Thermal power unit operation adjustment method, device, equipment and storage medium

Abstract

The application discloses a thermal power unit operation adjustment method, device and equipment and a storage medium. The thermal power unit operation adjustment method comprises the following steps: acquiring current operation state parameters and operation influence parameters of a thermal power unit; inputting each operation state parameter and all operation influence parameters to a neural network prediction model in sequence to obtain the correlation of each operation state parameter and all operation influence parameters; calculating the consumption difference of each operation state parameter; calculating the deviation value of the consumption difference of each operation state parameter and the corresponding consumption difference benchmark value obtained from a thermal power unit benchmark value database, and judging whether each deviation value exceeds a preset consumption difference deviation threshold value; and when the deviation value exceeds the preset consumption difference deviation threshold value, adjusting the operation influence parameters according to the correlation of the obtained operation state parameters and all operation influence parameters and the deviation value.

Description

Technical Field

[0001] This invention relates to the field of thermal power unit operation analysis technology, and in particular to a method, apparatus, equipment and storage medium for adjusting the operation of thermal power units. Background Technology

[0002] The nation is currently strongly advocating the integration of informatization, industrialization, and intelligentization. Thermal power units have largely achieved digital operation, and the large amount of operational data generated by these units serves as a crucial basis for monitoring their operational status, equipment safety, and energy consumption. Because the operating status of thermal power units is closely related to their coal consumption, current technology typically uses the difference in operating parameters to reflect the unit's operating condition, helping operators adjust their operations. This difference refers to the degree to which a certain operating parameter deviates from its corresponding benchmark value, impacting coal consumption. However, currently, this method cannot directly guide the specific operational behavior of unit personnel when adjusting unit operation; adjustments still primarily rely on the experience of the personnel. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide a method, device, equipment and storage medium for adjusting the operation of thermal power units, so as to directly guide the specific operation behavior of the unit personnel in real time, thereby achieving the purpose of adjusting the operation of thermal power units.

[0004] In a first aspect, the present invention provides a method for adjusting the operation of a thermal power unit, comprising: acquiring current operating status parameters and operational influence parameters of the thermal power unit; sequentially inputting each acquired operating status parameter and all operational influence parameters into a neural network prediction model to obtain the correlation between each operating status parameter and all operational influence parameters; calculating the consumption difference of each operating status parameter; calculating the deviation value between the consumption difference of each operating status parameter and the corresponding consumption difference benchmark value obtained from a thermal power unit benchmark value database, and determining whether each deviation value exceeds a preset consumption difference deviation threshold; when the deviation value exceeds the preset consumption difference deviation threshold, adjusting the operational influence parameters according to the obtained correlation between the operating status parameters and all operational influence parameters and the deviation value.

[0005] Secondly, the present invention also provides a thermal power unit operation adjustment device, which includes a unit for performing the above-described thermal power unit operation adjustment method.

[0006] Thirdly, the present invention also provides a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-mentioned thermal power unit operation adjustment method.

[0007] Fourthly, the present invention also provides a storage medium storing a computer program, the computer program including program instructions, which, when executed by a processor, can implement the above-described thermal power unit operation adjustment method.

[0008] Compared with existing technologies, this invention uses a neural network algorithm to calculate the correlation between various operating state parameters and operational influence parameters, and calculates the consumption difference of each operating state parameter and the deviation of this consumption difference from the corresponding consumption difference benchmark value obtained from the thermal power unit benchmark value database. When the deviation value exceeds a preset consumption difference deviation threshold, the operational influence parameters can be adjusted based on the obtained correlation between the operating state parameters and all operational influence parameters, as well as the deviation value. Therefore, this invention establishes the correlation between the operating state parameters and operational influence parameters, thereby identifying several operational influence parameters that are strongly correlated with each operating state parameter. When the consumption difference of the operating state parameter changes, and its When the deviation of the consumption difference benchmark value corresponding to the current operating condition exceeds the preset consumption difference deviation threshold, adjustment suggestions for the relevant operation influence parameters can be given based on the correlation and deviation value between the operating status parameters and the operation influence parameters. This provides real-time guidance to the unit personnel to adjust the relevant operation influence parameters, and constructs an operation influence parameter adjustment system based on the consumption difference change of the operating status parameters and the correlation between the operating status parameters and the operation influence parameters. This system is more reasonable than manual experience and can directly and in real-time guide the specific operating behavior of the unit personnel, thereby adjusting the operating status of the thermal power unit, and then adjusting the coal consumption of the thermal power unit, realizing closed-loop control, and improving the operating efficiency of the thermal power unit. Attached Figure Description

