Cement production optimization method and system based on energy consumption and output analysis

Abstract

The invention discloses a cement production optimization method and system based on energy consumption and output analysis. The method comprises the following steps: dividing production links of a cement production process and classifying the production links according to energy consumption types; energy consumption and output parameters of different types of production links are determined, and corresponding energy consumption and output data are collected; respectively calculating the energy efficiency of each production link based on a dynamic weight coefficient by adopting the energy consumption and output data; establishing an overall efficiency scoring model of the cement production process based on the energy consumption and output parameters, and inputting the energy consumption and output data into the overall efficiency scoring model to obtain an overall efficiency score of the cement production process; and identifying low-efficiency links based on the overall efficiency score and the energy efficiency of each production link, and performing optimization. The cement production energy efficiency can be scientifically, automatically and accurately optimized.

Description

Technical Field

[0001] The invention belongs to the technical field of cement production, and relates to a cement production optimization method and system based on energy consumption and output analysis. Background Art

[0002] At present, cement production is a typical high-energy consumption industry, and each production link consumes huge amounts of electricity and other energy. Therefore, it is particularly important to improve energy efficiency and optimize energy consumption management.

[0003] However, in the traditional cement production process, the energy consumption and output efficiency of each link vary significantly. Existing technologies are usually unable to effectively quantify the energy efficiency of each production link, and it is difficult to systematically and comprehensively analyze the specific energy consumption level and output efficiency of each production link, and it is difficult to accurately identify low-efficiency links, resulting in energy waste and increased costs. Therefore, it is difficult to effectively solve the imbalance between energy consumption and output efficiency in cement production. Summary of the invention

[0004] In order to solve the deficiencies in the prior art, the present invention provides a cement production optimization method and system based on energy consumption and output analysis, thereby scientifically, automatically and accurately optimizing the energy efficiency of cement production.

[0005] The present invention adopts the following technical solution.

[0006] The first aspect of the present invention proposes a cement production optimization method based on energy consumption and output analysis, comprising:

[0007] Step 1: Divide the production process of cement production and classify the production process according to energy consumption type;

[0008] Step 2: Determine the energy consumption and output parameters of different types of production links and collect corresponding energy consumption and output data;

[0009] Step 3: Using the energy consumption and output data, calculate the energy efficiency E of each production link based on the dynamic weight coefficient. i ;

[0010] Step 4: establishing an overall efficiency score model for the cement production process based on the energy consumption and output parameters, inputting the energy consumption and output data into the overall efficiency score model, and obtaining an overall efficiency score θ for the cement production process;

[0011] Step 5: Based on the overall efficiency score θ and the energy efficiency E of each production link i , identify inefficient links and optimize them.

[0012] Preferably, in step 1, the cement production process is divided into raw material preparation, raw material decomposition, clinker burning, waste heat utilization, cement grinding, powder selection, homogenization and packaging production links;

[0013] Preferably, in step 1, cement grinding, powder selection, homogenization, and packaging are classified as pure electricity consumption links;

[0014] Raw material preparation, raw material decomposition, clinker burning and waste heat utilization are classified as comprehensive energy consumption links.

[0015] Preferably, the step 2 of determining the energy consumption and output parameters of different types of production links includes:

[0016] The energy consumption parameter of the pure electricity consumption link is the power consumption Q i , the output parameter is the product output data

[0017] The energy consumption parameter of the comprehensive energy consumption link is the power consumption Q i , other energy consumption W i and output parameters are product output data

[0018] Among them, Q i , W i The units are kilowatt-hour and kilojoule. The unit is tons.

[0019] Preferably, in step 3, the energy efficiency of each production link is calculated using the energy consumption and output data, as follows:

[0020] For production link i, if it is a pure electricity consumption link, its energy efficiency is:

[0021]

[0022] If it is a comprehensive energy consumption link, its energy efficiency is:

[0023]

[0024] Among them, a and b are the dynamic weight coefficients of electric energy and other energy sources; is the theoretical maximum output of link i; λ is the efficiency correction coefficient; Q i is the power consumption of link i; W i is the other energy consumption of link i; is the output of link i.

[0025] Preferably, the dynamic weight coefficients a and b are recalculated when the system detects that the proportion of the power or other energy consumption of each link exceeds the set value, and the calculation method is:

[0026]

[0027] Among them, n is the total number of production links in the system; m is the total number of comprehensive energy consumption links in the system.

[0028] Preferably, the overall efficiency score model of the cement production process in step 4 is:

[0029]

[0030] Where: θ is the overall efficiency score of the cement production process; P ri is the product output of production link i;

[0031] X i Energy used for the product in production stage i; X i =(a*Q i +b*W i ), for the pure electricity consumption link, W i =0;Q i and W i are the actual electricity consumption and other energy consumption of production link i, respectively, and a and b are the weight coefficients of electricity and other energy;

[0032] u i and v i are the weight variables of output and energy consumption of production link i respectively; n is the number of production links in the cement production process.

