Online evaluation method and system for coal blending combustion effect of coal-fired power plant

Abstract

The embodiment of the invention provides a coal-fired power plant coal blending combustion effect online evaluation method and system, and the method comprises the steps: collecting the operation data in real time, and carrying out the preprocessing, and constructing a multi-dimensional evaluation system which covers the safety, economy and environmental protection. The method specifically comprises the following steps: calculating an equipment safety score, a load capacity score and a slag-bonding feedback score based on equipment operation parameters, and comprehensively obtaining a safety score; calculating an overall economic evaluation score and a power supply cost score based on the power supply coal consumption and the fuel cost, and comprehensively obtaining an economic score; calculating an environmental protection score according to the deviation between the pollutant emission concentration and the standard and optimal values; and finally, weighting the scores of the three dimensions according to a preset weight to obtain a total score. According to the method, quantitative models such as fuzzy logic and a neural network are adopted, the problems that an existing evaluation method is single in dimension, depends on subjective experience and is poor in real-time performance are solved, comprehensive, accurate and online dynamic evaluation on the coal blending combustion effect is achieved, and a scientific basis is provided for operation optimization.

Description

Technical Field

[0001] This invention relates to the field of coal blending evaluation technology in coal-fired power plants, and particularly to an online evaluation method and system for the effect of coal blending in coal-fired power plants. Background Technology

[0002] In the operation of coal-fired power plants, coal blending technology serves as a crucial means to optimize fuel cost structure and flexibly adapt to coal market fluctuations. The comprehensiveness and accuracy of its effect evaluation are vital for improving overall unit operating efficiency and ensuring safe production. However, current practices in evaluating the effects of coal blending in coal-fired power plants still face several key issues that urgently need to be addressed: First, the evaluation dimensions exhibit a significant limitation. When assessing the effects of co-firing, most power plants tend to overemphasize economic indicators (such as coal consumption rate for power generation) or environmental indicators (such as emission concentrations of pollutants like SO2 and NOx), while seriously neglecting key factors that directly affect equipment safety and operational stability, such as overloaded operation of coal mills and slagging on boiler heating surfaces. This one-sided evaluation approach can easily lead to an imbalance between the three objectives of safety, economy, and environmental protection, and may even cause serious consequences such as equipment damage.

[0003] Secondly, the lack of quantitative standards leads to excessive subjectivity in evaluation. Currently, the assessment of key parameters such as the degree of boiler slagging still relies heavily on the experience and judgment of operators, using qualitative descriptions such as "severe / slight slagging" without unified and objective quantitative standards. This subjective evaluation not only makes it difficult to guarantee the accuracy and comparability of the evaluation results, but also fails to provide a scientific basis for optimizing co-firing schemes.

[0004] Third, the lack of real-time evaluation severely restricts the dynamic optimization of co-firing schemes. Currently, most power plants still use offline data processing methods to evaluate the effects of co-firing, summarizing and analyzing data daily or monthly. This lagging evaluation model cannot capture short-term changes in the effects of co-firing schemes in a timely manner, nor can it provide real-time adjustment suggestions for operators. In the long run, the units may be in an inefficient or high-risk operating state for an extended period, affecting the economic benefits and safe production of the power plant.

[0005] In specific cases, one power plant, after blending low-quality coal, saw a reduction in coal consumption for power generation, but the output of its coal mill remained at 115% of its rated value for an extended period. Due to the lack of real-time evaluation of equipment safety, this ultimately led to damage to the coal mill bearings, resulting in significant economic losses. Another power plant focused solely on whether SO2 emissions met standards, failing to quantify the gap between "compliant" and "optimal" emission levels, thus missing the opportunity to further reduce environmental costs by fine-tuning the blending ratio. Therefore, developing a comprehensive, quantitatively accurate, and real-time online evaluation scheme for coal blending effects has become an urgent need for coal-fired power plants to improve their operational management and ensure safe production. Summary of the Invention

[0006] This invention provides an online evaluation method and system for the effect of coal blending in coal-fired power plants, in order to solve the problems of existing coal blending effect evaluation schemes having a single evaluation dimension, lack of unified quantitative standards, and poor real-time performance.

[0007] In a first aspect, embodiments of the present invention provide an online evaluation method for the blending effect of coal in coal-fired power plants, comprising: Real-time acquisition and preprocessing of operational data from coal-fired power plants; wherein the operational data includes pulverizer output, fan output, flue gas velocity, economizer inlet temperature, low-temperature reheater inlet temperature, actual coal consumption for power generation, designed coal consumption for power generation of different coal types, blending ratio of each type of coal, calorific value of each type of coal, price of each type of coal, transportation price of each type of coal, SO2 emission concentration, NO emission concentration, etc. x Emission concentration, particulate matter emission concentration, pollutant emission standards, and optimal operating levels for pollutants; Based on the preprocessed operating data, the equipment safety score, load capacity score, and slagging feedback score are calculated, and a comprehensive safety score is obtained. The equipment safety score is calculated based on the output of the coal mill, the output of the blower, and the flue gas velocity. The load capacity score is calculated based on the actual output of the auxiliary equipment and the rated output. The slagging feedback score is calculated based on the inlet temperature of the economizer and the inlet temperature of the low-temperature reheater. The overall economic evaluation score and power supply cost score are calculated based on the preprocessed operating data, and the economic score is obtained by combining them. The overall economic evaluation score is calculated based on the actual coal consumption for power supply and the coal consumption for power supply of the designed coal type. The power supply cost score is calculated based on the actual coal consumption for power supply, the blending ratio of each single coal, the calorific value of a single coal, the price of a single coal, and the transportation price of a single coal. Based on SO2 emission concentration, NO x The environmental score is calculated based on emission concentration, particulate matter emission concentration, pollutant emission standards, optimal operating levels of pollutants, and preset weighting coefficients for each pollutant. The safety score, economic score, and environmental score are weighted according to preset weights to obtain the total score.

[0008] Preferably, after calculating the total score, the method further includes: Based on the total score and the scores at each level, a tree diagram of the evaluation results is generated; The tree diagram includes first-level nodes, second-level nodes, and third-level nodes. The first-level nodes are used to display the total score and the corresponding evaluation level. The second-level nodes are used to display the safety score, economic score, and environmental score. The third-level nodes are used to display the equipment safety score, load capacity score, slagging feedback score, overall economic evaluation score, and power supply cost score, and include the calculation basis for each score. When the total score or any level score is lower than a preset threshold, an early warning is automatically triggered and corresponding adjustment suggestions are pushed to the operator's terminal.

[0009] Preferred online evaluation methods for the effects of coal blending in coal-fired power plants also include: Set an evaluation update cycle, and repeat the entire process from data collection from coal-fired power plants to calculation of the total score according to the evaluation update cycle, and update the evaluation results in real time; Adjust the coal blending ratio or unit operating parameters based on the updated evaluation results, continuously track the adjusted operating data and update the evaluation results to verify the adjustment effect.

