A thermal power plant operation control method and system based on multi-source data analysis

Abstract

The invention discloses a thermal power plant operation control method and system based on multi-source data analysis, which relates to the field of energy and power technology. The main scheme is: real-time acquisition of a multi-source data set including real-time environmental parameters, real-time fuel parameters, real-time electrical parameters, real-time boiler basic operation parameters and real-time turbine operation parameters, analysis and calculation of different parameters, obtaining an environmental impact coefficient by analyzing the real-time environmental parameters, calculating the fuel impact coefficient by combining the environmental impact coefficient and the fuel parameters, and also calculating a boiler basic operation index, a turbine basic operation index and a turbine impact operation index, setting a plurality of threshold sets, respectively comparing the corresponding coefficients with the threshold sets, judging whether to trigger environmental risk warning, fuel risk warning, electrical fault warning and turbine operation fault warning, and finally, receiving warning information and executing a response strategy to achieve efficient and stable operation control of the thermal power plant and improve the safety and reliability of the thermal power plant.

Description

Technical Field

[0001] The present invention relates to the field of energy and power technology, and in particular to a thermal power plant operation control method and system based on multi-source data analysis. Background Art

[0002] In the operation of thermal power plants, the existing technology usually uses decentralized sensors to monitor limited key parameters of boilers, steam turbines, electrical equipment, etc., such as boiler pressure and temperature, turbine speed, etc. The monitoring of environmental parameters and fuel parameters is relatively simple and may be intermittent. At the same time, the existing technology mainly relies on operators to analyze and judge based on these limited parameter values ​​based on experience, such as manually adjusting fuel input or ventilation volume when the boiler pressure is too high. In terms of fault warning, the alarm is often issued only when the fault is more serious;

[0003] These deficiencies lead to the following problems in the operation of thermal power plants: only collecting a few key parameters cannot fully reflect the overall operating status of the thermal power plant, and potential problems are easy to ignore. Secondly, there is a lack of comprehensive analysis, and it is impossible to comprehensively consider multiple aspects such as the environment, fuel, electricity, boilers and turbines, making it difficult to accurately assess the overall operating risks of the system. Furthermore, there is a high degree of dependence on manual labor, and the decision-making process mainly relies on the experience of operators, which is easily affected by subjective factors and has a slow response speed. Finally, there is a lack of early warning capabilities, and fault warnings are not timely, and potential fault risks cannot be discovered in advance, which can easily lead to equipment damage and production interruptions. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] In view of the shortcomings of the prior art, the present invention provides a thermal power plant operation control method and system based on multi-source data analysis. The data acquisition module obtains multi-source data including boilers, turbines, electrical equipment, fuels and environment, thereby overcoming the problem of single data deficiency in the prior art. The data analysis module calculates various special indexes to achieve a comprehensive evaluation of the operating status of the thermal power plant, solving the problem of lack of comprehensive analysis in the prior art. The early warning module judges fault warnings based on the turbine operating index and threshold set, solving the problem of weak early warning capability, improving the early warning capability, and timely discovering potential risks. The control decision module receives the early warning information for real-time control, reducing manual intervention and solving the problem of slow response speed.

[0006] (II) Technical solution

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: A thermal power plant operation control method based on multi-source data analysis, comprising:

[0008] Real-time acquisition of multi-source data sets, including real-time environmental parameters, real-time fuel parameters, real-time electrical parameters, real-time boiler basic operating parameters, and real-time turbine operating parameters;

[0009] Analyze real-time environmental parameters and calculate environmental impact coefficients ; Based on environmental impact factor Calculate fuel influence coefficient with real-time fuel parameters ; Calculate electrical influence coefficients based on real-time electrical parameters ; Analyze real-time boiler operating parameters and calculate boiler basic operating index , and based on real-time turbine operating parameters and boiler basic operating index , further calculate the turbine basic operation index ; According to the fuel influence coefficient , Electrical influence coefficient and steam turbine basic operation index , calculate the turbine operation impact index ;

[0010] Set the environmental impact index threshold set E, fuel impact coefficient threshold set YU, electrical impact coefficient threshold set HS and turbine impact threshold set F respectively; The comparison result with the environmental impact index threshold set E determines whether to trigger an environmental risk warning; based on the fuel impact coefficient The comparison result with the fuel influence coefficient threshold set YU determines whether to trigger the fuel risk warning; based on the electrical influence coefficient The comparison result with the electrical influence coefficient threshold set HS determines whether to trigger the electrical fault warning; based on the turbine influence operation index The comparison result with the turbine impact threshold set F determines whether to trigger the turbine operation fault warning;

[0011] Receive early warning information and implement response strategies.

[0012] In the above preferred embodiment of the thermal power plant operation control method based on multi-source data analysis: calculating the environmental impact index The specific steps are:

[0013] Real-time environmental parameters including real-time atmospheric temperature , Real-time atmospheric humidity , Real-time atmospheric pressure , Real-time atmospheric pressure average , Real-time dust concentration and the real-time noise level N;

[0014] Setting dust concentration threshold and the noise level threshold ;

[0015] Calculate environmental impact index based on real-time environmental parameters The specific formula is as follows:

[0016]

[0017] Among them, K is the normalization constant of the environmental impact index, and its value range is 0 <K≤10。

[0018] In the above preferred embodiment of the thermal power plant operation control method based on multi-source data analysis: Calculate the fuel influence coefficient The specific steps are:

[0019] The real-time fuel parameters include real-time fuel calorific value C, real-time fuel moisture B, real-time fuel sulfur content J and real-time fuel ash content A;

[0020] According to real-time fuel parameters and environmental impact coefficient Calculating the fuel impact factor The specific formula is as follows:

[0021]

[0022] Among them, c is the adjustment coefficient of fuel calorific value C, and its value range is [0.5, 2]; b is the adjustment coefficient of fuel moisture B, and its value range is [0.5, 3]; is the adjustment coefficient 2 of fuel moisture B, and its value range is [0.2, 1.5]; q is the adjustment coefficient 3 of fuel moisture B, and its value range is [0.5, 2]; j is the adjustment coefficient of fuel sulfur content J, and its value range is [0.5, 2]; is the adjustment coefficient of fuel ash content A, and takes the value [0.5,2].

[0023] In the above preferred embodiment of the thermal power plant operation control method based on multi-source data analysis: Calculate the electrical influence coefficient The specific steps are:

[0024] The real-time electrical parameters include real-time voltage V, real-time current I, real-time active power D, real-time reactive power G and real-time power factor H;

[0025] Calculate electrical influence coefficients based on real-time electrical parameters The specific formula is as follows:

[0026]

[0027] Among them, the value range of power factor H is H>0.

