal target value that the boiler efficiency should reach when the coal-fired unit is running at low load during peak load regulation, and further tap the energy-saving potential of the unit, the present application provides an embodiment of an electronic device for realizing all or part of the content of the method for online determination of the target value of boiler efficiency during peak load regulation of the coal-fired unit, and the electronic device specifically includes the following content:

[0156] Processor, memory, communication interface and bus; wherein the processor, memory and communication interface communicate with each other through the bus; the communication interface is used to realize the information transmission between the device for online determining the target value of boiler efficiency during peak load regulation of the coal-fired unit and related equipment such as the core business system, user terminal and related database; the logic controller can be a desktop computer, a tablet computer and a mobile terminal, etc., but the present embodiment is not limited thereto. In the present embodiment, the logic controller can be implemented with reference to the embodiment of the method for online determining the target value of boiler efficiency during peak load regulation of the coal-fired unit and the embodiment of the device for online determining the target value of boiler efficiency during peak load regulation of the coal-fired unit in the embodiment, and the contents thereof are incorporated herein, and the repeated parts are not repeated.

[0157] It is understandable that the user terminal may include a smart phone, a tablet electronic device, a network set-top box, a portable computer, a desktop computer, a personal digital assistant (PDA), a vehicle-mounted device, a smart wearable device, etc. Among them, the smart wearable device may include smart glasses, a smart watch, a smart bracelet, etc.

[0158] In practical applications, part of the method for online determination of the target value of boiler efficiency during peak load regulation of coal-fired units can be executed on the electronic device side as described above, or all operations can be completed in the client device. The selection can be made based on the processing capability of the client device and the limitations of the user's usage scenario. This application does not limit this. If all operations are completed in the client device, the client device may also include a processor.

[0159] The client device may have a communication module (i.e., a communication unit) that can communicate with a remote server to achieve data transmission with the server. The server may include a server on the task scheduling center side, and other implementation scenarios may also include a server on an intermediate platform, such as a server on a third-party server platform that has a communication link with the task scheduling center server. The server may include a single computer device, or a server cluster consisting of multiple servers, or a server structure of a distributed device.

[0160] Fig. 9 FIG. 9 is a schematic block diagram of the system structure of the electronic device 9600 according to an embodiment of the present application. Fig. 9 As shown, the electronic device 9600 may include a central processor 9100 and a memory 9140; the memory 9140 is coupled to the central processor 9100. It is worth noting that Fig. 9 is exemplary; other types of structures may also be used to supplement or replace this structure to implement telecommunication functions or other functions.

[0161] In one embodiment, the method function of determining the target value of boiler efficiency online during peak load regulation of coal-fired units can be integrated into the central processor 9100. The central processor 9100 can be configured to perform the following control:

[0162] S101: Determine an optimal target value of boiler efficiency based on the acquired real-time operation data and historical operation data;

[0163] S102: If it is determined that the current boiler efficiency has energy-saving potential, energy efficiency optimization adjustment is performed according to the optimal target value of the boiler efficiency and the real-time operation data.

[0164] From the above description, it can be seen that the method for online determining the target value of boiler efficiency during peak-shaving of coal-fired units provided in the present application can online determine the optimal target value that the boiler efficiency should reach when the coal-fired unit is operating at low load during peak-shaving, and then deeply analyze the reasons for the decline in boiler efficiency and determine the specific strategies for energy-saving upgrades and optimization transformation of the unit, further tapping the energy-saving potential of the unit, which is of great significance for reducing operating costs and improving the operating stability of the unit.

[0165] In another embodiment, the device for determining the target value of boiler efficiency online when the coal-fired unit is peak-shaving can be configured separately from the central processor 9100. For example, the data composite transmission device for determining the target value of boiler efficiency online when the coal-fired unit is peak-shaving can be configured as a chip connected to the central processor 9100, and the function of the method for determining the target value of boiler efficiency online when the coal-fired unit is peak-shaving is realized through the control of the central processor.

[0166] like Fig. 9 As shown, the electronic device 9600 may also include: a communication module 9110, an input unit 9120, an audio processor 9130, a display 9160, and a power supply 9170. It is worth noting that the electronic device 9600 does not necessarily have to include Fig. 9 In addition, the electronic device 9600 may also include Fig. 9 For components not shown, reference may be made to the prior art.