[0010] Preferably, the real-time acquisition and preprocessing of operational data from coal-fired power plants includes: Real-time reading of operational data from the distributed control system (DCS) or data acquisition system (DAS) of coal-fired power plants; The operating data is filtered and denoised to remove outliers that exceed the normal operating range of ±3σ, where σ is the standard deviation of historical data.

[0011] Preferably, the step of calculating the equipment safety score, load capacity score, and slagging feedback score based on the preprocessed operating data, and then comprehensively obtaining the safety score, includes: The ratio of actual output to rated output of coal mill, ratio of actual output to rated output of fan, and flue gas velocity are processed by fuzzy logic model to output equipment safety score; Calculate the ratio of the actual output of each auxiliary machine to the rated output of the corresponding auxiliary machine, take the arithmetic mean of each ratio to obtain the average output rate of the auxiliary machine, and output the load capacity score according to the value of the average output rate of the auxiliary machine and the preset rules. Based on the economizer inlet temperature change rate and the low-temperature reheater inlet temperature change rate, the degree of slagging is predicted by a pre-trained BP neural network model, and the slagging feedback score is calculated based on the degree of slagging. The safety score is obtained by taking the arithmetic mean of the equipment safety score, load capacity score, and slagging feedback score.

[0012] Preferably, the step of calculating the overall economic evaluation score and the power supply cost score based on the preprocessed operating data, and then comprehensively obtaining the economic score, includes: To obtain the actual coal consumption for power supply and the designed coal consumption for power supply of different coal types, use formula E. co =100-(b g -b g,s ) Calculate the overall economic evaluation score; where E co For the overall economic evaluation score, b g b represents the actual coal consumption for power supply. g,s Coal consumption for power supply based on the designed coal type; According to formula Q avg =Σ(α i ·Q i Calculate the weighted average calorific value of the mixed coal, where α i Let Q be the blending ratio of the i-th type of single coal. i Let i be the calorific value of the i-th type of coal; According to the formula Pu'=bg×29310 / Q avg ×[α1(P1+Ptr1)+α2(P2+Ptr2)+...+α n (P n +Ptr n )]×10 -6 Calculate the unit fuel cost for electricity supply, Pu'; where 29310 is the standard coal calorific value coefficient, and P... n For the price per unit of coal, Ptr n The price for each individual coal shipment; The unit power supply fuel cost Pu' is converted into a positive index Pu according to the formula Pu=1 / Pu'. The power supply cost score is then output according to the linear mapping rule based on the value of the positive index. The economic score is obtained by taking the arithmetic mean of the overall economic evaluation score and the power supply cost score.

[0013] Preferably, the formula for calculating the environmental score is: I=100{0.6+0.4·[λ1(SO 2S -SO2) / (SO 2S -SO 2min )+λ2(NO xs -NO x ) / (NO xs -NO xmin )+λ3(φ s -φ) / (φ s -φ min )]} Where I represents the environmental score; λ1, λ2, and λ3 represent SO2, NO, and NO, respectively. x The weighting coefficients for smoke and dust, and λ1+λ2+λ3=1; SO 2S The standard for SO2 pollutant emissions, where SO2 is the SO2 emission concentration. 2min For SO2, the optimal operating level is achieved; NO xs NO x Pollutant emission standards, NO x For actual NO x Emission concentration, NO xmin NO x Optimal operating level; φ s The emission standard for particulate matter is given by φ, where φ is the particulate matter emission concentration. min This represents the optimal operating level for smoke and dust.

[0014] Secondly, an embodiment of the present invention provides an online evaluation system for the blending effect of coal in a coal-fired power plant, comprising: The data acquisition module is used to acquire and preprocess the operating data of the coal-fired power plant in real time. The operating data includes the output of the coal mill, the output of the blower, the flue gas velocity, the economizer inlet temperature, the low-temperature reheater inlet temperature, the actual coal consumption for power supply, the designed coal consumption for power supply of the coal type, the blending ratio of each coal type, the calorific value of each coal type, the price of each coal type, the transportation price of each coal type, the SO2 emission concentration, the NOx emission concentration, the particulate matter emission concentration, the pollutant emission standards, and the optimal operating level of pollutants. The safety evaluation module is used to calculate the equipment safety score, load capacity score, and slagging feedback score based on preprocessed operating data, and to obtain a comprehensive safety score. The equipment safety score is calculated based on the output of the coal mill, the output of the fan, and the flue gas velocity. The load capacity score is calculated based on the actual output of the auxiliary equipment and the rated output. The slagging feedback score is calculated based on the economizer inlet temperature and the low-temperature reheater inlet temperature. The economic evaluation module is used to calculate the overall economic evaluation score and the power supply cost score based on the preprocessed operating data, and to obtain a comprehensive economic score. The overall economic evaluation score is calculated based on the actual coal consumption for power supply and the designed coal consumption for power supply of different coal types. The power supply cost score is calculated based on the actual coal consumption for power supply, the blending ratio of each coal type, the calorific value of each coal type, the price of each coal type, and the transportation price of each coal type. The environmental performance evaluation module is used to calculate the environmental performance score based on SO2 emission concentration, NOx emission concentration, particulate matter emission concentration, pollutant emission standards, optimal operating levels of pollutants, and preset weight coefficients for each pollutant. The comprehensive scoring module is used to calculate the total score by weighting the safety score, economic score, and environmental score according to preset weights.

[0015] Thirdly, the present invention also provides an electronic device, including a memory and a processor, wherein, The memory is used to store programs; The processor, coupled to the memory, is used to execute the program stored in the memory to implement the steps in the online evaluation method for coal blending effect in coal-fired power plants as described in the first aspect embodiment of the present invention.

[0016] Fourthly, the present invention also provides a computer-readable storage medium for storing a computer-readable program or instruction, which, when executed by a processor, can perform the steps in the online evaluation method for coal blending effect in coal-fired power plants as described in the first aspect embodiment of the present invention.

[0017] The online evaluation method and system for coal blending effect in coal-fired power plants provided in this invention have the following advantages compared with the prior art: (1) This invention breaks through the limitations of traditional single indicators and constructs a three-level evaluation system that integrates safety, economy, and environmental protection. By collecting multi-source data such as equipment operation, pollutant emissions, and fuel costs in real time, the system calculates equipment safety, load capacity, and slagging feedback scores to form a safety evaluation; it integrates power supply coal consumption and fuel costs to form an economic evaluation; and it combines multi-pollutant weighted calculations to achieve an environmental evaluation. Finally, the weighted summaries are used to obtain a total score. This multi-dimensional evaluation mechanism can simultaneously identify problems that are easily overlooked by traditional methods, such as slagging risk and equipment overload, and achieve a comprehensive and accurate assessment of the co-firing effect.

[0018] (2) To address the problem of relying on manual experience in traditional evaluations, this invention establishes a complete quantitative scoring system, transforming traditional qualitative descriptions such as coal mill overload and boiler slagging into precise scores of 0-100 points. In particular, a BP neural network model is used to establish a quantitative correlation between the economizer and reheater temperature change rate and the degree of slagging; a linear mapping rule is used to convert the auxiliary equipment output rate into a load capacity score; and a specific formula is used to convert multi-coal cost parameters into power supply cost scores. This effectively eliminates subjective judgment bias and provides a scientific and accurate basis for optimizing blending schemes.