[0009] Figure 1 This is a flowchart illustrating the thermal power unit operation adjustment method provided in the first embodiment of the present invention;

[0010] Figure 2 This is a schematic diagram of a sub-process of the thermal power unit operation adjustment method provided in the first embodiment of the present invention;

[0011] Figure 3 This is a flowchart illustrating the thermal power unit operation adjustment method provided in the second embodiment of the present invention;

[0012] Figure 4 This is a schematic block diagram of the thermal power unit operation adjustment device provided in the first embodiment of the present invention;

[0013] Figure 5 This is a schematic block diagram of a thermal power unit operation adjustment device provided in the second embodiment of the present invention;

[0014] Figure 6 A schematic block diagram of a computer device provided for an embodiment of the present invention. Detailed Implementation

[0015] To enable those skilled in the art to more clearly understand the purpose, technical solution, and advantages of the present invention, the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0016] Reference Figure 1 , Figure 1 This is a flowchart illustrating the thermal power unit operation adjustment method provided in the first embodiment of the present invention. As shown in the figure, the method includes the following steps S110-S150:

[0017] S110. Obtain the current operating status parameters and operation impact parameters of the thermal power unit.

[0018] In this step, real-time data of the thermal power unit during operation is collected. Among them, the operation impact parameters are the parameters that the unit personnel can directly operate and control during the unit operation, representing the variables corresponding to the operation behavior of the unit personnel. The operation status parameters are the main operation status parameters of the unit affected when the operation impact parameters change, representing the working status of the unit.

[0019] In this embodiment, the operational influencing parameters may include one or more of the following: coal feed rate, primary air volume, secondary damper opening, SOFA air volume, feedwater temperature, and desuperheating water volume; the operating status parameters may include one or more of the following: boiler oxygen content, main steam temperature, main steam pressure, reheat steam temperature, and plant power consumption rate.

[0020] S120. Input each obtained operating state parameter and all operation influence parameters into the neural network prediction model in sequence to obtain the correlation between each operating state parameter and all operation influence parameters.

[0021] In this invention, the unit's coal consumption is closely related to its operating status parameters, and the operational influence parameters directly or indirectly affect the operating status of the thermal power unit; that is, the operating status parameters change with the changes in the operational influence parameters.

[0022] In this step, a neural network algorithm is used to obtain the correlation between various operating state parameters and operational influence parameters, thereby identifying several operational influence parameters that are strongly correlated with each operating state parameter. By adjusting these operational influence parameters, the unit's closed-loop adjustment is achieved.

[0023] In this embodiment, the operational influence parameter can be represented by formula (1):

[0024] A = {A1, A2, A3, A4, A...} i ,...,A n},(1≤i≤n)(1)

[0025] In the formula, A represents the set of operational impact parameters corresponding to the operator's actions. i This indicates the operational impact parameter corresponding to one of the operator's actions, such as coal feed rate, primary air volume, secondary damper opening, SOFA air volume, feedwater temperature, or desuperheating water volume.

[0026] The operating status parameters can be expressed using formula (2):

[0027] B = {B1, B2, B3, B4, B} j ,...,B m},(1≤j≤m)(2)

[0028] In the formula, B represents the set of operating state parameters, B j This indicates one of the operating status parameters, such as boiler oxygen content, main steam temperature, main steam pressure, reheat steam temperature, or plant power consumption rate.

[0029] In this step, A can be the input and B the output. A neural network prediction model is used iteratively until the convergence function converges, satisfying the accuracy requirements of the neural network prediction model, thus obtaining the model output B' that meets the accuracy requirements. Let the correlation matrix between A and B be P, where P = [ρ A1B1 , ρ A2B1 , ρ A3B1 ...ρ AnB1 ;ρ A1B2 , ρ A2B2 , ρ A3B2 ...ρAnB2;...;ρ A1Bm , ρ A2Bm , ρ A3Bm ...ρ AnBm From AP = B', we know that P = B'A -1 This allows us to obtain each correlation coefficient ρ, thus revealing the correlation between operating state parameters and operational influence parameters.

