A method and system for online monitoring of power generation capacity of grid-connected coal-fired units

Abstract

The present invention relates to the technical field of power generation capacity monitoring, and in particular to an online monitoring method and system for the power generation capacity of a grid-connected coal-fired unit, the method comprising: collecting the operating parameters of important auxiliary equipment of the grid-connected coal-fired unit, and pre-processing the operating parameters of the important auxiliary equipment; performing cluster analysis on several typical operating conditions of the grid-connected coal-fired unit, and calculating the health status of the equipment; screening out the unavailable auxiliary equipment among the important auxiliary equipment; calculating the power generation capacity of the grid-connected coal-fired unit considering the health status of the equipment, coal quality, main operating parameters and heating conditions; selecting the minimum value of the power generation capacity of four grid-connected coal-fired units, and predicting the maximum load that the grid-connected coal-fired unit can carry. Through the present invention, the real-time online monitoring and evaluation of the power generation capacity of the grid-connected coal-fired unit is effectively realized, human errors are effectively reduced, and the real-time performance is good, providing data support for reliable power supply and optimized scheduling.

Description

Technical Field

[0001] The present invention relates to the technical field of power generation capacity monitoring, and in particular to an online monitoring method and system for power generation capacity of a grid-connected coal-fired unit. Background Art

[0002] Under the guidance of the "dual carbon" goal, the installed capacity of new energy continues to grow rapidly. However, due to its random, intermittent and volatile characteristics, grid-connected coal-fired units are still the main units for power supply, and will also play the role of "ballast stone" for power supply for a long time in the future. Especially during peak energy consumption periods such as peak summer and peak winter, in order to meet the growing demand for electricity for production and life, grid-connected coal-fired units need to be able to withstand and stabilize. However, due to the complexity and diversity of the power generation process of grid-connected coal-fired units, their power generation capacity is affected by multiple factors such as equipment health and coal quality. For a long time, the power generation capacity of grid-connected coal-fired units has only been roughly evaluated based on the experience of experts such as duty officers, unit leaders and unit operators, and real-time online monitoring and quantitative evaluation have not been achieved. The power dispatching department has very little information, so it is impossible to provide real-time data reference for power safety optimization and dispatching, which adds a certain degree of uncertainty to power supply. Summary of the invention

[0003] The present invention provides an online monitoring method and system for the power generation capacity of a grid-connected coal-fired unit, which can effectively solve the problems in the background technology.

[0004] In order to achieve the above object, the technical solution adopted by the present invention is:

[0005] An online monitoring method for power generation capacity of a grid-connected coal-fired unit, the method comprising:

[0006] Collecting the operating parameters of important auxiliary equipment of the grid-connected coal-fired units and preprocessing the operating parameters of the important auxiliary equipment;

[0007] Based on the pre-processed operating parameters of the important auxiliary equipment, cluster analysis is performed on several typical operating conditions of the grid-connected coal-fired unit to calculate the equipment health status of the important auxiliary equipment;

[0008] Based on the typical operating conditions, filter out unavailable auxiliary equipment from among the important auxiliary equipment according to the equipment health status;

[0009] Compare the number of auxiliary equipment in the unavailable state with the number of standby auxiliary equipment of the grid-connected coal-fired unit, and calculate the power generation capacity of the grid-connected coal-fired unit taking into account the health status of the equipment;

[0010] Calculate the power generation capacity of the grid-connected coal-fired unit considering coal quality, the power generation capacity of the grid-connected coal-fired unit considering main operating parameters, and the power generation capacity of the grid-connected coal-fired unit considering heating conditions;

[0011] The minimum value of the calculated power generation capacities of the four grid-connected coal-fired units is selected, and the maximum load that can be carried by the grid-connected coal-fired unit is predicted based on the minimum value.

[0012] Furthermore, the operating parameters of the important auxiliary equipment are preprocessed, including: preprocessing the collected operating parameter data of the important auxiliary equipment using one or more of the upper and lower limit constraint method, the improved 53H method, the association analysis method and the redundancy check method; for the alarm measurement points, replacing them with normal values ​​of historical similar operating conditions in the k-means clustering results.