[0019] (3) This invention sets an evaluation update cycle of 5-10 minutes, updates the results in real time, adjusts parameters based on the results, and continuously tracks and verifies. This real-time online evaluation can reflect the effects in a timely manner, help operators make quick adjustments, avoid inefficient or high-risk operation of the unit, and improve efficiency and safety. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 The flowchart of the online evaluation method for coal blending effect in coal-fired power plants provided by the present invention is shown below. Figure 2 This is a structural block diagram of the online evaluation system for coal blending effect in coal-fired power plants provided in an embodiment of the present invention.

[0022] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] The naming or numbering of steps in the embodiments of the present invention does not mean that the steps in the method flow must be executed in the time / logical order indicated by the naming or numbering. The execution order of the named or numbered process steps can be changed according to the technical purpose to be achieved, as long as the same or similar technical effect can be achieved.

[0025] Figure 1 The flowchart of the online evaluation method for coal blending effect in coal-fired power plants provided by the present invention is shown below. Figure 1 The method includes: Step S1: Acquire real-time operating data of coal-fired power plants and perform data preprocessing; In this context, the operational data of a coal-fired power plant refers to a set of key parameters directly obtained from the power plant's control system, reflecting the real-time status of the unit. In this embodiment, the operational data includes mill output, fan output, flue gas velocity, economizer inlet temperature, low-temperature reheater inlet temperature, actual coal consumption for power generation, designed coal consumption for power generation of different coal types, blending ratio of each type of coal, calorific value of each coal type, price of each coal type, transportation price of each coal type, SO2 emission concentration, and NO emission concentration. x Emission concentration, soot emission concentration, pollutant emission standards, and optimal operating levels for pollutants.

[0026] In this embodiment, the operating data in the distributed control system (DCS) or data acquisition system (DAS) of the coal-fired power plant is read in real time at a frequency of 1 time / minute. The operating data is then filtered and denoised to remove outliers that exceed the range of ±3σ under normal operating conditions, thus obtaining pre-processed effective data.

[0027] Step S2: Based on the preprocessed operating data, calculate the equipment safety score, load capacity score, and slagging feedback score, and then combine them to obtain the overall safety score.

[0028] The equipment safety score is calculated based on the output of the coal mill, the output of the fan, and the flue gas velocity; the load capacity score is calculated based on the actual output of the auxiliary equipment and the rated output; and the slagging feedback score is calculated based on the economizer inlet temperature and the low-temperature reheater inlet temperature.

[0029] Specifically, the equipment safety score reflects the safe operation of coal-fired power plant equipment during coal blending and combustion. It is calculated by analyzing parameters closely related to equipment safety, such as mill output, fan output, and flue gas velocity. The load capacity score reflects the load-bearing capacity of power plant equipment during coal blending and combustion, calculated based on the relationship between the actual output and rated output of auxiliary equipment. The slagging feedback score assesses the slagging situation of the boiler during coal blending and combustion, calculated based on changes in economizer inlet temperature and low-temperature reheater inlet temperature. The safety score is a comprehensive safety evaluation index that integrates the scores of equipment safety, load capacity, and slagging feedback, reflecting the impact of coal blending and combustion on the overall safety of the coal-fired power plant.

[0030] Step S3: Calculate the overall economic evaluation score and power supply cost score based on the preprocessed operating data, and obtain the overall economic score.

[0031] The overall economic evaluation score is calculated based on the actual coal consumption for power supply and the designed coal consumption for power supply of different coal types. The power supply cost score is calculated based on the actual coal consumption for power supply, the blending ratio of each type of coal, the calorific value of each type of coal, the price of each type of coal, and the transportation price of each type of coal.

[0032] Existing economic evaluation methods are generally one-dimensional: they only focus on coal consumption for power generation, ignoring actual cost factors such as coal price and transportation cost. For example, coal types with low coal consumption but high prices may result in higher total costs, failing to fully reflect the economic value of blending. Therefore, this invention constructs a two-dimensional economic evaluation system of "coal consumption + cost" to accurately quantify the actual economic effects of blending schemes, providing a basis for optimizing the blending ratio of coal types.

[0033] Step S4, based on SO2 emission concentration, NO xThe environmental score is calculated based on emission concentration, soot emission concentration, pollutant emission standards, optimal operating levels of pollutants, and preset weighting coefficients for each pollutant.

[0034] Environmental friendliness is an indispensable indicator for evaluating the effect of coal blending and combustion. Although existing technologies pay attention to environmental friendliness, they lack unified and objective quantitative standards.

[0035] This embodiment will use SO2 emission concentration and NO... x The emission concentrations and particulate matter emission concentrations are compared with pollutant emission standards and optimal operating levels, respectively, and calculated in conjunction with preset weighting coefficients for each pollutant. For example, for each pollutant, the difference between its emission concentration and the emission standard, as well as its proximity to the optimal operating level, are calculated. Then, these are weighted and summed according to the weighting coefficients to obtain an environmental score.

[0036] Step S5: The safety score, economic score, and environmental score are weighted according to preset weights to obtain the total score.

[0037] Specifically, based on the actual conditions of the coal-fired power plant and the evaluation requirements, weighting coefficients for safety, economic efficiency, and environmental performance scores are pre-set. For example, the safety weight is 0.4, the economic efficiency weight is 0.3, and the environmental performance weight is 0.3. The safety score obtained in step S2, the economic score obtained in step S3, and the environmental performance score obtained in step S4 are multiplied by their respective weighting coefficients, and then added together to obtain the total score.

[0038] This invention breaks through the limitations of traditional single-indicator evaluations, constructing a three-tiered evaluation system integrating safety, economy, and environmental protection. By collecting multi-source data in real time, including equipment operation, pollutant emissions, and fuel costs, it calculates scores for equipment safety, load capacity, and slagging feedback to form a safety evaluation; it integrates power supply coal consumption and fuel costs to form an economic evaluation; and it combines multi-pollutant weighted calculations to achieve an environmental evaluation. Finally, a weighted summary is obtained for the overall score. This multi-dimensional evaluation mechanism can simultaneously identify problems that are easily overlooked by traditional methods, such as slagging risk and equipment overload, achieving a comprehensive and accurate assessment of the co-firing effect.

[0039] In some embodiments of this application, after the total score is calculated in step S5, the online evaluation method for the coal blending effect of coal-fired power plants further includes: Based on the total score and the scores at each level, a tree diagram of the evaluation results is generated; wherein, the tree diagram includes first-level nodes, second-level nodes and third-level nodes, the first-level nodes are used to display the total score and the corresponding evaluation level, the second-level nodes are used to display the safety score, economic score and environmental score, and the third-level nodes are used to display the equipment safety score, load capacity score, slagging feedback score, overall economic evaluation score and power supply cost score, and include the calculation basis for each score; When the total score or any level score is lower than a preset threshold, an early warning is automatically triggered and corresponding adjustment suggestions are pushed to the operator's terminal.