[0030] S130. Calculate the consumption difference for each of the aforementioned operating state parameters.

[0031] like Figure 2 As shown, this step specifically includes:

[0032] S131. Obtain the benchmark values ​​of operating status parameters corresponding to the current operating conditions of the thermal power unit from the benchmark value database of thermal power units.

[0033] In this invention, the benchmark database for thermal power units includes the optimal operating influence parameters, operating status parameters, and consumption differences of operating status parameters corresponding to different operating conditions of thermal power units.

[0034] S132. Calculate the difference between the benchmark value of the operating status parameter and the current operating status parameter, and obtain the consumption difference of the operating status parameter based on the difference and the unit consumption difference.

[0035] In this step, the unit consumption difference refers to the degree of influence of a parameter deviating from its corresponding benchmark value on coal consumption. The product of the difference and the unit consumption difference is the consumption difference of the operating state parameter.

[0036] Understandably, a deviation of the real-time value of the operating status parameter from the benchmark value under the corresponding operating condition will result in a certain amount of coal consumption. The coal consumption resulting from this deviation is called the consumption difference. If the consumption difference deviates too much, especially the positive consumption difference (the larger the positive consumption difference, the more coal is used to produce one kilowatt-hour of electricity), manual intervention is required.

[0037] S140. Calculate the deviation between the consumption difference of each of the operating status parameters and the corresponding consumption difference benchmark value obtained from the thermal power unit benchmark value database, and determine whether each deviation value exceeds the preset consumption difference deviation threshold.

[0038] In this step, the deviation value is the consumption deviation value. The preset consumption deviation threshold corresponding to the consumption deviation value of each of the operating status parameters can be set according to actual needs. For example, the preset consumption deviation threshold corresponding to the consumption deviation value of the boiler oxygen can be set to 0.5, while the preset consumption deviation threshold corresponding to the consumption deviation value of the main steam temperature can be set to 1.

[0039] S150. When the deviation value exceeds the preset consumption deviation threshold, the operation influence parameters are adjusted according to the obtained operating status parameters, the correlation of all operation influence parameters, and the deviation value.

[0040] This step specifically includes: changing the operational behavior based on the obtained operating status parameters and the correlation of all operational influencing parameters, as well as the deviation value, thereby adjusting the corresponding operational influencing parameters; wherein, the operational behavior may include one or more of coal feeding control, damper control, feedwater control, and desuperheating water control, then the unit personnel can change the coal feed rate of coal feeding control, the damper opening of damper control, the primary air volume and SOFA air volume, the feedwater temperature of feedwater control and / or the desuperheating water volume of desuperheating water control, and other parameters that the unit personnel can directly operate and control during unit operation, based on the correlation and the deviation value.

[0041] For example, when the main steam temperature consumption deviation value is greater than its corresponding preset consumption deviation threshold, the relevant operational influence parameters are adjusted in descending order according to the magnitude of the deviation value and the correlation coefficient of the operational influence parameters related to the main steam temperature. That is, the adjustment is carried out in order from the operational influence parameters with higher correlation coefficients to the operational influence parameters with lower correlation coefficients, so that the deviation value is maintained within the normal deviation range.

[0042] In this invention, the change in the consumption difference of the operating status parameter is used as the basis for judgment. Combined with the correlation between the operating status parameter and the operation influence parameter, adjustment suggestions are given for the relevant operation influence parameter to remind the operator to take corresponding adjustment operations. That is, the operation influence parameter is adjusted by the change in the consumption difference of the operating status parameter so that the consumption difference of the operating status parameter is maintained within the normal deviation range.

