Dynamic adjustment method for coal supply strategy of thermal power generating unit

Abstract

The invention relates to the technical field of coal feeding strategy adjustment, and discloses a thermal power generating unit coal supply strategy dynamic adjustment method, which comprises the following steps: dividing coal types based on historical data stored in a coal yard to generate coal types of multiple grades; the coal type storage condition of each grade in the current coal yard is obtained, and the content value of the coal type of each grade is generated; generating a heat supply efficiency prediction curve based on the production plan of the current coal yard; and setting a coal feeding period and a coal type combination scheme in combination with the heat supply efficiency prediction curve. According to the method, coal type grades are divided according to an evaluation value set of coal types, and a coal type reference scheme set is generated by combining the coal type storage condition of each grade in a coal yard. In this way, the using sequence of different grades of coal types can be determined, the coal types which meet the heat supply requirement and have relatively sufficient reserves in the coal yard are preferentially used, and the overall utilization rate of coal yard resources is increased.

Description

Technical Field

[0001] The present invention relates to the technical field of coal feeding strategy adjustment, and particularly to a method for dynamically adjusting the coal feeding strategy of a thermal power unit. Background Art

[0002] The coal yard stores various types of coal. By dividing the coal types based on the historical data of the coal yard storage to generate multiple grades of coal types, the coal yard resources can be better managed. By understanding the storage situation of each grade of coal type and generating its content value, accurate inventory information basis can be provided for the coal feeding strategy.

[0003] Traditional coal yard management methods may not be able to effectively integrate the relationship between coal type characteristics, coal yard inventory and heating demand, lacking a systematic and dynamic method for adjusting the coal feeding strategy, and unable to achieve the optimal allocation of resources and the efficient operation of the heating process. Summary of the Invention

[0004] The purpose of the present invention is to continuously adjust the coal feeding strategy according to the heating prediction curve and the changes in the coal type status information (such as coal quality, supply, equipment adaptation, etc.), which can improve the overall operation efficiency of the heating system of the thermal power plant, reduce costs, and extend the service life of the equipment.

[0005] To achieve the above purpose, the present invention provides a method for dynamically adjusting the coal feeding strategy of a thermal power unit, including: Dividing coal types based on the historical data of the coal yard storage to generate multiple grades of coal types; Obtaining the storage situation of each grade of coal type in the current coal yard to generate the content value of each grade of coal type; Generating a heating efficiency prediction curve based on the production plan of the current coal yard; Setting the coal feeding cycle and the coal type combination plan in combination with the heating efficiency prediction curve.

[0006] In some embodiments of the present invention, when generating multiple grades of coal types, it further includes: Among them, generating multiple grades of coal types includes: Obtaining multiple types of coal based on the historical data of the coal yard storage; Obtaining the temperature increment of the boiler per unit mass when the current coal type is burned, and generating the calorific value of the current coal type based on the temperature increment of the boiler; Obtaining the calorific values of all types of coal to generate a set Q of coal type calorific values, Q = {q1, q2... qi... qn}; Wherein, qi is the calorific value of the i-th coal type, and n is the total amount of coal types; Obtaining the ashing time of each type of coal when burned to generate a set T of coal type ashing times, T = {t1, t2... ti... tn}; Among them, \(t_i\) is the ashing time of the \(i\)-th coal type, and \(n\) is the total number of coal types; Generate the evaluation value set \(P\) of coal types by combining the calorific value set \(Q\) of coal types and the ashing time set \(T\) of coal types, \(P = \{p_1, p_2 \cdots p_i \cdots p_n\}\); Among them, \(p_i\) is the evaluation value of the \(i\)-th coal type, and \(n\) is the total number of coal types; Divide the grade of coal types based on the evaluation value set \(P\) of coal types to generate the grade set \(D\) of coal types, \(D = \{d_1, d_2 \cdots d_j \cdots d_m\}\); Among them, \(d_j\) represents the average calorific value of the coal types of the \(j\)-th grade, \(m\) represents the total number of grades, and \(m < n\).

[0007] In some embodiments of the present invention, when generating the evaluation value set \(P\) of coal types, it includes: Obtain the evaluation value \(p_i\) of the \(i\)-th coal type; \(p_i = a_1\times(w_1\times q_i + w_2\times t_i)\); Among them, \(a_1\) is a fixed coefficient, \(w_1\) is the weight of the calorific value \(q_i\) of the \(i\)-th coal type, and \(w_2\) is the weight of the ashing time \(t_i\) of the \(i\)-th coal type; Obtain the evaluation values \(p_i\) of all types of coal types to generate the evaluation value set \(P\).