[0040] Specifically, a tree diagram of the evaluation results is generated based on the total score and the scores at each level. The tree diagram contains first-level nodes, second-level nodes, and third-level nodes. The first-level nodes display the total score and the corresponding evaluation level. The evaluation level is determined by the total score: a total score of 90 or higher is excellent, 80 to 89 is good, 70 to 79 is average, and less than 70 is poor. The second-level nodes display the safety score, economic score, and environmental score, corresponding to the safety score calculated in step S2, the economic score calculated in step S3, and the environmental score calculated in step S4, respectively. The three-level nodes display equipment safety scores, load capacity scores, slagging feedback scores, overall economic evaluation scores, and power supply cost scores. Each three-level node includes the calculation basis for the corresponding score: the equipment safety score is calculated based on the output of the coal mill, the output of the fan, and the flue gas velocity; the load capacity score is calculated based on the average output rate of the auxiliary equipment calculated from the actual output and rated output; the slagging feedback score is calculated based on the economizer inlet temperature change rate, the low-temperature reheater inlet temperature change rate, and the trained BP neural network model; the overall economic evaluation score is calculated based on the actual coal consumption for power supply and the coal consumption for power supply of the designed coal type; and the power supply cost score is calculated based on the actual coal consumption for power supply, the blending ratio of each single coal, the calorific value of a single coal, the price of a single coal, and the transportation price of a single coal.

[0041] The system presets score thresholds for each level, for example, 60 points as the preset threshold. When the total score is lower than the preset threshold, or any of the safety, economic, or environmental scores in the second-level node is lower than the preset threshold, or any of the equipment safety, load capacity, slagging feedback, overall economic evaluation, or power supply cost scores in the third-level node is lower than the preset threshold, the system automatically triggers an audible and visual warning. Simultaneously, the system pushes corresponding adjustment suggestions to the operator's terminal. For example, when the slagging feedback score is lower than the threshold, suggestions are made to reduce the furnace heat load and check the sootblower's operating status; when the environmental score is lower than the threshold, suggestions are made to increase the proportion of low-sulfur coal blending; and when the equipment safety score is lower than the threshold, suggestions are made to reduce the coal mill output.

[0042] This embodiment generates a tree diagram to clearly and intuitively display the evaluation results of coal blending and combustion effects, as well as the score details at each level, allowing operators to quickly understand the overall and local situation. When the score falls below the threshold, an automatic warning is issued and adjustment suggestions are pushed, enabling timely detection of problems and guiding operators to take measures. This effectively improves the coal blending and combustion effect, ensures the safe, economical, and environmentally friendly operation of the power plant, reduces operational risks and costs, and improves energy utilization efficiency and pollutant control levels.

[0043] In some embodiments of this application, the online evaluation method for the coal blending effect in coal-fired power plants further includes: Set an evaluation update cycle, and repeat steps S1 to S5 above from data collection from coal-fired power plants to calculation of the total score according to the evaluation update cycle, and update the evaluation results in real time. Based on the updated evaluation results, operators adjust the coal blending ratio or unit operating parameters accordingly: if the environmental score is low, the blending ratio of low-sulfur coal is increased; if the equipment safety score is insufficient, the output of the coal mill or blower is reduced. After the adjustment, the adjusted operating data is continuously collected according to the evaluation update cycle, and the data preprocessing, score calculation for each dimension, and total score calculation steps are repeated to update the evaluation results. By comparing the evaluation results before and after the adjustment, the improvement effect of the adjustment measures on the coal blending effect is verified. If the score of the corresponding dimension improves after the adjustment, it indicates that the adjustment is effective; if the score does not improve, the adjustment plan is further optimized.

[0044] This embodiment updates results in real time by setting an evaluation update cycle of 5-10 minutes, and adjusts parameters based on the results for continuous tracking and verification. This real-time online evaluation can promptly reflect the effects, helping operators to make quick adjustments, avoid inefficient or high-risk operation of the unit, and improve efficiency and safety.

[0045] In some embodiments of this application, step S2, which involves calculating the equipment safety score, load capacity score, and slagging feedback score based on the preprocessed operating data, and then comprehensively obtaining the safety score, includes: The ratio of actual output to rated output of coal mill, ratio of actual output to rated output of fan, and flue gas velocity are processed by fuzzy logic model to output equipment safety score; Calculate the ratio of the actual output of each auxiliary machine to the rated output of the corresponding auxiliary machine, take the arithmetic mean of each ratio to obtain the average output rate of the auxiliary machine, and output the load capacity score according to the value of the average output rate of the auxiliary machine and the preset rules. Based on the economizer inlet temperature change rate and the low-temperature reheater inlet temperature change rate, the degree of slagging is predicted by a pre-trained BP neural network model, and the slagging feedback score is calculated based on the degree of slagging. The safety score is obtained by taking the arithmetic mean of the equipment safety score, load capacity score, and slagging feedback score.

[0046] Specifically, in the equipment safety score calculation stage, the actual output of the coal mill, the rated output of the coal mill, the actual output of the blower, the rated output of the blower, and the flue gas velocity are extracted from the pre-processed operating data. The ratio of the actual output of the coal mill to the rated output and the ratio of the actual output of the blower to the rated output are calculated respectively. These two output ratios and the flue gas velocity are input into a pre-constructed fuzzy logic model. The model has preset rules for the correspondence between input and output scores. Based on the range of the output ratio of the coal mill and the blower (e.g., ≤90%, 90%-100%, 100%-110%, >110%) and the range of the flue gas velocity (e.g., ≤15m / s, 15-18m / s, 18-20m / s, >20m / s), the corresponding rules are matched to output an equipment safety score of 0-100 points.

[0047] In the load capacity score calculation stage, the auxiliary machines involved in the calculation are identified as coal mills, forced draft fans, and induced draft fans. The actual output and corresponding rated output of each auxiliary machine are extracted from the pre-processed operating data, and the ratio of actual output to rated output for each auxiliary machine is calculated. The sum of these ratios for all auxiliary machines is then divided by the number of auxiliary machines to obtain the average output rate of the auxiliary machines. A pre-defined rule for the correspondence between the average output rate of the auxiliary machines and the score is established. Based on the output rate range (e.g., ≤90%, 90%-100%, 100%-110%, >110%), the load capacity score from 0 to 100 is output according to the matching rule.

[0048] In the slagging feedback score calculation stage, the economizer inlet temperature and the low-temperature reheater inlet temperature for the current and previous evaluation periods are extracted from the pre-processed operational data. Combined with the preset evaluation update cycle length, the economizer inlet temperature change rate (the difference between the current cycle temperature and the previous cycle temperature divided by the update cycle length) and the low-temperature reheater inlet temperature change rate are calculated respectively. These two temperature change rates are input into a pre-trained BP neural network model, which has been trained on over 300 sets of historical temperature change rate-slagging degree data from power plants. The input layer consists of the two temperature change rates, the hidden layer has 8-12 neurons, and the output layer represents the slagging degree score from 0 to 10. The slagging feedback score is calculated using the formula: Slagging Feedback Score = 100 - 10 × Slagging Degree.