[0013] Furthermore, based on the pre-processed operating parameters of the important auxiliary equipment, cluster analysis is performed on several typical operating conditions of the grid-connected coal-fired unit to calculate the equipment health status of the important auxiliary equipment, including:

[0014] Cluster analysis is performed on the operating parameters of the important auxiliary equipment by using the K-means algorithm and the GMM algorithm, and the operating parameters of the important auxiliary equipment are divided into 100 typical operating conditions;

[0015] For each of the typical operating conditions, the normal values ​​of the operating parameters of each of the important auxiliary equipment are calculated using the BP neural network;

[0016] Based on the normal value, the normal health of each of the important auxiliary equipment operating parameters is calculated by cosine similarity to obtain the equipment health status.

[0017] Further, the number of auxiliary equipment in the unavailable state is compared with the number of standby auxiliary equipment of the grid-connected coal-fired unit, and the power generation capacity of the grid-connected coal-fired unit considering the health state of the equipment is calculated, including:

[0018] Comparing the number of auxiliary equipment in the unavailable state with the number of standby auxiliary equipment of the grid-connected coal-fired unit;

[0019] If the number of auxiliary equipment in the unavailable state is less than or equal to the number of standby auxiliary equipment of the grid-connected coal-fired unit, the power generation capacity of the grid-connected coal-fired unit will not be affected;

[0020] If the number of auxiliary equipment in the unavailable state is greater than the number of standby auxiliary equipment of the grid-connected coal-fired unit, the power generation capacity of the grid-connected coal-fired unit is affected. The power generation capacity of the grid-connected coal-fired unit considering the health status of the equipment is calculated as follows:

[0021] u1=U l[1-(n1-n2) / n+λ(n-n1+n2)];

[0022] Among them, U l is the rated load of the grid-connected coal-fired unit, n1, n2, and n are respectively the number of unavailable equipment, the number of standby equipment, and the number of equipment running at full load of the same type of equipment, and λ is the output margin of the important auxiliary equipment.

[0023] Furthermore, the power generation capacity of the grid-connected coal-fired unit considering the coal quality is calculated using the following formula:

[0024]

[0025] Among them, n3 is the total number of available and spare coal feeders, ω is the maximum coal feeding rate of the coal feeder, κ1, κ2, κ3, κ4, κ5 are rated load, main steam pressure, main steam temperature, reheat steam temperature and back pressure correction coefficient respectively, and β is the raw coal consumption rate of power supply under the current operating conditions.

[0026] Further, when considering the power generation capacity of the grid-connected coal-fired unit of the main operating parameters, if the main operating parameters deviate from the normal values ​​under the current operating conditions, an alarm signal is issued, and the power generation capacity of the grid-connected coal-fired unit is set according to the alarm signal.

[0027] Furthermore, the power generation capacity of the grid-connected coal-fired unit considering the heating situation is calculated as follows:

[0028]

[0029] Among them, f gy 、f cn are the heating flow rates for industrial heating and heating respectively; h gy 、h cn 、h w are the enthalpy values ​​of industrial heating, heating supply and heating return water respectively; μ qj is the turbine efficiency under current operating conditions.

[0030] Furthermore, the minimum value of the power generation capacity of the four grid-connected coal-fired units obtained by calculation is selected, and the calculation formula is:

[0031] u=min(u1,u2,u3,u4);

[0032] Among them, u is the power generation capacity of the grid-connected coal-fired unit, and u1, u2, u3, and u4 are the power generation capacities of the grid-connected coal-fired unit taking into account the equipment health status, coal quality, main operating parameters, and heating conditions of important auxiliary equipment.

[0033] Furthermore, the maximum load that the grid-connected coal-fired unit can carry in the next 15 minutes is predicted based on the minimum value, and the calculation formula is:

[0034] u 15 =u r +15ξ;

[0035] Among them, u r is the real-time load of the grid-connected coal-fired unit under the current operating conditions, and ξ is the maximum load regulation rate of the grid-connected coal-fired unit under similar historical operating conditions.