[0033] Preferably, in step 5, the energy efficiency E of each production link is compared. i , the energy efficiency E i The lower production links are determined as inefficient links, and the inefficient links are optimized based on the optimization algorithm of linear programming, the ratio of electric energy to other energy sources in the inefficient links is adjusted, and the energy efficiency value of each link is dynamically updated;

[0034] Preferably, the optimization goal of optimizing the inefficient links by using the optimization algorithm based on linear programming is:

[0035]

[0036]

[0037] The constraints are:

[0038]

[0039] P total ≤P max (9)

[0040] Where θ is the overall efficiency score of the cement production process; is the product output of production link i;

[0041] X i Energy used for the product in production stage i; X i =(a*Qi +b*W i ), for the pure electricity consumption link, W i =0;Q i and W i are the actual electricity consumption and other energy consumption of production link i, respectively, and a and b are the weight coefficients of electricity and other energy;

[0042] u i and v i are the weight variables of output and energy consumption respectively; n is the number of production links in the cement production process;

[0043] P total , P max They are the total electricity consumption and the upper limit of electricity consumption of each production link in the cement production process respectively.

[0044] Preferably, in step 5, the overall efficiency score θ of the cement production process is also compared with a threshold value. If the overall efficiency score θ of the cement production process is lower than the threshold value, the weight variables u of the output and energy consumption of each production link are reconfigured. i and v i , recalculate the overall efficiency score to ensure global energy efficiency optimization of the system.

[0045] The second aspect of the present invention proposes a cement production optimization system based on energy consumption and output analysis, comprising:

[0046] The production link division and classification module is used to divide the production links of cement production process and classify the production links according to energy consumption type;

[0047] Data collection module, used to determine the energy consumption and output parameters of different types of production links and collect corresponding energy consumption and output data;

[0048] The energy efficiency calculation module is used to use the energy consumption and output data to calculate the energy efficiency E of each production link based on the dynamic weight coefficient. i ;

[0049] An overall efficiency score calculation module, used to establish an overall efficiency score model of the cement production process based on the energy consumption and output parameters, wherein the energy consumption and output data are input into the overall efficiency score model to obtain an overall efficiency score θ of the cement production process;

[0050] Optimization module, used to optimize the energy efficiency E of each production link based on the overall efficiency score θ i , identify inefficient links and optimize them.

[0051] A third aspect of the present invention provides a terminal, comprising 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 the method.

[0052] A fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the method when executed by a processor.

[0053] Compared with the prior art, the beneficial effects of the present invention include at least:

[0054] The present invention subdivides the cement production process, classifies and quantifies the energy consumption parameters of each link, and uses the data envelopment analysis (DEA) method to construct an overall "energy consumption-output" model to score the overall efficiency of the cement production process. The overall efficiency score of the cement production process can evaluate the relative efficiency of each production link, help cement companies identify and optimize links with high energy consumption, thereby reducing production costs and improving production efficiency.

[0055] The present invention uses the overall efficiency score model of cement production process as the overall "energy-output" model, which can monitor and evaluate the overall energy efficiency of the enterprise in real time and provide real-time data support. The model can dynamically track and adapt to changes in production conditions, significantly improving the resource utilization efficiency in the cement production process.

[0056] The present invention optimizes cement production based on the overall efficiency score and the energy efficiency of each link, significantly improving the energy efficiency management of cement production. By accurately quantifying the relationship between energy consumption and output of each production link, it can effectively identify low-efficiency links, provide targeted optimization solutions, and promote the improvement of overall energy efficiency.

[0057] The present invention can enable the model to flexibly respond to changes in the production environment through integrated real-time data monitoring and dynamic feedback mechanisms, ensure real-time reflection of energy efficiency status, and reduce energy waste and improve the overall economic benefits of cement production by identifying inefficient links and optimizing their energy usage structure. Through dynamic adjustment, continuous optimization and energy efficiency improvement of each production link are achieved, forming a sustainable energy-saving solution. In practical applications, the model can continuously improve the energy usage structure of cement production and achieve long-term effects of energy saving and consumption reduction.

[0058] The present invention adopts a systematic and comprehensive analysis process and optimization to subdivide the production process into multiple links, providing enterprises with comprehensive insights into energy consumption characteristics and output efficiency, supporting decision makers to make scientific optimization choices in process adjustment, equipment upgrades and resource allocation, and helping enterprises to formulate scientific energy-saving strategies. This not only helps to reduce energy consumption and waste emissions, in line with global requirements for sustainable production, but also significantly improves the economic benefits and market competitiveness of enterprises.

[0059] The model proposed in the present invention has good scalability and adaptability, and can be extended to energy efficiency optimization in other industries, helping enterprises to maintain their advantages in the fierce market competition, achieve sustainable development, and effectively reduce the energy consumption expenditure of enterprises.