[0028] In the above preferred embodiment of the thermal power plant operation control method based on multi-source data analysis:

[0029] The method for determining whether to trigger an environmental risk warning is as follows: the environmental impact index threshold set E includes a normal operation threshold E1, a first-level risk threshold E2, and a second-level risk threshold E3, wherein E1<E2<E3;

[0030] When the environmental impact index When ≤E1, the environmental risk warning will not be triggered;

[0031] When E1<Environmental Impact Index When ≤E2, the first-level environmental risk warning is triggered;

[0032] When E2<Environmental Impact Index When ≤E3, the second-level environmental risk warning is triggered;

[0033] When the environmental impact index >E3, triggering the third-level environmental risk warning;

[0034] The method for determining whether to trigger the fuel risk warning is as follows: the fuel impact coefficient threshold set YU includes a normal operation threshold YU1, a first-level risk threshold YU2, and a second-level risk threshold YU3, wherein YU1<YU2<YU3;

[0035] When the fuel influence coefficient When ≤YU1, the fuel risk warning will not be triggered;

[0036] When YU1<fuel influence coefficient When ≤YU2, the primary fuel risk warning is triggered;

[0037] When YU2<fuel influence coefficient When ≤YU3, a medium fuel risk warning is triggered;

[0038] When the fuel influence coefficient >YU3, triggering high fuel risk warning;

[0039] The method for determining whether to trigger an electrical fault warning is as follows: the electrical influence coefficient threshold set HS includes a normal operation threshold HS1, a primary fault threshold HS2, and a secondary fault threshold HS3, wherein HS1<HS2<HS3;

[0040] When the electrical influence factor When ≤HS1, the electrical fault warning will not be triggered;

[0041] When HS1<Electrical influence coefficient When ≤HS2, the first-level electrical fault warning is triggered;

[0042] When HS2<Electrical influence coefficient When ≤HS3, the second-level electrical fault warning is triggered;

[0043] When the electrical influence factor >HS3, the third-level electrical fault warning is triggered.

[0044] In the above preferred embodiment of the thermal power plant operation control method based on multi-source data analysis: Calculate the boiler basic operation index The specific steps are:

[0045] The real-time boiler basic operating parameters include real-time boiler temperature parameters, real-time boiler pressure parameters, real-time boiler oxygen parameters, real-time fuel flow parameters and real-time feed water flow parameters; the real-time boiler basic operating parameters are normalized and pre-processed to obtain temperature parameter pre-processing value T, pressure parameter pre-processing value P, oxygen parameter pre-processing value O, fuel flow parameter pre-processing value Z and feed water flow parameter pre-processing value W respectively;

[0046] Calculate the boiler basic operation index based on the real-time boiler operation parameters after normalization preprocessing The specific formula is as follows:

[0047] .

[0048] In the above preferred embodiment of the thermal power plant operation control method based on multi-source data analysis: calculating the basic operation index of the steam turbine The specific steps are:

[0049] The real-time steam turbine operating parameters include the real-time steam turbine speed S, the real-time thermal efficiency R, the real-time steam pressure Q, the real-time steam temperature Y and the real-time load rate U;

[0050] According to the real-time turbine operating parameters and boiler basic operating index , calculate the turbine basic operation index The specific formula is as follows:

[0051]

[0052] Among them, the value range of load rate U is 0 <U≤1。

[0053] In the above preferred embodiment of the thermal power plant operation control method based on multi-source data analysis: calculating the steam turbine operation index The specific steps are:

[0054] According to the fuel influence factor , Electrical influence coefficient and turbine basic operation index , calculate the turbine operation impact index The specific formula is as follows:

[0055]

[0056] in, Electrical influence coefficient The weight factor is 0.1≤ ≤0.3, is the basic operation index of the steam turbine The weight factor is 0.3≤ ≤0.6, Fuel influence coefficient The weight factor is 0.3≤ ≤0.6, and .

[0057] In the above preferred embodiment of the thermal power plant operation control method based on multi-source data analysis, the specific steps of determining whether to trigger a turbine operation fault warning are as follows:

[0058] The turbine impact threshold set F includes a normal operation threshold F1, a first-level risk threshold F2, and a second-level risk threshold F3, where F1<F2<F3;

[0059] When the steam turbine affects the operating index When ≤F1, the operation fault warning will not be triggered;

[0060] When F1<Turbine Influence Operation Index When ≤F2, the first-level operation fault warning is triggered;

[0061] When F2<Turbine Influence Operation Index When ≤F3, the second-level operation fault warning is triggered;

[0062] When the steam turbine affects the operating index >F3, trigger the third level operation fault warning.

[0063] The present invention also discloses a thermal power plant operation control system based on multi-source data analysis, comprising the following steps:

[0064] A data acquisition module is used to acquire multi-source data sets in real time, and the multi-source data sets include real-time environmental parameters, real-time fuel parameters, real-time electrical parameters, real-time boiler basic operating parameters, and real-time turbine operating parameters;

[0065] Data analysis module, used to analyze real-time environmental parameters and calculate environmental impact coefficients ; Based on environmental impact factor Calculate fuel influence coefficient with real-time fuel parameters ; Calculate electrical influence coefficients based on real-time electrical parameters ; Analyze real-time boiler operating parameters and calculate boiler basic operating index , and based on real-time turbine operating parameters and boiler basic operating index , further calculate the turbine basic operation index ; According to the fuel influence coefficient , Electrical influence coefficient and steam turbine basic operation index , calculate the turbine operation impact index ;

[0066] The early warning module is used to set the environmental impact index threshold set E, the fuel impact coefficient threshold set YU, the electrical impact coefficient threshold set HS and the turbine impact threshold set F respectively; based on the environmental impact coefficient The comparison result with the environmental impact index threshold set E determines whether to trigger an environmental risk warning; based on the fuel impact coefficient The comparison result with the fuel influence coefficient threshold set YU determines whether to trigger the fuel risk warning; based on the electrical influence coefficient The comparison result with the electrical influence coefficient threshold set HS determines whether to trigger the electrical fault warning; based on the turbine influence operation index The comparison result with the turbine impact threshold set F determines whether to trigger the turbine operation fault warning;

[0067] The control decision module is used to receive the warning information from the warning module and execute the response strategy.

[0068] (III) Beneficial effects

[0069] The present invention provides a thermal power plant operation control method and system based on multi-source data analysis, which has the following beneficial effects:

[0070] (1) Data acquisition module: It acquires multi-source data in real time to form a multi-source data set, covering all key aspects of the operation of the thermal power plant, providing a rich and accurate data source for subsequent analysis and control, ensuring the timeliness of the data, enabling the system to quickly respond to changes in the operating status of the thermal power plant, discover problems in a timely manner and take measures, and comprehensively collects parameters of boilers, turbines, electrical equipment, fuels and environment, fully reflecting the overall operation of the thermal power plant, avoiding the limitations of a single data source;

[0071] (2) Data analysis module, which calculates each special index and sets corresponding early warnings. It can independently and accurately evaluate the electrical system, fuel impact and environmental impact, provide a strong basis for comprehensive judgment, grasp the changing trend of the operating status of the thermal power plant, discover potential problems in advance, and buy time for taking preventive measures;

[0072] (3) Early warning module, which calculates the turbine operation impact index based on multiple impact data By comparing with the turbine impact threshold set F, it is possible to timely discover abnormal conditions in the operation of thermal power plants, issue fault warnings in advance, and avoid accidents. Setting threshold sets can achieve graded warnings, and take corresponding measures according to different warning levels to improve the pertinence and effectiveness of responding to faults. Through the early warning function, thermal power plants are prompted to adjust their operating status in a timely manner to ensure the safe and stable operation of equipment and reduce economic losses.