[0036] An online monitoring system for power generation capacity of a grid-connected coal-fired unit, the system comprising:

[0037] An operating parameter collection module collects operating parameters of important auxiliary equipment of the grid-connected coal-fired unit and pre-processes the operating parameters of the important auxiliary equipment;

[0038] A health status calculation module, based on the pre-processed operating parameters of the important auxiliary equipment, performs cluster analysis on several typical operating conditions of the grid-connected coal-fired unit to calculate the health status of the important auxiliary equipment;

[0039] An auxiliary equipment screening module, based on the typical operating conditions, screens out unavailable auxiliary equipment from the important auxiliary equipment according to the equipment health status;

[0040] A power generation capacity calculation module compares the number of auxiliary equipment in the unavailable state with the number of standby auxiliary equipment of the grid-connected coal-fired unit, and calculates the power generation capacity of the grid-connected coal-fired unit taking into account the health status of the equipment; calculates the power generation capacity of the grid-connected coal-fired unit taking into account the coal quality, the power generation capacity of the grid-connected coal-fired unit taking into account the main operating parameters, and the power generation capacity of the grid-connected coal-fired unit taking into account the heating conditions;

[0041] The loadable load prediction module selects the minimum value of the calculated power generation capacities of the four grid-connected coal-fired units, and predicts the maximum loadable load of the grid-connected coal-fired unit according to the minimum value.

[0042] The technical solution of the present invention can achieve the following technical effects:

[0043] It effectively realizes the real-time online monitoring and evaluation of the power generation capacity of grid-connected coal-fired units, transforms expert experience into mathematical models, effectively reduces human errors, and has good real-time performance, which can provide data support for reliable power supply and optimized scheduling.

[0044] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0046] Figure 1 A schematic diagram of a process for online monitoring of power generation capacity of a grid-connected coal-fired unit;

[0047] Figure 2 A schematic diagram of a process for setting the power generation capacity of a grid-connected coal-fired unit according to an alarm signal;

[0048] Figure 3 The schematic diagram is a structural diagram of an online monitoring system for the power generation capacity of a grid-connected coal-fired unit. DETAILED DESCRIPTION

[0049] The technical solutions in the embodiments of the present invention will be clearly and completely described 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.

[0050] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items.

[0051] Embodiment 1:

[0052] like Figure 1 As shown, an online monitoring method for power generation capacity of a grid-connected coal-fired unit comprises:

[0053] S1: Collect the operating parameters of important auxiliary equipment of the grid-connected coal-fired units and pre-process the operating parameters of important auxiliary equipment;

[0054] S2: Based on the pre-processed operating parameters of important auxiliary equipment, cluster analysis is performed on several typical operating conditions of grid-connected coal-fired units to calculate the equipment health status of important auxiliary equipment;

[0055] Specifically, the health status of important auxiliary equipment directly affects the power generation capacity of grid-connected coal-fired units. Important auxiliary equipment should at least include primary fans, forced draft fans, induced draft fans, air preheaters, coal mills, coal feeders, sealed fans, fire detection cooling fans, lubricating oil pumps, EH oil pumps, sealed oil pumps, steam pump pre-pumps, feed water pumps, condensate pumps, circulating water pumps, vacuum pumps, slurry circulating pumps and other major equipment. The health status of the equipment can be analyzed using a clustering analysis algorithm that combines the K-means algorithm with the EM-based GMM algorithm.

[0056] S3: Based on several typical operating conditions, filter out unavailable auxiliary equipment from important auxiliary equipment according to the equipment health status;

[0057] The actual health of each current operating condition should be compared with the normal health of one of the corresponding 100 typical operating conditions. If the actual health is lower than 0.6 times the normal health under the current operating condition, it is determined that the current equipment is severely degraded and is unavailable.

[0058] S4: Compare the number of unavailable auxiliary equipment and the number of standby auxiliary equipment of the grid-connected coal-fired units, and calculate the power generation capacity of the grid-connected coal-fired units considering the health status of the equipment;

[0059] S5: Calculate the power generation capacity of the grid-connected coal-fired units considering coal quality, the power generation capacity of the grid-connected coal-fired units considering main operating parameters, and the power generation capacity of the grid-connected coal-fired units considering heating conditions;

[0060] S6: Select the minimum value of the calculated power generation capacity of the four grid-connected coal-fired units, and predict the maximum load that the grid-connected coal-fired units can carry based on the minimum value.