[0060] When the present invention monitors that the proportional change of electric energy or other energy consumption in each link exceeds the set value, the system triggers the recalculation of weight coefficients a and b in the energy efficiency calculation model of the comprehensive energy consumption link to adapt to the dynamically changing production environment, which can effectively improve the energy efficiency accuracy of the comprehensive energy consumption link. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 is a flow chart of the method of the present invention;

[0062] Figure 2 This is a schematic diagram of the DEA analysis principle. DETAILED DESCRIPTION

[0063] 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 part of the embodiments of the present invention, not all of them. Based on the spirit of the present invention, other embodiments obtained by ordinary technicians in this field without creative work are all within the scope of protection of the present invention.

[0064] Embodiment 1 of the present invention provides a cement production optimization method based on energy consumption and output analysis, such as Figure 1 As shown, including:

[0065] Step 1: Divide the production process of cement production and classify the production process according to energy consumption type;

[0066] Further preferably, the cement production process is divided into a plurality of main links, including but not limited to raw material preparation, raw material decomposition, clinker burning, waste heat utilization, cement grinding, powder selection, homogenization and packaging; the specific links are as follows:

[0067] 1. Raw material preparation: including the crushing, screening and lifting of ore to prepare the required raw materials (such as limestone, clay, etc.).

[0068] 2. Raw material decomposition: refers to the process of preheating and decomposing raw materials in the rotary kiln to produce clinker. This process usually requires high temperature and involves a lot of energy consumption.

[0069] 3. Clinker firing: It is the process of firing raw materials at high temperature to produce clinker. This link consumes extremely high energy.

[0070] 4. Utilization of waste heat: Recover the waste heat generated during the clinker firing process and use it for drying or heating subsequent processes.

[0071] 5. Cement mill: Cement mill is used to grind clinker and other raw materials into cement, which consumes a lot of electricity.

[0072] 6. Powder selection: Separate the finely ground cement from the large particles to ensure that the fineness of the cement meets the standard.

[0073] 7. Homogenization: Treat cement to make it uniform to ensure the consistency of product quality.

[0074] 8. Packaging: Pack the cement products for easy transportation and storage.

[0075] According to the energy consumption structure of each production link, the above links are divided into the following two categories:

[0076] 1. Pure electricity consumption:

[0077] Definition: A process that relies solely on electricity to operate.

[0078] Expressed as Where Q i For power consumption, For output.

[0079] For example, in cement grinding, powder selection, homogenization and packaging, only the electricity consumption is considered.

[0080] 2. Comprehensive energy use:

[0081] Definition: In addition to electricity consumption, it also involves other energy sources (such as natural gas, coal, etc.).

[0082] Format: Expressed as Where Wi is other energy consumption.

[0083] For example, in the stages of raw material preparation, raw material decomposition, clinker burning and waste heat utilization, the consumption of electricity and other energy (such as fuel and heat) should be considered.

[0084] Step 2: Determine the energy consumption and output parameters of different types of production links and collect corresponding energy consumption and output data;

[0085] Further preferably, the parameters of the pure electricity consumption link include power consumption (Q i ) and output

[0086] The parameters of comprehensive energy consumption include power consumption (Q i ), other energy consumption (W i ) and output

[0087] Design an integrated monitoring device to collect the actual power consumption (Q i) and other energy consumption (W i ) data in kilowatt-hours (kWh) and kilojoules (kJ), and collect the corresponding product output data The unit is ton (t).

[0088] Step 3: Use the energy consumption and output data to calculate the energy efficiency E of each production link i ;

[0089] Preferably, a multi-step analysis method is used to independently evaluate the energy efficiency of each production link, and the energy efficiency of a link is iteratively calculated in each step, and then gradually optimized using a linear programming method.

[0090] For production link i, if it is a pure electricity-consuming link, its energy efficiency is calculated using the following formula:

[0091]

[0092] Where: E i is the energy efficiency of production link i; Q i is the electricity consumption of production link i; is the output of production link i.

[0093] If it is a comprehensive energy consumption link, its energy efficiency model takes into account the consumption of electricity and other energy sources and is calculated using the following formula:

[0094]

[0095] Among them, a and b are the dynamic weight coefficients of electric energy and other energy sources; is the theoretical maximum output of link i; λ is the efficiency correction coefficient, which measures the optimization potential of the link and ranges from [0,1]; Q i is the power consumption of link i; W i is the other energy consumption of link i; is the output of link i.

[0096] a and b represent the relative importance of the weight coefficients of electric energy and other energy sources in the energy efficiency model. The dynamic weight coefficients a and b are recalculated when the system detects that the proportion of electric energy or other energy consumption in each link changes by more than 10%. The calculation method is:

[0097]

[0098] Among them, n is the total number of production links in the system; m is the total number of comprehensive energy consumption links in the system.