[0043] In summary, this invention constructs the correlation between operating status parameters and operational influence parameters, thereby identifying several operational influence parameters that are strongly correlated with each operating status parameter. When the consumption difference of an operating status parameter changes, and its deviation from the consumption difference benchmark value corresponding to the current operating condition exceeds a preset consumption difference deviation threshold, adjustment suggestions for the relevant operational influence parameters can be given based on the correlation and deviation value between the operating status parameters and the operational influence parameters. This provides real-time guidance to unit personnel to adjust the relevant operational influence parameters. In other words, this invention adjusts the relevant operational influence parameters by finding the correlation between operating status parameters and operational influence parameters, combined with the changes in the consumption difference of the operating status parameters. This is more reasonable than manual experience. This invention can directly provide adjustment suggestions for the relevant operational influence parameters, directly and in real-time guiding operators to take corresponding adjustment operations, thereby adjusting the operating status of the thermal power unit, and further adjusting the coal consumption of the thermal power unit, realizing closed-loop control, and improving the operating efficiency of the thermal power unit.

[0044] Reference Figure 3 , Figure 3 This is a flowchart illustrating the thermal power unit operation adjustment method provided in the second embodiment of the present invention. As shown in the figure, the method includes the following steps S210-S280:

[0045] S210. Obtain historical operating status parameters and historical operation impact parameters of thermal power units.

[0046] S220. Each historical operating state parameter and all historical operation influence parameters are sequentially input into the neural network model for training to obtain a neural network prediction model that characterizes the correlation between operating state parameters and operation influence parameters.

[0047] In this step, initially, historical data from thermal power units are used to train a neural network model to correct the initial neural network model and obtain a neural network prediction model for obtaining the correlation between operating status parameters and operational impact parameters.

[0048] S230. Obtain the current operating status parameters and operation impact parameters of the thermal power unit.

[0049] This step is similar to step S110, and will not be described again here.

[0050] S240. Input each obtained operating state parameter and all operation influence parameters into the neural network prediction model in sequence to obtain the correlation between each operating state parameter and all operation influence parameters.

[0051] This step is similar to step S120, and will not be described again here.

[0052] S250. Construct a correlation table between the operating status parameters and the operating influence parameters based on the correlation magnitude between each operating status parameter and all operating influence parameters.

[0053] In this step, the parameters are sorted in descending order based on the correlation between each operating status parameter and all operational influence parameters. A correlation table between the operating status parameters and operational influence parameters is then constructed based on the descending order. In other words, by sorting the operating status parameters and each operational influence parameter according to their correlation coefficients, several operational influence parameters with close correlations can be identified, and a correlation table can be constructed.

[0054] S260. Calculate the consumption difference for each of the aforementioned operating state parameters.

[0055] This step is similar to step S130, and will not be described again here.

[0056] S270. Calculate the deviation between the consumption difference of each of the operating status parameters and the corresponding consumption difference benchmark value obtained from the thermal power unit benchmark value database, and determine whether each of the deviation values ​​exceeds the preset consumption difference deviation threshold.

[0057] This step is similar to step S140 and will not be described again here.

[0058] S280. When the deviation value exceeds the preset consumption deviation threshold, the operation influence parameters are adjusted according to the correlation table and the deviation value.

[0059] In this embodiment, the step specifically includes: when the deviation between the consumption difference of the operating status parameter and the corresponding consumption difference benchmark value exceeds a preset consumption difference deviation threshold, obtaining several operational influence parameters that are strongly correlated with the operating status parameter according to the constructed correlation table, and adjusting the obtained several operational influence parameters that are strongly correlated according to the deviation value. In this embodiment, several operational influence parameters that are strongly correlated with the operating status parameter are obtained from the constructed correlation table.

[0060] Understandably, in this embodiment, the operational behavior corresponding to several operational influence parameters with strong correlation to the deviation value is changed, thereby adjusting the several operational influence parameters; that is, the crew can change the operational behavior corresponding to the highly correlated operational influence parameters according to the correlation and the deviation value. For example, when the main steam temperature consumption deviation value is greater than its corresponding preset consumption deviation threshold, the relevant operational influence parameters are adjusted in descending order according to the magnitude of the deviation value and the correlation coefficient of the operational influence parameters related to the main steam temperature. That is, the operational influence parameters with higher correlation coefficients are adjusted sequentially from those with higher correlation coefficients to those with lower correlation coefficients. For example, operational influence parameters with a correlation coefficient greater than 0.5 can be adjusted to keep the deviation value within the normal deviation range.

[0061] In this invention, the change in consumption difference of operating status parameters is used as the basis for judgment. Combining the correlation between operating status parameters and operational influence parameters, adjustment suggestions are given for operational influence parameters that are strongly correlated with the operating status parameters, so as to remind operators to take corresponding adjustment operations.