[0073] (4) The control decision module can quickly issue an early warning after receiving the early warning information, helping maintenance personnel to detect problems in advance and avoid the expansion of faults. It can also assist maintenance personnel in reducing the time for troubleshooting and improving the efficiency of problem solving by accurately responding to different early warning categories, thus preventing serious consequences caused by untimely fault handling, improving management efficiency and reducing maintenance costs. At the same time, it can provide support for management and help thermal power plants achieve sustainable development. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] Figure 1 The present invention is a flowchart of a thermal power plant operation control method based on multi-source data analysis. DETAILED DESCRIPTION

[0075] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present invention.

[0076] See also Figure 1 The present invention provides a thermal power plant operation control method based on multi-source data analysis, comprising:

[0077] Acquire multi-source data sets in real time, including real-time environmental parameters, real-time fuel parameters, real-time electrical parameters, real-time boiler basic operating parameters, and real-time turbine operating parameters.

[0078] Specifically, it is crucial to ensure the accuracy and real-time nature of the data, as this data directly affects the reliability of subsequent analysis and decision-making. Preprocessing and verifying the collected data can improve data quality and reduce errors.

[0079] Analyze real-time environmental parameters and calculate environmental impact coefficients ; Based on environmental impact factor Calculate fuel influence coefficient with real-time fuel parameters ; Calculate electrical influence coefficients based on real-time electrical parameters ; Analyze real-time boiler operating parameters and calculate boiler basic operating index , and based on real-time turbine operating parameters and boiler basic operating index , further calculate the turbine basic operation index ; According to the fuel influence coefficient , Electrical influence coefficient and steam turbine basic operation index , calculate the turbine operation impact index .

[0080] Set the environmental impact index threshold set E, fuel impact coefficient threshold set YU, electrical impact coefficient threshold set HS and turbine impact threshold set F respectively; The comparison result with the environmental impact index threshold set E determines whether to trigger an environmental risk warning; based on the fuel impact coefficient The comparison result with the fuel influence coefficient threshold set YU determines whether to trigger the fuel risk warning; based on the electrical influence coefficient The comparison result with the electrical influence coefficient threshold set HS determines whether to trigger the electrical fault warning; based on the turbine influence operation index The comparison result with the turbine impact threshold set F determines whether to trigger the turbine operation fault warning.

[0081] Specifically, using the boiler basic operation index The steam turbine basic operation index reflects the current operation status of the steam turbine based on the real-time steam turbine operating parameters. and steam turbine basic operation index Calculate the turbine operation impact index This coefficient comprehensively considers the impact of the electrical system and the turbine operating status on the turbine; set the turbine impact threshold set, and calculate the turbine impact operation index Compared with the threshold set, if the turbine operation impact index exceeds the threshold range, it is determined that there may be a turbine operation failure and an early warning is triggered.

[0082] Receive early warning information and implement response strategies.

[0083] Specifically, based on the early warning information and the operating status of the current system, analysis and decision-making are carried out. According to the decision results, matching maintenance instructions are generated, which may include adjusting fuel supply, controlling ventilation volume, adjusting electrical system parameters, etc., to ensure the safe and stable operation of the equipment in the thermal power plant.

[0084] In a preferred embodiment of the above thermal power plant operation control method based on multi-source data analysis: Calculate the environmental impact index The specific steps are as follows:

[0085] The real-time environmental parameters include real-time atmospheric temperature , real-time atmospheric humidity and real-time atmospheric pressure , average atmospheric pressure , real-time dust concentration and real-time noise level N.

[0086] Set the dust concentration threshold and the noise level threshold , the dust concentration threshold and the noise level threshold can be estimated based on the average values of the dust concentration and noise concentration in the normal state of the historical environmental data.

[0087] Calculate the environmental impact index according to the real-time environmental parameters , and the specific formula is as follows:

[0088]

[0089] Among them, K is the normalization constant of the environmental impact index, and the value range is 0 < K ≤ 10; the average atmospheric pressure is calculated by taking the average of the atmospheric pressure values collected within a unit time period; the real-time dust concentration is obtained from the dust concentration sensor; the real-time noise level N is obtained from the noise sensor.

[0090] It should be noted that the real-time atmospheric temperature reflects the temperature condition of the environment around the thermal power plant. The change in temperature may affect the heat dissipation efficiency and material properties of the equipment, and thus affect the operation of the thermal power plant; is the real-time atmospheric humidity, such processing of humidity can, to a certain extent, make the influence of humidity changes more smoothly reflected in the formula. The change in humidity may affect the insulation performance and corrosion rate of the equipment; is the real-time atmospheric pressure, is the average real-time atmospheric pressure, - The difference between the pressure fluctuation and the mean value reflects the change of atmospheric pressure. Pressure changes may affect combustion efficiency, ventilation effect, etc. is the real-time dust concentration, is the dust concentration threshold value set, This ratio reflects the current dust concentration relative to the threshold. Too high dust concentration may affect the heat dissipation of the equipment and increase wear. N is the real-time noise level. is the noise level threshold set, This ratio reflects the degree of noise level relative to the threshold. Excessive noise may indicate abnormal operation of the equipment and may also affect the health and work efficiency of the staff. K is the normalization constant of the environmental impact index, ranging from 0 to <K≤10。

[0091] The formula comprehensively considers multiple real-time environmental parameters, including atmospheric temperature, humidity, pressure, dust concentration and noise level, and comprehensively reflects the environmental conditions in which the thermal power plant operates. This enables the thermal power plant operation control system to more accurately evaluate the impact of the environment on equipment operation and take corresponding adjustment measures in a timely manner. By performing specific mathematical processing on each parameter, such as taking the logarithm of humidity and subtracting pressure from the mean, the changes in different parameters can be evaluated under a unified framework, avoiding the one-sidedness of a single parameter. At the same time, dust concentration thresholds and noise level thresholds are set and incorporated into the formula in the form of ratios, highlighting the impact of environmental factors beyond the normal range and improving the pertinence of early warning. The setting of constant K can adjust the output range of the formula, which is convenient for comparison and comprehensive analysis with other coefficients and indexes, and provides strong support for the refined management of thermal power plants. By setting environmental risk warnings at different levels, potential problems can be discovered in a timely manner before environmental factors have a significant impact on the operation of thermal power plants.

[0092] In the above preferred embodiment of the thermal power plant operation control method based on multi-source data analysis: Calculate the fuel influence coefficient The specific steps are:

[0093] The real-time fuel parameters include real-time fuel calorific value C, real-time fuel moisture B, real-time fuel sulfur content J and real-time fuel ash content A.

[0094] According to real-time fuel parameters and environmental impact coefficient Calculating the fuel impact factor , the specific formula is as follows:

[0095]

[0096] Among them, c is the adjustment coefficient of fuel calorific value C, and its value range is [0.5, 2]; b is the adjustment coefficient of fuel moisture B, and its value range is [0.5, 3]; is the adjustment coefficient 2 of fuel moisture B, and its value range is [0.2, 1.5]; q is the adjustment coefficient 3 of fuel moisture B, and its value range is [0.5, 2]; j is the adjustment coefficient of fuel sulfur content J, and its value range is [0.5, 2]; is the adjustment coefficient of fuel ash content A, and takes the value [0.5,2].