[0099] Step 4: establishing an overall efficiency score model for the cement production process based on the energy consumption and output parameters, inputting the energy consumption and output data into the overall efficiency score model, and obtaining an overall efficiency score θ for the cement production process;

[0100] More preferably, by Figure 2 The data envelopment analysis (DEA) method shown in the figure quantifies the "energy-output" efficiency in the cement production process. Each production link is taken as a decision-making unit (DMU), and its energy input and output efficiency are analyzed. The efficiency of each link is quantified through a multi-input and multi-output method. The input variables of each production link include the power consumption Q i (The comprehensive energy consumption also includes other energy consumption W i ), the output variable is the output include:

[0101] Efficiency frontier analysis: DEA is used to analyze the relationship between energy consumption and output of each link, and efficiency scores are generated to form an "efficiency frontier", which can effectively quantify the relative efficiency of different links and help identify inefficient links with high energy consumption and low output. Links below the efficiency frontier will be identified as inefficient links.

[0102] The overall efficiency score model of the cement production process is:

[0103]

[0104] Where: θ is the overall efficiency score of the cement production process;

[0105] is the product output of production link i;

[0106] X i Energy used for the product in production stage i; X i =(a*Q i +b*W i ), for the pure electricity consumption link, W i =0;Q i and W i are the actual electricity consumption and other energy consumption of production link i, respectively, and a and b are the weight coefficients of electricity and other energy;

[0107] u i and v i They are weight variables for output and energy consumption, which can be set based on historical experience;

[0108] n is the number of production links in the cement production process.

[0109] The overall efficiency scoring model of the cement production process mentioned above is an overall "energy-output" model, which can monitor and evaluate the overall energy efficiency of the enterprise in real time and provide real-time data support. The model can dynamically track and adapt to changes in production conditions, significantly improving the resource utilization efficiency in the cement production process.

[0110] Step 5: Based on the overall efficiency score θ and the energy efficiency E of each production link i , identify inefficient links and optimize them.

[0111] Further preferably, the overall efficiency score θ is used as the "efficiency frontier" of DEA. When the efficiency score of the entire system is lower than a preset threshold (for example, 0.8), the system will automatically trigger the redistribution of the weights of each link and recalculate the overall efficiency score to ensure global energy efficiency optimization of the system.

[0112] Compare the energy efficiency of each production link i , the energy efficiency E i The lower production link is determined as an inefficient link, and the inefficient link is optimized based on the optimization algorithm of linear programming, the ratio of electric energy to other energy sources in the inefficient link is adjusted, and the target energy efficiency value of the link is dynamically updated;

[0113] DEA analysis methods usually use linear programming optimization methods to minimize electricity consumption and other energy consumption under given output conditions. When optimizing the inefficient links, the optimization goal can be expressed as the following linear programming equation:

[0114]

[0115] The constraints are:

[0116] v i ≥0 to meet the non-negativity requirement of DEA analysis,

[0117] P total ≤P max (9)

[0118] Among them, θ is the overall efficiency score of the cement production process, and a score of 1 indicates optimal efficiency;

[0119] is the product output of production link i; X i Energy used for the product in production stage i; Q i and W i are the actual electricity consumption and other energy consumption of production link i, respectively, and a and b are the weight coefficients of electricity and other energy;

[0120] u i and v iare the weight variables of output and energy consumption respectively; n is the number of production links in the cement production process;

[0121] P total , P max They are the total electricity consumption and the upper limit of electricity consumption of each production link in the cement production process respectively.

[0122] For inefficient links, the above linear programming optimization can minimize their energy consumption under given output conditions. Optimization methods include: reducing electricity consumption (Q i ) or other energy consumption (W i ); Increase production through equipment upgrades or process improvements

[0123] The optimization priority is determined according to the following logic:

[0124] (1) Links where energy efficiency is lower than the system average;

[0125] (2) Links with relatively large absolute energy consumption (such as clinker burning);

[0126] (3) Prioritize the optimization links with lower cost and higher feasibility.

[0127] The optimization process of DEA analysis method and the automatic adjustment module can continuously adjust the power consumption Q of inefficient links. i and other energy consumption W i , ensuring that energy consumption in each link is minimized. Through linear programming solution and feedback control, the automatic adjustment module can effectively reduce the energy consumption expenditure of the enterprise.

[0128] For the above P total , the calculation example is given by taking the following link as an example.

[0129] (1) Raw material preparation

[0130] In the raw material preparation process, the relationship between electricity consumption and raw material output can usually be assumed to be linear. The formula can be expressed as:

[0131] P raw =a raw ×Q raw +b raw

[0132] in:

[0133] P raw Power for raw material preparation;

[0134] Q raw is the raw material output, i.e. Parameter value;

[0135] a rawand b raw is the empirical coefficient.