[0062] Reference Figure 4 , Figure 4 This is a block diagram of the thermal power unit operation adjustment device 300 provided in the first embodiment of the present invention. Figure 4 As shown, corresponding to the thermal power unit operation adjustment method of the first embodiment above, the present invention also provides a thermal power unit operation adjustment device 300. This thermal power unit operation adjustment device 300 includes a unit for executing the thermal power unit operation adjustment method of the first embodiment above, and the thermal power unit operation adjustment device 300 can be configured in a server. Specifically, please refer to... Figure 4 The thermal power unit operation adjustment device 300 includes an acquisition unit 301, a correlation construction unit 302, a first calculation unit 303, a judgment unit 304, and an adjustment unit 305.

[0063] The acquisition unit 301 is used to acquire the current operating status parameters and operation influence parameters of the thermal power unit, and also to acquire the deviation value of the consumption difference benchmark value corresponding to the current operating condition from the benchmark value database of the thermal power unit based on the acquired real-time operating status parameters. This invention collects real-time data of the thermal power unit during operation through the acquisition unit 301. The operation influence parameters are parameters that can be directly operated and controlled by the unit personnel during unit operation, representing variables corresponding to the personnel's operational behavior. The operating status parameters are the main operating status parameters of the unit affected when the operation influence parameters change, representing the unit's working state. In this embodiment, the operation influence parameters may include one or more of the following: coal feed rate, primary air volume, secondary damper opening, SOFA air volume, feedwater temperature, and desuperheating water volume; the operating status parameters may include one or more of the following: boiler oxygen content, main steam temperature, main steam pressure, reheat steam temperature, and plant power consumption rate.

[0064] The correlation construction unit 302 is used to sequentially input each acquired operating state parameter and all operational influence parameters into the neural network prediction model to obtain the correlation between each operating state parameter and all operational influence parameters. Specifically, the correlation between each operating state parameter and operational influence parameter is obtained using a neural network algorithm, thereby identifying several operational influence parameters that are strongly correlated with each operating state parameter. By adjusting these operational influence parameters, closed-loop adjustment of the unit can be achieved.

[0065] The first calculation unit 303 is used to calculate the consumption difference of each of the operating state parameters, and also to calculate the deviation between the consumption difference of each of the operating state parameters and the corresponding consumption difference benchmark value obtained from the thermal power unit benchmark value database. Specifically, calculating the consumption difference of each of the operating state parameters includes: obtaining the operating state parameter benchmark value corresponding to the current operating condition of the thermal power unit from the thermal power unit benchmark value database, calculating the difference between the operating state parameter benchmark value and the current operating state parameter, and obtaining the consumption difference of the operating state parameter based on the difference and the unit consumption difference. The unit consumption difference refers to the degree of influence of a parameter deviating from its corresponding operating condition benchmark value by a unit value on coal consumption. Understandably, a deviation of the real-time value of an operating state parameter from its corresponding operating condition benchmark value will result in a certain amount of coal consumption. This coal consumption caused by the deviation is called the consumption difference. If the consumption difference deviates too much, manual intervention is required. In this invention, the related operational influence parameters are adjusted by changing the consumption difference of the operating state parameter, so that the consumption difference of the operating state parameter is maintained within the normal deviation range.

[0066] The judgment unit 304 is used to determine whether each deviation value exceeds a preset consumption deviation threshold.

[0067] The adjustment unit 305 is used to adjust the operation-influencing parameters based on the obtained operating status parameters, the correlation between all operation-influencing parameters, and the deviation value when the deviation value exceeds a preset consumption deviation threshold. Specifically, in this embodiment, the adjustment unit 305 changes the operation behavior based on the obtained operating status parameters, the correlation between all operation-influencing parameters, and the deviation value, thereby adjusting the corresponding operation-influencing parameters; wherein, the operation behavior includes one or more of coal feeding control, damper control, feedwater control, and desuperheating water control, so the unit personnel can change the coal feeding rate of coal feeding control, the damper opening of damper control, the primary air volume and SOFA air volume, the feedwater temperature of feedwater control, and / or the desuperheating water volume of desuperheating water control, etc., which are parameters that the unit personnel can directly operate and control during unit operation, based on the correlation and the deviation value.