[0097] It should be noted that this formula calculates the fuel impact coefficient by making a specific mathematical combination of parameters such as the calorific value, humidity, sulfur content and ash content of the fuel, and combining it with the environmental impact coefficient. , each part of the formula considers the impact of different fuel parameters on the operation of thermal power plants, for example, This partly reflects the interaction between calorific value and humidity, where higher calorific value and lower humidity are usually more favorable for combustion; This partly reflects the relationship between sulfur content and humidity; The ash content and humidity are taken into account. Part of it is used to further adjust for the effect of humidity, and finally, multiplied by the environmental impact factor , comprehensively considering the impact of environmental factors on fuel combustion and utilization, thus obtaining a fuel impact coefficient that can fully reflect the impact of fuel on the operation of thermal power plants.

[0098] The formula comprehensively considers key parameters such as the calorific value, humidity, sulfur content and ash content of the real-time fuel, and can accurately reflect the comprehensive impact of fuel characteristics on the operation of thermal power plants. Through the combination of different parameters and the setting of adjustment coefficients, it can adapt to different types of fuels and thermal power plant operating conditions, improve the flexibility and accuracy of the calculation, and introduce the environmental impact coefficient. , fully considers the interaction between environmental factors and fuel, making the calculation of fuel impact coefficient closer to the actual operation situation, which helps thermal power plants to better evaluate the applicability of fuel under different environmental conditions. The formula provides a quantitative fuel impact indicator for the operation control system of thermal power plants, which is convenient for the system to monitor and analyze in real time, adjust fuel supply strategies and combustion parameters in time, improve the operation efficiency of thermal power plants, reduce pollution emissions and equipment losses, and achieve more stable and sustainable operation. Fuel risk warning helps thermal power plants to respond quickly to fuel problems and reduce the impact of fuel quality fluctuations on production. By taking measures in advance, production interruptions or load reduction caused by fuel problems can be avoided, and the production efficiency and reliability of thermal power plants can be improved. At the same time, the early warning system can also help thermal power plants to reasonably arrange fuel procurement and inventory management, ensure a stable supply of fuel, and further improve production efficiency.

[0099] In the above preferred embodiment of the thermal power plant operation control method based on multi-source data analysis: Calculate the electrical influence coefficient The specific steps are:

[0100] The real-time electrical parameters include the real-time voltage V and the real-time current I.

[0101] The real-time active power D, real-time reactive power G and real-time power factor H are obtained in real time according to the power meter.

[0102] Calculate electrical influence coefficients based on real-time electrical parameters , the specific formula is as follows:

[0103]

[0104] Among them, the value range of power factor H is H>0.

[0105] It should be noted that this formula is based on a specific mathematical combination of real-time electrical parameters. Part of it is a comprehensive processing of parameters such as voltage, current, active power, reactive power, etc. to reflect the operating status of the electrical system. Taking the logarithm may be to make the result smoother within a certain range, to facilitate subsequent analysis and calculation, and to provide a quantitative indicator that comprehensively considers electrical parameters for the operation control system of a thermal power plant.

[0106] This formula comprehensively considers a variety of real-time electrical parameters, including quantities related to voltage, current, active power, reactive power, and power factor, and can fully reflect the operating status of the electrical system. By making specific mathematical combinations of these parameters, changes in different parameters can reflect the impact on the electrical system under a unified framework, avoiding the one-sidedness of a single parameter. This formula provides a quantitative electrical impact indicator for the operation and control system of a thermal power plant, which helps the system to monitor the operating status of the electrical system in real time, adjust the operating parameters of electrical equipment in a timely manner, improve the efficiency and stability of the electrical system, and reduce energy loss and equipment failure risks. Electrical fault warnings at different levels can send out signals in a timely manner at the early stage of problems in the electrical system, allowing thermal power plant staff to have enough time to take preventive measures. Through monitoring and analysis of real-time electrical parameters, the early warning system can respond quickly to abnormal changes in parameters such as voltage, current, and power factor to avoid further deterioration of the problem.

[0107] In the above preferred embodiment of the thermal power plant operation control method based on multi-source data analysis:

[0108] The method for determining whether to trigger an environmental risk warning is as follows: the environmental impact index threshold set E includes a normal operation threshold E1, a first-level risk threshold E2, and a second-level risk threshold E3, wherein E1<E2<E3.

[0109] When the environmental impact index When ≤E1, the environmental risk warning will not be triggered.

[0110] When E1<Environmental Impact Index When ≤E2, the first-level environmental risk warning is triggered.

[0111] When E2<Environmental Impact Index When ≤E3, the second-level environmental risk warning is triggered.

[0112] When the environmental impact index >E3, the third-level environmental risk warning is triggered.

[0113] The triggering of the first-level environmental risk warning indicates that the environmental conditions around the thermal power plant have changed to a certain extent, which may have a potential impact on the operation of the thermal power plant. Specifically, there may be more obvious fluctuations in parameters such as atmospheric temperature, humidity, and pressure, or the dust concentration and noise level are close to the level that requires attention. In this case, the operation control system of the thermal power plant should begin to pay close attention to the changing trends of environmental parameters and check the equipment and systems that may be affected. For example, high temperature and high humidity environment may affect the heat dissipation efficiency of electrical equipment, and the temperature monitoring of electrical equipment needs to be strengthened; increased dust concentration may affect the air intake and heat dissipation of equipment, and the air filtration system needs to be checked. At the same time, relevant personnel can be arranged to monitor and record environmental parameters more frequently to detect problems in a timely manner and take countermeasures.

[0114] When E2<Environmental Impact Index When ≤E3, the second-level environmental risk warning is triggered, which means that the environmental conditions have had a significant impact on the operation of the thermal power plant. At this time, the thermal power plant needs to take more active measures to deal with environmental risks and adjust the operating parameters of some equipment to adapt to environmental changes. For example, if the atmospheric pressure changes greatly, the combustion control parameters of the boiler may need to be adjusted to ensure combustion efficiency and stability. At the same time, professionals should be organized to conduct in-depth analysis of the environmental impact, evaluate its long-term impact on the equipment and systems of the thermal power plant, and formulate corresponding response strategies. It is necessary to consider increasing the investment in environmental monitoring equipment and improving the monitoring accuracy and frequency of environmental parameters in order to better grasp the environmental changes.

[0115] When the environmental impact index >E3, the third-level environmental risk warning is triggered, which means that the environmental conditions have posed a serious threat to the safe operation of the thermal power plant. In this case, the thermal power plant must immediately take emergency measures to ensure the safety of equipment and personnel, and it is necessary to suspend the operation of some equipment, or take emergency protective measures, such as strengthening the sealing of equipment, increasing ventilation, etc., to reduce the impact of environmental factors on the equipment. At the same time, the emergency plan should be immediately activated, and relevant departments and personnel should be notified for emergency response. Communication and coordination should be carried out with the environmental protection department, meteorological department, etc. to jointly respond to environmental risks. Before the environmental conditions are improved, the thermal power plant should continue to maintain a high degree of vigilance, closely monitor environmental parameters and equipment operation status, and ensure that normal production is gradually resumed under the premise of safety.

[0116] The method for determining whether to trigger the fuel risk warning is as follows: the fuel influence coefficient threshold set YU includes a normal operation threshold YU1, a first-level risk threshold YU2 and a second-level risk threshold YU3, wherein YU1<YU2<YU3.

[0117] When the fuel influence coefficient When ≤YU1, the fuel risk warning will not be triggered.

