Coal-fired unit peak regulation optimization method, device and equipment and storage medium

Abstract

The invention discloses a coal-fired unit peak regulation optimization method and device, equipment and a storage medium, and belongs to the field of coal-fired unit peak regulation, and the method comprises the steps: obtaining a first operation scheme under a first load in a coal-fired unit peak regulation process; obtaining a cost index, an environmental benefit index and a safety and stability index of the first operation scheme; determining the weight of each index in the cost index, the environmental benefit index and the safety and stability index by adopting an optimal and worst method; obtaining the score of each index in the cost index, the environmental benefit index and the safety and stability index; based on the weight of each index, performing weighted summation on the score of each index to obtain a score of the first operation scheme; and optimizing the first operation scheme based on the score of the first operation scheme. According to the method, the peak regulation scheme of the coal-fired unit can be systematically and comprehensively optimized in the three dimensions of environment, cost and safety.

Description

Technical Field

[0001] The present disclosure relates to the field of peak load regulation of coal-fired units, and in particular to a method, device, equipment and storage medium for optimizing peak load regulation of coal-fired units. Background Art

[0002] Peak shaving of coal-fired units refers to the process of adjusting the operating parameters of coal-fired units to adapt to fluctuations in power load, maintain active power balance, and ensure system frequency stability.

[0003] At present, the peak-shaving optimization method of coal-fired units mainly optimizes the cost and benefit aspects. However, optimizing only the cost and benefit aspects is not comprehensive enough, and the reference value of the optimization plan is low. Summary of the invention

[0004] The present disclosure provides a method, device, equipment and storage medium for optimizing peak load of coal-fired units, which can systematically and comprehensively optimize the peak load scheme of coal-fired units in terms of environment, cost and safety. The technical scheme includes at least the following schemes: In a first aspect, a method for optimizing peak load of a coal-fired unit is provided, comprising: obtaining a first operation plan at a first load during the peak load of the coal-fired unit; obtaining a cost indicator, an environmental benefit indicator, and a safety and stability indicator of the first operation plan; using the best-worst method to determine the weight of each of the cost indicator, the environmental benefit indicator, and the safety and stability indicator; obtaining a score for each of the cost indicator, the environmental benefit indicator, and the safety and stability indicator; based on the weight of each indicator, performing weighted summation on the score of each indicator to obtain a score for the first operation plan; and optimizing the first operation plan based on the score of the first operation plan.

[0005] Optionally, the cost index, the environmental benefit index and the safety and stability index correspond to three secondary indicators respectively. The secondary indicators corresponding to the cost index are coal cost, operation and maintenance and depreciation costs, and environmental protection equipment operation costs; the secondary indicators corresponding to the environmental benefit index are nitrogen oxide emissions, sulfur oxide emissions and carbon dioxide emissions; the secondary indicators corresponding to the safety and stability index are combustion stability, equipment corrosion and equipment thermal stress.

[0006] Optionally, the use of the best-worst method to determine the weight of each indicator among the cost indicator, the environmental benefit indicator and the safety and stability indicator includes: obtaining a first comparison vector and a second comparison vector, the first comparison vector is determined based on the best indicator, the second comparison vector is determined based on the worst indicator, the best indicator and the worst indicator are indicators among the 9 secondary indicators; establishing a planning problem based on the first comparison vector, the second comparison vector and a weight vector, and using a genetic algorithm to solve the planning problem to obtain the weight vector, wherein the weight vector is used to indicate the weight of each secondary indicator among the 9 secondary indicators.

[0007] Optionally, the first comparison vector is expressed by the following formula:

[0008] in, is the first comparison vector, are the 9 dimensions in the first comparison vector, indicating the importance of the optimal indicator compared with the 9 secondary indicators respectively; The second comparison vector is expressed by the following formula:

[0009] in, is the second comparison vector, are 9 dimensions in the second comparison vector, indicating the importance of the worst indicator compared with the 9 secondary indicators respectively; The planning problem is expressed as follows:

[0010] Among them, k is the consistency index value, is the weight of the optimal indicator, is the weight of the worst indicator, is the weight of the j-th secondary indicator, is the j-th dimension of the first comparison vector, is the j-th dimension of the second comparison vector, where j is an integer and the value range of j is 1 to 9.

[0011] Optionally, the first indicator corresponds to multiple indicator ranges, any of the indicator ranges corresponds to a score range, the first indicator is any of the secondary indicators, and the obtaining of the score of each of the cost indicator, the environmental benefit indicator, and the safety and stability indicator includes: using the following formula to determine the score of the first indicator:

[0012] in, is the score of the first indicator, is the value of the first indicator, , is the i-th indicator range corresponding to the first indicator, , is the score range corresponding to the i-th indicator range.

[0013] Optionally, optimizing the first operating plan based on the score of the first operating plan includes: obtaining scores of other operating plans under the first load in historical data; and in the case that a second operating plan exists, optimizing the first operating plan according to the scores of each secondary indicator in the second operating plan, the second operating plan being an operating plan with the load being the first load in the historical data, and the score of the second operating plan being greater than that of the first operating plan.