[0136] (2) Raw material decomposition

[0137] The raw material decomposition process involves chemical reactions, which are usually nonlinear. Assume that the energy consumption of the decomposition furnace varies with output and temperature as follows:

[0138]

[0139] in:

[0140] P decomp The power of raw material decomposition;

[0141] is the output of the decomposition furnace;

[0142] T is the decomposition temperature;

[0143] a decomp , α, β and b decomp It is an empirical parameter and its specific value needs to be obtained through experiments or historical data fitting.

[0144] (3) Clinker firing

[0145] The energy consumption of the clinker burning process is mainly affected by temperature and load rate, which usually shows a nonlinear relationship. Assume that the power demand of this link is:

[0146]

[0147] in:

[0148] P clinker The power of clinker burning;

[0149] Q clinker is the clinker output;

[0150] T is the firing temperature;

[0151] a clinker , γ, δ and b clinker is an empirical parameter.

[0152] (4) Waste heat utilization

[0153] The efficiency of waste heat utilization is related to the exhaust gas temperature and load rate generated by the kiln, which is usually nonlinear. The waste heat recovery power can be expressed as:

[0154] P waste_heat =μ wh ×Q exhaust ×(T exhaust -T ambient )

[0155] in:

[0156] P waste_heat is the power of waste heat recovery;

[0157] μ wh The efficiency of waste heat utilization;

[0158] Q exhaust is the exhaust gas flow rate;

[0159] T exhaust and T ambient are the exhaust gas temperature and the ambient temperature, respectively.

[0160] (5) Cement mill

[0161] The energy consumption of cement mill and the output of ground cement are linearly related within a certain range, and the formula can be:

[0162] P grinding =a grind ×Q grinding +b grind

[0163] in:

[0164] P grinding is the power of cement mill;

[0165] Q grinding is the cement mill output;

[0166] a grind and b grind is the linear coefficient.

[0167] (6) Packaging

[0168] The energy consumption in the packaging process is linearly related to the packaging speed or output, which can be expressed as:

[0169] P pack =a pack ×Q pack +b back

[0170] in:

[0171] P pack is the power of the package;

[0172] Q pack is the packaging volume;

[0173] a pack and b back is the linear coefficient.

[0174] Total power P total =P raw +P decomp +Pclinker +P waste_heat +P grinding +P pack

[0175] Should satisfy P total ≤P max , which is used as a constraint in DEA analysis to more accurately simulate and optimize the energy consumption of each link in the cement production process. The specific parameter value can be determined through data collection and historical data fitting.

[0176] Further preferably, the method may also include: according to the above DEA method analysis results, after dynamically optimizing and adjusting the energy consumption structure of each link, monitoring the overall efficiency score θ of the optimized cement production process, and using real-time, historical, and predicted data to adjust the overall efficiency score model parameter u of the cement production process through a dynamic feedback mechanism. i and v i Make dynamic adjustments to continuously optimize production efficiency.

[0177] It can also summarize the energy efficiency data of all links to provide a basis for energy-saving optimization for enterprises. By analyzing and fitting the historical data of the efficiency of each production link and the overall efficiency score θ, the corresponding trend curve can be generated for the enterprise's energy-saving strategy formulation.

[0178] In addition to the above-mentioned overall efficiency score θ, the efficiency evaluation index of the present invention also proposes scale efficiency (ScaleEfficiency): Among them, θ CRS is the constant scale efficiency; θ VRS is the variable scale efficiency. In the specific implementation, the overall efficiency score θ before and after optimization is taken respectively.

[0179] The above-mentioned overall efficiency score θ is the technical efficiency indicator: it evaluates the efficiency of each production link on the optimal boundary and is used to identify inefficient links; the scale efficiency indicator SE measures the impact of changes in production scale on energy efficiency and forms a visual analysis report, regularly reviews the improvement of energy efficiency, and gradually adjusts the model parameters based on internal management feedback.

[0180] The present invention can also use visualization tools (such as line graphs and bar graphs) to display the efficiency of each link, so that the enterprise management can intuitively understand and analyze the data, generate a decision support report containing detailed energy consumption analysis for the enterprise, and put forward suggestions for adjusting the production process, optimizing energy configuration or upgrading equipment.

[0181] The present invention can also set key performance indicators (KPIs) for improving energy efficiency, such as comparing efficiency scores based on the reduction in energy consumption per unit of output, and regularly monitoring the improvement effect. Based on the DEA analysis results, measures such as engineering technology improvements (such as introducing high-efficiency equipment) and optimizing process flows can be adopted to further improve energy efficiency and reduce costs.