[0049] Finally, calculate the safety score. Add the equipment safety score, load capacity score, and slagging feedback score together, divide by 3, and take the arithmetic mean to obtain the final safety score.

[0050] This embodiment establishes a complete quantitative scoring system, transforming traditional qualitative descriptions such as coal mill overload and boiler slagging into precise scores ranging from 0 to 100. Specifically, a BP neural network model is used to establish a quantitative correlation between the economizer and reheater temperature change rates and the degree of slagging; a linear mapping rule is used to convert auxiliary equipment output rates into load capacity scores; and a specific formula is used to convert multi-coal cost parameters into power supply cost scores. This effectively eliminates subjective judgment bias and provides a scientific and accurate basis for optimizing blending schemes.

[0051] In some embodiments of this application, step S3, which involves calculating the overall economic evaluation score and the power supply cost score based on the preprocessed operating data, and then combining them to obtain the overall economic score, includes: First, obtain the actual coal consumption for power supply and the designed coal consumption for power supply of different coal types from the preprocessed operating data, and then use formula E... co =100-(b g -b g,s ) Calculate the overall economic evaluation score; where E co For the overall economic evaluation score, b g b represents the actual coal consumption for power supply. g,s The coal consumption for power generation is designed based on the coal type. If the calculated E... co If the score is greater than 120, then 120 is taken as the overall economic evaluation score; if E co If the score is less than 0, then 0 is taken as the overall economic evaluation score, so as to ensure that the score is within a reasonable range and accurately reflects the impact of the deviation between the actual coal consumption for power supply and the design benchmark on the economy.

[0052] Next, according to formula Q avg =Σ(α i ·Q i Calculate the weighted average calorific value of the mixed coal, where α i Let Q be the blending ratio of the i-th type of single coal. i Let be the calorific value of the i-th type of single coal. The weighted average calorific value of the blended coal is obtained by multiplying the blending ratio of each type of single coal by its calorific value and summing the results. This calorific value is used to calculate the unit fuel cost for power generation and reflects the overall energy characteristics of the blended coal.

[0053] According to the formula Pu'=bg×29310 / Q avg ×[α1(P1+Ptr1)+α2(P2+Ptr2)+...+α n (P n +Ptr n )]×10 -6 Calculate the unit fuel cost for electricity supply, Pu'; where 29310 is the standard coal calorific value coefficient, and P... n For the price per unit of coal, Ptr nThis represents the transportation price for each individual coal unit. [α1(P1+Ptr1)+α2(P2+Ptr2)+...+α] n (P n +Ptr n The total cost per unit mass of mixed coal (including purchase and transportation costs) can be represented by this formula, which can accurately quantify the fuel cost consumed for every 1 kWh of electricity output.

[0054] Then, the power supply cost score is calculated. The unit power supply fuel cost Pu' is converted into a positive index Pu using the formula Pu=1 / Pu'. The larger the Pu value, the lower the unit cost and the better the economic efficiency. Subsequently, the power supply cost score is determined according to the linear mapping rule: if Pu≥0.005kWh / yuan, the power supply cost score is 100 points; if Pu≤0.003kWh / yuan, the power supply cost score is 40 points; if Pu is between 0.003kWh / yuan and 0.005kWh / yuan, the score is calculated using the formula Power Supply Cost Score=30000Pu-50, achieving a reasonable correspondence between cost and score.

[0055] Finally, the economic performance score is calculated. The overall economic evaluation score is added to the power supply cost score, then divided by 2 and the arithmetic mean is taken to obtain the final economic performance score. This score comprehensively reflects the economic performance of the unit in terms of both coal consumption optimization and cost control.

[0056] This embodiment establishes a complete economic evaluation system by separately calculating the overall economic evaluation score reflecting operational efficiency and the power supply cost score reflecting cost control. This method not only focuses on the traditional economic indicator of coal consumption but also innovatively introduces multi-coal cost calculation, incorporating fuel procurement prices, transportation costs, and calorific value characteristics into the evaluation scope. Ultimately, a comprehensive and objective economic score is obtained through integrated calculation, providing a scientific and precise quantitative basis for the economic optimization of blending schemes.

[0057] In some embodiments of this application, the formula for calculating the environmental score in step S4 is as follows: I=100{0.6+0.4·[λ1(SO 2S -SO2) / (SO 2S -SO 2min )+λ2(NO xs -NO x ) / (NO xs -NO xmin )+λ3(φ s -φ) / (φ s -φ min )]} Where I represents the environmental score; λ1, λ2, and λ3 represent SO2, NO, and NO, respectively. x The weighting coefficients for smoke and dust, and λ1+λ2+λ3=1; SO2S The standard for SO2 pollutant emissions, where SO2 is the SO2 emission concentration. 2min For SO2, the optimal operating level is achieved; NO xs NO x Pollutant emission standards, NO x For actual NO x Emission concentration, NO xmin NO x Optimal operating level; φ s The emission standard for particulate matter is given by φ, where φ is the particulate matter emission concentration. min This represents the optimal operating level for smoke and dust.

[0058] First, real-time emission concentration data for three main pollutants—sulfur dioxide, nitrogen oxides, and particulate matter—are collected. This real-time data is then comprehensively compared with preset pollutant emission standards and optimal operating levels. Pollutant emission standards are mandatory limits set by environmental regulations, while optimal operating levels represent the best emission values ​​that the power plant can achieve under ideal conditions, typically set at 50% of the emission standards.

[0059] In calculating the environmental performance score, the relative position of the emission level of each pollutant with respect to the standard and the optimal value is calculated separately. For each pollutant, the difference between the emission standard and the actual emission concentration is calculated, and then divided by the difference between the emission standard and the optimal operating level. This calculation quantifies the relative position of the current emission level between the compliance line and the optimal line. When the actual emission concentration just meets the emission standard, the ratio of this sub-item is zero; when the optimal operating level is reached, the ratio of this sub-item is one.

[0060] The system assigns configurable weighting coefficients to the three pollutants, with the sum of the three weighting coefficients always being one. This allows power plants to flexibly adjust the evaluation focus according to regional environmental policy requirements and operational priorities, such as increasing the weighting coefficient for sulfur dioxide in areas with key sulfur control requirements.

[0061] This embodiment, by clearly defining the weighting coefficients for each pollutant, can highlight the degree of impact of different pollutants on environmental performance based on actual conditions. Comprehensive data on pollutant emission standards, actual emission concentrations, and optimal operating levels are collected and used to calculate an environmental performance score using a specific formula. This score accurately reflects the gap between pollutant emissions and standards during coal blending and combustion, as well as the degree of proximity to optimal operating levels, helping power plants to adjust coal blending schemes in a timely manner and reduce pollutant emissions.

[0062] In some embodiments of this application, the actual operation process and effect verification process of the system of the present invention are fully demonstrated through a 600MW unit example of three types of coal co-firing.