[0014] In the second aspect, a coal-fired unit peak-shaving optimization device is also provided, including: a first acquisition module, used to obtain a first operating plan under a first load during the peak-shaving process of the coal-fired unit; a second acquisition module, used to obtain the cost index, environmental benefit index and safety and stability index of the first operating plan; a weight determination module, used to determine the weight of each of the cost index, the environmental benefit index and the safety and stability index by using the best and worst method; a third acquisition module, used to obtain the score of each of the cost index, the environmental benefit index and the safety and stability index; a weighted summation module, used to perform weighted summation on the score of each indicator based on the weight of each indicator to obtain the score of the first operating plan; an optimization module, used to optimize the first operating plan based on the score of the first operating plan.

[0015] Optionally, in the second acquisition module, the cost indicator, the environmental benefit indicator and the safety and stability indicator correspond to three secondary indicators respectively. The secondary indicators corresponding to the cost indicator are coal cost, operation and maintenance and depreciation costs, and environmental protection equipment operation costs; the secondary indicators corresponding to the environmental benefit indicator are nitrogen oxide emissions, sulfur oxide emissions and carbon dioxide emissions; the secondary indicators corresponding to the safety and stability index are combustion stability, equipment corrosion and equipment thermal stress.

[0016] Optionally, the weight determination module is also used to obtain a first comparison vector and a second comparison vector, the first comparison vector is determined based on an optimal indicator, and the second comparison vector is determined based on a worst indicator, the optimal indicator and the worst indicator are indicators among the 9 secondary indicators; a planning problem is established based on the first comparison vector, the second comparison vector and a weight vector, and a genetic algorithm is used to solve the planning problem to obtain the weight vector, and the weight vector is used to indicate the weight of each secondary indicator among the 9 secondary indicators.

[0017] Optionally, in the weight determination module, the first comparison vector is expressed by the following formula:

[0018] in, is the first comparison vector, are the 9 dimensions in the first comparison vector, indicating the importance of the optimal indicator compared with the 9 secondary indicators respectively; The second comparison vector is expressed by the following formula:

[0019] in, is the second comparison vector, are 9 dimensions in the second comparison vector, indicating the importance of the worst indicator compared with the 9 secondary indicators respectively; The planning problem is expressed as follows:

[0020] Among them, k is the consistency index value, is the weight of the optimal indicator, is the weight of the worst indicator, is the weight of the j-th secondary indicator, is the j-th dimension of the first comparison vector, is the j-th dimension of the second comparison vector, where j is an integer and the value range of j is 1 to 9.

[0021] Optionally, the first indicator corresponds to multiple indicator ranges, any of the indicator ranges corresponds to a score range, the first indicator is any of the secondary indicators, and the third acquisition module is further used to determine the score of the first indicator using the following formula:

[0022] in, is the score of the first indicator, is the value of the first indicator, , is the i-th indicator range corresponding to the first indicator, , is the score range corresponding to the i-th indicator range.

[0023] Optionally, the optimization module is also used to obtain scores of other operating plans under the first load in historical data; when there is a second operating plan, the first operating plan is optimized according to the scores of each secondary indicator in the second operating plan, and the second operating plan is an operating plan with the load being the first load in the historical data, and the score of the second operating plan is greater than that of the first operating plan.

[0024] In a third aspect, a computer device is also provided, comprising: a memory and a processor, wherein at least one computer program is stored in the memory, and the at least one computer program is loaded and executed by the processor, thereby executing the coal-fired unit peak-shaving optimization method described in the above embodiment.

[0025] In a fourth aspect, a computer-readable storage medium is also provided, in which at least one computer program is stored. The at least one computer program is loaded and executed by a processor to execute the coal-fired unit peak-shaving optimization method described in the above embodiment.

[0026] In a fifth aspect, a computer program product is provided, comprising a computer program / instruction, wherein when the computer program / instruction is executed by a processor, the method described in the first aspect is implemented.

