Cement plant energy efficiency quantitative analysis method and system

Abstract

The invention discloses a cement plant energy efficiency quantitative analysis method and system, and the method comprises the steps: obtaining cement production energy efficiency index data, employing an interpretation structure model to carry out the sorting of the hierarchical relation between production energy efficiency indexes, and obtaining an index adjacency matrix; calculating an index reachable matrix based on the obtained index adjacent matrix, and performing hierarchical division on the index reachable matrix to establish an index structure model; calculating the weight of each level of index based on the obtained index structure model; and based on the calculated weight of each level of index, calculating the score of each level of index, and performing cement plant energy efficiency quantitative evaluation according to the score condition of each level of index. The method provides important theoretical support and practical basis for developing energy efficiency evaluation, energy efficiency improvement and energy conservation and emission reduction work in the cement production industry by exploring specific measures and methods for improving the production energy efficiency of cement production enterprises.

Description

Technical Field

[0001] The invention belongs to the technical field of cement energy efficiency evaluation, and in particular relates to a cement plant energy efficiency quantitative analysis method and system. Background Art

[0002] With the development of social economy, energy problems have become more prominent, and energy conservation and emission reduction of enterprises have become another major issue. As a major energy consumer, cement production enterprises are the first to bear the brunt. Energy efficiency evaluation of enterprises can not only assess the overall energy use effect of enterprises, but also find out the weak links of energy efficiency use of enterprises, which has important practical significance for energy conservation planning and technological reform of enterprises. At present, there are not many studies on energy efficiency evaluation of cement production enterprises, and the studies involved have not considered the characteristics of cement production enterprises themselves.

[0003] In order to improve the production energy efficiency of cement production enterprises and promote energy conservation and emission reduction, it is necessary to establish a scientific and reasonable cement plant energy efficiency quantitative analysis and improvement indicator system.

[0004] CN202410756914.4A discloses a method for evaluating energy efficiency of cement production. The method includes: establishing a cement production energy efficiency evaluation data database; constructing a comprehensive evaluation system for cement production energy efficiency; based on the cement production energy efficiency evaluation data database, the production process structure and the input-output relationship of the material flow and energy flow of each equipment, using Simulink to establish a production simulation model, and combining the comprehensive evaluation system to establish a cement production energy efficiency evaluation model; constructing a cement production energy efficiency evaluation simulation system; using the cement production energy efficiency comprehensive evaluation system as an indicator and the cement production energy efficiency evaluation simulation system as a tool, by modifying the production structure of the production simulation model, the operating parameters of each equipment, the material allocation ratio and the production plan, the corresponding energy efficiency evaluation results are obtained. This method only involves objective quantitative indicators, and does not consider subjective factors; the hierarchical relationship between the indicators is not reflected in the indicator system.

[0005] CN202311215431.5A discloses a method and system for evaluating energy efficiency and carbon efficiency of clinker burning in the cement industry; the total amount of electricity consumption and coal consumption of the clinker burning process in the set time period are calculated according to the cement output in the set time period; the energy efficiency level and carbon efficiency level of the clinker burning process in the cement industry are calculated according to the total amount of electricity consumption, the total amount of coal consumption and the cement output, which are used to evaluate the energy efficiency and carbon efficiency of the cement clinker burning process. This method only covers the total amount of electricity consumption, the total amount of coal consumption and the cement output, and the evaluation system is not systematic and comprehensive enough; the evaluation system is not clear enough and fails to form an evaluation index system.

[0006] Therefore, there is an urgent need for a quantitative analysis method for cement plant energy efficiency that can take subjective factors into account and reflect the hierarchical relationship between various indicators, so that the evaluation can objectively reflect the actual situation. Summary of the invention

[0007] In order to solve the deficiencies in the prior art, the present invention provides a cement plant energy efficiency quantitative analysis method.

[0008] The present invention adopts the following technical solution.

[0009] A method for quantitative analysis of energy efficiency of a cement plant, the method comprising the following steps:

[0010] Step 1: Obtain cement production energy efficiency index data, use the explanatory structural model to sort out the hierarchical relationship between production energy efficiency indicators, and obtain the indicator adjacency matrix;

[0011] Step 2: Calculate the indicator reachability matrix based on the indicator adjacency matrix obtained in step 1, and divide the indicator reachability matrix into levels to establish the indicator structure model;

[0012] Step 3: Based on the indicator structure model obtained in step 2, calculate the weights of indicators at all levels;

[0013] Step 4: Based on the weights of indicators at each level calculated in step 3, calculate the scores of indicators at each level, and conduct a quantitative evaluation of the energy efficiency of the cement plant based on the scores of indicators at each level.