[0182] The examples are as follows:

[0183] A large cement production company has been facing the challenge of rising production costs in the past few years, especially in terms of energy costs. In order to improve production efficiency and reduce energy consumption, the company optimized cement production based on energy consumption and output analysis, including:

[0184] Step 1: Identify the various stages of cement production and classify the production stages;

[0185] (1) The enterprise first divides the production process into the following main links:

[0186] Raw material preparation: Crushing, screening and lifting of ore, energy consumption mainly comes from electricity.

[0187] Raw material decomposition: The raw materials are heated in a rotary kiln to decompose and produce clinker, which is a high energy consumption process.

[0188] Clinker firing: The decomposed raw materials are fired at high temperature, which consumes the most energy.

[0189] Waste heat utilization: Recover the waste heat generated during the firing process.

[0190] Cement mill: Grinding clinker into cement mainly relies on electricity.

[0191] Subsequent steps include powder selection, homogenization, packaging, etc.

[0192] (2) Classification of production links

[0193] 1. Raw material preparation

[0194] Category: Comprehensive energy consumption

[0195] Rationale: It involves ore crushing, screening and lifting, which, although mainly dependent on electricity, may involve mechanical energy consumption and other energy sources (such as fuel equipment).

[0196] 2. Raw material decomposition

[0197] Category: Comprehensive energy consumption

[0198] Reason: The pyrolysis process requires a lot of electrical energy and other energy (such as fuel) to support it.

[0199] 3. Clinker firing

[0200] Category: Comprehensive energy consumption

[0201] Reason: High-temperature firing is extremely energy-intensive and usually involves the dual consumption of electricity and fuel (such as coal or natural gas).

[0202] 4. Utilization of waste heat

[0203] Category: Comprehensive energy consumption

[0204] Rationale: Recovery and utilization of waste heat may involve electricity consumption for heat conversion equipment.

[0205] 5. Cement mill

[0206] Category: Pure electricity consumption

[0207] Reason: Grinding clinker into cement mainly through electric powered equipment.

[0208] 6. Select powder

[0209] Category: Pure electricity consumption

[0210] Reason: Material separation by electric equipment is completely dependent on electricity.

[0211] 7. Homogenization

[0212] Category: Pure electricity consumption

[0213] Rationale: Homogenization processes primarily use electrically driven stirring or vibrating equipment.

[0214] 8. Packaging

[0215] Category: Pure electricity consumption

[0216] Reason: The packaging process involves automated equipment and conveying equipment, which are completely dependent on electricity.

[0217] Step 2: Determine the energy consumption and output parameters of different types of production links and collect corresponding energy consumption and output data;

[0218] The company collected the actual electricity consumption, other energy consumption and output data of each link, and the units are as follows: Electricity consumption Q i is the electricity consumption, kilowatt-hour (kWh); is the output, tons (t); Wi is the energy consumption of other energy sources, kilojoules (kJ), the data are shown in Table 1:

[0219] Table 1

[0220]

[0221] Step 3: Use the energy consumption and output data and dynamic weight coefficient to calculate the energy efficiency E of each production link. i ;

[0222] Use formula (3) (4) to dynamically calculate the electric energy weight coefficient a and other energy weight coefficient b:

[0223]

[0224] get:

[0225]

[0226] According to formulas (1) and (2), the energy efficiency of each link is calculated:

[0227]

[0228] Assumptions Combined with the optimization potential coefficient λ = 0.2, a = 0.375, b = 0.625, the energy efficiency of each link is shown in Table 2:

[0229] Table 2

[0230]

[0231] Step 4: DEA analysis: Calculate the overall efficiency score using formula (3):

[0232]

[0233] Assume u i and v i = 1, rounding a = 0.375, b = 0.625 above to a = 0.4, b = 0.6, then:

[0234] Total output:

[0235] Total energy consumption: ∑X i =(0.6*1200+0.4*800)+…+(0.6*600+0.4*0)=15500 units of energy consumption;

[0236]

[0237] Step 5: Identify inefficient links and optimize them;

[0238] By comparing the energy efficiency of each link, inefficient links are identified: it is found that clinker burning and waste heat utilization are relatively inefficient links and the optimization measures are relatively simple.

[0239] Optimization measures:

[0240] (1) Clinker firing:

[0241] It is recommended to introduce high-efficiency kiln technology, which is expected to reduce energy consumption by 15%.

[0242] Optimize ingredients and reduce heat loss.

[0243] (2) Waste heat utilization:

[0244] Improving the efficiency of waste heat recovery equipment is expected to increase energy efficiency by 20%.

[0245] After optimization, the energy consumption of clinker burning and waste heat utilization was reduced, and the overall efficiency score was recalculated. As shown in Table 3.

[0246] Table 3

[0247] Links Energy efficiency before optimization (tons / unit energy consumption) Energy efficiency after optimization (tons / unit energy consumption) Clinker firing 0.010 0.011 Waste heat utilization 0.030 0.033

[0248] Overall efficiency score after optimization:

[0249]

[0250] The overall energy consumption was reduced by 3.2%; the overall efficiency score was increased from 0.034 to 0.035; the energy efficiency of clinker burning and waste heat utilization was improved, the energy cost was reduced, and a scientific basis was provided for the enterprise to save energy and reduce consumption.