[0027] The beneficial effects brought by the technical solution provided by the embodiments of the present disclosure include at least: In the disclosed embodiment, the cost index, environmental benefit index and safety and stability index of the first operation plan are determined by adopting the best and worst method, which can reduce the amount of data to be processed in the process of determining the weight of each index, and also reduce the possibility of errors caused by confusion due to too many comparisons when experts score. The score of the first operation plan is obtained by weighted summing of the scores of each indicator, and the first operation plan is optimized based on the score of the first operation plan, which can achieve systematic and comprehensive optimization of the peak-shaving plan of coal-fired units in terms of environment, cost and safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0029] Figure 1 A flow chart of a coal-fired unit peak load optimization method provided by an exemplary embodiment of the present disclosure is shown; Figure 2 A flow chart of a coal-fired unit peak load optimization method provided by another exemplary embodiment of the present disclosure is shown; Figure 3 It is a schematic diagram of the secondary indicators; Figure 4 A schematic structural diagram of a peak load optimization device for a coal-fired unit provided by an exemplary embodiment of the present disclosure is shown; Figure 5 It is a schematic diagram of the structure of a computer device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0030] Unless otherwise defined, the technical or scientific terms used herein shall have the usual meanings understood by persons of ordinary skill in the field to which the present disclosure belongs. The words "first", "second", "third" and similar words used in the patent application specification and claims of the present disclosure do not indicate any order, quantity or importance, but are only used to distinguish different components. Similarly, words such as "one" or "one" do not indicate a quantitative limitation, but rather indicate the presence of at least one. Words such as "include" or "comprise" and similar words mean that the elements or objects appearing before "include" or "comprises" cover the elements or objects listed after "include" or "comprises" and their equivalents, and do not exclude other elements or objects.

[0031] In order to make the objectives, technical solutions and advantages of the present disclosure more clear, the embodiments of the present disclosure will be further described in detail below with reference to the accompanying drawings.

[0032] Figure 1 A flowchart of a method for optimizing peak load regulation of a coal-fired unit provided by an exemplary embodiment of the present disclosure is shown. The method can be executed by a computer device. Figure 1 , the method comprising: In step 101, a first operation plan under a first load during a peak load regulation process of a coal-fired unit is obtained.

[0033] Exemplarily, the first load may be the real-time load of the coal-fired unit, and the first operation plan is the current operation plan of the coal-fired unit for peak load regulation under the first load. The first operation plan includes but is not limited to the operation parameters of each device in the coal-fired unit under the first load and the quality of the coal, etc. It is necessary to evaluate the pros and cons of the first operation plan and optimize the first operation plan to achieve peak load regulation optimization of the coal-fired unit.

[0034] In step 102, the cost index, environmental benefit index and safety and stability index of the first operation scheme are obtained.

[0035] In step 103, the best-worst method is used to determine the weight of each indicator among the cost indicator, the environmental benefit indicator and the safety and stability indicator.

[0036] The Best-Worst Method (BWM) is a multi-criteria decision-making method. Compared with the traditional analytic hierarchy process, the Best-Worst Method greatly reduces the number of comparisons between indicators. There are many related technologies for the implementation of the Best-Worst Method, which will not be described in detail here.

[0037] In step 104, the score of each of the cost index, environmental benefit index and safety and stability index is obtained.

[0038] In step 105, based on the weight of each indicator, the score of each indicator is weighted and summed to obtain the score of the first operation plan.

[0039] In step 106 , the first operation plan is optimized based on the score of the first operation plan.

[0040] In the disclosed embodiment, the cost index, environmental benefit index and safety and stability index of the first operation plan are determined by adopting the best and worst method, which can reduce the amount of data to be processed in the process of determining the weight of each index, and also reduce the possibility of errors caused by confusion due to too many comparisons when experts score. The score of the first operation plan is obtained by weighted summing of the scores of each indicator, and the first operation plan is optimized based on the score of the first operation plan, which can achieve systematic and comprehensive optimization of the peak-shaving plan of coal-fired units in terms of environment, cost and safety.

[0041] Figure 2 A flow chart of a method for optimizing peak load regulation of a coal-fired unit provided by another exemplary embodiment of the present disclosure is shown, and the method can be executed by a computer device. Figure 2 , the method comprising: In step 201, a first operation plan at a first load during a peak load regulation process of a coal-fired unit is obtained.

[0042] For the relevant contents of the first load and the first operation plan, please refer to the aforementioned step 101, and the detailed description is omitted here.

[0043] In step 202, the cost index, environmental benefit index and safety and stability index of the first operation scheme are obtained.

[0044] Optionally, the cost index, environmental benefit index and safety and stability index correspond to three secondary indicators respectively, that is, a total of 9 secondary indicators are included. Figure 3 This is a schematic diagram of the secondary indicators. Figure 3 The nine secondary indicators are explained.

[0045] The secondary indicators corresponding to the cost indicators are: coal cost, operation and maintenance and depreciation expenses, and environmental protection equipment operating costs.

[0046] Optionally, the coal cost is calculated using formula (1).

[0047] (1) In formula (1), The cost of coal burning, is the price of coal used in coal-fired units, Unit coal consumption of coal-fired units at the first load, is the power of the coal-fired unit, It is the annual utilization hours of coal-fired units.

[0048] Optionally, a DCS (Distributed Control System) system of the coal-fired unit, online coal quality monitoring and pulverized coal flexible storage and supply equipment coupled with the DCS system, and a small pulverized coal silo in the coal-fired unit are used to obtain real-time coal quality and coal consumption.

[0049] Optionally, operation and maintenance and depreciation costs are calculated using formula (2).

[0050] (2) In formula (2), For operation and maintenance and depreciation expenses, is the total investment cost of coal-fired units, is the operation and maintenance factor, is the residual value rate, The depreciation period.