[0167] like Fig. 9 As shown, the central processing unit 9100 is sometimes also referred to as a controller or an operation control, and may include a microprocessor or other processor device and / or logic device. The central processing unit 9100 receives input and controls the operation of various components of the electronic device 9600.

[0168] The memory 9140 may be, for example, one or more of a cache, a flash memory, a hard drive, a removable medium, a volatile memory, a non-volatile memory or other suitable devices. The above-mentioned information related to the failure may be stored, and a program for executing the relevant information may also be stored. The CPU 9100 may execute the program stored in the memory 9140 to implement information storage or processing, etc.

[0169] The input unit 9120 provides input to the central processing unit 9100. The input unit 9120 is, for example, a key or a touch input device. The power supply 9170 is used to provide power to the electronic device 9600. The display 9160 is used to display display objects such as images and texts. The display may be, for example, an LCD display, but is not limited thereto.

[0170] The memory 9140 may be a solid-state memory, such as a read-only memory (ROM), a random access memory (RAM), a SIM card, etc. It may also be a memory that saves information even when the power is off, can be selectively erased, and is provided with more data, examples of which are sometimes referred to as EPROMs, etc. The memory 9140 may also be some other type of device. The memory 9140 includes a buffer memory 9141 (sometimes referred to as a buffer). The memory 9140 may include an application / function storage unit 9142, which is used to store application programs and function programs or processes for executing the operation of the electronic device 9600 through the central processor 9100.

[0171] The memory 9140 may also include a data storage unit 9143 for storing data, such as contacts, digital data, pictures, sounds, and / or any other data used by the electronic device. The driver storage unit 9144 of the memory 9140 may include various drivers for communication functions of the electronic device and / or for executing other functions of the electronic device (such as messaging applications, address book applications, etc.).

[0172] The communication module 9110 is a transmitter / receiver 9110 that sends and receives signals via an antenna 9111. The communication module (transmitter / receiver) 9110 is coupled to the central processor 9100 to provide input signals and receive output signals, which may be the same as the case of a conventional mobile communication terminal.

[0173] Based on different communication technologies, multiple communication modules 9110 may be provided in the same electronic device, such as a cellular network module, a Bluetooth module and / or a wireless LAN module. The communication module (transmitter / receiver) 9110 is also coupled to a speaker 9131 and a microphone 9132 via an audio processor 9130 to provide an audio output via the speaker 9131 and receive an audio input from the microphone 9132, thereby realizing a common telecommunication function. The audio processor 9130 may include any suitable buffer, decoder, amplifier, etc. In addition, the audio processor 9130 is also coupled to the central processor 9100, so that recording can be performed on the local machine through the microphone 9132, and the sound stored on the local machine can be played through the speaker 9131.

[0174] The embodiment of the present application also provides a computer-readable storage medium capable of implementing all the steps of the method for online determining the target value of boiler efficiency when the coal-fired unit is peak-shaving when the execution subject is a server or a client in the above embodiment. The computer-readable storage medium stores a computer program. When the computer program is executed by a processor, all the steps of the method for online determining the target value of boiler efficiency when the coal-fired unit is peak-shaving when the execution subject is a server or a client in the above embodiment are implemented. For example, when the processor executes the computer program, the following steps are implemented:

[0175] S101: Determine an optimal target value of boiler efficiency based on the acquired real-time operation data and historical operation data;

[0176] S102: If it is determined that the current boiler efficiency has energy-saving potential, energy efficiency optimization adjustment is performed according to the optimal target value of the boiler efficiency and the real-time operation data.

[0177] From the above description, it can be seen that the method for online determining the target value of boiler efficiency during peak-shaving of coal-fired units provided in the present application can online determine the optimal target value that the boiler efficiency should reach when the coal-fired unit is operating at low load during peak-shaving, and then deeply analyze the reasons for the decline in boiler efficiency and determine the specific strategies for energy-saving upgrades and optimization transformation of the unit, further tapping the energy-saving potential of the unit, which is of great significance for reducing operating costs and improving the operating stability of the unit.