[0118] When YU1<fuel influence coefficient When ≤YU2, the primary fuel risk warning is triggered.

[0119] When YU2<fuel influence coefficient When ≤YU3, a medium fuel risk warning is triggered.

[0120] When the fuel influence coefficient >YU3, a high-level fuel risk warning is triggered.

[0121] When YU1<fuel influence coefficient When YU≤YU2, the primary fuel risk warning is triggered, which indicates that some characteristics or parameters of the fuel have changed to a certain extent, which has a potential impact on the operation of the thermal power plant, but the impact is relatively small. For example, the humidity of the fuel has increased slightly, the sulfur content is close to the level that requires attention, or the calorific value of the fuel has fluctuated slightly. In this case, the operation control system of the thermal power plant should begin to pay close attention to the changing trend of the fuel parameters, check the affected equipment and systems, and fine-tune the fuel supply system, such as adjusting the dryness of the fuel, optimizing the fuel mixing ratio, etc., to mitigate potential impacts. At the same time, arrange relevant personnel to monitor and record the fuel parameters more frequently, detect problems in a timely manner and take countermeasures.

[0122] When YU2<fuel influence coefficient When ≤YU3, a medium fuel risk warning is triggered, which means that the change in fuel has had a significant impact on the operation of the thermal power plant. At this time, the thermal power plant needs to take more active measures to deal with fuel risks and adjust the operating parameters of some equipment to adapt to changes in fuel characteristics. For example, if the sulfur content of the fuel increases, it may be necessary to adjust the combustion control parameters of the boiler to reduce sulfur oxide emissions and prevent corrosion to the equipment. At the same time, professionals should be organized to conduct in-depth analysis of the impact of fuel, evaluate its long-term impact on thermal power plant equipment and systems, and formulate corresponding response strategies, consider adjusting the fuel procurement strategy, and choose more suitable fuel suppliers or fuel varieties to reduce fuel risks.

[0123] When the fuel influence coefficient >YU3, a high-level fuel risk warning is triggered, which means that the characteristics of the fuel have posed a serious threat to the safe operation of the thermal power plant. In this case, the thermal power plant must immediately take emergency measures to ensure the safety of equipment and personnel, suspend the operation of some equipment, take emergency protective measures, strengthen the anti-corrosion treatment of equipment, improve the operating efficiency of exhaust gas treatment equipment, etc., to reduce the damage of fuel to equipment and pollution to the environment. At the same time, the emergency plan should be immediately activated, and relevant departments and personnel should be notified to respond urgently. Emergency communication should be conducted with fuel suppliers to jointly find solutions, such as adjusting the quality standards of fuel, speeding up the supply of fuel, etc. Before the fuel problem is resolved, the thermal power plant should continue to remain highly vigilant, closely monitor fuel parameters and equipment operating status, and ensure that normal production is gradually resumed under the premise of safety.

[0124] The method for determining whether to trigger an electrical fault warning is as follows: the electrical influence coefficient threshold set HS includes a normal operation threshold HS1, a primary fault threshold HS2 and a secondary fault threshold HS3, wherein HS1<HS2<HS3.

[0125] When the electrical influence factor When ≤HS1, the electrical fault warning will not be triggered.

[0126] When HS1<Electrical influence coefficient When ≤HS2, the first-level electrical fault warning is triggered.

[0127] When HS2<Electrical influence coefficient When ≤HS3, the second-level electrical fault warning is triggered.

[0128] When the electrical influence factor >HS3, the third-level electrical fault warning is triggered.

[0129] When HS1<Electrical influence coefficient When HS2 is less than or equal to HS2, the first-level electrical fault warning is triggered, which indicates that there are some early signs of abnormality in the electrical system, but the problem is relatively minor. It may be that the voltage and current have fluctuated slightly, or the ratio of active power to reactive power has changed to a certain extent, and the power factor has also begun to deviate from the normal range. In this case, the operation control system of the thermal power plant should begin to pay close attention to the changing trend of electrical parameters and strengthen the monitoring of electrical equipment. For example, check whether the operating temperature and sound of equipment such as transformers and circuit breakers are normal, and observe the changes in instrument readings. At the same time, relevant personnel can be arranged to conduct preliminary inspections and diagnoses of the electrical system to find possible root causes of the problem, such as whether there are problems such as poor line contact and equipment aging.

[0130] When HS2<Electrical influence coefficient When ≤HS3, the second-level electrical fault warning is triggered, which means that the problem of the electrical system is relatively serious and has had a certain impact on the normal operation of the thermal power plant. At this time, the thermal power plant needs to take more active measures to deal with the risk of electrical failures. It is necessary to adjust the operating parameters of some electrical equipment, such as adjusting the tap of the transformer to stabilize the voltage, or adjusting the reactive compensation device to improve the power factor. At the same time, professional electrical technicians should be organized to conduct in-depth fault diagnosis and analysis to determine the specific location and cause of the problem, which involves detailed testing and inspection of electrical equipment, such as using professional testing instruments to perform insulation tests and electrical performance tests on cables, motors and other equipment.

[0131] When the electrical influence factor >HS3, the third-level electrical fault warning is triggered, which means that a serious fault has occurred in the electrical system, which will pose a major threat to the safe operation of the thermal power plant. In this case, the thermal power plant must immediately take emergency measures to ensure the safety of equipment and personnel, and immediately stop the operation of some or all electrical equipment to prevent the fault from further expanding. At the same time, the emergency plan should be activated and the relevant departments and personnel should be notified to carry out emergency repairs. Professional and technical personnel should arrive at the scene quickly to conduct a comprehensive investigation and repair of the fault, replace damaged electrical equipment, repair cable faults, re-debug the control system, etc. After the fault is eliminated, the electrical system needs to be fully tested and inspected to ensure that it resumes normal operation and can provide stable and reliable power support for the thermal power plant.

[0132] In the above preferred embodiment of the thermal power plant operation control method based on multi-source data analysis: Calculate the boiler basic operation index The specific steps are:

[0133] The real-time basic boiler operating parameters include real-time boiler temperature parameters, real-time boiler pressure parameters, real-time boiler oxygen parameters, real-time fuel flow parameters and real-time feed water flow parameters; the real-time basic boiler operating parameters are preprocessed by Z-score normalization to obtain the temperature parameter preprocessing value T, pressure parameter preprocessing value P, oxygen parameter preprocessing value O, fuel flow parameter preprocessing value Z and feed water flow parameter preprocessing value W respectively.

[0134] Calculate the boiler basic operation index based on the real-time boiler operation parameters after normalization preprocessing , the specific formula is as follows:

[0135] .

[0136] It should be noted that this formula calculates the boiler basic operation index by performing square and square root operations on multiple key parameters of real-time boiler operation. The square of each parameter indicates the emphasis on that parameter, making the larger parameter value have a more significant impact on the index. The square root operation combines these parameters to obtain a value that can reflect the overall operating status of the boiler. For example, when parameters such as temperature, pressure, and oxygen content are within the appropriate range, the basic boiler operation index will be relatively high, indicating that the boiler is operating well; and if a certain parameter is abnormal, such as too high temperature, too low pressure, or insufficient oxygen, the basic boiler operation index will decrease, indicating that there may be operating problems. This calculation method can provide a quantitative boiler operation status indicator for the thermal power plant operation control system, which is convenient for the system to monitor and analyze in real time, and adjust the boiler operation parameters in time to ensure the safe, stable and efficient operation of the boiler.