[0051] The operation and maintenance coefficient is an empirical value and can be set according to experience. There are many methods for determining the residual value rate and the depreciation period in the relevant technology, and the detailed description is omitted here.

[0052] Optionally, the operating cost of the environmental protection equipment includes the operating cost of the desulfurization equipment and the operating cost of the denitrification equipment.

[0053] The operating cost of the desulfurization equipment is calculated using formula (3).

[0054] (3) In formula (3), The operating cost of the desulfurization equipment is For the price of limestone, is the mass fraction of sulfur in the coal of the coal-fired unit, is the coal consumption of coal-fired units for power generation, It represents the ratio of the molecular weight of calcium carbonate and sulfur. is the calcium-sulfur ratio, is the purity of limestone. The meanings of other parameters in formula (3) are the same as those in formula (1), and detailed description is omitted here.

[0055] Taking the denitration equipment as an SCR (Selective Catalytic Reduction) denitration device as an example, the operating cost of the denitration equipment is calculated using formula (4).

[0056] (4) In formula (4), The operating cost of the denitrification equipment is It is the molar ratio of ammonia (NH3) and nitrogen oxides (NOx), generally 0.8-1.2. is the mass of NOx removed from unit volume of flue gas (in terms of NO), is the flow rate of flue gas at the SCR inlet, 17 and 30 are the molecular weights of NH3 and NO, respectively. is the proportion of NO in NOx.

[0057] In this case, the operating cost of environmental protection equipment is calculated using formula (5).

[0058] (5) In formula (5), is the operating cost of the environmental protection equipment. The meanings of other parameters in formula (5) are the same as those in formula (3) and formula (4), and their detailed description is omitted here.

[0059] The secondary indicators corresponding to the environmental benefit indicators are nitrogen oxide emissions, sulfur oxide emissions and carbon dioxide emissions.

[0060] Optionally, nitrogen oxides (NO x ) emissions, sulfur oxygen (SO x ) emissions and carbon dioxide (CO2) emissions are obtained through the smoke exhaust end measurement points of the power plant in the coal-fired unit. For example, smoke exhaust monitoring equipment for monitoring nitrogen oxides, sulfur oxides, and carbon dioxide can be installed at the smoke exhaust end of the power plant in the coal-fired unit, and the nitrogen oxide emissions, sulfur oxide emissions, and carbon dioxide emissions can be obtained through the smoke exhaust monitoring equipment.

[0061] The secondary indicators corresponding to the safety and stability indicators are combustion stability, equipment corrosion and equipment thermal stress.

[0062] Optionally, the combustion stability is calculated using formula (6).

[0063] (6) In formula (6), For combustion stability, is the combustion flicker frequency component, calculated using formula (7); is the combustion intensity component, which is calculated using formula (8).

[0064] (7) In formula (7), is the measured combustion flicker frequency, is the lower limit of the combustion flicker frequency, is the standard value of the combustion flicker frequency, and the meanings of other parameters in formula (7) are the same as those in formula (6), and detailed description is omitted here. Among them, the lower limit value of the combustion flicker frequency and the standard value of the combustion flicker frequency are set according to experience, and the embodiment of the present disclosure does not limit this.

[0065] (8) In formula (8), is the measured burning intensity, is the lower limit of combustion intensity, is the standard value of the combustion intensity, and the meanings of other parameters in formula (8) are the same as those in formula (6), and detailed description is omitted here. Among them, the lower limit value of the combustion intensity and the standard value of the combustion intensity are set according to experience, and the embodiments of the present disclosure do not limit this.

[0066] For example, the measured combustion flicker frequency and the measured combustion intensity may be obtained through a DCS system and flame detection equipment of the coal-fired unit.

[0067] Optionally, the equipment corrosion condition is determined based on the concentration of hydrogen sulfide (H2S) in the combustion zone of the coal-fired unit boiler. In implementation, a first correspondence between the hydrogen sulfide concentration in the combustion zone of the boiler and the equipment corrosion condition can be established through testing, and the first correspondence can be stored in a memory. Subsequently, it is only necessary to measure the real-time hydrogen sulfide concentration in the combustion zone of the boiler to determine the equipment corrosion condition corresponding to the real-time hydrogen sulfide concentration based on the first correspondence. The real-time hydrogen sulfide concentration can be obtained through the gas monitoring equipment in the boiler. Optionally, the thermal stress of the equipment is determined based on the temperature data obtained from the measuring points in the boiler of the coal-fired unit. For example, a boiler model can be established in advance and the stress analysis calculation software can be combined in the boiler model. In this way, after the temperature data obtained from the measuring points in the boiler is input into the boiler model, the stress analysis software can output the current thermal stress of the equipment. The temperature data can be obtained through the temperature measuring point equipment in the boiler.

[0068] In step 203, the best-worst method is used to determine the weight of each indicator among the cost indicator, the environmental benefit indicator and the safety and stability indicator.