[0008] In some embodiments of the present invention, when generating the grade set \(D\) of coal types, it includes: Set the preset value of the evaluation value of coal types based on the evaluation value set \(P\) of coal types in the obtained historical data; Divide the evaluation value set \(P\) of coal types based on the preset value of the evaluation value of coal types to generate the grade set \(D\) of coal types, \(D = \{d_1, d_2 \cdots d_j \cdots d_m\}\).

[0009] In some embodiments of the present invention, when generating the heating efficiency prediction curve, it includes: Set the heating prediction period \(H\) of the current thermal power plant by combining historical data and the ashing time set \(T\) of coal types; Generate the heating prediction curve \(HQ\) based on the production plan of the current thermal power plant within the obtained heating prediction period \(H\); Segment the heating prediction curve \(HQ\) based on historical data to generate multiple sub-heating prediction curves \(\{hq_1, hq_2 \cdots hq\) z \(\cdots hq\) r \(\}\); Among them, \(hq\) z represents the \(z\)-th sub-heating prediction curve, and \(r\) represents the total number of generated sub-heating prediction curves.

[0010] In some embodiments of the present invention, when setting the coal feeding cycle and the coal type combination plan by combining the heating efficiency prediction curve, it includes: Obtain the current sub-heating prediction curve \(hq\) zThe corresponding heat supply prediction value Cd; Generate the coal type grade margin set DY of the current coal yard by combining the grade set D of the coal type and the storage situation of the coal yard; Obtain the status information of the coal type grade; Set the priority weight of the corresponding coal type grade by combining the status information of the coal type grade to generate the priority weight set Y of the coal type grade; Generate the coal type reference plan set K by combining the heat supply prediction value Cd, the coal type grade margin set DY and the priority weight set Y, K = {d1, d2…dx…dg}; Among them, dx represents the xth coal type reference plan, and g represents the total number of generated coal type reference plans; Based on the next sub-heat supply prediction curve hq (z+1) And select the current sub-heat supply prediction curve hq from the coal type reference plan set K z The corresponding coal type reference plan.

[0011] In some embodiments of the present invention, when generating the priority weight set Y of the coal type grade, it includes: Obtain the coal quality status information, supply status information and equipment adaptation status information of the current coal type; Based on historical data, set the weight factor F1 of the coal quality status information, the weight factor F2 of the supply status information and the weight factor F3 of the equipment adaptation status information respectively, and F1 + F2 + F3 = 1; Construct a priority weight model for the coal type grade by combining historical data:

[0012] Among them, Is the coefficient of the th coal quality status information, Is the th coal quality status information, Is the total number of coal quality status information, Is the coefficient of the th supply status information, Is the th supply status information, Is the total number of supply status information, Is the coefficient of the th equipment adaptation status information, Is the th equipment adaptation status information, Is the total number of equipment adaptation status information, Is the priority weight of the current coal type grade; Obtain the status information reference value of all coal type grades to generate the priority weight set Y of the coal type grade.

[0013] In some embodiments of the present invention, when generating the coal type reference plan set K, it includes: Based on the current sub-heating prediction curve hq z Obtain the corresponding heating prediction value Cd;

[0014] Wherein, is the proportionality coefficient of the j-th grade coal type, is the average heat production value of the j-th grade coal type, and A is the deviation value adjustment coefficient; Generate a primary coal type reference plan set based on the proportionality coefficient of each grade coal type; Sort the primary coal type reference plans based on the priority weight set Y to generate a secondary coal type reference plan set; Screen the primary coal type reference value plans based on the coal type grade margin set DY, and eliminate the secondary coal type reference plans that do not meet the coal type grade margin to generate the coal type reference plan set K.

[0015] In some embodiments of the present invention, when generating the secondary coal type reference plan set, it includes:

[0016] Wherein, is the priority evaluation value of the current primary coal type reference plan, is the priority weight of the j-th grade coal type; Obtain the priority evaluation values of all primary coal type reference plans, sort them from large to small, and generate a secondary coal type reference plan set.

[0017] In some embodiments of the present invention, when selecting the coal type reference plan corresponding to the current sub-heating prediction curve hq z it includes: Obtain the first secondary coal type reference plan k'1 in the secondary coal type reference plan set corresponding to the heating demand of the next sub-heating prediction curve hq (z+1) ; Obtain the first coal type reference plan corresponding to the heating demand of the next sub-heating prediction curve hq (z+1) to generate a comparison reference plan k'1; Calculate the similarity Ds between the comparison reference plan k'1 and all coal type reference plans in the current coal type reference plan set K in sequence; Ds = f * NS; NS is the number of the same coal type grades between the comparison reference plan k'1 and all coal type reference plans in the current coal type reference plan set K, and f is the first fixed coefficient; Select the coal type reference plan with the largest similarity Ds to generate the current sub-heating prediction curve hq zCorresponding coal type reference plan.