[0137] This formula comprehensively considers multiple key parameters such as real-time boiler temperature, pressure, oxygen content, fuel flow and feed water flow, and can fully reflect the operating status of the boiler. Through the comprehensive calculation of these parameters, abnormal conditions in boiler operation can be discovered in time, providing accurate monitoring indicators for the thermal power plant operation control system. The square and square root calculation method is used to make the influence of each parameter more balanced and significant. Larger parameter values ​​have a greater impact on the index, which can highlight the importance of abnormal parameters and facilitate rapid location of problems. At the same time, this calculation method also makes the change of the index smoother, avoiding misjudgment caused by small fluctuations of a single parameter. The formula provides thermal power plant operators with an intuitive quantitative indicator of boiler operating status, which helps them to adjust the boiler operating parameters in time, optimize the combustion process, improve the thermal efficiency and safety of the boiler, and reduce operating costs and failure risks.

[0138] In the above preferred embodiment of the thermal power plant operation control method based on multi-source data analysis: calculating the basic operation index of the steam turbine The specific steps are:

[0139] The real-time steam turbine operating parameters include the real-time steam turbine speed S, the real-time thermal efficiency R, the real-time steam pressure Q, the real-time steam temperature Y and the real-time load rate U.

[0140] According to the real-time turbine operating parameters and boiler basic operating index , calculate the turbine basic operation index , the specific formula is as follows:

[0141]

[0142] Among them, the value range of load rate U is 0 <U≤1。

[0143] It should be noted that this formula comprehensively considers the operating parameters of the steam turbine itself and its relationship with the operation of the boiler, and combines the load rate to comprehensively evaluate the operating status of the steam turbine. By performing specific mathematical operations and combinations on each parameter, it can accurately reflect the comprehensive impact of different parameters on the operation of the steam turbine. For example, when the steam turbine speed is high, the thermal efficiency is high, the boiler operates well, and the load rate is moderate, the values ​​of each parameter in the formula are relatively ideal, so that the basic operation index of the steam turbine is high, indicating that the steam turbine is in a good operating state. On the contrary, if a parameter is abnormal, such as too low speed, reduced thermal efficiency, unstable boiler operation, or too high or too low load rate, the basic operation index of the steam turbine will decrease, triggering the system to make corresponding adjustments and early warnings to ensure the safe, stable and efficient operation of the thermal power plant.

[0144] The formula takes into account multiple key parameters, including the speed, thermal efficiency, steam pressure and temperature that are directly related to the operation of the turbine, as well as the turbine operating index and load rate. This enables the basic operating index of the turbine to fully reflect the actual operating status of the turbine and provide accurate monitoring indicators for the thermal power plant operation control system. The influence of each parameter is adjusted through mathematical operations such as logarithm, square, and square root. For example, logarithmic operations make the changes in parameters smoother and avoid large changes in the index due to small fluctuations in parameters. Square operations enhance the influence of important parameters and highlight their key role in turbine operation. Combined with the turbine operating index and load rate, the relationship between the boiler and the turbine and the operating characteristics of the turbine under different load conditions are taken into account, which helps the system to adjust the operating strategy in time and improve the overall operating efficiency and safety of the thermal power plant.

[0145] In the above preferred embodiment of the thermal power plant operation control method based on multi-source data analysis: calculating the steam turbine operation index The specific steps are:

[0146] According to the fuel influence factor , Electrical influence coefficient and the turbine basic operation index , calculate the turbine operation impact index , the specific formula is as follows:

[0147]

[0148] in, Electrical influence coefficient The weight factor is 0.1≤ ≤0.3, is the basic operation index of the steam turbine The weight factor is 0.3≤ ≤0.6, Fuel influence coefficient The weight factor is 0.3≤ ≤0.6, and .

[0149] It should be noted that this formula is obtained by substituting the electrical influence coefficient , Steam Turbine Basic Operation Index and fuel influence factor Multiply them by the corresponding weight factors and add them together to calculate the turbine operation impact index The principle is to take into account that the operating status of the electrical system and the steam turbine will affect the operation of the boiler. The stability and performance of the electrical system will affect the energy supply and control of the boiler, and the operating requirements of the steam turbine will determine the steam output of the boiler. By assigning different weight factors, the relative importance of electrical and steam turbine factors in the steam turbine impact operation index can be adjusted according to actual conditions. This calculation method can provide a quantitative indicator for the thermal power plant operation control system that comprehensively considers the impact of electrical and steam turbine factors on boiler operation, so that the system can more accurately evaluate the operating status of the boiler and take corresponding control measures to ensure the overall stable operation of the thermal power plant.

[0150] This formula takes into account the electrical influence coefficient and the turbine basic operation index , which can fully reflect the impact of the electrical system and steam turbine on the operation of the boiler. By setting the weight factor, the importance of the two factors can be flexibly adjusted to adapt to the actual operation conditions of different thermal power plants. The relationship between the electrical system, steam turbine and boiler is clarified. The stability of the electrical system provides a reliable energy supply for the boiler. The operating status of the steam turbine determines the steam output demand of the boiler. This formula helps the thermal power plant operation control system to better coordinate these three key parts, improve the overall operating efficiency, and provide quantitative indicators for the operation management of the thermal power plant. By calculating the turbine impact operation index, the operator can intuitively understand the degree to which the boiler is affected by electrical and steam turbine factors, and take timely adjustment measures, such as optimizing electrical parameters, adjusting steam turbine load, etc., to ensure the safe and stable operation of the thermal power plant and reduce operating costs and risks.

[0151] In the above preferred embodiment of the thermal power plant operation control method based on multi-source data analysis, the specific steps of determining whether to trigger a turbine operation fault warning are as follows:

[0152] According to the data and probability of abnormal situations caused by the turbine in different states in the historical turbine impact data, the turbine impact threshold set F is set to include the normal operation threshold F1, the first-level risk threshold F2 and the second-level risk threshold F3, where F1<F2<F3.

[0153] When the steam turbine affects the operating index When ≤F1, the operation fault warning will not be triggered.

[0154] When F1<Turbine Influence Operation Index When ≤F2, the first level operation fault warning is triggered.

[0155] When F2<Turbine Influence Operation Index When ≤F3, the second-level operation fault warning is triggered.

[0156] When the steam turbine affects the operating index >F3, trigger the third level operation fault warning.

[0157] When the steam turbine affects the operating index F1<Turbine Impact Operation Index When the value is in the range of ≤F2, the first-level operation fault warning is triggered, which indicates that the operation status of the steam turbine has a certain degree of abnormality, but the problem is relatively minor. It may be some early potential problems or slight deviations from normal operation. At this time, the operation control system of the thermal power plant should pay attention and start to monitor and analyze the relevant parameters more closely, check the links where problems may occur, such as slight fluctuations in the electrical system, small changes in certain operating parameters of the steam turbine, etc. At the same time, relevant technical personnel can be arranged to conduct preliminary inspections and diagnoses so that timely measures can be taken to make adjustments to prevent the problem from further deteriorating.