[0069] Optionally, step 203 includes the following steps ab: Step a: obtaining a first comparison vector and a second comparison vector.

[0070] The first comparison vector is determined based on the best indicator (Best to other, BO), and the second comparison vector is determined based on the worst indicator (Others to worst, OW). The best indicator and the worst indicator are indicators among the 9 secondary indicators.

[0071] Optionally, the first comparison vector is expressed by formula (9): (9) In formula (9), is the first comparison vector, are the 9 dimensions in the first comparison vector, indicating the importance of the optimal index compared with the 9 secondary indicators.

[0072] Here, importance is a score from 1 to 9. In formula (9), if a secondary indicator scores 1, it means that the secondary indicator is equally important as the optimal indicator. If a secondary indicator scores 9, it means that the secondary indicator is the most important as compared with the optimal indicator. Obviously, when the secondary indicator is the optimal indicator, the importance of the secondary indicator is 1 (that is, the optimal indicator is equally important when compared with itself).

[0073] Optionally, the second comparison vector is expressed by formula (10): (10) In formula (10), is the second comparison vector, are the 9 dimensions in the second comparison vector, indicating the importance of the worst indicator compared with the 9 secondary indicators.

[0074] In formula (10), importance is also a score from 1 to 9. If a secondary indicator scores 1, it means that the secondary indicator is equally unimportant compared to the worst indicator. If a secondary indicator scores 9, it means that the secondary indicator is the least important compared to the best indicator. Obviously, when the secondary indicator is the worst indicator, the importance of the secondary indicator is 1 (that is, the worst indicator is equally unimportant when compared to itself).

[0075] Among them, the best index, the worst index, the first comparison vector and the second comparison vector are all obtained through expert scoring and are pre-set. The embodiment of the present disclosure does not limit the selection of the best index, the worst index, the first comparison vector and the second comparison vector.

[0076] Step b: establishing a planning problem based on the first comparison vector, the second comparison vector and the weight vector, and solving the planning problem using a genetic algorithm to obtain the weight vector.

[0077] The weight vector is used to indicate the weight of each of the 9 secondary indicators.

[0078] Exemplarily, the planning problem is formulated as follows:

[0079] (11) In formula (11), k is the consistency index value, is the weight of the optimal indicator, is the weight of the worst indicator, is the weight of the j-th secondary indicator, is the j-th dimension of the first comparison vector, is the jth dimension of the second comparison vector, j is an integer and the value range of j is 1 to 9. Here, is a variable, and the planning problem needs to be solved to find the optimal The final weights of the 9 secondary indicators are determined by the combination of

[0080] In the planning problem shown in formula (11), the objective function is , that is, the consistency index value is the smallest, and the constraint condition is , it can be seen There are 4 items in total, which means there are multiple constraints.

[0081] In the case of an objective function and multiple constraints, a genetic algorithm can be used to solve the planning problem. There are many related technologies for implementing the genetic algorithm to solve the planning problem in the best-worst method, which will be omitted here.

[0082] Finally, the weight of each secondary index under the condition of minimum consistency index value can be solved, that is, 9 weights, which can be expressed as a weight vector. For example, the weight vector is expressed by formula (12).

[0083] (12) In formula (12), is the weight vector, are the 9 dimensions of the weight vector, representing the weights of the 9 secondary indicators respectively.

[0084] In determining When calculating the weight of an indicator, the conventional hierarchical analysis method needs to obtain In the best-worst method, only the best index and the worst index need to be compared with Compare with other indicators and get Therefore, the best-worst method greatly reduces the amount of data that needs to be processed (number of comparisons), and also reduces the possibility of errors caused by confusion due to too many comparisons when experts score.

[0085] In step 204, the score of each of the cost index, environmental benefit index and safety and stability index is obtained.

[0086] Since the cost index, environmental benefit index and safety and stability index correspond to three secondary indicators respectively, that is, there are a total of nine secondary indicators, a total of nine secondary indicators need to be scored in step 204 .

[0087] Optionally, the first indicator corresponds to multiple indicator ranges, and any indicator range corresponds to a score range. The first indicator is any secondary indicator among the 9 secondary indicators.

[0088] The indicator range corresponding to a certain secondary indicator is determined according to the value range of the secondary indicator. The value range can be obtained through the historical best data and the historical worst data of the secondary indicator in the DCS system of the coal-fired unit, or the ideal value can be set artificially to avoid the situation where the actual measured value exceeds the scoring range. For example, if the value range of a certain secondary indicator is [A, B], that is, the value of the secondary indicator must be in [A, B], then the value range can be divided into multiple sub-value ranges of equal length (for example, each k% can be used as a sub-value range, k is an integer), and these sub-value ranges are the multiple indicator ranges corresponding to the secondary indicator.