[0018] Compared with the prior art, the beneficial effects of a method for dynamically adjusting the coal supply strategy of a thermal power unit provided by an embodiment of the present invention are as follows: By comprehensively considering the calorific value and ashing time of coal types to generate an evaluation value set P, and then classifying the coal types. This method can more accurately classify coal types, making the distinction between different grades of coal types in terms of heating efficiency and impact on equipment clearer.

[0019] Taking into account the calorific value of coal types (reflecting heating capacity) and the ashing time (related to equipment maintenance and operation stability) helps to comprehensively evaluate the performance of coal types and avoid unreasonable coal feeding strategies caused by only focusing on a single factor.

[0020] By sorting the primary coal type reference plan based on the priority weight set Y to generate a secondary coal type reference plan set, the selection order of coal type combinations is further optimized, and coal type combinations that better meet various requirements (such as coal quality, supply, equipment adaptation, etc.) are preferentially selected.

[0021] When selecting the coal type reference plan corresponding to the current sub-heating prediction curve hq z By comparing the similarity between the next sub-heating prediction curve hq (z + 1) and the current coal type reference plan set K, the coal type selection can have better coherence and adaptability between different heating stages, which helps to avoid problems such as fluctuations in heating efficiency or unstable operation of equipment caused by too abrupt coal type switching.

[0022] By continuously adjusting the coal feeding strategy according to the changes in the heating prediction curve and coal type status information (such as coal quality, supply, equipment adaptation, etc.), the overall operating efficiency of the thermal power plant heating system can be improved, costs can be reduced, and the service life of equipment can be extended. Brief Description of the Drawings

[0023] Figure 1 is a flowchart of a method for dynamically adjusting the coal supply strategy of a thermal power unit provided by an embodiment of the present invention. Detailed Embodiments

[0024] The following combines the drawings and embodiments to further describe the detailed embodiments of the present invention in detail. The following embodiments are used to illustrate the present invention, but are not used to limit the scope of the present invention.

[0025] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. is based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation to the present invention.

[0026] The terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the present invention, unless otherwise specified, the meaning of "a plurality of" is two or more.

[0027] In the description of the present invention, it should be noted that unless otherwise clearly specified and limited, the terms "installed", "connected", and "coupled" should be understood in a broad sense. For example, it may be a fixed connection, a detachable connection, or an integral connection; it may be a mechanical connection or an electrical connection; it may be directly connected or indirectly connected through an intermediate medium, and it may be the communication inside two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0028] Embodiment 1: A method for dynamically adjusting the coal supply strategy of a thermal power unit provided by an embodiment of the present invention, as Figure 1 shown, includes: Dividing coal types based on the historical data of coal yard storage to generate coal types of multiple grades; Obtaining the storage situation of each grade of coal type in the current coal yard to generate the content value of each grade of coal type; Generating a heat supply efficiency prediction curve based on the production plan of the current coal yard; Setting the coal feeding cycle and the coal type combination plan in combination with the heat supply efficiency prediction curve.

[0029] Embodiment 2: When generating coal types of multiple grades, it further includes: Among them, generating coal types of multiple grades includes: Obtaining multiple types of coal based on the historical data of coal yard storage; Obtaining the temperature increment of the boiler per unit mass when the current coal type is burned, and generating the calorific value of the current coal type based on the temperature increment of the boiler; Obtaining the calorific values of all types of coal to generate a coal type calorific value set Q, Q = {q1, q2... qi... qn}; Among them, qi is the calorific value of the i-th type of coal, and n is the total number of coal types; Obtain the ashing time of each type of coal during combustion to generate a set T of coal type ashing times, T = {t1, t2…ti…tn}; Among them, ti is the ashing time of the i-th type of coal, and n is the total number of coal types; Combine the set Q of coal type calorific values and the set T of coal type ashing times to generate a set P of evaluation values for coal types, P = {p1, p2…pi…pn}; Among them, pi is the evaluation value of the i-th type of coal, and n is the total number of coal types; Based on the set P of evaluation values for coal types, divide the grades of coal types to generate a set D of coal type grades, D = {d1, d2…dj…dm}; Among them, dj represents the average calorific value of the coal of the j-th grade, m represents the total number of grades, and m < n.