[0014] In step 1, the cement production energy efficiency indicators include transformer and power distribution energy consumption indicators, power quality energy efficiency evaluation technical indicators, power-mechanical energy equipment energy consumption indicators, power-thermal energy equipment energy consumption indicators, power-light energy equipment energy consumption indicators, and power supply system measurement and monitoring indicators;

[0015] The energy consumption assessment economic indicators include a comprehensive energy consumption indicator per unit product and a power consumption indicator per unit product.

[0016] In step 1, the hierarchical relationship between production energy efficiency indicators is sorted out using the explanatory structural model, and the indicator adjacency matrix is ​​obtained, including: judging the correlation and causality between production energy efficiency indicators Si and Sj, whose value is 0 or 1, and constructing the indicator adjacency matrix A based on the judgment results; among them, 0 represents that there is no direct influence between Si and Sj, that is, there is no coupling effect, and 1 represents that there is a direct influence between Si and Sj, that is, there is a coupling effect.

[0017] In step 2, the calculation formula of the indicator reachability matrix P is as follows:

[0018] P=(A+I) n+1

[0019] Among them, A represents the index adjacency matrix, I represents the identity matrix, and n represents the number of times the adjacency matrix plus the identity matrix are multiplied by themselves.

[0020] In step 2, the hierarchical division of the reachable matrix and the establishment of the indicator structure model include: dividing the reachable matrix P into a reachable set R(Si) and a preceding set A(Si), calculating the intersection of R(Si) and A(Si), and obtaining the highest indicator; deleting the corresponding row of the highest indicator in the reachable matrix to obtain the second-level indicator, and deleting the corresponding column of the highest indicator in the reachable matrix to obtain the third-level indicator; using a directed graph to represent the hierarchical structure of the indicator structure model, the top layer corresponds to the highest indicator, and the following are the second-level indicator and the third-level indicator.

[0021] The reachable set R(Si) is the set of column indices corresponding to matrix elements containing 1 in the row corresponding to the index Si in the reachable matrix.

[0022] The predecessor set A(Si) is a set of row indices corresponding to matrix elements having 1 in the column corresponding to the index Si in the reachable matrix.

[0023] In step 3, the weights of indicators at all levels are calculated including:

[0024] Step 301: construct a judgment matrix, the elements in the judgment matrix represent the relative importance of each pair of indicators at the same level, and a scale is used to represent the relative importance of the indicators;

[0025] Step 302: Find the maximum eigenvalue of the judgment matrix;

[0026] Step 303: Perform a consistency check on the judgment matrix. If the consistency check passes, proceed to step 304. If the consistency check fails, return to step 301 to reconstruct the judgment matrix.

[0027] Step 304: normalize the eigenvector corresponding to the maximum eigenvalue of the judgment matrix to obtain a weight sequence of the same-level index to the previous-level index.

[0028] In step 303, the consistency check of the judgment matrix includes calculating the check coefficient according to the following formula:

[0029]

[0030] in, represents the consistency index; RI represents the average random consistency index of the judgment matrix; λmax is the maximum eigenvalue of the judgment matrix, and n is the order of the judgment matrix; if CR is less than 0.1, it is considered that the judgment matrix has passed the one-time test; if CR is greater than or equal to 0.1, it is considered that the judgment matrix has not passed the consistency test, and it is necessary to return to step A1 to reconstruct the judgment matrix.