[0089] The score range corresponding to any indicator range of the secondary indicator can also be determined according to the value range of the secondary indicator. For example, if the optional score range of the secondary indicator is [C, D], the optional score range can be divided proportionally according to the division ratio of the indicator range in the value range, so as to obtain multiple score ranges and any indicator range corresponds to one score range.

[0090] Here, the optional score range is usually a fixed value, and the optional score range of each secondary indicator is the same. When the score of the indicator is a ten-point system, the optional score range is [0, 10], and when the score of the indicator is a hundred-point system, the optional score range is [0, 100]. The optional score range (that is, the scoring system) can be set according to demand, and the embodiments of the present disclosure do not limit this.

[0091] In this case, the score of the first indicator can be determined by linear interpolation method, which can be expressed by formula (13).

[0092] (13) in, is the score of the first indicator, is the value of the first indicator, , is the i-th indicator range corresponding to the first indicator, , is the score range corresponding to the i-th indicator range. i is an integer, i is greater than 0 and i is less than or equal to the number of indicator ranges corresponding to the first indicator.

[0093] For the other 8 secondary indicators among the 9 secondary indicators except the first indicator, the scores can also be obtained in the manner of step 204, so that the score of each secondary indicator can be obtained.

[0094] In step 205, based on the weight of each indicator, the score of each indicator is weighted and summed to obtain the score of the first operation plan.

[0095] After obtaining the weight of each indicator and the score of each indicator, the scores of the nine secondary indicators can be weighted and summed according to the weights, thereby obtaining the score of the first operation plan.

[0096] In step 206 , the first operation plan is optimized based on the score of the first operation plan.

[0097] Optionally, step 206 includes the following steps cd.

[0098] Step c, obtaining scores of other operation schemes under the first load in historical data; In the embodiment of the present disclosure, the historical data includes multiple operation schemes under multiple loads, and any load corresponds to multiple operation schemes. For any operation scheme under any load, the method in steps 201-205 can be used to obtain the score of the operation scheme, and the score of each operation scheme can be pre-stored in the memory.

[0099] Step d: if there is a second operation plan, optimize the first operation plan according to the scores of each secondary indicator in the second operation plan.

[0100] The second operation plan is an operation plan in which the load in the historical data is the first load, and the score of the second operation plan is greater than that of the first operation plan.

[0101] After querying the historical data, the scores of multiple operation plans under the first load in the historical data can be obtained, and the scores of multiple operation plans under the first load in the historical data are compared with the score of the first operation plan. If there is an operation plan with a higher score than the first operation plan in the historical data, it means that the first operation plan needs to be optimized. At this time, the second operation plan can be determined and step d is executed. If the score of each operation plan in the historical data is lower than the score of the first operation plan, it means that the first operation plan does not need to be optimized, and the current step is exited.

[0102] When there is an operation scenario having a higher score than the first operation scenario in the historical data, the operation scenario having the highest score among the plurality of operation scenarios of the first load in the historical data is set as the second operation scenario.

[0103] In this case, step d includes: comparing the scores of each secondary indicator in the first operating plan and the second operating plan to obtain at least one second indicator; adjusting the operating parameters in the coal-fired unit according to the at least one second indicator to improve the score of the second indicator in the first operating plan.

[0104] Among them, the score of the second indicator in the second operation plan is higher than the score of the second indicator in the first operation plan.

[0105] The operating parameters in the coal-fired unit include but are not limited to steam pressure, main steam temperature, excess air coefficient, exhaust pressure of each cylinder and other parameters that can affect the scores of each secondary indicator.

[0106] Exemplarily, a machine learning method can be used to obtain a first correspondence between the operating parameters in the coal-fired unit and the scores of each secondary indicator, and the first correspondence is stored in a memory. The first correspondence is used to indicate the influence of the operating parameters in the coal-fired unit on the scores of each secondary indicator, for example, including which operating parameters can be adjusted to improve the score of a certain secondary indicator. In this way, through the first correspondence and the second indicator, it can be determined which operating parameters need to be adjusted to improve the score of the second indicator in the first operation plan, thereby optimizing the first operation plan.

[0107] The following are device embodiments of the present application. For details not described in detail in the device embodiments, reference may be made to the above method embodiments.

[0108] Figure 4 A schematic diagram of a peak load optimization device for a coal-fired unit provided by an exemplary embodiment of the present disclosure is shown. Figure 4 The coal-fired unit peak-shaving optimization device 400 includes: a first acquisition module 401, a second acquisition module 402, a weight determination module 403, a third acquisition module 404, a weighted summation module 405 and an optimization module 406.

[0109] The first acquisition module 401 is used to acquire a first operation plan under a first load during the peak load regulation process of the coal-fired unit.

[0110] The second acquisition module 402 is used to acquire the cost index, environmental benefit index and safety and stability index of the first operation plan.

[0111] The weight determination module 403 is used to determine the weight of each indicator among the cost indicator, the environmental benefit indicator and the safety and stability indicator by adopting the best and worst method.