[0158] When the steam turbine affects the operating index F2<Turbine Impact Operation Index When the level 2 operation fault warning is triggered in the range of ≤F3, it means that the operation problem of the steam turbine is relatively serious and may have had a significant impact on the normal operation of the thermal power plant. At this time, the system should immediately start a more stringent monitoring and emergency response procedure. It may be necessary to adjust some equipment of the thermal power plant or limit the load to reduce the pressure on the steam turbine. At the same time, a professional technical team should be organized to conduct in-depth fault diagnosis and analysis, determine the root cause of the problem, and develop a detailed solution. The level 2 warning indicates that action needs to be taken as soon as possible to avoid a greater threat to the safety and stable operation of the thermal power plant.

[0159] When the steam turbine affects the operating index When it is greater than, the third-level operation fault warning is triggered, which means that there is a serious fault in the operation of the turbine, which may pose a major threat to the safe operation of the thermal power plant. In this case, the system should immediately take emergency measures, such as automatic shutdown or emergency safety protection operations, to prevent equipment damage and accidents. At the same time, initiate a comprehensive emergency response plan and notify relevant departments and personnel to carry out emergency repairs and processing. The third-level warning is the most serious situation, and quick and decisive action is needed to ensure the safety of the thermal power plant and resume normal operation as soon as possible.

[0160] When the steam turbine affects the operating index When within the normal operating threshold range, the control system performs routine monitoring and control of the equipment.

[0161] When the first level operation fault warning or the second level operation fault warning is triggered, the turbine affects the operation index. When the system enters the warning range, the control system sends out a warning signal to notify the operator and maintenance personnel to carry out maintenance. When the normal operation threshold conditions are met, the operation fault warning is lifted, and the turbine operation index is continuously monitored. and changes in various parameters.

[0162] When the third-level operation fault warning is triggered, the turbine affects the operation index If the warning range is exceeded, the emergency plan is activated, emergency shutdown is implemented, and professionals are notified to conduct troubleshooting and repairs, and the equipment is restarted. When the condition is ≤F1, the operation fault warning is lifted, and the turbine operation index is continuously monitored. and changes in various parameters.

[0163] When the turbine operating index is within the normal range, the control system performs routine monitoring and control of the equipment, which includes continuous collection and analysis of multi-source data, such as real-time environmental parameters, fuel parameters, electrical parameters and basic boiler operating parameters. Maintenance instructions mainly focus on maintaining stable operation of the equipment, such as maintaining a stable rate of fuel supply, maintaining appropriate electrical parameters, controlling ventilation volume to ensure boiler combustion efficiency, etc. At the same time, the equipment is regularly inspected and maintained to ensure the normal operation of each component.

[0164] When the first or second level operation fault warning is triggered, the control system sends out a warning signal, determines the specific root cause of the problem through data analysis, takes control measures and generates corresponding adjustment instructions according to the warning cause. If the electrical parameters are abnormal, the voltage, current or power factor may be adjusted, such as changing the voltage by adjusting the transformer tap, or adjusting the reactive compensation equipment to improve the power factor. If it is a problem with the turbine operation parameters, the steam flow, pressure or temperature may be adjusted, such as adjusting the valve opening to control the steam flow. If it is affected by the boiler operation status, adjust the fuel supply rate, ventilation volume, etc. to improve combustion efficiency and steam output.

[0165] Continuously monitoring the changes in the turbine operating index and various parameters will help determine whether the measures taken are effective and whether further adjustments are needed. After the maintenance order is implemented, the turbine operating index gradually returns to the normal range and the various parameters tend to be stable, which means that the control measures are effective; if the situation does not improve, it may be necessary to re-analyze the problem and adjust the control measures.

[0166] When the third-level operation fault warning is triggered, the turbine operation impact index exceeds the warning range, the emergency plan is activated, the specific root cause of the problem is determined through data analysis, and professionals are notified to conduct fault investigation and maintenance, and the operating equipment is restarted. When the turbine operation impact index is met When the condition of ≤F0 is met, the operation fault warning is lifted. After the maintenance is completed, the system is restarted and tested to ensure the normal operation of the equipment. The changes in the turbine operating index and various parameters are continuously monitored, and the effectiveness of the control measures is evaluated to ensure the stable operation of the system and prevent similar faults from happening again.

[0167] On the other hand, the present invention also discloses a thermal power plant operation control system based on multi-source data analysis, comprising the following steps:

[0168] The data acquisition module is used to obtain multi-source data sets in real time. The multi-source data sets include real-time environmental parameters, real-time fuel parameters, real-time electrical parameters, real-time boiler basic operating parameters, and real-time turbine operating parameters.

[0169] Data analysis module, used to analyze real-time environmental parameters and calculate environmental impact coefficients ; Based on environmental impact factor Calculate fuel influence coefficient with real-time fuel parameters ; Calculate electrical influence coefficients based on real-time electrical parameters ; Analyze real-time boiler operating parameters and calculate boiler basic operating index , and based on real-time turbine operating parameters and boiler basic operating index , further calculate the turbine basic operation index ; According to the fuel influence coefficient , Electrical influence coefficient and steam turbine basic operation index , calculate the turbine operation impact index .

[0170] The early warning module is used to set the environmental impact index threshold set E, the fuel impact coefficient threshold set YU, the electrical impact coefficient threshold set HS and the turbine impact threshold set F respectively; based on the environmental impact coefficient The comparison result with the environmental impact index threshold set E determines whether to trigger an environmental risk warning; based on the fuel impact coefficient The comparison result with the fuel influence coefficient threshold set YU determines whether to trigger the fuel risk warning; based on the electrical influence coefficient The comparison result with the electrical influence coefficient threshold set HS determines whether to trigger the electrical fault warning; based on the turbine influence operation index The comparison result with the turbine impact threshold set F determines whether to trigger the turbine operation fault warning.

[0171] The control decision module is used to receive the warning information from the warning module and execute the response strategy.

[0172] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product. A person of ordinary skill in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented in electronic hardware or in combination with computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution.