[0031] In step 4, the calculation of the scores of indicators at all levels includes:

[0032] Step 401: For the third-level indicator A k,j , calculate the third-level index score F k,j , determine the evaluation effect of each third-level indicator according to the score;

[0033] Step 402: Determine the weight ω of each third-level indicator k,j , for each second-level indicator A k (k=1,2...m), determine the weight ω of each third-level indicator it contains k,j , satisfying ω k,j >0;

[0034] Step 403: Calculate the score F of the second-level indicator k ,in, p k is the number of second-tier indicators, and the evaluation effect of each second-tier indicator is determined according to the score;

[0035] Step 404: Determine the weight ω of each second-layer indicator k , the evaluation target is the weight ω of each indicator in the indicator adjacency matrix k >0, and

[0036] Step 405: Calculate the comprehensive evaluation score F, where:

[0037] In step 401, the third-level index score F is calculated. k,j include:

[0038] The third-level indicators are scored according to the following formula:

[0039]

[0040] Among them, μ1(x), μ2(x), and μ3(x) are the membership functions of the third-layer indicators, which are used to calculate the membership of the third-layer energy indicators for good, medium, and poor; a1, a2, and a3 are the values ​​for judging the good, medium, and poor of the third-layer indicators.

[0041] At the same time, the present invention provides a cement plant energy efficiency quantitative analysis system, including an indicator adjacency matrix construction module, an indicator structure model construction module, an indicator weight calculation module and an indicator score calculation module;

[0042] The indicator adjacency matrix construction module is used to obtain cement production energy efficiency indicator data, and use the explanatory structural model to sort out the hierarchical relationship between production energy efficiency indicators to obtain the indicator adjacency matrix;

[0043] The indicator structure model building module calculates the indicator reachability matrix based on the obtained indicator adjacency matrix and divides the indicator reachability matrix into levels to establish the indicator structure model;

[0044] The indicator weight calculation module calculates the weights of indicators at all levels based on the obtained indicator structure model;

[0045] The indicator score calculation module calculates the scores of indicators at each level based on the weights of the indicators at each level, and conducts quantitative evaluation of the energy efficiency of the cement plant based on the scores of indicators at each level.

[0046] A terminal comprises a processor and a storage medium; the storage medium is used to store instructions; the processor is used to operate according to the instructions to execute the steps of any one of the methods.

[0047] A computer-readable storage medium stores a computer program, which implements the steps of any one of the methods when executed by a processor.

[0048] The beneficial effect of the present invention is that, compared with the prior art, the present invention has the following significant advantages: the present invention takes cement production energy efficiency as the overall evaluation target, and establishes a set of multi-level cement plant energy efficiency evaluation index system, which includes two first-level indicators, eight second-level indicators, and thirty-nine third-level indicators, with clear classification, progressive level by level, and comprehensive system, so that the evaluation result is more accurate. In the evaluation process, the present invention uses the three-level quantitative indicators as the underlying basis for evaluating qualitative indicators, and the thirty-nine quantitative indicators can obtain accurate data through measurement, calculation, statistics, etc., thereby improving the objectivity of the evaluation method; at the same time, the relative importance scale of the judgment matrix is ​​given in the evaluation process, and a margin for subjective adjustment is left; the combination of subjectivity and objectivity enables the evaluation to objectively reflect the actual situation and make corresponding adjustments according to different scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 A flowchart of a cement plant energy efficiency quantitative analysis method according to the present invention;

[0050] Figure 2 This is a schematic diagram of the evaluation index system of the present invention. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical scheme and advantages of the present invention clearer, the technical scheme of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. The embodiments described in this application are only embodiments of a part of the present invention, rather than all embodiments. Based on the spirit of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work belong to the protection scope of the present invention.

[0052] The technical solution of the present invention is further described below in conjunction with the accompanying drawings.

[0053] The present invention provides a method for quantitative analysis of energy efficiency of cement plants. Figure 1 The flowchart of the method for quantitative analysis of energy efficiency of cement plants according to the present invention is shown, and the method comprises:

[0054] Step 1: Obtain cement production energy efficiency indicators, use the explanatory structural model to sort out the hierarchical relationship between production energy efficiency indicators, and obtain the indicator adjacency matrix.

[0055] In one embodiment of the present invention, in step 1, the cement production energy efficiency indicators include transformer and power distribution energy consumption indicators, power quality energy efficiency evaluation technical indicators, power-mechanical energy equipment energy consumption indicators, power-thermal energy equipment energy consumption indicators, power-photovoltaic energy equipment energy consumption indicators, power supply system measurement and monitoring indicators; the energy consumption evaluation economic indicators include unit product energy consumption comprehensive indicators and unit product electricity consumption indicators.