[0061] In order to improve the timeliness and accuracy of the evaluation of the power generation capacity of the grid-connected coal-fired units, the collected data can be preprocessed, and the operating conditions can be clustered and analyzed into 100 categories. Then, the normal values ​​and normal health of the parameters can be obtained through data mining methods, and the health status of the equipment can be calculated. The power generation capacity of the grid-connected coal-fired unit considering the health status of the equipment is calculated by determining whether the equipment is available. There are many factors that affect the power generation capacity of the unit, which can be summarized as failure of important auxiliary equipment, excessive limit of main operating parameters, poor coal quality, etc. The power generation capacity of the grid-connected coal-fired unit considering coal quality, main operating parameters and heating conditions is calculated respectively, and the smaller value is taken as the real-time evaluation value of the power generation capacity of the grid-connected coal-fired unit. Based on the maximum load increase rate under the same historical operating conditions, the maximum load that the unit can carry in the next 15 minutes can be predicted.

[0062] Through the present invention, real-time online monitoring and evaluation of the power generation capacity of grid-connected coal-fired units is effectively realized, expert experience is converted into a mathematical model, human errors are effectively reduced, and real-time performance is good, which can provide data support for reliable power supply and optimized scheduling.

[0063] On the basis of the above-mentioned embodiment, the operating parameters of important auxiliary equipment are preprocessed, including: the collected operating parameter data of important auxiliary equipment are preprocessed by one or more of the upper and lower limit constraint method, the improved 53H method, the association analysis method and the redundancy check method; for the alarm measuring points, the normal values ​​of historical similar operating conditions in the k-means clustering results are used to replace them.

[0064] In order to improve the data quality, this step can pre-process the data collected from the DCS, including one or more of the upper and lower limit constraint method, the improved 53H method, the correlation analysis method and the redundancy check method. The upper and lower limit constraints perform upper and lower limit checks on the monitoring data of the alarm measuring points and eliminate abnormal values ​​that exceed the range; the improved 53H method can smooth the measuring point data, eliminate the influence of noise, and retain effective information; the correlation analysis method uses correlation analysis to check the relationship between different measuring points and find out potential abnormal patterns; the redundancy check method verifies the accuracy and consistency of the data by cross-comparing the data of multiple measuring points. For the abnormal data of the alarm measuring points, the historical normal values ​​are used to replace the abnormal data, which can maintain the continuity of the data and reduce the interference with subsequent analysis.

[0065] As a preferred embodiment of this embodiment, based on the pre-processed operating parameters of important auxiliary equipment, cluster analysis is performed on several typical operating conditions of the grid-connected coal-fired units to calculate the equipment health status of the important auxiliary equipment, including:

[0066] A1: Cluster analysis is performed on the operating parameters of important auxiliary equipment using the K-means algorithm and the GMM algorithm, and the operating parameters of important auxiliary equipment are divided into 100 typical operating conditions;

[0067] Specifically, K-means is an unsupervised clustering algorithm that clusters data into preset K clusters by minimizing the distance from data points to their respective cluster centers. In this step, the collected auxiliary equipment monitoring data can be preliminarily clustered through the K-means algorithm; GMM is a more flexible clustering model. The EM algorithm is the core of GMM, which is used to estimate the probability that each data point belongs to a different Gaussian distribution, so that the model can adapt to clusters of different shapes and provide more accurate clustering results. GMM can help refine and correct the results of K-means to obtain a more reasonable 100 operating condition categories, accurately reflecting the diversity and complexity of the health status of different equipment.

[0068] A2: For each typical operating condition, the BP neural network is used to calculate the normal values ​​of the operating parameters of each important auxiliary equipment;

[0069] A3: Based on the normal value, the normal health of the operating parameters of each important auxiliary equipment is calculated through cosine similarity to obtain the equipment health status.