[0030] In this embodiment, multiple types of coal are obtained based on the historical data stored in the coal yard; From the past storage records of the coal yard, determine which different types of coal exist. These historical data contain various information about the coal types, such as sources, compositions, etc., and are the basis for subsequent analysis.

[0031] Obtain the temperature increment of the boiler per unit mass during the combustion of the current coal type, and generate the calorific value of the current coal type based on the temperature increment of the boiler; By measuring the temperature increment that each type of coal raises the boiler per unit mass during combustion, the calorific value of this type of coal is determined. The calorific value is an important indicator for measuring the heat generation capacity of coal types and is crucial for evaluating the role of coal types in heat supply.

[0032] Obtain the calorific values of all types of coal to generate a set Q of coal type calorific values. Collect the calorific values of all coal types to form a set Q. Among them, qi represents the calorific value of the i-th type of coal, and n is the total number of coal types. This set can facilitate the overall analysis and comparison of the heat generation capabilities of different coal types.

[0033] Obtain the ashing time of each type of coal during combustion to generate a set T of coal type ashing times. In addition to the calorific value, the ashing time after coal combustion is also an important characteristic. Record the ashing time of each type of coal during combustion and form a set T. The ashing time may affect operations such as equipment maintenance and ash cleaning cycles.

[0034] The ashing time is one of the important indicators for evaluating the performance of coal types. By combining the calorific value of the coal type and the ashing time, the evaluation value of the coal type can be calculated, so as to more comprehensively understand the characteristics of the coal type. For example, a certain coal type may have a high calorific value, but if its ashing time is very short, it may cause frequent ash cleaning of the equipment, affecting the stable operation of the equipment. Therefore, comprehensively considering the calorific value and the ashing time can more accurately evaluate the advantages and disadvantages of the coal type.

[0035] Generate the evaluation value set P of the coal type by combining the calorific value set Q of the coal type and the ashing time set T of the coal type.

[0036] Comprehensively consider the two factors of calorific value and ashing time to evaluate the value of each coal type. In this way, according to the actual needs, the importance of the calorific value and the ashing time can be adjusted to obtain the comprehensive evaluation value set P of each coal type.

[0037] Based on the evaluation value set P of the coal type, divide the grades of the coal type to generate the grade set D of the coal type. According to the preset evaluation value, divide the evaluation value set P of the coal type, so as to obtain different grades of coal type sets D. dj represents the average calorific value of the coal of the j-th grade, and m represents the total number of grades and m < n. The grade division helps to preferentially select the appropriate grade of coal according to different heating demands in subsequent operations.

[0038] Example 3: When generating the evaluation value set P of the coal type, it includes: Obtain the evaluation value pi of the i-th coal type; pi = a1 * (w1 * qi + w2 * ti); Wherein, a1 is a fixed coefficient, w1 is the weight of the calorific value qi of the i-th coal type, and w2 is the weight of the ashing time ti of the i-th coal type; Obtain the evaluation values pi of all types of coal to generate the evaluation value set P.

[0039] In this embodiment, the fixed coefficient a1 is a preset value, and its function is to adjust the overall evaluation value proportionally to meet the requirements of the entire evaluation system. This coefficient may be determined according to experience or some basic parameters of the entire heating system. For example, it may be related to factors such as the total heating capacity of the heating system and the maximum available proportion of the coal type in the system.

[0040] The calorific value qi is an important indicator for measuring the heat generation ability of the coal type. The weight w1 reflects the relative importance of the calorific value in the comprehensive evaluation of the coal type. If the heating system has a very urgent demand for heat generation and is relatively insensitive to other characteristics of the coal type, w1 may be set relatively large. For example, during the heating peak period in cold regions, in order to ensure sufficient heat supply, the weight of the calorific value may be increased.

[0041] The determination of the weight w1 may also consider the difference range of calorific values of different coal types. If the difference in calorific values between coal types is large, in order to highlight the influence of calorific value on coal type evaluation, w1 may also increase accordingly.

[0042] The ashing time ti is related to the ash treatment after coal combustion. The weight w2 reflects the importance of the ashing time in the evaluation. If the ash cleaning equipment in the coal yard has limited processing capacity, or the ash cleaning cycle has a greater impact on the continuous operation of the heating system, then w2 may be set to a larger value. For example, for a coal yard with low automation and complex ash cleaning operations, coal types with longer ashing times may have a greater impact on production, and at this time, w2 should be appropriately increased.