[0056] In one embodiment of the present invention, an explanatory structural model is used to sort out the hierarchical relationship between production energy efficiency indicators, and an adjacency matrix is ​​obtained according to the correlation between the indicators. The correlation and causality between the two indicators are judged, and the value is 0 or 1; 0 represents that there is no direct influence between the indicators, that is, there is no coupling effect, and 1 represents that there is a direct influence between them, that is, there is a coupling effect; a direct relationship matrix (adjacency matrix) A between the indicators is established.

[0057] Step 2: Calculate the indicator reachability matrix based on the indicator adjacency matrix obtained in step 1, and divide the indicator reachability matrix into levels to establish the indicator structure model.

[0058] In one embodiment of the present invention, calculating the indicator reachability matrix based on the indicator adjacency matrix obtained in step 1 includes: for Si, Sj∈S, Si, Sj represent the indicators in the adjacency matrix, if there is any path from Si to Sj, then Si is said to be reachable to Sj.

[0059] In this embodiment, after obtaining the indicator adjacency matrix, the indicator adjacency matrix is ​​added to the unit matrix, and after at most n times of power operation, the reachable matrix P = (A + I) can be obtained. n+1 =(A+I) n ≠(A+I) n-1 ≠…≠(A+I) 2 ≠(A+I), where A represents the indicator adjacency matrix, and n represents the number of times the indicator adjacency matrix plus the unit matrix is ​​multiplied by itself. After n times of power operation, the matrix no longer changes. The reachable matrix P reflects the direct and indirect relationships between the indicators in the system.

[0060] The hierarchical division of the reachable matrix and the establishment of the structural model are as follows: the reachable matrix P is divided into two sets: the reachable set R(Si) and the predecessor set A(Si). The set of column indices corresponding to the matrix elements with 1 in the row corresponding to the indicator Si in the reachable matrix represents the indicator reached by the indicator Si, which is expressed as:

[0061] R(S i )={S j ∈Nm ij =1}

[0062] Where N is the set of all nodes; m ij is the reachable value of the association from node i to node j. When node i is associated with node j, m ij =1.

[0063] The column corresponding to the indicator Si in the reachable matrix contains the set of row indicators corresponding to the matrix elements with 1, which represents the indicator that will reach the indicator, expressed as:

[0064] A(S i )={S j ∈Nm ij =1}

[0065] Where N is the set of all nodes; m ij is the reachable value of the association from node i to node j. When node i is associated with node j, m ij =1.

[0066] Calculate the intersection of R(Si) and A(Si), the index in R(Si)∩A(Si)=R(Si) is the top index of the system, that is, the index of the highest level target layer; after obtaining the top index, temporarily cross out the corresponding row of the top index in the reachable matrix to obtain the second level index; cross out the corresponding column of the top index in the reachable matrix to obtain the third level index; after the hierarchical level is allocated, use a directed graph to represent the hierarchical structure of the index structure model, the top level corresponds to the top index, and the following are the second level index and the third level index. The present invention divides all index sets into three layers to construct an evaluation index system model, such as Figure 2 As shown, A is the highest level indicator;

[0067] A1, A2…Am are the second-layer indicators included in the first-layer indicator A; Am1,…Ampm are the third-layer indicators included in the second-layer Am.

[0068] Step 3: Based on the indicator structure model obtained in step 2, calculate the weights of indicators at all levels.

[0069] In one embodiment of the present invention, in step 3, calculating the weights of indicators at each level using the analytic hierarchy process includes:

[0070] Step 301: construct a judgment matrix, the elements in the judgment matrix represent the relative importance of each pair of indicators at the same level, and a scale is used to represent the relative importance of the indicators;

[0071] Step 302: Find the maximum eigenvalue of the judgment matrix;

[0072] Step 303: Perform a consistency check on the judgment matrix. If the consistency check passes, proceed to step 304. If the consistency check fails, return to step 301 to reconstruct the judgment matrix.

[0073] Step 304: normalize the eigenvector corresponding to the maximum eigenvalue of the judgment matrix to obtain a weight sequence of the same-level index to the previous-level index.