[0063] First, let's define the basic parameters for the case: bituminous coal blending ratio α1=50%, calorific value Q1=25000kJ / kg, price P1=800 yuan / t, transportation price Ptr1=50 yuan / t; lignite blending ratio α2=30%, calorific value Q2=18000kJ / kg, price P2=500 yuan / t, transportation price Ptr2=40 yuan / t; lean coal blending ratio α3=20%, calorific value Q3=22000kJ / kg, price P3=650 yuan / t, transportation price Ptr3=45 yuan / t.

[0064] The first step is to preset the parameters, setting the coal consumption for power generation (bg,s) to 290g / kWh and the SO2 emission standard (SO2s) to 50mg / Nm³. 3 NO x Pollutant Emission Standard NO x s=50mg / Nm 3 Emission standards for particulate matter φ s =20mg / Nm 3 ;Optimal operating level of SO2 2min =25mg / Nm 3 NO x Optimal operating level NO x min=25mg / Nm 3 The optimal operating level for smoke and dust is φmin = 10 mg / Nm³. 3 The evaluation period is 5 minutes; the weights for safety, economy, and environmental protection are 30%, 40%, and 30%, respectively.

[0065] The second step is to calculate the safety score. Regarding equipment safety, the coal mill output is 92% of its rated value, the fan output is 88% of its rated value, and the flue gas velocity is 17 m / s. According to the fuzzy rules, this scores 90 points. Regarding load capacity, the auxiliary equipment included in the calculation consists of two coal mills, two forced draft fans, and one induced draft fan. The output rates of each auxiliary equipment are 92%, 92%, 88%, 88%, and 90%, respectively. The average output rate of the auxiliary equipment is (92%+92%+88%+88%+90%) / 5=90%, resulting in a score of 100. Regarding slagging feedback, the economizer inlet temperature change rate ΔT1 / Δt=0.3℃ / min and the low-temperature reheater inlet temperature change rate ΔT2 / Δt=0.2℃ / min. The BP neural network outputs a slagging degree score of 0, resulting in a score of 100. The overall safety score is (90+100+100) / 3≈96.7 points.

[0066] The third step is to calculate the economic score. Regarding the overall economic evaluation score, the actual coal consumption for power generation (b) is... g =285g / kWh, substituting into the formula Eco=100-(285-290)=105 points; regarding the score for power supply cost, first use the formula Q avg=0.5×25000+0.3×18000+0.2×22000=22300kJ / kg Calculate the weighted average calorific value of the mixed coal; then substitute it into the formula Pu'=285×29310 / 22300×[0.5×(800+50)+0.3×(500+40)+0.2×(650+45)]×10 -6 The unit fuel cost for power generation is calculated as approximately 0.25 yuan / kWh; it is converted to a positive index using the formula Pu=1 / 0.25=4kWh / yuan, and then scored according to the linear mapping rule = 30000×0.004-50=70 points; the economic score is (105+70) / 2=87.5 points.

[0067] The fourth step is to calculate the environmental score, given that the SO2 emission concentration is 30 mg / Nm³. 3 NO x Emission concentration = 28 mg / Nm 3 Smoke and dust emission concentration = 12 mg / Nm 3 The weight coefficients for each pollutant are λ1=λ2=λ3=1 / 3; calculate the individual factors (50-30) / (50-25)=0.8, (50-28) / (50-25)=0.88, (20-12) / (20-10)=0.8 respectively; substitute them into the formula I=100×[0.6+0.4×(0.8+0.88+0.8) / 3]≈85.1 points.

[0068] The fifth step is to calculate the overall score. The overall score is approximately 90.0 points (96.7×30%+87.5×40%+85.1×30%), which is rated as excellent. The overall score, the second-level dimension score, and the third-level sub-module score are displayed in a tree diagram. No score is lower than the preset threshold, and no warning is triggered.

[0069] The sixth step involves dynamic optimization, increasing the lignite blending ratio to 40% after one hour, and reducing SO2 emission concentration to 26 mg / Nm³. 3 The environmental performance score rose to 89.3 points, and the overall score improved to 91.2 points, verifying the optimization effect of the co-firing scheme.

[0070] In addition, the implementation process also involved model adaptation and anomaly handling. Regarding model adaptation, for the blending of three coal types, the economic evaluation module automatically expanded the calculation dimension of the weighted average calorific value of the blended coal, while the environmental evaluation module maintained its weight setting logic without requiring additional code modifications. Regarding anomaly handling, when the DCS system failed to transmit economizer inlet temperature data, the data acquisition module automatically used the average of the previous three temperatures as temporary data to avoid evaluation interruption, and automatically corrected the data once it was restored. Simultaneously, optimization verification was conducted. Under the initial blending scheme, the environmental score was 72 points. The system suggested increasing the lignite blending ratio to 40%, after which the SO2 emission concentration decreased to 32 mg / Nm³.3 The environmental protection score rose to 81 points, verifying the guiding value of the evaluation method for co-firing schemes.

[0071] This embodiment verifies the practicality and effectiveness of the system of the present invention through complete operational data. The system can comprehensively and quantitatively evaluate multi-coal blending schemes, accurately reflect the operational status in terms of safety, economy, and environmental protection, and guide operational adjustments through a dynamic optimization mechanism. Examples demonstrate that the system has good engineering adaptability, can automatically handle data anomalies, and significantly improves environmental performance by optimizing blending ratios, providing a reliable online decision support tool for coal-fired power plant coal blending management.

[0072] Figure 2 The above is a structural block diagram of the online evaluation system for coal blending effect in coal-fired power plants provided by the present invention, with reference to... Figure 2 The online evaluation system for the blending effect of coal in coal-fired power plants includes: The data acquisition module 201 is used to acquire and preprocess the operating data of the coal-fired power plant in real time. The operating data includes the output of the coal mill, the output of the blower, the flue gas velocity, the economizer inlet temperature, the low-temperature reheater inlet temperature, the actual coal consumption for power supply, the designed coal consumption for power supply of the coal type, the blending ratio of each coal type, the calorific value of each coal type, the price of each coal type, the transportation price of each coal type, the SO2 emission concentration, the NOx emission concentration, the particulate matter emission concentration, the pollutant emission standards, and the optimal operating level of pollutants. The safety evaluation module 202 is used to calculate the equipment safety score, load capacity score, and slagging feedback score based on the pre-processed operating data, and to obtain a comprehensive safety score. The equipment safety score is calculated based on the output of the coal mill, the output of the fan, and the flue gas velocity. The load capacity score is calculated based on the actual output of the auxiliary equipment and the rated output. The slagging feedback score is calculated based on the inlet temperature of the economizer and the inlet temperature of the low-temperature reheater. The economic evaluation module 203 is used to calculate the overall economic evaluation score and the power supply cost score based on the preprocessed operating data, and to obtain a comprehensive economic score. The overall economic evaluation score is calculated based on the actual power supply coal consumption and the designed coal type power supply coal consumption, and the power supply cost score is calculated based on the actual power supply coal consumption, the blending ratio of each single coal, the calorific value of a single coal, the price of a single coal, and the transportation price of a single coal. The environmental performance evaluation module 204 is used to calculate the environmental performance score based on SO2 emission concentration, NOx emission concentration, particulate matter emission concentration, pollutant emission standards, optimal operating levels of pollutants, and preset weight coefficients for each pollutant. The comprehensive scoring module 205 is used to calculate the total score by weighting the safety score, economic score and environmental score according to preset weights.