[0070] On the basis of the above embodiment, for each typical working condition, the BP neural network is used to calculate the normal value of the operating parameters of each auxiliary equipment. The network is trained with a large amount of historical data and can adapt to the nonlinear relationship under different working conditions and output the normal value of the parameters under each working condition. To obtain the health status of the equipment, the cosine similarity of the current operating parameter vector of the equipment and the normal value vector under the working condition can be calculated to evaluate the current health. The higher the health, the closer the operating status of the equipment is to the normal state; a lower health indicates that an abnormality may exist.

[0071] Furthermore, the number of unavailable auxiliary equipment and the number of standby auxiliary equipment of the grid-connected coal-fired units are compared to calculate the power generation capacity of the grid-connected coal-fired units considering the health status of the equipment, including:

[0072] B1: Compare the number of unavailable auxiliary equipment with the number of standby auxiliary equipment of grid-connected coal-fired units;

[0073] B2: If the number of unavailable auxiliary equipment is less than or equal to the number of standby auxiliary equipment of the grid-connected coal-fired units, the power generation capacity of the grid-connected coal-fired units will not be affected;

[0074] B3: If the number of unavailable auxiliary equipment is greater than the number of standby auxiliary equipment of the grid-connected coal-fired units, the power generation capacity of the grid-connected coal-fired units will be affected. The power generation capacity of the grid-connected coal-fired units considering the health status of the equipment is calculated using the following formula:

[0075] u1=U l [1-(n1-n2) / n+λ(n-n1+n2)];

[0076] Among them, U l is the rated load of the grid-connected coal-fired units, n1, n2, and n are the number of unavailable equipment, the number of standby equipment, and the number of equipment in operation at full load of the same type, respectively, and λ is the output margin of important auxiliary equipment, which is taken as 10%.

[0077] Furthermore, the power generation capacity of the grid-connected coal-fired units considering the coal quality is calculated as follows:

[0078]

[0079] Among them, n3 is the total number of available and spare coal feeders, ω is the maximum coal feeding rate of the coal feeder, κ1, κ2, κ3, κ4, κ5 are the rated load, main steam pressure, main steam temperature, reheat steam temperature and back pressure correction coefficient respectively, and β is the raw coal consumption rate of power supply under the current operating conditions.

[0080] Specifically, the coal feeder has a maximum coal feeding rate limit. When the coal quality is very poor, the grid-connected coal-fired unit may not be able to carry the rated load due to coal quality problems. The generator active power (maximum variation range ±1% rated load), main steam flow (maximum variation range ±15t / h), main steam temperature (maximum variation range ±3℃), main steam pressure (maximum variation range ±0.5MPa), reheat steam temperature (maximum variation range ±3℃) and back pressure (maximum variation range ±0.5kPa), ambient temperature (maximum variation range ±3℃) are used as judgment conditions to determine whether the current operating conditions are stable. If stable, the condensate heat recovery extraction system and the feed water heat recovery extraction system are taken as the objects, and the condensate flow is used as the benchmark. The main steam flow is calculated through 7 iterations to calculate the turbine heat rate, and finally the power supply raw coal consumption rate is calculated based on the counter-balance boiler efficiency; if unstable, the power supply raw coal consumption rate of similar historical conditions is used as a substitute based on the similarity principle through k-means clustering. On the basis of the current raw coal consumption rate for power supply, according to the latest thermal test report data, taking into account the rated load, main steam pressure, main steam temperature, reheat steam temperature and back pressure correction, the raw coal consumption rate for power supply under rated operating conditions is obtained.

[0081] Based on the above embodiments, Figure 2 As shown, when the power generation capacity of the grid-connected coal-fired unit is considered based on the main operating parameters, if the main operating parameters deviate from the normal values ​​under the current operating conditions, an alarm signal is issued, and the power generation capacity of the grid-connected coal-fired unit is set according to the alarm signal.