[0043] At the same time, w2 is also affected by the degree of difference in ashing times of coal types. If the ashing time differences between different coal types are obvious, the value of w2 may be adjusted accordingly to better distinguish the advantages and disadvantages of coal types in this characteristic.

[0044] Once the values of a1, w1, w2, qi, and ti are determined, the evaluation value pi of the i-th coal type can be calculated according to the formula pi = a1*(w1qi + w2ti). This formula comprehensively considers the influence of calorific value and ashing time on coal types. The multiplication of the calorific value qi by w1 represents the contribution part of the calorific value to the evaluation value, the multiplication of the ashing time ti by w2 represents the contribution part of the ashing time to the evaluation value, and the sum of the two is then multiplied by a1 to obtain the final evaluation value pi.

[0045] Example 4: When generating the grade set D of coal types, it includes: Setting a preset value of the evaluation value of coal types based on the set of evaluation values P of coal types in the obtained historical data; Dividing the set of evaluation values P of coal types based on the preset value of the evaluation value of coal types to generate the grade set D of coal types, D = {d1, d2... dj... dm}.

[0046] In this embodiment, each evaluation value pi in the set of evaluation values P is judged according to the set preset value of the evaluation value. For example, if the upper limit preset value of the low grade is set to p_low, then for coal types with pi <= p_low, they are initially classified as low grade coal types.

[0047] For coal types in different preset value intervals, they are respectively classified into different grades. For example, coal types with p_low < pi <= p_mid (p_mid is the preset value between medium and low grades) are classified as lower medium grades, coal types with p_mid < pi <= p_high (p_high is the lower limit preset value of high grades) are classified as upper medium grades, and coal types with pi > p_high are classified as high grades.

[0048] After completing the grading of the evaluation values pi of all coal types, summarize the coal types of each grade. For example, summarize the relevant information of all low-grade coal types (such as average evaluation value, number of coal types, etc.) as d1, the lower-middle grade as d2, and so on, finally forming the grade set D of coal types = {d1, d2... dj... dm}. Among them, dj represents the relevant summary information of the coal types of the j-th grade, and m represents the total number of grades.

[0049] When determining dj, in addition to including the average evaluation value of the coal types of this grade, other relevant information can also be considered, such as the main sources of the coal types of this grade, storage locations in the coal yard, etc., so as to more comprehensively utilize this information in subsequent operations such as formulating coal feeding strategies.

[0050] Example 5: When generating the heating efficiency prediction curve, it includes: Set the heating prediction period H of the current thermal power plant in combination with historical data and the coal type ashification time set T; Generate the heating prediction curve HQ based on the production plan of the current thermal power plant within the obtained heating prediction period H; Segment the heating prediction curve HQ based on historical data to generate multiple sub-heating prediction curves {hq1, hq2... hq z …hq r}; Among them, hq z represents the z-th sub-heating prediction curve, and r represents the total number of generated sub-heating prediction curves.

[0051] In this example, review the sharp change points of heating demand in the historical data within the heating prediction period H. For example, in some time periods, the heating demand may suddenly increase or decrease, and these points may be caused by sudden changes in temperature or sudden changes in industrial heat demand, etc.

[0052] Segment according to the change situation of heating efficiency in historical data. If the heating efficiency changes greatly due to equipment maintenance, coal type switching, etc. in a certain time period, this time period can also be used as the basis for segmentation.

[0053] Check the special arrangements in the production plan, such as equipment maintenance plans. During equipment maintenance, the heating capacity will decrease, which is an important factor for segmenting the heating prediction curve HQ.

[0054] If there are arrangements for temporarily increasing or decreasing heating tasks in the production plan, it also needs to be considered during segmentation.

[0055] According to the above segmentation basis, the heating prediction curve HQ is divided into multiple sub-heating prediction curves {hq1, hq2…hq z …hq r}. Each sub-heating prediction curve hq z represents the heating prediction situation within a specific time period or under a specific heating state during the heating prediction period H.

[0056] Embodiment 6: When setting the coal feeding cycle and the coal type combination plan in combination with the heating efficiency prediction curve, it includes: Obtain the corresponding heating prediction value Cd of the current sub-heating prediction curve hq z ; Generate the remaining coal type grade set DY of the current coal yard by combining the grade set D of the coal type and the coal yard storage situation; Obtain the status information of the coal type grade; Set the priority weight of the corresponding coal type grade in combination with the status information of the coal type grade to generate the priority weight set Y of the coal type grade; Generate the coal type reference plan set K by combining the heating prediction value Cd, the remaining coal type grade set DY, and the priority weight set Y, K = {d1, d2…dx…dg}; wherein, dx represents the xth coal type reference plan, and g represents the total number of generated coal type reference plans; Based on the next sub-heating prediction curve hq (z+1) and the coal type reference plan set K, select the corresponding coal type reference plan of the current sub-heating prediction curve hq z .