[0068] In summary, when the thermal power unit operation adjustment device 300 of this embodiment is applied to a thermal power unit, the consumption difference of the operating status parameters will also change when the operating conditions of the thermal power unit change. When the consumption difference deviation is greater than a certain threshold, the thermal power unit operation adjustment device 300 automatically recommends operation adjustment suggestions, directly and in real time guides the specific operation behavior of the unit personnel, and realizes closed-loop control. That is, the thermal power unit operation adjustment device 300 of this invention establishes the correlation between operating status parameters and operation influence parameters, avoids the irrationality of manual judgment, and guides operation by using the consumption difference deviation threshold early warning method, which has high operability.

[0069] Reference Figure 5 , Figure 5 This is a schematic block diagram of a thermal power unit operation adjustment device 300 provided in the second embodiment of the present invention. Figure 5 As shown, the thermal power unit operation adjustment device 300 in this embodiment is based on the first device embodiment described above, with the addition of a model training unit 306 and a table construction unit 307.

[0070] The acquisition unit 301 is further configured to acquire historical operating status parameters and historical operational influence parameters of the thermal power unit. The model training unit 306 is configured to sequentially input each acquired historical operating status parameter and all historical operational influence parameters into the neural network model for training, thereby obtaining a neural network prediction model for characterizing the correlation between operating status parameters and operational influence parameters; that is, initially, the neural network model can also be trained using historical data of the thermal power unit to correct the initial neural network model and obtain a neural network prediction model for acquiring the correlation between operating status parameters and operational influence parameters. The table construction unit 307 is used to construct a correlation table of the operating state parameters and the operating influence parameters based on the correlation magnitude of each operating state parameter and all operating influence parameters. Preferably, in this embodiment, the table construction unit 307 is specifically used to sort the operating state parameters and all operating influence parameters in descending order based on the correlation magnitude of each operating state parameter and all operating influence parameters, and construct the correlation table of the operating state parameters and the operating influence parameters based on the descending order sorting result. Correspondingly, in this embodiment, the adjustment unit 305 is specifically used to obtain a number of operating influence parameters that are strongly correlated with the operating state parameters based on the constructed correlation table when the deviation value between the consumption difference of the operating state parameter and the corresponding consumption difference benchmark value exceeds a preset consumption difference deviation threshold, and adjust the obtained number of strongly correlated operating influence parameters based on the deviation value.

[0071] It should be noted that those skilled in the art can clearly understand that the specific implementation process of the above-mentioned thermal power unit operation adjustment device 300 and each unit can be referred to the corresponding description in the foregoing method embodiments. For the sake of convenience and brevity, it will not be repeated here.

[0072] The aforementioned thermal power unit operation adjustment device 300 can be implemented as a computer program, which can, for example... Figure 6 It runs on the computer device shown. Please refer to [link / reference]. Figure 6 , Figure 6 This is a schematic block diagram of a computer device provided in an embodiment of the present invention. The computer device 500 can be a server, which can be a standalone server or a server cluster composed of multiple servers.

[0073] See Figure 6 The computer device 500 includes a processor 502, a memory, and a network interface 505 connected via a system bus 501. The memory may include a non-volatile storage medium 503 and internal memory 504.

[0074] The non-volatile storage medium 503 may store an operating system 5031 and a computer program 5032. The computer program 5032 includes program instructions that, when executed, cause the processor 502 to perform a method for adjusting the operation of a thermal power unit.

[0075] The processor 502 provides computing and control capabilities to support the operation of the entire computer device 500.

[0076] The internal memory 504 provides an environment for the operation of the computer program 5032 in the non-volatile storage medium 503. When the computer program 5032 is executed by the processor 502, the processor 502 can execute a thermal power unit operation adjustment method.