[0082] In this embodiment, when the main operating parameters deviate from the normal value or issue an alarm, the power generation capacity of the grid-connected coal-fired unit is affected. If, under the current operating conditions, the actual health of a certain operating parameter is lower than 0.6 times the normal health, it is determined that the current parameter is severely deteriorated and an alarm signal is issued. When the DCS has an MFT or ETS alarm, the power generation capacity of the grid-connected coal-fired unit can be set to 0; when the DCS has an RB signal of failure of important auxiliary equipment such as the induced draft fan, primary fan, forced draft fan or steam-driven feedwater pump, the power generation capacity of the grid-connected coal-fired unit can be set to 0.55 times the rated load; when the wind-water-coal ratio is uncoordinated and the output of the main equipment reaches the upper limit, the power generation capacity of the grid-connected coal-fired unit can be set to the current generator active power; when the condenser back pressure, main steam pressure, main steam pressure temperature, high-pressure cylinder exhaust temperature, economizer outlet oxygen content, generator wire rod temperature, generator hydrogen pressure, feedwater flow, lubricating oil pressure, EH oil pressure, circulating water filter differential pressure, etc. deviate from the normal value or issue an alarm due to severe deterioration, the load will be reduced by 0.1 times the active power of the generator under the current operating conditions until the alarm is eliminated.

[0083] Furthermore, the power generation capacity of the grid-connected coal-fired units considering the heating situation is calculated as follows:

[0084]

[0085] Among them, f gy 、f cn are the heating flow rates for industrial heating and heating respectively; h gy 、h cn 、h w are the enthalpy values ​​of industrial heating, heating supply and heating return water respectively; μ qj is the turbine efficiency under current operating conditions.

[0086] Furthermore, the minimum value of the power generation capacity of the four grid-connected coal-fired units is selected, and the calculation formula is:

[0087] u=min(u1,u2,u3,u4);

[0088] Among them, u is the power generation capacity of the grid-connected coal-fired unit, and u1, u2, u3, and u4 are the power generation capacities of the grid-connected coal-fired unit taking into account the equipment health status, coal quality, main operating parameters, and heating conditions of important auxiliary equipment.

[0089] When the grid-connected coal-fired units are in operation, the power generation capacity of the grid-connected coal-fired units mainly considers the health status of important auxiliary equipment, coal quality, main operating parameters and heating conditions. The power generation capacity of the grid-connected coal-fired units takes the minimum value among them.

[0090] Furthermore, the maximum load that the grid-connected coal-fired unit can carry in the next 15 minutes is predicted based on the minimum value. The calculation formula is:

[0091] u 15 =u r +15ξ;

[0092] Among them, u r is the real-time load of the grid-connected coal-fired unit under the current operating conditions, and ξ is the maximum load regulation rate of the grid-connected coal-fired unit under similar historical conditions.

[0093] Embodiment 2:

[0094] like Figure 3 As shown, an online monitoring system for power generation capacity of a grid-connected coal-fired unit includes:

[0095] The operating parameter collection module collects the operating parameters of important auxiliary equipment of the grid-connected coal-fired units and pre-processes the operating parameters of important auxiliary equipment;

[0096] The health status calculation module performs cluster analysis on several typical operating conditions of grid-connected coal-fired units based on the pre-processed operating parameters of important auxiliary equipment, and calculates the equipment health status of important auxiliary equipment;

[0097] The auxiliary equipment screening module, based on several typical operating conditions, screens out unavailable auxiliary equipment from important auxiliary equipment according to the health status of the equipment;

[0098] The power generation capacity calculation module compares the number of unavailable auxiliary equipment and the number of standby auxiliary equipment of the grid-connected coal-fired units, and calculates the power generation capacity of the grid-connected coal-fired units taking into account the health status of the equipment; calculates the power generation capacity of the grid-connected coal-fired units taking into account the coal quality, the power generation capacity of the grid-connected coal-fired units taking into account the main operating parameters, and the power generation capacity of the grid-connected coal-fired units taking into account the heating conditions;

[0099] The loadable load prediction module selects the minimum value of the calculated power generation capacity of the four grid-connected coal-fired units and predicts the maximum loadable load of the grid-connected coal-fired units based on the minimum value.

[0100] Specifically, the system adopts a master-substation mode. In order to reduce the amount of data sent up and the amount of data calculation at the power grid master station, a cloud-edge collaborative method is adopted. The edge terminal is used at the power plant substation to complete data calculation and mining, realize the health status monitoring of important auxiliary equipment and online monitoring and real-time evaluation of power generation capacity, and upload the relevant results to the power grid master station for storage and calculation in the cloud, so as to realize the standard coal consumption rate, real-time raw coal consumption rate, main parameter alarms, health status of important auxiliary equipment and power generation capacity of grid-connected coal-fired units under typical operating conditions. Information monitoring.