[0251] By implementing the "energy consumption-output" DEA analysis of cement production based on power load analysis, the company has achieved remarkable results in reducing energy consumption, improving production efficiency and optimizing resource allocation, laying a solid foundation for subsequent continuous improvement and development.

[0252] Embodiment 2 of the present invention provides a cement production optimization system based on energy consumption and output analysis, the system comprising:

[0253] The production link division and classification module is used to divide the production links of cement production process and classify the production links according to energy consumption type;

[0254] Data collection module, used to determine the energy consumption and output parameters of different types of production links and collect corresponding energy consumption and output data;

[0255] The energy efficiency calculation module is used to use the energy consumption and output data to calculate the energy efficiency E of each production link based on the dynamic weight coefficient. i ;

[0256] An overall efficiency score calculation module, used to establish an overall efficiency score model of the cement production process based on the energy consumption and output parameters, wherein the energy consumption and output data are input into the overall efficiency score model to obtain an overall efficiency score θ of the cement production process;

[0257] Optimization module, used to optimize the energy efficiency E of each production link based on the overall efficiency score θ i , identify inefficient links and optimize them.

[0258] Embodiment 3 of the present invention provides a terminal, including 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 the method.

[0259] Embodiment 4 of the present invention provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the method when executed by a processor.

[0260] Compared with the prior art, the beneficial effects of the present invention include at least:

[0261] The present invention subdivides the cement production process, classifies and quantifies the energy consumption parameters of each link, and uses the data envelopment analysis (DEA) method to construct an overall "energy consumption-output" model to score the overall efficiency of the cement production process. The overall efficiency score of the cement production process can evaluate the relative efficiency of each production link, help cement companies identify and optimize links with high energy consumption, thereby reducing production costs and improving production efficiency.

[0262] The present invention optimizes cement production based on the overall efficiency score and the energy efficiency of each link, significantly improving the energy efficiency management of cement production. By accurately quantifying the relationship between energy consumption and output of each production link, it can effectively identify low-efficiency links, provide targeted optimization solutions, and promote the improvement of overall energy efficiency.

[0263] The present invention can enable the model to flexibly respond to changes in the production environment through integrated real-time data monitoring and dynamic feedback mechanisms, ensure real-time reflection of energy efficiency status, and reduce energy waste and improve the overall economic benefits of cement production by identifying inefficient links and optimizing their energy usage structure. Through dynamic adjustment, continuous optimization and energy efficiency improvement of each production link are achieved, forming a sustainable energy-saving solution. In practical applications, the model can continuously improve the energy usage structure of cement production and achieve long-term effects of energy saving and consumption reduction.

[0264] The present invention adopts a systematic and comprehensive analysis process and optimization to subdivide the production process into multiple links, providing enterprises with comprehensive insights into energy consumption characteristics and output efficiency, supporting decision makers to make scientific optimization choices in process adjustment, equipment upgrades and resource allocation, and helping enterprises to formulate scientific energy-saving strategies. This not only helps to reduce energy consumption and waste emissions, in line with global requirements for sustainable production, but also significantly improves the economic benefits and market competitiveness of enterprises.

[0265] The model proposed in the present invention has good scalability and adaptability, and can be extended to energy efficiency optimization in other industries, helping enterprises to maintain their advantages in the fierce market competition, achieve sustainable development, and effectively reduce the energy consumption expenditure of enterprises.

[0266] When the present invention monitors that the proportional change of electric energy or other energy consumption in each link exceeds the set value, the system triggers the recalculation of weight coefficients a and b in the energy efficiency calculation model of the comprehensive energy consumption link to adapt to the dynamically changing production environment, which can effectively improve the energy efficiency accuracy of the comprehensive energy consumption link.

[0267] 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.

[0268] 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.

[0269] 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.

[0270] 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.

[0271] 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 production optimization method based on energy consumption and output analysis, characterized in that: include: Step 1: Divide the production process of cement production and classify the production process according to energy consumption type; Step 2: Determine the energy consumption and output parameters of different types of production links and collect corresponding energy consumption and output data; Step 3: Using the energy consumption and output data, calculate the energy efficiency E of each production link based on the dynamic weight coefficient. i ; Step 4: establishing an overall efficiency score model for the cement production process based on the energy consumption and output parameters, inputting the energy consumption and output data into the overall efficiency score model, and obtaining an overall efficiency score θ for the cement production process; Step 5: Based on the overall efficiency score θ and the energy efficiency E of each production link i , identify inefficient links and optimize them.