[0077] This network interface 505 is used for network communication with other devices. Those skilled in the art will understand that... Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device 500 to which the present application is applied. The specific computer device 500 may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0078] The processor 502 is used to run a computer program 5032 stored in the memory to perform the following steps: acquiring the current operating status parameters and operational influence parameters of the thermal power unit; sequentially inputting each acquired operating status parameter and all operational influence parameters into a neural network prediction model to obtain the correlation between each operating status parameter and all operational influence parameters; calculating the consumption difference of each operating status parameter; calculating the deviation value between the consumption difference of each operating status parameter and the corresponding consumption difference benchmark value obtained from the thermal power unit benchmark value database, and determining whether each deviation value exceeds a preset consumption difference deviation threshold; when the deviation value exceeds the preset consumption difference deviation threshold, adjusting the operational influence parameters according to the obtained correlation between the operating status parameters and all operational influence parameters and the deviation value. The operating status parameters include one or more of the following: boiler oxygen content, main steam temperature, main steam pressure, reheat steam temperature, and plant power consumption rate.

[0079] In some embodiments, before acquiring the current operating status parameters and operational impact parameters of the thermal power unit, the processor 502 further includes: acquiring historical operating status parameters and historical operational impact parameters of the thermal power unit; sequentially inputting each acquired historical operating status parameter and all historical operational impact parameters into a neural network model for training, thereby obtaining a neural network prediction model for characterizing the correlation between the operating status parameters and operational impact parameters.

[0080] In some embodiments, after obtaining the correlation between each operating state parameter and all operating influence parameters, the processor 502 further includes: constructing a correlation table between the operating state parameters and the operating influence parameters based on the magnitude of the correlation between each operating state parameter and all operating influence parameters.

[0081] In some embodiments, when the deviation value exceeds a preset consumption deviation threshold, adjusting the operation influence parameters based on the correlation between the obtained operating status parameters and all operation influence parameters, as well as the deviation value, specifically includes: when the deviation value between the consumption difference of the operating status parameter and the corresponding consumption difference benchmark value exceeds the preset consumption deviation threshold, obtaining a number of operation influence parameters that are strongly correlated with the operating status parameter according to a constructed correlation table, and adjusting the obtained number of strongly correlated operation influence parameters according to the deviation value.

[0082] In some embodiments, adjusting the operation-influence parameters based on the obtained operating status parameters, the correlation between all operation-influence parameters, and the deviation value specifically includes: changing the operation behavior based on the obtained operating status parameters, the correlation between all operation-influence parameters, and the deviation value, thereby adjusting the corresponding operation-influence parameters; wherein, the operation behavior includes one or more of coal feeding control, damper control, water supply control, and desuperheating water control, and the operation-influence parameters include one or more of coal feed rate, primary air volume, secondary damper opening, SOFA air volume, water supply temperature, and desuperheating water volume.

[0083] In some embodiments, calculating the consumption difference of each of the operating state parameters specifically includes: obtaining the benchmark value of the operating state parameter corresponding to the current operating condition of the thermal power unit from the benchmark value database of thermal power units; calculating the difference between the benchmark value of the operating state parameter and the current operating state parameter; and obtaining the consumption difference of the operating state parameter based on the difference and the unit consumption difference.

[0084] It should be understood that, in the embodiments of this application, the processor 502 may be a central processing unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0085] It will be understood by those skilled in the art that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program includes program instructions and can be stored in a storage medium, which is a computer-readable storage medium. The program instructions are executed by at least one processor in the computer system to implement the process steps of the embodiments of the above methods.

[0086] Therefore, the present invention also provides a storage medium. This storage medium can be a computer-readable storage medium. The storage medium stores a computer program, wherein the computer program includes program instructions. When these program instructions are executed by a processor, they can implement the thermal power unit operation adjustment method described in the above embodiments.

[0087] The storage medium can be any computer-readable storage medium capable of storing program code, such as a USB flash drive, portable hard drive, read-only memory (ROM), magnetic disk, or optical disk.

[0088] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0089] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a client, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention.

[0090] Furthermore, it should be understood that the disclosed apparatus and methods can be implemented in other ways, as presented in the several embodiments provided in this invention. For example, the apparatus embodiments described above are merely illustrative. For example, the division of each unit is only a logical functional division, and there may be other division methods in actual implementation. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed.

[0091] It should be further noted that the descriptions of each embodiment in the above embodiments have different emphases. Parts not described in detail in a certain embodiment can be referred to in the relevant descriptions of other embodiments. For the foregoing method embodiments, for the sake of simplicity, they are all described as a series of actions. However, those skilled in the art should understand that the present invention is not limited to the described order of actions, because according to the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the present invention.