[0101] The above-mentioned adjustment system in the present invention can effectively realize the online monitoring method for the power generation capacity of the grid-connected coal-fired unit, and the technical effects that can be achieved are as described in the above-mentioned embodiments, which will not be repeated here.

[0102] Although the present application has been described in conjunction with specific features and embodiments thereof, it is apparent that various modifications and combinations may be made thereto without departing from the spirit and scope of the present application. Accordingly, this specification and the accompanying drawings are merely exemplary illustrations of the present application as defined herein, and are deemed to have covered any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application is intended to include these modifications and variations.

Claims

1. An online monitoring method for the power generation capacity of a grid-connected coal-fired unit, characterized in that: The method comprises: Collecting the operating parameters of important auxiliary equipment of the grid-connected coal-fired units and preprocessing the operating parameters of the important auxiliary equipment; Based on the pre-processed operating parameters of the important auxiliary equipment, cluster analysis is performed on several typical operating conditions of the grid-connected coal-fired unit to calculate the equipment health status of the important auxiliary equipment; Based on the typical operating conditions, filter out unavailable auxiliary equipment from among the important auxiliary equipment according to the equipment health status; Compare the number of auxiliary equipment in the unavailable state with the number of standby auxiliary equipment of the grid-connected coal-fired unit, and calculate the power generation capacity of the grid-connected coal-fired unit taking into account the health status of the equipment; Calculate the power generation capacity of the grid-connected coal-fired unit considering coal quality, the power generation capacity of the grid-connected coal-fired unit considering main operating parameters, and the power generation capacity of the grid-connected coal-fired unit considering heating conditions; The minimum value of the calculated power generation capacities of the four grid-connected coal-fired units is selected, and the maximum load that can be carried by the grid-connected coal-fired unit is predicted based on the minimum value.

2. The method for online monitoring of power generation capacity of a grid-connected coal-fired unit according to claim 1, characterized in that: The operating parameters of the important auxiliary equipment are preprocessed, including: using one or more of the upper and lower limit constraint method, the improved 53H method, the association analysis method and the redundancy check method to preprocess the collected operating parameter data of the important auxiliary equipment, and for the alarm measurement points, using the normal values ​​of historical similar operating conditions in the k-means clustering results to replace them.

3. The method for online monitoring of power generation capacity of a grid-connected coal-fired unit according to claim 2, characterized in that: Based on the pre-processed operating parameters of the important auxiliary equipment, cluster analysis is performed on several typical operating conditions of the grid-connected coal-fired unit to calculate the equipment health status of the important auxiliary equipment, including: Cluster analysis is performed on the operating parameters of the important auxiliary equipment by using the K-means algorithm and the GMM algorithm, and the operating parameters of the important auxiliary equipment are divided into 100 typical operating conditions; For each of the typical operating conditions, the normal values ​​of the operating parameters of each of the important auxiliary equipment are calculated using the BP neural network; Based on the normal value, the normal health of each of the important auxiliary equipment operating parameters is calculated by cosine similarity to obtain the equipment health status.

4. The method for online monitoring of power generation capacity of a grid-connected coal-fired unit according to claim 1, characterized in that: The number of auxiliary equipment in the unavailable state is compared with the number of standby auxiliary equipment of the grid-connected coal-fired unit, and the power generation capacity of the grid-connected coal-fired unit considering the health state of the equipment is calculated, including: Comparing the number of auxiliary equipment in the unavailable state with the number of standby auxiliary equipment of the grid-connected coal-fired unit; If the number of auxiliary equipment in the unavailable state is less than or equal to the number of standby auxiliary equipment of the grid-connected coal-fired unit, the power generation capacity of the grid-connected coal-fired unit will not be affected; If the number of auxiliary equipment in the unavailable state is greater than the number of standby auxiliary equipment of the grid-connected coal-fired unit, the power generation capacity of the grid-connected coal-fired unit is affected. The power generation capacity of the grid-connected coal-fired unit considering the health status of the equipment is calculated as follows: u1=U l [1-(n1-n2) / n+λ(n-n1+n2)]; Among them, U l is the rated load of the grid-connected coal-fired unit, n1, n2, and n are respectively the number of unavailable equipment, the number of standby equipment, and the number of equipment running at full load of the same type of equipment, and λ is the output margin of the important auxiliary equipment.