[0073] The online evaluation system for coal blending effect in coal-fired power plants provided by the present invention is used to execute the online evaluation method for coal blending effect in coal-fired power plants provided in the foregoing embodiments. The online evaluation method for coal blending effect in coal-fired power plants has been described in detail in the foregoing embodiments, and will not be repeated here.

[0074] In some embodiments of this application, the security evaluation module 202 includes: The equipment safety submodule is used to process the ratio of the actual output to the rated output of the coal mill, the ratio of the actual output to the rated output of the fan, and the flue gas velocity through a fuzzy logic model, and output the equipment safety score. The load capacity calculation submodule is used to calculate the ratio of the actual output of each auxiliary machine to the rated output of the corresponding auxiliary machine, take the arithmetic mean of each ratio to obtain the average output rate of the auxiliary machine, and output the load capacity score according to the value of the average output rate of the auxiliary machine and preset rules. The slagging feedback submodule is used to predict the degree of slagging based on the economizer inlet temperature change rate and the low-temperature reheater inlet temperature change rate using a pre-trained BP neural network model, and to calculate the slagging feedback score based on the degree of slagging.

[0075] In some embodiments of this application, the economic evaluation module 203 includes: The overall economic evaluation submodule is used to obtain the actual coal consumption for power supply and the designed coal consumption for power supply based on formula E. co =100-(b g -b g,s ) Calculate the overall economic evaluation score; where E co For the overall economic evaluation score, b g b represents the actual coal consumption for power supply. g,s Coal consumption for power supply based on the designed coal type; The power supply cost submodule is used to calculate the weighted average calorific value of mixed coal and the unit power supply fuel cost Pu'; the unit power supply fuel cost Pu' is converted into a positive index Pu according to the formula Pu=1 / Pu', and the power supply cost score is output according to the linear mapping rule based on the value of the positive index.

[0076] Figure 3 A structural block diagram of the electronic device provided by the present invention, such as Figure 3 As shown, the present invention also provides an electronic device, which 300 can be a mobile terminal, desktop computer, laptop, handheld computer, server, or other computing device. The electronic device 300 includes a processor 301 and a memory 302, wherein the memory 302 stores an online evaluation program 303 for the coal blending effect in coal-fired power plants.

[0077] In some embodiments, memory 302 may be an internal storage unit of a computer device, such as a hard disk or memory. In other embodiments, memory 302 may be an external storage device of a computer device, such as a plug-in hard disk, smart media card (SMC), secure digital card (SD), flash card, etc. Further, memory 302 may include both internal and external storage units of the computer device. Memory 302 is used to store application software and various types of data installed on the computer device, such as program code for installing the computer device. Memory 302 can also be used to temporarily store data that has been output or will be output. In one embodiment, when the online evaluation program 303 for the coal blending effect of a coal-fired power plant is executed by processor 301, the following steps are implemented: Real-time acquisition of operational data from coal-fired power plants and data preprocessing; Based on the preprocessed operating data, the equipment safety score, load capacity score, and slagging feedback score are calculated, and a comprehensive safety score is obtained. The overall economic evaluation score and power supply cost score are calculated based on the preprocessed operating data, and the overall economic score is obtained by combining them. Based on SO2 emission concentration, NO x The environmental score is calculated based on emission concentration, particulate matter emission concentration, pollutant emission standards, optimal operating levels of pollutants, and preset weighting coefficients for each pollutant. The safety score, economic score, and environmental score are weighted according to preset weights to obtain the total score.

[0078] In some embodiments, processor 301 may be a central processing unit (CPU), microprocessor, or other data processing chip, used to run program code stored in memory 302 or process data, such as executing an online evaluation program for the blending effect of coal in a coal-fired power plant.

[0079] This embodiment also provides a computer-readable storage medium storing an online evaluation program for the coal blending effect of a coal-fired power plant. When executed by a processor, this online evaluation program for the coal blending effect of a coal-fired power plant performs the following steps: Real-time acquisition of operational data from coal-fired power plants and data preprocessing; Based on the preprocessed operating data, the equipment safety score, load capacity score, and slagging feedback score are calculated, and a comprehensive safety score is obtained. The overall economic evaluation score and power supply cost score are calculated based on the preprocessed operating data, and the overall economic score is obtained by combining them. Based on SO2 emission concentration, NO x The environmental score is calculated based on emission concentration, particulate matter emission concentration, pollutant emission standards, optimal operating levels of pollutants, and preset weighting coefficients for each pollutant. The safety score, economic score, and environmental score are weighted according to preset weights to obtain the total score.

[0080] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the appended claims.

[0081] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for online evaluation of the coal blending effect in coal-fired power plants, characterized in that, include: Real-time acquisition and preprocessing of operational data from coal-fired power plants; wherein the operational data includes pulverizer output, fan output, flue gas velocity, economizer inlet temperature, low-temperature reheater inlet temperature, actual coal consumption for power generation, designed coal consumption for power generation of different coal types, blending ratio of each type of coal, calorific value of each type of coal, price of each type of coal, transportation price of each type of coal, SO2 emission concentration, NO emission concentration, etc. x Emission concentration, particulate matter emission concentration, pollutant emission standards, and optimal operating levels for pollutants; Based on the preprocessed operating data, the equipment safety score, load capacity score, and slagging feedback score are calculated, and a comprehensive safety score is obtained. The equipment safety score is calculated based on the output of the coal mill, the output of the blower, and the flue gas velocity. The load capacity score is calculated based on the actual output of the auxiliary equipment and the rated output. The slagging feedback score is calculated based on the inlet temperature of the economizer and the inlet temperature of the low-temperature reheater. The overall economic evaluation score and power supply cost score are calculated based on the preprocessed operating data, and the economic score is obtained by combining them. The overall economic evaluation score is calculated based on the actual coal consumption for power supply and the coal consumption for power supply of the designed coal type. The power supply cost score is calculated based on the actual coal consumption for power supply, the blending ratio of each single coal, the calorific value of a single coal, the price of a single coal, and the transportation price of a single coal. Based on SO2 emission concentration, NO x The environmental score is calculated based on emission concentration, particulate matter emission concentration, pollutant emission standards, optimal operating levels of pollutants, and preset weighting coefficients for each pollutant. The safety score, economic score, and environmental score are weighted according to preset weights to obtain the total score.