[0173] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0174] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A thermal power plant operation control method based on multi-source data analysis, characterized in that: include: Real-time acquisition of multi-source data sets, including real-time environmental parameters, real-time fuel parameters, real-time electrical parameters, real-time boiler basic operating parameters, and real-time turbine operating parameters; Analyze real-time environmental parameters and calculate environmental impact coefficients ; Based on environmental impact factor Calculate fuel influence coefficient with real-time fuel parameters ; Calculate fuel influence coefficient The specific steps are: The real-time fuel parameters include real-time fuel calorific value C, real-time fuel moisture B, real-time fuel sulfur content J and real-time fuel ash content A; According to real-time fuel parameters and environmental impact coefficient Calculating the fuel impact factor The specific formula is as follows: Among them, c is the adjustment coefficient of fuel calorific value C, and its value range is [0.5, 2]; b is the adjustment coefficient of fuel moisture B, and its value range is [0.5, 3]; is the adjustment coefficient 2 of fuel moisture B, and its value range is [0.2,1.5]; q is the adjustment coefficient 3 of fuel moisture B, and its value range is [0.5,2]; j is the adjustment coefficient of fuel sulfur content J, and its value range is [0.5.2]; is the adjustment coefficient of fuel ash content A, with a value of [0.5,2]; Calculate electrical influence factors based on real-time electrical parameters ; Calculate the electrical influence coefficient The specific steps are: The real-time electrical parameters include real-time voltage V, real-time current I, real-time active power D, real-time reactive power G and real-time power factor H; Calculate electrical influence coefficients based on real-time electrical parameters The specific formula is as follows: Among them, the value range of power factor H is H>0; Analyze real-time boiler operating parameters and calculate boiler basic operating index , calculate the boiler basic operation index The specific steps are: The real-time boiler basic operating parameters include real-time boiler temperature parameters, real-time boiler pressure parameters, real-time boiler oxygen parameters, real-time fuel flow parameters and real-time feed water flow parameters; the real-time boiler basic operating parameters are normalized and pre-processed to obtain temperature parameter pre-processing value T, pressure parameter pre-processing value P, oxygen parameter pre-processing value O, fuel flow parameter pre-processing value Z and feed water flow parameter pre-processing value W respectively; Calculate the boiler basic operation index based on the real-time boiler operation parameters after normalization preprocessing The specific formula is as follows: Based on real-time turbine operating parameters and boiler basic operating index , further calculate the turbine basic operation index ; Calculate the basic operation index of the steam turbine The specific steps are: The real-time steam turbine operating parameters include the real-time steam turbine speed S, the real-time thermal efficiency R, the real-time steam pressure Q, the real-time steam temperature Y and the real-time load rate U; According to the real-time turbine operating parameters and boiler basic operating index , calculate the turbine basic operation index The specific formula is as follows: Among them, the value range of load rate U is 0 <U≤1; According to the fuel influence factor , Electrical influence coefficient and steam turbine basic operation index , calculate the turbine operation impact index ; Calculate the turbine operation impact index The specific steps are: According to the fuel influence factor , Electrical influence coefficient and turbine basic operation index , calculate the turbine operation impact index The specific formula is as follows: in, Electrical influence coefficient The weight factor is 0.1≤ ≤0.3, is the basic operation index of the steam turbine The weight factor is 0.3≤ ≤0.6, Fuel influence coefficient The weight factor is 0.3≤ ≤0.6, and ; Set the environmental impact index threshold set E, fuel impact coefficient threshold set YU, electrical impact coefficient threshold set HS and turbine impact threshold set F respectively; The comparison result with the environmental impact index threshold set E determines whether to trigger an environmental risk warning; based on the fuel impact coefficient The comparison result with the fuel influence coefficient threshold set YU determines whether to trigger the fuel risk warning; based on the electrical influence coefficient The comparison result with the electrical influence coefficient threshold set HS determines whether to trigger the electrical fault warning; based on the turbine influence operation index The comparison result with the turbine impact threshold set F determines whether to trigger the turbine operation fault warning; Receive early warning information and implement response strategies.

2. The method for controlling operation of a thermal power plant based on multi-source data analysis according to claim 1, characterized in that: Calculating the Environmental Impact Index The specific steps are: Real-time environmental parameters including real-time atmospheric temperature , Real-time atmospheric humidity , Real-time atmospheric pressure , Real-time atmospheric pressure average , Real-time dust concentration and the real-time noise level N; Setting dust concentration threshold and the noise level threshold ; Calculate environmental impact index based on real-time environmental parameters The specific formula is as follows: Among them, K is the normalization constant of the environmental impact index, and its value range is 0 <K≤10。 3. The method for controlling operation of a thermal power plant based on multi-source data analysis according to claim 2, characterized in that: The method for determining whether an environmental risk warning is triggered is: The environmental impact index threshold set E includes a normal operation threshold E1, a first-level risk threshold E2, and a second-level risk threshold E3, where E1<E2<E3; When the environmental impact index When ≤E1, the environmental risk warning will not be triggered; When E1<Environmental Impact Index When ≤E2, the first-level environmental risk warning is triggered; When E2<Environmental Impact Index When ≤E3, the second-level environmental risk warning is triggered; When the environmental impact index >E3, triggering the third-level environmental risk warning; The method for determining whether a fuel risk warning is triggered is: The fuel influence coefficient threshold set YU includes a normal operation threshold YU1, a first-level risk threshold YU2 and a second-level risk threshold YU3, wherein YU1<YU2<YU3; When the fuel influence coefficient When ≤YU1, the fuel risk warning will not be triggered; When YU1<fuel influence coefficient When ≤YU2, the primary fuel risk warning is triggered; When YU2<fuel influence coefficient When ≤YU3, a medium fuel risk warning is triggered; When the fuel influence coefficient >YU3, triggering high fuel risk warning; The method for determining whether an electrical fault warning is triggered is: The electrical influence coefficient threshold set HS includes a normal operation threshold HS1, a primary fault threshold HS2 and a secondary fault threshold HS3, wherein HS1<HS2<HS3; When the electrical influence factor When ≤HS1, the electrical fault warning will not be triggered; When HS1<Electrical influence coefficient When ≤HS2, the first-level electrical fault warning is triggered; When HS2<Electrical influence coefficient When ≤HS3, the second-level electrical fault warning is triggered; When the electrical influence factor >HS3, the third-level electrical fault warning is triggered.

4. The method for controlling operation of a thermal power plant based on multi-source data analysis according to claim 3 is characterized in that: The specific steps to determine whether the turbine operation fault warning is triggered are: The turbine impact threshold set F includes a normal operation threshold F1, a first-level risk threshold F2, and a second-level risk threshold F3, where F1<F2<F3; When the steam turbine affects the operating index When ≤F1, the operation fault warning will not be triggered; When F1<Turbine Influence Operation Index When ≤F2, the first-level operation fault warning is triggered; When F2<Turbine Influence Operation Index When ≤F3, the second-level operation fault warning is triggered; When the steam turbine affects the operating index >F3, trigger the third level operation fault warning.

5. A thermal power plant operation control system based on multi-source data analysis, characterized in that: A thermal power plant operation control method for implementing any one of claims 1 to 4 above, comprising: A data acquisition module is used to acquire multi-source data sets in real time, and the multi-source data sets include real-time environmental parameters, real-time fuel parameters, real-time electrical parameters, real-time boiler basic operating parameters, and real-time turbine operating parameters; Data analysis module, used to analyze real-time environmental parameters and calculate environmental impact coefficients ; Based on environmental impact factor Calculate fuel influence coefficient with real-time fuel parameters ; Calculate electrical influence coefficients based on real-time electrical parameters ; Analyze real-time boiler operating parameters and calculate boiler basic operating index , and based on real-time turbine operating parameters and boiler basic operating index , further calculate the turbine basic operation index ; According to the fuel influence coefficient , Electrical influence coefficient and steam turbine basic operation index , calculate the turbine operation impact index ; The early warning module is used to set the environmental impact index threshold set E, the fuel impact coefficient threshold set YU, the electrical impact coefficient threshold set HS and the turbine impact threshold set F respectively; based on the environmental impact coefficient The comparison result with the environmental impact index threshold set E determines whether to trigger an environmental risk warning; based on the fuel impact coefficient The comparison result with the fuel influence coefficient threshold set YU determines whether to trigger the fuel risk warning; based on the electrical influence coefficient The comparison result with the electrical influence coefficient threshold set HS determines whether to trigger the electrical fault warning; based on the turbine influence operation index The comparison result with the turbine impact threshold set F determines whether to trigger the turbine operation fault warning; The control decision module is used to receive the warning information from the warning module and execute the response strategy.

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