Combined heat and power generation air compression intelligent control method, intelligent control type combined heat and power generation air compression system and medium

Abstract

The invention relates to the field of combined heat and power generation, and provides a combined heat and power generation air compression intelligent control method, an intelligent control type combined heat and power generation air compression system and a medium. The intelligent control method comprises the following steps: acquiring operation data of each air compressor; acquiring monitoring data acquired by a monitoring assembly arranged in the compressed air station; the operation data and the monitoring data are input into a dynamic simulation model corresponding to the compressed air station, the comprehensive state of the compressed air station is obtained, and the dynamic simulation model corresponds to the entity structure of the compressed air station; determining whether the compressed air station is abnormal based on the comprehensive state; and when it is determined that the compressed air station is abnormal, an abnormity processing flow is automatically executed. By the adoption of the technical scheme, the operation data of the air compressor and the monitoring data collected by the monitoring assembly can be combined to conduct simulation and abnormity monitoring on the overall operation state of the compressed air station, and therefore the safety of overall operation of the compressed air station can be improved.

Description

Technical Field

[0001] The present application relates to the field of cogeneration, and in particular to a cogeneration air compressor intelligent control method, an intelligently controlled cogeneration air compressor system and a medium. Background Art

[0002] At present, cogeneration systems have been widely used in the energy field. As an important component, air compressors have become increasingly energy-consuming. In some design schemes, the energy efficiency level of the four air compressors and combined dryers in the cogeneration system cannot meet the latest national standards according to the latest GB 19153-2019 Energy efficiency limit values ​​and energy efficiency levels for positive displacement air compressors. At the same time, the air compressors are all star-delta started, without air volume adjustment function, and have a high unloading rate.

[0003] In order to improve the operating efficiency and reliability of compressed air stations, the solutions currently commonly used in the industry mainly include regular manual inspections, manual recording of equipment operating parameters, and monitoring the basic operating status of air compressors by setting fixed thresholds.

[0004] Although the above-mentioned measures can ensure the basic operation of the air compressor to a certain extent, it is difficult to timely and accurately judge the potential problems and abnormal conditions in the compressed air station, which will increase the safety risks in the production process. Summary of the invention

[0005] In order to help improve the safety of the production process, the present application provides a cogeneration air compressor intelligent control method, an intelligent control cogeneration air compressor system and a medium.

[0006] In the first aspect, the present application provides a cogeneration air compressor intelligent control method, which adopts the following technical solution: A cogeneration air compressor intelligent control method is used in a compressed air station, wherein the compressed air station includes at least one air compressor, and the method includes: Acquiring the operating data of each of the air compressors; Acquiring monitoring data collected by a monitoring component provided in the compressed air station; Inputting the operating data and the monitoring data into a dynamic simulation model corresponding to the compressed air station to obtain a comprehensive state of the compressed air station, wherein the dynamic simulation model corresponds to the physical structure of the compressed air station; determining whether there is an abnormality in the compressed air station based on the comprehensive status; When it is determined that the compressed air station has an abnormality, the abnormality handling process is automatically executed.

[0007] By adopting the above technical scheme, the comprehensive status of the compressed air station can be determined based on the operating data of the air compressor and the monitoring data collected by the monitoring component, and when it is determined that the compressed air station has an abnormality based on the comprehensive status, the abnormality handling process is automatically executed. In this way, the overall operating status of the compressed air station can be simulated and abnormalities can be monitored in combination with different data, which can help improve the overall operation safety of the compressed air station.

[0008] Optionally, the monitoring data includes equipment monitoring data collected by a monitoring component disposed on the equipment to be monitored of the compressed air station, and the operation data and the monitoring data are input into a dynamic simulation model corresponding to the compressed air station to obtain a comprehensive state of the compressed air station, including: Inputting the operation data and the equipment monitoring data into the dynamic simulation model to update the equipment parameters of each of the air compressors and the equipment to be monitored in the dynamic simulation model; The comprehensive status of the compressed air station is determined based on the equipment parameters of each of the air compressors and the equipment to be monitored.

[0009] By adopting the above technical solution, the comprehensive status can comprehensively reflect the conditions of different equipment in the compressed air station, which can help improve the accuracy of the determined comprehensive status.

[0010] Optionally, determining the comprehensive status of the compressed air station based on the status of each of the air compressors and the equipment to be monitored includes: Determine the equipment parameters of the reference equipment in the dynamic simulation model based on the equipment parameters of each of the air compressors and the equipment parameters of the equipment to be monitored, wherein the reference equipment is different from the air compressor and the equipment to be monitored, and there is an association relationship between the reference equipment and the air compressor and / or the equipment to be monitored; The comprehensive status of the compressed air station is determined based on the equipment parameters of each of the air compressors, the equipment to be monitored and the reference equipment.