2. The online evaluation method for the coal blending effect in coal-fired power plants according to claim 1, characterized in that, After calculating the total score, the method further includes: Based on the total score and the scores at each level, a tree diagram of the evaluation results is generated; The tree diagram includes first-level nodes, second-level nodes, and third-level nodes. The first-level nodes are used to display the total score and the corresponding evaluation level. The second-level nodes are used to display the safety score, economic score, and environmental score. The third-level nodes are used to display the equipment safety score, load capacity score, slagging feedback score, overall economic evaluation score, and power supply cost score, and include the calculation basis for each score. When the total score or any level score is lower than the preset threshold, an early warning is automatically triggered and corresponding adjustment suggestions are pushed to the operator's terminal.

3. The online evaluation method for the coal blending effect in coal-fired power plants according to claim 1, characterized in that, Also includes: Set an evaluation update cycle, and repeat the entire process from data collection from coal-fired power plants to calculation of the total score according to the evaluation update cycle, and update the evaluation results in real time; Adjust the coal blending ratio or unit operating parameters based on the updated evaluation results, continuously track the adjusted operating data and update the evaluation results to verify the adjustment effect.

4. The online evaluation method for the coal blending effect in coal-fired power plants according to claim 1, characterized in that, The real-time acquisition and preprocessing of operational data from coal-fired power plants includes: Real-time reading of operational data from the distributed control system (DCS) or data acquisition system (DAS) of coal-fired power plants; The operating data is filtered and denoised to remove outliers that exceed the normal operating range of ±3σ, where σ is the standard deviation of historical data.

5. The online evaluation method for the coal blending effect in coal-fired power plants according to claim 1, characterized in that, Based on the preprocessed operating data, the equipment safety score, load capacity score, and slagging feedback score are calculated, and a comprehensive safety score is obtained, including: The ratio of actual output to rated output of coal mill, ratio of actual output to rated output of fan, and flue gas velocity are processed by fuzzy logic model to output equipment safety score; Calculate the ratio of the actual output of each auxiliary machine to the rated output of the corresponding auxiliary machine, take the arithmetic mean of each ratio to obtain the average output rate of the auxiliary machine, and output the load capacity score according to the value of the average output rate of the auxiliary machine and the preset rules. Based on the economizer inlet temperature change rate and the low-temperature reheater inlet temperature change rate, the degree of slagging is predicted by a pre-trained BP neural network model, and the slagging feedback score is calculated based on the degree of slagging. The safety score is obtained by taking the arithmetic mean of the equipment safety score, load capacity score, and slagging feedback score.

6. The online evaluation method for the coal blending effect in coal-fired power plants according to claim 1, characterized in that, The overall economic evaluation score and power supply cost score are calculated based on the preprocessed operational data, and a comprehensive economic score is obtained, including: To obtain the actual coal consumption for power supply and the designed coal consumption for power supply of different coal types, use formula E. co =100-(b g -b g,s ) Calculate the overall economic evaluation score; where E co For the overall economic evaluation score, b g b represents the actual coal consumption for power supply. g,s Coal consumption for power supply based on the designed coal type; According to formula Q avg =Σ(α i ·Q i Calculate the weighted average calorific value of the mixed coal, where α i Let Q be the blending ratio of the i-th type of single coal. i Let i be the calorific value of the i-th type of coal; According to the formula Pu'=bg×29310 / Q avg ×[α1(P1+Ptr1)+α2(P2+Ptr2)+...+α n (P n +Ptr n )]×10 -6 Calculate the unit fuel cost for electricity supply, Pu'; where 29310 is the standard coal calorific value coefficient, and P... n For the price per unit of coal, Ptr n The price for each individual coal shipment; The unit power supply fuel cost Pu' is converted into a positive index Pu according to the formula Pu=1 / Pu'. The power supply cost score is then output according to the linear mapping rule based on the value of the positive index. The economic score is obtained by taking the arithmetic mean of the overall economic evaluation score and the power supply cost score.

7. The online evaluation method for the coal blending effect in coal-fired power plants according to claim 1, characterized in that, The formula for calculating the environmental score is as follows: I=100{0.6+0.4·[λ1(SO 2S -SO2) / (SO 2S -SO 2min )+λ2(NO xs -NO x ) / (NO xs -NO xmin )+λ3(φ s -φ) / (φ s -φ min )]} Where I represents the environmental score; λ1, λ2, and λ3 represent SO2, NO, and NO, respectively. x The weighting coefficients for smoke and dust, and λ1+λ2+λ3=1; SO 2S The standard for SO2 pollutant emissions, where SO2 is the SO2 emission concentration. 2min For SO2, the optimal operating level is achieved; NO xs NO x Pollutant emission standards, NO x For actual NO x Emission concentration, NO xmin NO x Optimal operating level; φ s The emission standard for particulate matter is given by φ, where φ is the particulate matter emission concentration. min This represents the optimal operating level for smoke and dust.

8. An online evaluation system for the coal blending effect in a coal-fired power plant, the system being used to execute the online evaluation method for the coal blending effect in a coal-fired power plant as described in any one of claims 1-7, characterized in that, The system includes: The data acquisition module is used to acquire and preprocess the operating data of the coal-fired power plant in real time. The operating data includes the output of the coal mill, the output of the blower, the flue gas velocity, the economizer inlet temperature, the low-temperature reheater inlet temperature, the actual coal consumption for power supply, the designed coal consumption for power supply of the coal type, the blending ratio of each coal type, the calorific value of each coal type, the price of each coal type, the transportation price of each coal type, the SO2 emission concentration, the NOx emission concentration, the particulate matter emission concentration, the pollutant emission standards, and the optimal operating level of pollutants. The safety evaluation module is used to calculate the equipment safety score, load capacity score, and slagging feedback score based on preprocessed operating data, and to obtain a comprehensive safety score. The equipment safety score is calculated based on the output of the coal mill, the output of the fan, and the flue gas velocity. The load capacity score is calculated based on the actual output of the auxiliary equipment and the rated output. The slagging feedback score is calculated based on the economizer inlet temperature and the low-temperature reheater inlet temperature. The economic evaluation module is used to calculate the overall economic evaluation score and the power supply cost score based on the preprocessed operating data, and to obtain a comprehensive economic score. The overall economic evaluation score is calculated based on the actual coal consumption for power supply and the designed coal consumption for power supply of different coal types. The power supply cost score is calculated based on the actual coal consumption for power supply, the blending ratio of each coal type, the calorific value of each coal type, the price of each coal type, and the transportation price of each coal type. The environmental performance evaluation module is used to calculate the environmental performance score based on SO2 emission concentration, NOx emission concentration, particulate matter emission concentration, pollutant emission standards, optimal operating levels of pollutants, and preset weight coefficients for each pollutant. The comprehensive scoring module is used to calculate the total score by weighting the safety score, economic score, and environmental score according to preset weights.

9. An electronic device, Its features are, Including memory and processor, among which, The memory is used to store programs; The processor, coupled to the memory, is used to execute the program stored in the memory to implement the steps in the online evaluation method for coal blending effect in coal-fired power plants according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, Used to store computer-readable programs or instructions, which, when executed by a processor, can implement the steps in the online evaluation method for coal blending effect in coal-fired power plants as described in any one of claims 1 to 7.

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