[0178] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, devices, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0179] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (apparatus), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0180] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0181] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0182] The present invention uses specific embodiments to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A method for determining a target value of boiler efficiency online during peak load regulation of a coal-fired unit, characterized in that: include: Determine the optimal target value of boiler efficiency based on the acquired real-time operation data and historical operation data; If it is determined that the current boiler efficiency has energy-saving potential, energy efficiency optimization adjustment is performed according to the optimal target value of the boiler efficiency and the real-time operation data.

2. The method for determining the target value of boiler efficiency online during peak load regulation of a coal-fired unit according to claim 1, characterized in that: Determining the optimal target value of boiler efficiency based on the acquired real-time operation data and historical operation data includes: Performing cluster analysis on the real-time operation data and historical operation data to filter out normal operation data; The optimal target value of boiler efficiency is determined using the normal operation data.

3. The method for online determining the boiler efficiency target value during peak load regulation of a coal-fired unit according to claim 2, characterized in that: The determining the optimal target value of boiler efficiency by using the normal operation data comprises: The total reduction in boiler efficiency is determined based on the increase in solid incomplete combustion loss caused by the change in coal type, the increase in smoke exhaust loss caused by the change in coal type, and the reduction in boiler efficiency caused by the change in air temperature; The optimal target value of the boiler efficiency is determined according to the inherent value of the boiler efficiency under the current load and the total amount of the boiler efficiency decrease.

4. The method for determining the target value of boiler efficiency online during peak load regulation of a coal-fired unit according to claim 1, characterized in that: If it is determined that the current boiler efficiency has energy-saving potential, energy efficiency optimization adjustment is performed according to the optimal target value of the boiler efficiency and the real-time operation data, including: Determining whether the current boiler efficiency is less than the optimal target value of boiler efficiency; If so, determining that the current boiler efficiency has energy saving potential; An energy efficiency optimization adjustment strategy is determined according to the measurement point values ​​in the real-time operation data and the corresponding design values ​​to perform energy efficiency optimization adjustment.

5. A device for determining the target value of boiler efficiency online during peak load regulation of coal-fired units, characterized in that: include: An optimal target determination unit, used to determine the optimal target value of boiler efficiency based on the acquired real-time operation data and historical operation data; The energy efficiency optimization and adjustment unit is used to optimize and adjust the energy efficiency according to the optimal target value of the boiler efficiency and the real-time operation data if it is determined that the current boiler efficiency has energy-saving potential.

6. The device for online determining boiler efficiency target value during peak load regulation of coal-fired units according to claim 5, characterized in that: The optimal target determination unit comprises: A normal data screening module is used to perform cluster analysis on the real-time operation data and historical operation data to screen normal operation data; The optimal target determination module is used to determine the optimal target value of the boiler efficiency by using the normal operation data.

7. The device for determining the target value of boiler efficiency online during peak load regulation of coal-fired units according to claim 6, characterized in that: The optimal target determination module comprises: A total reduction determination module is used to determine the total reduction in boiler efficiency based on the increase in solid incomplete combustion loss caused by the change in coal type, the increase in smoke exhaust loss caused by the change in coal type, and the reduction in boiler efficiency caused by the change in air temperature; The optimal efficiency determination module is used to determine the optimal target value of the boiler efficiency according to the inherent value of the boiler efficiency under the current load and the total amount of the boiler efficiency reduction.

8. The device for determining the target value of boiler efficiency online during peak load regulation of coal-fired units according to claim 5, characterized in that: The energy efficiency optimization and adjustment unit comprises: An efficiency comparison module, used to determine whether the current boiler efficiency is less than the optimal target value of the boiler efficiency; An energy-saving potential judgment module, used for judging that the current boiler efficiency has energy-saving potential; The tuning strategy determination module is used to determine the energy efficiency optimization adjustment strategy according to the measurement point values ​​in the real-time operation data and the corresponding design values, so as to perform energy efficiency optimization adjustment.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps of the method for online determining the boiler efficiency target value during peak load regulation of a coal-fired unit as described in any one of claims 1 to 4 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for online determining the target value of boiler efficiency during peak load regulation of a coal-fired unit as described in any one of claims 1 to 4 are implemented.

11. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instruction is executed by a processor, the steps of the method for online determining the target value of boiler efficiency during peak load regulation of a coal-fired unit as described in any one of claims 1 to 4 are implemented.

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