[0092] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for adjusting the operation of a thermal power unit, characterized in that, include: Obtain the current operating status parameters and operational impact parameters of the thermal power unit; Each obtained running state parameter and all operation influence parameters are sequentially input into the neural network prediction model to obtain the correlation between each running state parameter and all operation influence parameters; wherein, the correlation is represented by a correlation matrix, and the elements in the correlation matrix are the correlation coefficients determined by the trained neural network prediction model based on the operation influence parameters and the output of the neural network prediction model; Calculate the consumption difference for each of the aforementioned operating state parameters; Calculate the deviation between the consumption difference of each of the operating status parameters and the corresponding consumption difference benchmark value obtained from the thermal power unit benchmark value database, and determine whether each deviation value exceeds the preset consumption difference deviation threshold. When the deviation value exceeds the preset consumption deviation threshold, the operation influence parameters are adjusted according to the obtained operating status parameters and the correlation between all operation influence parameters and the deviation value.

2. The method for adjusting the operation of a thermal power unit as described in claim 1, characterized in that, Before obtaining the current operating status parameters and operational impact parameters of the thermal power unit, the following steps are also included: Obtain historical operating status parameters and historical operation impact parameters of thermal power units; Each historical operating state parameter and all historical operation influence parameters are sequentially input into the neural network model for training, thereby obtaining a neural network prediction model that characterizes the correlation between operating state parameters and operation influence parameters.

3. The method for adjusting the operation of a thermal power unit as described in claim 1, characterized in that, After obtaining the correlation between each operating state parameter and all operational influence parameters, the process further includes: A correlation table of the operating status parameters and the operating influence parameters is constructed based on the correlation magnitude between each operating status parameter and all operating influence parameters.

4. The method for adjusting the operation of a thermal power unit as described in claim 3, characterized in that, When the deviation value exceeds a preset consumption deviation threshold, the operation influence parameters are adjusted based on the correlation between the obtained operating status parameters and all operation influence parameters, as well as the deviation value. Specifically, this includes: When the deviation between the consumption difference of the operating status parameter and the corresponding consumption difference benchmark value exceeds a preset consumption difference deviation threshold, several operation influence parameters that are strongly correlated with the operating status parameter are obtained according to the constructed correlation table, and the obtained several operation influence parameters that are strongly correlated are adjusted according to the deviation value.

5. The method for adjusting the operation of a thermal power unit as described in claim 1, characterized in that, The adjustment of the operation influence parameters based on the correlation between the obtained operating status parameters and all operation influence parameters, as well as the deviation value, specifically includes: The operational behavior is changed based on the obtained operating status parameters and the correlation magnitude of all operational influence parameters, as well as the deviation value, thereby adjusting the corresponding operational influence parameters; wherein, the operational behavior includes one or more of coal feeding control, damper control, water supply control, and desuperheating water control, and the operational influence parameters include one or more of coal feed rate, primary air volume, secondary damper opening, SOFA air volume, water supply temperature, and desuperheating water volume.

6. The method for adjusting the operation of a thermal power unit as described in claim 1, characterized in that, The calculation of the consumption difference for each of the aforementioned operating state parameters specifically includes: Obtain benchmark values ​​of operating status parameters corresponding to the current operating conditions of the thermal power unit from the benchmark value database of thermal power units; Calculate the difference between the benchmark value of the operating status parameter and the current operating status parameter, and obtain the consumption difference of the operating status parameter based on the difference and the unit consumption difference.

7. The method for adjusting the operation of a thermal power unit as described in claim 1, characterized in that, The operating status parameters include one or more of the following: boiler oxygen content, main steam temperature, main steam pressure, reheat steam temperature, and plant power consumption rate.

8. A thermal power unit operation adjustment device, characterized in that, It includes a unit for performing the thermal power unit operation adjustment method as described in any one of claims 1-7.

9. A computer device, characterized in that, The computer device includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the thermal power unit operation adjustment method as described in any one of claims 1-7.

10. A storage medium, characterized in that, The storage medium stores a computer program, which includes program instructions that, when executed by a processor, can implement the thermal power unit operation adjustment method as described in any one of claims 1-7.

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