[0011] By adopting the above technical solution, it is possible to enrich the dimensions of data used to determine the comprehensive state through a dynamic simulation model without adding monitoring components, thereby helping to improve the reference value of the determined comprehensive state.

[0012] Optionally, the monitoring data includes pipeline monitoring data collected by a monitoring component arranged on a pipeline of the compressed air station, and the comprehensive state of the compressed air station is determined based on the equipment parameters of each of the air compressors and the equipment to be monitored, including: Determining the equipment status of the compressed air station based on the equipment parameters of each of the air compressors and the equipment to be monitored; determining a pipeline status of the compressed air station based on the pipeline monitoring data; determining whether the device state matches the pipeline state; In the case where the equipment status matches the pipeline status, the comprehensive status of the compressed air station is determined based on the equipment parameters of each of the air compressors and the equipment to be monitored.

[0013] By adopting the above technical solution, the pipeline status can be determined in combination with the pipeline monitoring data, and when the equipment status matches the pipeline status, the comprehensive status of the compressed air station can be determined based on the equipment parameters of the air compressor and the equipment to be tested. This can help ensure the validity of the equipment parameters used to determine the comprehensive status, and can help ensure the accuracy of the determined comprehensive status.

[0014] Optionally, after determining whether the device state matches the pipeline state, the method further includes: In the case where the device state matches the pipeline state, determining whether to modify the device state; In the case where it is determined that the device state is to be corrected, a step of correcting the device state is performed so that the device state matches the pipeline state; When it is determined that the equipment status is not to be corrected, it is directly determined that an abnormality exists in the compressed air station.

[0015] By adopting the above technical solution, when it is determined that the device state does not match the pipeline state, it can be determined whether to correct the device state, and when it is determined that the device state should be corrected, the device state is corrected so that the device state matches the pipeline state, which can help improve the efficiency and accuracy of abnormality judgment.

[0016] Optionally, the method further includes: Predicting the gas consumption of the gas-consuming equipment connected to the compressed air station to obtain the predicted gas consumption; The control strategy of the compressed air station is adjusted based on the predicted gas consumption.

[0017] By adopting the above technical solution, the gas consumption of gas-consuming equipment can be predicted, and the control strategy of the compressed air station can be adjusted based on the predicted gas consumption. This can help improve the matching degree between the gas production of the compressed air station and the needs of the gas-consuming equipment, and further help improve the accuracy of the compressed air station control, and also help improve the energy efficiency of the compressed air station.

[0018] Optionally, the gas-consuming equipment includes power generation equipment, and predicting the gas consumption of the gas-consuming equipment connected to the compressed air station to obtain the predicted gas consumption includes: Obtaining historical power generation changes of the power generation equipment; Predicting the power generation of the power generation equipment based on the historical power generation change to obtain predicted power generation; The predicted gas consumption corresponding to the power generation equipment is determined based on the predicted power generation.

[0019] By adopting the above technical solution, the power generation is predicted based on the historical power generation changes, and the predicted gas consumption is determined based on the predicted power generation, which can help to achieve accurate estimation of gas consumption.

[0020] Optionally, after adjusting the control strategy of the compressed air station based on the predicted gas consumption, the method further includes: Determining whether a control strategy of the compressed air station matches a control strategy of a heat recovery system corresponding to the compressed air station; In the case where the control strategy of the compressed air station does not match the control strategy of the heat recovery system, the control strategy of the heat recovery system is adjusted based on the control strategy of the compressed air station.

[0021] By adopting the above technical solution, the control strategy of the heat recovery system can be adjusted based on the control strategy of the compressed air station, which can help match the working strategy of the heat recovery system with the control strategy of the compressed air station, and further help improve the heat energy recovery rate of the heat recovery system.

[0022] In the second aspect, the present application provides an intelligent controlled cogeneration air compression system, which adopts the following technical solution: A smart controlled cogeneration air compression system, the system comprising a compressed air station, the compressed air station comprising at least one air compression device, at least one monitoring component and a control device connected to the air compression device and the monitoring component by signal, the control device being used to execute any one of the cogeneration air compression smart control methods provided in the first aspect.

[0023] In a second aspect, the present application provides an electronic device, which adopts the following technical solution: An electronic device, comprising: at least one processor; Memory; At least one application, wherein at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute any one of the cogeneration air compression intelligent control methods provided in the first aspect.

[0024] In summary, the present application includes at least one of the following beneficial technical effects: 1. The overall operating status of the compressed air station can be simulated and abnormal monitoring can be carried out by combining the operating data of the air compressor and the monitoring data collected by the monitoring components, which can help improve the overall operating safety of the compressed air station.