[0057] Embodiment 7: When generating the priority weight set Y of the coal type grade, it includes: Obtain the coal quality status information, supply status information, and equipment adaptation status information of the current coal type; Based on historical data, set the weight factor F1 of the coal quality status information, the weight factor F2 of the supply status information, and the weight factor F3 of the equipment adaptation status information respectively, and F1 + F2 + F3 = 1; Build the priority weight model of the coal type grade in combination with historical data:

[0058] wherein, is the coefficient of the th coal quality status information, is the th coal quality status information, is the total number of coal quality status information, is the th coefficient of the supply status information, is the kind of supply status information, is the total number of supply status information, is the coefficient of the kind of device adaptation status information, is the kind of device adaptation status information, is the total number of device adaptation status information, is the priority weight of the current coal type grade; Obtain the status information reference values of all coal type grades to generate the priority weight set Y of coal type grades.

[0059] In this embodiment, carefully analyze the current sub-heating prediction curve hq z . If hq z is represented in the form of a function, for example hq z(t) (t is the time variable), then obtain the heating prediction value Cd by integrating this function over the corresponding time period; First, determine the average heat production E(qj) of the coal of the j-th grade; this value can be obtained by statistically analyzing the historical heat production data of the coal of this grade, for example, taking the average of multiple measured heat production values.

[0060] The deviation value adjustment coefficient A is a value set according to the actual operation of the heating system. It may be related to factors such as the error tolerance of the heating system and the performance fluctuation of the equipment.

[0061] Embodiment 8: When generating the coal type reference plan set K, it includes: Based on the current sub-heating prediction curve hq z obtain the corresponding heating prediction value Cd;

[0062] Among them, is the proportional coefficient of the coal of the j-th grade, is the average heat production of the coal of the j-th grade, A is the deviation value adjustment coefficient; Generate a primary coal type reference plan set based on the proportional coefficient of each grade of coal; Sort the primary coal type reference plans based on the priority weight set Y to generate a secondary coal type reference plan set; Based on the coal type grade margin set DY, screen the primary coal type reference value plans, and eliminate the secondary coal type reference plans that do not meet the coal type grade margin to generate the coal type reference plan set K.

[0063] In this embodiment, the coal type grade margin of each secondary coal type reference plan is checked. For each plan in the set of secondary coal type reference plans, it is compared with the set DY of coal type grade margins. Check whether the usage of each grade of coal type is less than or equal to the corresponding coal type grade margin.

[0064] The remaining secondary coal type reference plans after screening form the final set K of coal type reference plans. The plans in this set satisfy the heating prediction value Cd and consider the priority weights, while also ensuring the feasibility of the coal type grade margin.

[0065] Embodiment 9: When generating the set of secondary coal type reference plans, it includes:

[0066] Among them, is the priority evaluation value of the current primary coal type reference plan, is the priority weight of the j-th grade of coal type; Obtain the priority evaluation values of all primary coal type reference plans, sort them from large to small, and generate the set of secondary coal type reference plans.

[0067] Embodiment 10: When selecting the coal type reference plan corresponding to the current sub-heating prediction curve hq z it includes: Obtain the first secondary coal type reference plan k'1 in the set of secondary coal type reference plans corresponding to the heating demand of the next sub-heating prediction curve hq (z+1) ; Obtain the first coal type reference plan corresponding to the heating demand of the next sub-heating prediction curve hq (z+1) to generate the comparison reference plan k'1; Calculate the similarity Ds between the comparison reference plan k'1 and all coal type reference plans in the current set K of coal type reference plans in sequence; Ds = f * NS; NS is the number of the same coal type grades between the comparison reference plan k'1 and all coal type reference plans in the current set K of coal type reference plans, and f is the first fixed coefficient; Select the coal type reference plan with the largest similarity Ds to generate the coal type reference plan corresponding to the current sub-heating prediction curve hq z .

[0068] In this embodiment, first, it is necessary to deeply study the heating demand characteristics of the next sub-heating prediction curve hq (z + 1) . This includes checking the shape of the curve (such as rising steadily, dropping sharply, etc.), the total heating demand within the time period covered by the curve, and the time distribution of the heating demand.