[0074] In one embodiment of the present invention, cement production energy efficiency is taken as the overall evaluation target, and the total index includes two first-level indicators: energy efficiency evaluation technical indicators and energy consumption evaluation economic indicators; the energy efficiency evaluation technical indicators include six second-level indicators: transformer and power distribution energy consumption indicators, power quality energy efficiency evaluation technical indicators, power-mechanical energy equipment energy consumption indicators, power-thermal energy equipment energy consumption indicators, power-photovoltaic energy equipment energy consumption indicators, and power supply system measurement and monitoring indicators; the transformer and power distribution energy consumption indicators include eight third-level indicators: transformer efficiency, transformer load rate, transformer load rate, transformer load peak-to-valley difference rate, energy-saving transformer proportion, power factor, high-loss distribution transformer proportion, and line loss rate; the power quality energy efficiency evaluation technical indicators include five third-level indicators: voltage deviation limit, harmonic voltage limit, harmonic current limit, voltage fluctuation limit, and frequency deviation limit; the power-mechanical energy equipment energy consumption indicators include motor average load rate, motor average operating efficiency, motor There are five third-level indicators under the energy consumption indicators of electric energy-thermal energy equipment, namely, rotary kiln thermal efficiency, rotary kiln load rate, rotary kiln power consumption, grate cooler power consumption, and kiln tail high-temperature fan power consumption; there are two third-level indicators under the energy consumption indicators of electric energy-photoelectric energy equipment, namely, lighting luminous efficiency and the ratio of the number of high-efficiency energy-saving lamps; there are three third-level indicators under the measurement and monitoring indicators of the power supply system, namely, the completeness rate of electric energy meter configuration, the qualified rate of electric energy meter, and the automation rate of electric energy metering; there are two second-level indicators under the economic indicators of energy consumption assessment, namely, the comprehensive index of energy consumption per unit product and the power consumption index per unit product; there are four third-level indicators under the comprehensive index of energy consumption per unit product, namely, the comprehensive power consumption of clinker, the comprehensive coal consumption of clinker, the comprehensive energy consumption of clinker, and the comprehensive power consumption of cement; there are seven third-level indicators under the power consumption indicators of unit product, namely, the power consumption of raw material crushing, the power consumption of raw material pre-homogenization, the power consumption of raw material grinding, the power consumption of raw material homogenization, the power consumption of clinker burning, the power consumption of clinker transportation, and the power consumption of coal powder preparation.

[0075] Table 1 Quantitative index system for cement production

[0076]

[0077]

[0078] In this embodiment, the weights of indicators at each level are calculated using the analytic hierarchy process as follows:

[0079] A1: Construct a judgment matrix. The elements in the judgment matrix represent the relative importance of indicators at the same level. By comparing indicators two by two, the inaccuracy caused by comparing factors of different natures can be reduced. A scale of 1-9 is used to represent the relative importance of indicators.

[0080] A2: Find the maximum eigenvalue of the judgment matrix;

[0081] A3: Define the consistency index CI. The consistency test of the judgment matrix includes calculating the test coefficient according to the following formula:

[0082]

[0083] Among them, λ max is the maximum eigenvalue of the judgment matrix, n is the order of the judgment matrix, and the average random consistency index RI of the judgment matrix. The standard value of RI is determined by the order of the judgment matrix. The final test coefficient is obtained by CI and RI. If CR < 0.1, it is considered that the judgment matrix has passed the one-time test. If CR ≥ 0.1, it has not passed the consistency test and needs to return to step A1 to reconstruct the judgment matrix.

[0084] A4: After normalizing the eigenvector corresponding to the maximum eigenvalue of the judgment matrix, the weight sequence of the indicators at the same level to the indicators at the previous level can be obtained.

[0085] Table 2 Meaning of each matrix

[0086] Serial number matrix Degree Representative meaning 1 H1 8×8 AHP judgment matrix for power distribution energy consumption 2 H2 5×5 Power Quality Assessment AHP Judgment Matrix 3 H3 5×5 AHP Judgment Matrix for Power Consumption of Mechanical Equipment 4 H4 4×4 AHP Judgment Matrix for Energy Consumption of Thermal Energy Equipment 5 H5 2×2 AHP Judgment Matrix for Energy Consumption of Photovoltaic Equipment 6 H6 3×3 AHP judgment matrix for power supply monitoring system 7 H7 4×4 AHP judgment matrix of comprehensive index of unit product energy consumption 8 H8 7×7 AHP judgment matrix of unit product power consumption index 9 H9 6×6 AHP judgment matrix for power consumption evaluation indicators 10 H10 2×2 AHP judgment matrix of power energy consumption economic indicators

[0087] Table 3 Weight vector of each indicator

[0088]

[0089]

[0090] Step 4: Based on the weights of indicators at each level calculated in step 3, calculate the scores of indicators at each level, and conduct a quantitative evaluation of the energy efficiency of the cement plant based on the scores of indicators at each level.