[0112] The third acquisition module 404 is used to obtain the score of each indicator among the cost indicator, the environmental benefit indicator and the safety and stability indicator.

[0113] The weighted sum module 405 is used to perform weighted summation on the score of each indicator based on the weight of each indicator to obtain the score of the first operation plan.

[0114] The optimization module 406 is used to optimize the first operation plan based on the score of the first operation plan.

[0115] Optionally, in the second acquisition module 402, the cost index, environmental benefit index and safety and stability index correspond to three secondary indicators respectively. The secondary indicators corresponding to the cost index are coal cost, operation and maintenance and depreciation costs, and environmental protection equipment operation costs; the secondary indicators corresponding to the environmental benefit index are nitrogen oxide emissions, sulfur oxide emissions and carbon dioxide emissions; the secondary indicators corresponding to the safety and stability index are combustion stability, equipment corrosion and equipment thermal stress.

[0116] Optionally, the weight determination module 403 is also used to obtain a first comparison vector and a second comparison vector, the first comparison vector is determined based on an optimal indicator, and the second comparison vector is determined based on a worst indicator, the best indicator and the worst indicator are indicators among the 9 secondary indicators; a planning problem is established based on the first comparison vector, the second comparison vector and the weight vector, and a genetic algorithm is used to solve the planning problem to obtain a weight vector, which is used to indicate the weight of each of the 9 secondary indicators.

[0117] Optionally, in the weight determination module 403, the first comparison vector is expressed by the following formula:

[0118] in, is the first comparison vector, are the 9 dimensions in the first comparison vector, indicating the importance of the optimal index compared with the 9 secondary indicators respectively; The second comparison vector is expressed by the following formula:

[0119] in, is the second comparison vector, are the 9 dimensions in the second comparison vector, indicating the importance of the worst indicator compared with the 9 secondary indicators; The planning problem is expressed as follows:

[0120] Among them, k is the consistency index value, is the weight of the optimal indicator, is the weight of the worst indicator, is the weight of the j-th secondary indicator, is the j-th dimension of the first comparison vector, is the j-th dimension of the second comparison vector, j is an integer and the value range of j is 1 to 9.

[0121] Optionally, the first indicator corresponds to multiple indicator ranges, any indicator range corresponds to a score range, the first indicator is any secondary indicator, and the third acquisition module 404 is further used to use the following formula to determine the score of the first indicator:

[0122] in, is the score of the first indicator, is the value of the first indicator, , is the i-th indicator range corresponding to the first indicator, , is the score range corresponding to the i-th indicator range.

[0123] Optionally, the optimization module 406 is also used to obtain the scores of other operating plans under the first load in the historical data; when there is a second operating plan, the first operating plan is optimized according to the scores of each secondary indicator in the second operating plan, and the second operating plan is an operating plan with the load being the first load in the historical data, and the score of the second operating plan is greater than that of the first operating plan.

[0124] It should be noted that: when the peak-shaving optimization device for coal-fired units provided in the above embodiment optimizes the peak-shaving scheme of coal-fired units, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the peak-shaving optimization device for coal-fired units provided in the above embodiment and the peak-shaving optimization method embodiment of coal-fired units belong to the same concept. The specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0125] The division of modules in the embodiments of the present disclosure is schematic and is only a logical function division. There may be other division methods in actual implementation. In addition, each functional module in each embodiment of the present disclosure may be integrated into a processor, or may exist physically separately, or two or more modules may be integrated into one module. The above-mentioned integrated modules may be implemented in the form of hardware or in the form of software functional modules.

[0126] If the integrated module is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present disclosure is essentially 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. The computer software product is stored in a storage medium, including several instructions to enable a terminal device (which can be a personal computer, mobile phone, or communication device, etc.) or a processor (processor) to execute all or part of the steps of the method of each embodiment of the present disclosure. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc., various media that can store program codes.

[0127] Figure 5 Schematic diagram of the structure of the computer device provided by the embodiment of the present disclosure. Figure 5 As shown, the computer device 500 includes: a processor 501 and a memory 502 .

[0128] The processor 501 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 501 may be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). The processor 501 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the awake state, also known as a CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in the standby state. In some embodiments, the processor 501 may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 501 may also include an AI (Artificial Intelligence) processor, which is used to process computing operations related to machine learning.

[0129] The memory 502 may include one or more computer-readable storage media, which may be non-transitory. The memory 502 may also include a high-speed random access memory, and a non-volatile memory, such as one or more disk storage devices, flash memory storage devices. In some embodiments, the non-transitory computer-readable storage medium in the memory 502 is used to store at least one instruction, which is used to be executed by the processor 501 to implement the coal-fired unit peak-shaving optimization method provided in the embodiment of the present disclosure.

[0130] Those skilled in the art will understand that Figure 5 The structure shown in the figure does not constitute a limitation on the computer device 500, and the computer device 500 may include more or less components than those shown in the figure, or combine some components, or adopt a different arrangement of components.