5. The method for online monitoring of power generation capacity of a grid-connected coal-fired unit according to claim 1, characterized in that: The power generation capacity of the grid-connected coal-fired unit considering the coal quality is calculated as follows: Among them, n3 is the total number of available and spare coal feeders, ω is the maximum coal feeding rate of the coal feeder, κ1, κ2, κ3, κ4, κ5 are rated load, main steam pressure, main steam temperature, reheat steam temperature and back pressure correction coefficient respectively, and β is the raw coal consumption rate of power supply under the current operating conditions.

6. The method for online monitoring of power generation capacity of a grid-connected coal-fired unit according to claim 1, characterized in that: When considering the power generation capacity of the grid-connected coal-fired unit of the main operating parameters, if the main operating parameters deviate from the normal values ​​under the current operating conditions, an alarm signal is issued, and the power generation capacity of the grid-connected coal-fired unit is set according to the alarm signal.

7. The method for online monitoring of power generation capacity of a grid-connected coal-fired unit according to claim 1, characterized in that: The power generation capacity of the grid-connected coal-fired unit considering the heating situation is calculated as follows: Among them, f gy 、f cn are the heating flow rates for industrial heating and heating respectively; h gy 、h cn 、h w are the enthalpy values ​​of industrial heating, heating supply and heating return water respectively; μ qj is the turbine efficiency under current operating conditions.

8. The method for online monitoring of power generation capacity of a grid-connected coal-fired unit according to claim 1, characterized in that: The minimum value of the power generation capacity of the four grid-connected coal-fired units obtained by calculation is selected, and the calculation formula is: u=min(u1,u2,u3,u4); Among them, u is the power generation capacity of the grid-connected coal-fired unit, and u1, u2, u3, and u4 are the power generation capacities of the grid-connected coal-fired unit taking into account the equipment health status, coal quality, main operating parameters, and heating conditions of important auxiliary equipment.

9. The method for online monitoring of power generation capacity of a grid-connected coal-fired unit according to claim 1, characterized in that: The maximum load that the grid-connected coal-fired unit can carry in the next 15 minutes is predicted based on the minimum value, and the calculation formula is: u 15 =u r +15ξ; Among them, u r is the real-time load of the grid-connected coal-fired unit under the current operating conditions, and ξ is the maximum load regulation rate of the grid-connected coal-fired unit under similar historical operating conditions.

10. An online monitoring system for the power generation capacity of a grid-connected coal-fired unit, characterized in that: The system comprises: An operating parameter collection module collects operating parameters of important auxiliary equipment of the grid-connected coal-fired unit and pre-processes the operating parameters of the important auxiliary equipment; A health status calculation module, based on the pre-processed operating parameters of the important auxiliary equipment, performs cluster analysis on several typical operating conditions of the grid-connected coal-fired unit to calculate the health status of the important auxiliary equipment; An auxiliary equipment screening module, based on the typical operating conditions, screens out unavailable auxiliary equipment from the important auxiliary equipment according to the equipment health status; A power generation capacity calculation module compares the number of auxiliary equipment in the unavailable state with the number of standby auxiliary equipment of the grid-connected coal-fired unit, and calculates the power generation capacity of the grid-connected coal-fired unit taking into account the health status of the equipment; calculates the power generation capacity of the grid-connected coal-fired unit taking into account the coal quality, the power generation capacity of the grid-connected coal-fired unit taking into account the main operating parameters, and the power generation capacity of the grid-connected coal-fired unit taking into account the heating conditions; The loadable load prediction module selects the minimum value of the calculated power generation capacities of the four grid-connected coal-fired units, and predicts the maximum loadable load of the grid-connected coal-fired unit according to the minimum value.

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