[0091] In one embodiment of the present invention, the fuzzy evaluation method is used to calculate the scores of various indicators, including:

[0092] Step 401: For the third-level indicator Ak,j , calculate the third-level index score F k,j , determine the evaluation effect of each third-level indicator according to the score;

[0093] Step 402: Determine the weight ω of each third-level indicator k,j , for each second-level indicator A k (k=1,2...m), determine the weight ω of each third-level indicator it contains k,j , satisfying ω k,j >0;

[0094] Step 403: Calculate the score F of the second-level indicator k ,in, p k is the number of second-tier indicators, and the evaluation effect of each second-tier indicator is determined according to the score;

[0095] Step 404: Determine the weight ω of each second-layer indicator k , the evaluation target is the weight ω of each indicator in the indicator adjacency matrix k >0, and

[0096] Step 405: Calculate the comprehensive evaluation score F, where:

[0097] In one embodiment of the present invention, the third layer score F is calculated in step 401. k,j include:

[0098] The third-level indicators are scored according to the following formula:

[0099]

[0100] Among them, μ1(x), μ2(x), and μ3(x) are the membership functions of the third-level indicators, which are used to calculate the membership of the third-level energy indicators for good, medium, and poor; a1, a2, and a3 are the values ​​for judging the good, medium, and poor of the third-level indicators. The membership of each level of indicators and the calculation results are shown in Tables 4 and 5

[0101] Table 4 Function membership and index scores

[0102]

[0103]

[0104] Table 5 Secondary indicators and primary indicators scores

[0105]

[0106] The overall power efficiency of the cement production enterprise has reached a good level, with the scores of the two first-level indicators being 83.81 and 82.37 respectively. In recent years, the cement production enterprise has strengthened the construction and management of energy-saving systems, introduced an electric energy monitoring system, and assessed each production team. This measure is consistent with the evaluation result with the highest score for the power supply system measurement and monitoring indicators. The main reason for the low score of power distribution is the great influence of the efficiency of the indicator transformer. The enterprise mainly uses electric motors as the main power-consuming equipment. Since its load is intermittent, the equipment operation is flexibly adjusted according to the production tasks, the working hours fluctuate greatly, and the effective load rate is not high, which leads to relatively low scores for the transformer and power distribution energy consumption indicators.

[0107] Among the three-level scores, the pass rate of electric energy meters scored the highest, with a score of 90.2 points, and the lowest score was for transformer efficiency, with a score of 69.3 points. The scores of the secondary indicators were relatively balanced, with the highest score being the power supply system measurement and monitoring indicator, followed by the power-heat equipment energy consumption indicator. The reason for the high score of the power-heat equipment energy consumption indicator is that the thermal efficiency of the rotary kiln and the power consumption of the grate cooler under this secondary indicator scored high. The reason for the high scores of these two third-level indicators is that the cement company has updated and upgraded the grate cooler, replacing the original third-generation product with the fourth-generation product, which has improved the clinker cooling efficiency and the heat recovery level, reducing the clinker coal consumption by 2kg / t, from the original 109kg / t to 107kg / t, and reducing the power consumption by 1kW / t, significantly reducing the system energy consumption. In addition, the cement plant has expanded the capacity of the decomposition furnace, and the daily output of cement has increased by 200t, and the unit consumption has been reduced by 0.5kW / t, which also proves that the power consumption and thermal efficiency of the rotary kiln have scored very high.

[0108] The average load rate of the motor in the energy consumption index of electrical-mechanical equipment is relatively low, with a score of 79.72 points. Due to the particularity of cement production, high-power belts play an important role in electromechanical equipment. The cement conveying load is intermittent, and the operation of all electromechanical equipment is adjusted according to the adjustment of production tasks, resulting in large fluctuations in transportation volume and working hours. In addition, the belts used in cement production and transportation are relatively long, and there is a certain amount of idle time when starting, stopping and transferring. This idle time accounts for about 1 / 6 of the belt operation time. Therefore, the belt conveyor's electrical energy efficiency is relatively low.