[0069] According to the heating demand characteristics of hq(z + 1), combined with the previously generated set of reference schemes for secondary coal types (this set of schemes is generated based on various conditions such as coal type grade margin, priority weight, etc.), determine the reference scheme for secondary coal types that meets its heating demand.

[0070] From these schemes that meet the requirements, select the first reference scheme for secondary coal types and label it as K’1. This scheme is selected according to a certain predefined order (such as the generation order of the schemes or the sorting order of the scheme priorities). At the same time, specifically for the next sub-heating prediction curve hq (z + 1) 's heating demand, directly generate the first reference scheme for coal types, which is also labeled as K’1. This scheme is generated independently of the previous set of reference schemes for secondary coal types and is a benchmark scheme specifically used for comparison with the current set of reference schemes for coal types K.

[0071] Given NS and the first fixed coefficient f, the calculation method of this similarity is simply based on the number of coal types at the same grade, and the numerical range of the similarity is adjusted by multiplying by the fixed coefficient f. The value of the fixed coefficient f can be determined according to the specific requirements and experience of the heating system. For example, if it is desired that the numerical range of the similarity is between 0 and 1, the value of f can be reasonably set according to the total number of coal type grades.

[0072] After calculating the similarity Ds between the comparison reference scheme k’1 and each scheme in the current set of reference schemes for coal types K, compare these similarity values.

[0073] Find the coal type reference scheme with the largest similarity Ds, and this scheme is selected as the coal type reference scheme corresponding to the current sub-heating prediction curve hq z The purpose of selecting this scheme is to, while meeting the current heating demand (hq z ), make the current coal type selection match the heating demand of the next sub-heating prediction curve hq (z + 1) as much as possible, so as to ensure the continuity and stability of the heating process.

[0074] Finally, it should be noted that: Obviously, those skilled in the art can make various changes and deformations to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention also intends to include these changes and deformations.

[0075] The above is only a preferred embodiment of the present invention and is not intended to limit the protection scope of the present invention.

Claims

1. A method for dynamically adjusting coal supply strategy of a thermal power unit, characterized in that: include: Based on the historical data stored in the coal yard, coal types are divided into multiple grades of coal; Obtain the storage situation of each grade of coal in the current coal yard and generate the content value of each grade of coal; Generate a heating efficiency prediction curve based on the current coal yard production plan; The coal loading cycle and coal type combination plan are set based on the heating efficiency prediction curve.

2. The method for dynamically adjusting the coal supply strategy of a thermal power unit according to claim 1, characterized in that: When generating multiple grades of coal, include: Among them, the types of coal that generate multiple grades include: Obtain multiple types of coal based on historical data stored in historical coal yards; Obtain the temperature increment of the boiler per unit mass when the current type of coal is burned, and generate the calorific value of the current type of coal based on the temperature increment of the boiler; Obtain the calorific value of all types of coal to generate a coal calorific value set Q, Q = {q1, q2…qi…qn}; Among them, qi is the calorific value of the i-th type of coal, and n is the total amount of coal; Obtain the ash-forming time of each type of coal combustion to generate a set of coal ash-forming time T, T={t1,t2…ti…tn}; Among them, ti is the ash-making time of the i-th coal type, and n is the total amount of coal type; Combine the coal type calorific value set Q and the coal type ashing time set T to generate the coal type evaluation value set P, P = {p1, p2…pi…pn}; Among them, pi is the evaluation value of the i-th coal type, and n is the total amount of coal types; Based on the evaluation value set P of coal types, the coal types are divided into grades to generate a grade set D of coal types, D = {d1, d2…dj…dm}; Among them, dj represents the average heat production of the j-th grade of coal, m represents the total number of grades, and m <n。 3. The method for dynamically adjusting the coal supply strategy of a thermal power unit according to claim 2, characterized in that: The generation of the evaluation value set P of the coal type includes: Get the evaluation value pi of the i-th coal type; pi=a1*(w1*qi+w2*ti); Among them, a1 is a fixed coefficient, w1 is the weight of the calorific value qi of the i-th coal type, and w2 is the weight of the ashification time ti of the i-th coal type; Get the evaluation values ​​pi of all types of coal to generate the evaluation value set P.

4. The method for dynamically adjusting the coal supply strategy of a thermal power unit according to claim 3, characterized in that: The generation of the coal grade set D includes: Setting a preset value of the evaluation value of the coal type based on the evaluation value set P of the coal type in the acquired historical data; Based on the preset values ​​of the evaluation values ​​of the coal types, the evaluation value set P of the coal types is divided to generate a grade set D of the coal types, D={d1,d2…dj…dm}.