[0131] The embodiment of the present disclosure also provides a non-temporary computer-readable storage medium. When the instructions in the storage medium are executed by the processor of a computer device, the computer device is enabled to execute the coal-fired unit peak-shaving optimization method provided in the embodiment of the present disclosure.

[0132] The embodiments of the present disclosure also provide a computer program product, including a computer program / instruction, which, when executed by a processor, implements the coal-fired unit peak-shaving optimization method provided in the embodiments of the present disclosure.

[0133] The above description is only an optional embodiment of the present disclosure and is not intended to limit the present disclosure. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A method for optimizing peak load of coal-fired units, characterized in that: The method comprises: Obtaining a first operation plan at a first load during the peak load regulation process of the coal-fired unit; Obtaining cost indicators, environmental benefit indicators, and safety and stability indicators of the first operation plan; The weight of each of the cost index, the environmental benefit index and the safety and stability index is determined by using the best and worst method; Obtaining a score for each of the cost index, the environmental benefit index, and the safety and stability index; Based on the weight of each indicator, weighted sum is performed on the score of each indicator to obtain the score of the first operation plan; The first operation plan is optimized based on the score of the first operation plan.

2. The method according to claim 1, characterized in that The cost index, the environmental benefit index and the safety and stability index correspond to three secondary indicators respectively. The secondary indicators corresponding to the cost indicators are coal cost, operation and maintenance and depreciation costs, and environmental protection equipment operating costs; The secondary indicators corresponding to the environmental benefit indicators are nitrogen oxide emissions, sulfur oxide emissions and carbon dioxide emissions; The secondary indicators corresponding to the safety and stability indicators are combustion stability, equipment corrosion and equipment thermal stress.

3. The method according to claim 2, characterized in that The method of using the best and worst method to determine the weight of each of the cost index, the environmental benefit index and the safety and stability index includes: Obtain a first comparison vector and a second comparison vector, wherein the first comparison vector is determined based on an optimal indicator, and the second comparison vector is determined based on a worst indicator, and the optimal indicator and the worst indicator are indicators among the 9 secondary indicators; A planning problem is established based on the first comparison vector, the second comparison vector and the weight vector, and a genetic algorithm is used to solve the planning problem to obtain the weight vector, which is used to indicate the weight of each secondary indicator among the 9 secondary indicators.

4. The method according to claim 3, characterized in that The first comparison vector is expressed by the following formula: in, is the first comparison vector, are the 9 dimensions in the first comparison vector, indicating the importance of the optimal indicator compared with the 9 secondary indicators respectively; The second comparison vector is expressed by the following formula: in, is the second comparison vector, are 9 dimensions in the second comparison vector, indicating the importance of the worst indicator compared with the 9 secondary indicators respectively; The planning problem is expressed as follows: Among them, k is the consistency index value, is the weight of the optimal indicator, is the weight of the worst indicator, is the weight of the j-th secondary indicator, is the j-th dimension of the first comparison vector, is the j-th dimension of the second comparison vector, where j is an integer and the value range of j is 1 to 9.

5. The method according to any one of claims 2 to 4, characterized in that: The first indicator corresponds to multiple indicator ranges, any of the indicator ranges corresponds to a score range, and the first indicator is any of the secondary indicators. The obtaining of the score of each of the cost index, the environmental benefit index and the safety and stability index comprises: The following formula is used to determine the score of the first indicator: in, is the score of the first indicator, is the value of the first indicator, , is the i-th indicator range corresponding to the first indicator, , is the score range corresponding to the i-th indicator range.

6. The method according to any one of claims 2 to 4, characterized in that: The step of optimizing the first operation scheme based on the score of the first operation scheme includes: Obtaining scores of other operation schemes under the first load in historical data; When there is a second operating plan, the first operating plan is optimized according to the scores of each secondary indicator in the second operating plan, the second operating plan is an operating plan in which the load in the historical data is the first load, and the score of the second operating plan is greater than that of the first operating plan.

7. A coal-fired unit peak load optimization device, characterized in that: The device comprises: A first acquisition module is used to acquire a first operation plan under a first load during a peak load regulation process of a coal-fired unit; A second acquisition module is used to acquire a cost index, an environmental benefit index, and a safety and stability index of the first operation plan; A weight determination module, used to determine the weight of each of the cost index, the environmental benefit index and the safety and stability index by adopting the best and worst method; A third acquisition module is used to obtain the score of each of the cost index, the environmental benefit index and the safety and stability index; A weighted summation module, configured to perform weighted summation on the score of each indicator based on the weight of each indicator to obtain a score of the first operation scheme; An optimization module is used to optimize the first operation plan based on the score of the first operation plan.

8. A computer device, characterized in that: The computer device comprises: a memory and a processor, wherein at least one computer program is stored in the memory, and the at least one computer program is loaded and executed by the processor to implement the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores at least one computer program, and the at least one computer program is loaded and executed by a processor to implement the method according to any one of claims 1 to 6.

10. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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