2. The cement production optimization method based on energy consumption and output analysis according to claim 1 is characterized in that: In step 1, the cement production process is divided into raw material preparation, raw material decomposition, clinker burning, waste heat utilization, cement grinding, powder selection, homogenization and packaging production links.

3. The cement production optimization method based on energy consumption and output analysis according to claim 2 is characterized in that: In step 1, cement grinding, powder selection, homogenization, and packaging are classified as pure electricity consumption links; Raw material preparation, raw material decomposition, clinker burning and waste heat utilization are classified as comprehensive energy consumption links.

4. The cement production optimization method based on energy consumption and output analysis according to claim 1 is characterized in that: Step 2 determines the energy consumption and output parameters of different types of production links, including: The energy consumption parameter of the pure electricity consumption link is the power consumption Q i , the output parameter is the product output data The energy consumption parameter of the comprehensive energy consumption link is the power consumption Q i , other energy consumption W i and output parameters are product output data Among them, Q i , W i The units are kilowatt-hour and kilojoule. The unit is tons.

5. The cement production optimization method based on energy consumption and output analysis according to claim 4 is characterized in that: In step 3, the energy efficiency of each production link is calculated using the energy consumption and output data, as follows: For production link i, if it is a pure electricity consumption link, its energy efficiency is: If it is a comprehensive energy consumption link, its energy efficiency is: Among them, a and b are the dynamic weight coefficients of electric energy and other energy sources; is the theoretical maximum output of link i; λ is the efficiency correction coefficient; Q i is the power consumption of link i; W i is the other energy consumption of link i; is the output of link i.

6. The cement production optimization method based on energy consumption and output analysis according to claim 5 is characterized in that: The dynamic weight coefficients a and b are recalculated when the system detects that the proportion of electricity or other energy consumption in each link exceeds the set value. The calculation method is: Among them, n is the total number of production links in the system; m is the total number of comprehensive energy consumption links in the system.

7. The cement production optimization method based on energy consumption and output analysis according to claim 1 is characterized in that: The overall efficiency score model of the cement production process described in step 4 is: Where: θ is the overall efficiency score of the cement production process; is the product output of production link i; X i Energy used for the product in production stage i; X i =(a*Q i +b*W i ), for the pure electricity consumption link, W i =0;Q i and W i are the actual electricity consumption and other energy consumption of production link i, respectively, and a and b are the weight coefficients of electricity and other energy; u i and v i are the weight variables of output and energy consumption of production link i respectively; n is the number of production links in the cement production process.

8. The cement production optimization method based on energy consumption and output analysis according to claim 1, characterized in that: In step 5, compare the energy efficiency E of each production link i , the energy efficiency E i The lower production links are determined to be inefficient links, and the inefficient links are optimized based on the optimization algorithm of linear programming, the ratio of electric energy to other energy sources in the inefficient links is adjusted, and the energy efficiency value of each link is dynamically updated.

9. The cement production optimization method based on energy consumption and output analysis according to claim 8 is characterized in that: The optimization goal of optimizing the inefficient links based on the optimization algorithm of linear programming is: The constraints are: P total ≤P max (9) Where θ is the overall efficiency score of the cement production process; is the product output of production link i; X i Energy used for the product in production stage i; X i =(a*Q i +b*W i ), for the pure electricity consumption link, W i =0;Q i and W i are the actual electricity consumption and other energy consumption of production link i, respectively, and a and b are the weight coefficients of electricity and other energy; u i and v i are the weight variables of output and energy consumption respectively; n is the number of production links in the cement production process; P total , P max They are the total electricity consumption and the upper limit of electricity consumption of each production link in the cement production process respectively.

10. The cement production optimization method based on energy consumption and output analysis according to claim 8, characterized in that: In step 5, the overall efficiency score θ of the cement production process is also compared with the threshold. If the overall efficiency score θ of the cement production process is lower than the threshold, the weight variables u of the output and energy consumption of each production link are reconfigured. i and v i , recalculate the overall efficiency score to ensure global energy efficiency optimization of the system.

11. A cement production optimization system based on energy consumption and output analysis, using the method according to any one of claims 1 to 10, characterized in that: The system comprises: The production link division and classification module is used to divide the production links of cement production process and classify the production links according to energy consumption type; Data collection module, used to determine the energy consumption and output parameters of different types of production links and collect corresponding energy consumption and output data; The energy efficiency calculation module is used to use the energy consumption and output data to calculate the energy efficiency E of each production link based on the dynamic weight coefficient. i ; An overall efficiency score calculation module, used to establish an overall efficiency score model of the cement production process based on the energy consumption and output parameters, wherein the energy consumption and output data are input into the overall efficiency score model to obtain an overall efficiency score θ of the cement production process; Optimization module, used to optimize the energy efficiency E of each production link based on the overall efficiency score θ i , identify inefficient links and optimize them.

12. 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 1-10.

13. 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 10 are implemented.

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