5. The method for dynamically adjusting the coal supply strategy of a thermal power unit according to claim 4, characterized in that: The generating of the heating efficiency prediction curve includes: Combine historical data and coal ashing time set T to set the heat supply forecast period H of the current thermal power plant; Generate a heat supply forecast curve HQ based on the production plan of the current thermal power plant within the obtained heat supply forecast period H; Based on historical data, the heating forecast curve HQ is segmented to generate multiple sub-heating forecast curves {hq1, hq2…hq z …hq r }; Among them, hq z represents the zth sub-heating forecast curve, and r represents the total number of generated sub-heating forecast curves.

6. The method for dynamically adjusting the coal supply strategy of a thermal power unit according to claim 5, characterized in that: The setting of the coal feeding cycle and the coal type combination scheme in combination with the heating efficiency prediction curve includes: Get the current sub-heating forecast curve hq z The corresponding heating forecast value Cd; Combine the coal grade set D and the coal yard storage situation to generate the coal grade surplus set DY of the current coal yard; Get the status information of coal grade; The priority weights of the corresponding coal types are set in combination with the status information of the coal types to generate a priority weight set Y of the coal types; Combine the heat supply forecast value Cd, the coal grade surplus set DY and the priority weight set Y to generate the coal type reference solution set K, K = {d1, d2…dx…dg}; Among them, dx represents the xth coal type reference scheme, and g represents the total number of generated coal type reference schemes; Based on the next sub-heating prediction curve hq (z+1) And the coal type reference solution set K selects the current sub-heating prediction curve hq z Corresponding coal type reference plan.

7. The method for dynamically adjusting the coal supply strategy of a thermal power unit according to claim 6, characterized in that: The generation of the priority weight set Y of the coal type level includes: Obtain coal quality status information, supply status information and equipment adaptation status information of the current coal type; Based on historical data, the weight factor F1 of coal quality status information, the weight factor F2 of supply status information and the weight factor F3 of equipment adaptation status information are set respectively, and F1+F2+F3=1; Combine historical data to build a priority weight model for coal grade: in, For the The coefficient of the coal quality status information, For the Coal quality status information, is the total amount of coal quality status information, For the The coefficient of supply status information, For the Supply status information, is the total number of supply status information, For the The coefficient of the device adaptation status information, For the Device adaptation status information, is the total number of device adaptation status information, is the priority weight of the current coal grade; The status information reference values ​​of all coal grades are obtained to generate a priority weight set Y of the coal grades.

8. The method for dynamically adjusting the coal supply strategy of a thermal power unit according to claim 7, characterized in that: The generation of the coal type reference solution set K includes: Based on the current sub-heating prediction curve hq z Obtain the corresponding heating prediction value Cd; in, is the proportion coefficient of the j-th grade coal, is the average heat production of the j-th grade coal, and A is the deviation adjustment coefficient; Generate a first-level coal type reference solution set based on the proportion coefficient of each grade of coal type; Sort the primary coal type reference schemes based on the priority weight set Y to generate a secondary coal type reference scheme set; The primary coal type reference value schemes are screened based on the coal type grade margin set DY, and the secondary coal type reference schemes that do not meet the coal type grade margin are eliminated to generate a coal type reference scheme set K.

9. The method for dynamically adjusting the coal supply strategy of a thermal power unit according to claim 8, characterized in that: The generation of the secondary coal type reference scheme set includes: in, is the priority evaluation value of the current primary coal reference scheme, is the priority weight of the j-th grade coal; Obtain the priority evaluation values ​​of all primary coal type reference schemes and sort them from large to small to generate a set of secondary coal type reference schemes.

10. The method for dynamically adjusting the coal supply strategy of a thermal power unit according to claim 9, characterized in that: The current sub-heating prediction curve hq is selected z The corresponding coal type reference plan includes: Get the next sub-heating forecast curve hq (z+1) The first secondary coal type reference scheme k'1 in the secondary coal type reference scheme set corresponding to the heating demand; Get the next sub-heating forecast curve hq (z+1) The first coal type reference scheme corresponding to the heating demand is generated and compared with the reference scheme k'1; Calculate the similarity Ds between the comparison reference scheme k'1 and all the coal type reference schemes in the current coal type reference scheme set K in sequence; Ds=f*NS; NS is the number of the same coal grade between the comparison reference scheme k'1 and all the coal reference schemes in the current coal reference scheme set K, and f is the first fixed coefficient; Select the coal type reference scheme with the largest similarity Ds to generate the current sub-heating prediction curve hq z Corresponding coal type reference plan.

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