[0109] At the same time, the present invention provides a cement plant energy efficiency quantitative analysis system, including an indicator adjacency matrix construction module, an indicator structure model construction module, an indicator weight calculation module and an indicator score calculation module, which is characterized by:

[0110] The indicator adjacency matrix construction module is used to obtain cement production energy efficiency indicator data, and use the explanatory structural model to sort out the hierarchical relationship between production energy efficiency indicators to obtain the indicator adjacency matrix;

[0111] The indicator structure model building module calculates the indicator reachability matrix based on the obtained indicator adjacency matrix and divides the indicator reachability matrix into levels to establish the indicator structure model;

[0112] The indicator weight calculation module calculates the weights of indicators at all levels based on the obtained indicator structure model;

[0113] The indicator score calculation module calculates the scores of indicators at each level based on the weights of the indicators at each level, and conducts quantitative evaluation of the energy efficiency of the cement plant based on the scores of indicators at each level.

[0114] The present disclosure may be a system, a method and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present disclosure.

[0115] A computer-readable storage medium may be a tangible device that can hold and store instructions used by an instruction execution device. A computer-readable storage medium may be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples of computer-readable storage media (a non-exhaustive list) include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a raised structure in a groove on which instructions are stored, and any suitable combination of the foregoing. As used herein, a computer-readable storage medium is not to be interpreted as a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse through a fiber optic cable), or an electrical signal transmitted through a wire.

[0116] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0117] The computer program instructions for performing the operation of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. Computer-readable program instructions may be executed completely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or completely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be customized by utilizing the state information of the computer-readable program instructions, and the electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present disclosure.

[0118] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents, and any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A cement plant energy efficiency quantitative analysis method, characterized in that: The method comprises the following steps: Step 1: Obtain cement production energy efficiency index data, use the explanatory structural model to sort out the hierarchical relationship between production energy efficiency indicators, and obtain the indicator adjacency matrix; Step 2: Calculate the indicator reachability matrix based on the indicator adjacency matrix obtained in step 1, and divide the indicator reachability matrix into levels to establish the indicator structure model; Step 3: Based on the indicator structure model obtained in step 2, calculate the weights of indicators at all levels; Step 4: Based on the weights of indicators at each level calculated in step 3, calculate the scores of indicators at each level, and conduct a quantitative evaluation of the energy efficiency of the cement plant based on the scores of indicators at each level.

2. A cement plant energy efficiency quantitative analysis method according to claim 1, characterized in that: In step 1, the cement production energy efficiency indicators include transformer and power distribution energy consumption indicators, power quality energy efficiency evaluation technical indicators, power-mechanical energy equipment energy consumption indicators, power-thermal energy equipment energy consumption indicators, power-light energy equipment energy consumption indicators, and power supply system measurement and monitoring indicators; The energy consumption assessment economic indicators include a comprehensive energy consumption indicator per unit product and a power consumption indicator per unit product.

3. The method for quantitative analysis of energy efficiency of a cement plant according to claim 1, characterized in that: In step 1, the hierarchical relationship between production energy efficiency indicators is sorted out using the explanatory structural model, and the indicator adjacency matrix is ​​obtained, including: The correlation and causality between the production energy efficiency indicators Si and Sj are judged, and the value is 0 or 1. The indicator adjacency matrix A is constructed based on the judgment results; Among them, 0 means that there is no direct influence between Si and Sj, that is, there is no coupling effect, and 1 means that there is a direct influence between Si and Sj, that is, there is a coupling effect.

4. A cement plant energy efficiency quantitative analysis method according to claim 1 or 3, characterized in that: In step 2, the calculation formula of the indicator reachability matrix P is as follows: P=(A+I) n+1 Among them, A represents the index adjacency matrix, I represents the identity matrix, and n represents the number of times the adjacency matrix plus the identity matrix are multiplied by themselves.

5. A cement plant energy efficiency quantitative analysis method according to claim 1, characterized in that: In step 2, the hierarchical division of the reachability matrix and the establishment of an indicator structure model include: Divide the reachable matrix P into the reachable set R(Si) and the predecessor set A(Si), calculate the intersection of R(Si) and A(Si), and get the highest index; The second-level index is obtained by crossing out the row corresponding to the highest index in the reachable matrix, and the third-level index is obtained by crossing out the column corresponding to the highest index in the reachable matrix; A directed graph is used to represent the hierarchical structure of the indicator structure model. The top layer corresponds to the highest-level indicator, followed by the second-level indicators and the third-level indicators.

6. A cement plant energy efficiency quantitative analysis method according to claim 5, characterized in that: The reachable set R(Si) is the set of column indices corresponding to matrix elements containing 1 in the row corresponding to the index Si in the reachable matrix.

7. A cement plant energy efficiency quantitative analysis method according to claim 5, characterized in that: The predecessor set A(Si) is a set of row indices corresponding to matrix elements containing 1 in the column corresponding to the index Si in the reachable matrix.

8. A cement plant energy efficiency quantitative analysis method according to claim 1, characterized in that: In step 3, the weights of indicators at all levels are calculated including: Step 301: construct a judgment matrix, the elements in the judgment matrix represent the relative importance of each pair of indicators at the same level, and a scale is used to represent the relative importance of the indicators; Step 302: Find the maximum eigenvalue of the judgment matrix; Step 303: Perform a consistency check on the judgment matrix. If the consistency check passes, proceed to step 304. If the consistency check fails, return to step 301 to reconstruct the judgment matrix. Step 304: normalize the eigenvector corresponding to the maximum eigenvalue of the judgment matrix to obtain a weight sequence of the same-level index to the previous-level index.

9. A cement plant energy efficiency quantitative analysis method according to claim 8, characterized in that: In step 303, the consistency check of the judgment matrix includes calculating the check coefficient according to the following formula: in, represents the consistency index; RI represents the average random consistency index of the judgment matrix; λmax is the maximum eigenvalue of the judgment matrix, and n is the order of the judgment matrix; if CR is less than 0.1, it is considered that the judgment matrix has passed the one-time test; if CR is greater than or equal to 0.1, it is considered that the judgment matrix has not passed the consistency test, and it is necessary to return to step A1 to reconstruct the judgment matrix.

10. A cement plant energy efficiency quantitative analysis method according to claim 1, 5 or 8, characterized in that: In step 4, the calculation of the scores of indicators at all levels includes: Step 401: For the third-level indicator A k,j , calculate the third-level index score F k,j , determine the evaluation effect of each third-level indicator according to the score; Step 402: Determine the weight ω of each third-level indicator k,j , for each second-level indicator A k (k=1,2...m), determine the weight ω of each third-level indicator it contains k,j , satisfying ω k,j >0; Step 403: Calculate the score F of the second-level indicator k ,in, p k is the number of second-tier indicators, and the evaluation effect of each second-tier indicator is determined according to the score; Step 404: Determine the weight ω of each second-layer indicator k , the evaluation target is the weight ω of each indicator in the indicator adjacency matrix k >0, and Step 405: Calculate the comprehensive evaluation score F, where:

11. A cement plant energy efficiency quantitative analysis method according to claim 10, characterized in that: In step 401, the third-level index score F is calculated. k,j include: The third-level indicators are scored according to the following formula: Among them, μ1(x), μ2(x), and μ3(x) are the membership functions of the third-layer indicators, which are used to calculate the membership of the third-layer energy indicators for good, medium, and poor; a1, a2, and a3 are the values ​​for judging the good, medium, and poor of the third-layer indicators.

12. A cement plant energy efficiency quantitative analysis system using the method according to any one of claims 1 to 11, comprising an indicator adjacency matrix construction module, an indicator structure model construction module, an indicator weight calculation module and an indicator score calculation module, characterized in that: The indicator adjacency matrix construction module is used to obtain cement production energy efficiency indicator data, and use the explanatory structural model to sort out the hierarchical relationship between production energy efficiency indicators to obtain the indicator adjacency matrix; The indicator structure model building module calculates the indicator reachability matrix based on the obtained indicator adjacency matrix and divides the indicator reachability matrix into levels to establish the indicator structure model; The indicator weight calculation module calculates the weights of indicators at all levels based on the obtained indicator structure model; The indicator score calculation module calculates the scores of indicators at each level based on the weights of the indicators at each level, and conducts quantitative evaluation of the energy efficiency of the cement plant based on the scores of indicators at each level.

13. A terminal comprising a processor and a storage medium; characterized in that: The storage medium is used to store instructions; The processor is configured to operate according to the instructions to execute the steps of the method according to any one of claims 1-11.

14. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to any one of claims 1 to 11 are implemented.

Images