[0025] 2. The state of the compressed air station can be dynamically simulated based on the dynamic simulation model, so that the determined comprehensive state can better reflect the actual situation of the compressed air station, which can help improve the accuracy of abnormal monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a flow chart of a cogeneration air compressor intelligent control method provided in an embodiment of the present application; Figure 2 It is a flowchart of a comprehensive state determination method provided in an embodiment of the present application; Figure 3 is a structural schematic diagram of a cogeneration system provided in an embodiment of the present application; Figure 4 is a flowchart of another comprehensive state determination method provided in an embodiment of the present application; Figure 5 It is a flow chart of another cogeneration air compressor intelligent control method provided in an embodiment of the present application; Figure 6 It is a structural schematic diagram of an intelligent control type cogeneration air compression system provided in an embodiment of the present application; Figure 7 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical solutions and advantages of this application more clear, the following Figures 1 to 7 It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0028] The embodiment of the present application discloses a cogeneration air compressor intelligent control method, which is used in a compressed air station, and the compressed air station includes at least one air compressor. In actual implementation, the compressed air station may also include gas storage tanks, filters, dryers, pipelines, valves, drainers and other components. This embodiment does not limit the structure of the compressed air station.

[0029] Reference Figure 1 The cogeneration air compressor intelligent control method includes the following steps: Step 101, obtaining the operating data of each air compressor.

[0030] The operating data refers to data that can be used to measure the operating status of the air compressor. In one example, the operating data includes data that can be actually collected, such as operating pressure, volume flow, power, speed, and operating temperature. In actual implementation, the operating data may also include data such as work efficiency that is calculated based on the data actually collected. This embodiment does not limit the type of operating data.

[0031] In one example, the operation data is obtained at preset time intervals, such as 30 seconds. In actual implementation, the operation data can be reported by the air compressor when it detects that the change in the current operation data compared with the last reported operation data is greater than the preset range, which can help improve the response speed to the change in the operation data.

[0032] Step 102, obtaining monitoring data collected by a monitoring component provided in the compressed air station.

[0033] Among them, the monitoring component is used to monitor the working condition of the compressed air station.

[0034] In one example, the monitoring component is set on the equipment to be monitored in the compressed air station. At this time, the monitoring component can monitor the working condition of the equipment to be monitored. Accordingly, the monitoring data may include the temperature, jitter, noise level and other data of the equipment to be monitored. It should be noted that the equipment to be monitored may be an air compressor, or other equipment in the compressed air station, such as an air storage tank, a dryer, etc.

[0035] In another example, the monitoring component is disposed on a pipeline of a compressed air station, and the pipeline is used to connect different equipment of the compressed air station. At this time, the monitoring component can monitor the status of the pipeline. Accordingly, the monitoring data may include temperature, flow, jitter and other data of the pipeline.

[0036] Step 103, inputting the operation data and monitoring data into the dynamic simulation model corresponding to the compressed air station to obtain the comprehensive status of the compressed air station.

[0037] The dynamic simulation model corresponds to the physical structure of the compressed air station. Specifically, the dynamic simulation model includes the equipment of the compressed air station and the pipelines between the equipment. In this way, the overall operation process of the compressed air station can be simulated through the dynamic simulation model, which can help to realize remote monitoring and fault diagnosis of the compressed air station.

[0038] The comprehensive status refers to the overall operating status of the compressed air station. Specifically, after the operating data and monitoring data are input into the dynamic simulation model, the dynamic simulation model will simulate the actual operating conditions of the compressed air station in combination with the operating data and monitoring data to obtain the comprehensive status.

[0039] Optionally, the comprehensive state can be represented by at least one state parameter, and the dynamic simulation model records the corresponding relationship between the operating data and monitoring data and the state parameter.

[0040] In one example, the state parameter includes a ratio of operating data to monitoring data. In one example, the operating data includes working pressure, and the monitoring data includes pipeline pressure collected by a pressure sensing assembly provided in the pipeline. Accordingly, the state parameter may include a pressure ratio, i.e., a ratio of the working pressure to the pipeline pressure. In another example, the operating data includes speed, and the monitoring data may include vibration data collected by a vibration sensor provided on the air compressor. Accordingly, the state parameter includes a speed-vibration ratio, i.e., a ratio of the speed to the vibration data.

[0041] In another example, the state parameter may also be determined based only on the operating data or the monitoring data. In one example, the air compressor includes multiple air compressors, and accordingly, the state parameter may include the maximum pressure difference, that is, the maximum difference in the working pressures corresponding to each air compressor. In another example, the monitoring data includes the pipeline pressures corresponding to different pipelines, and accordingly, the state parameter may include the pipeline pressure difference, that is, the difference in the pipeline pressures corresponding to different pipelines. In actual implementation, the pipeline used to calculate the pipeline pressure difference can be selected according to the connection relationship between the pipelines.

[0042] In actual implementation, the status can be integrated or directly represented by the status of each device in the compressed air station. In this case, the status of the equipment can be updated directly in the dynamic simulation model using operating data and monitoring data.

[0043] Step 104: determine whether there is any abnormality in the compressed air station based on the comprehensive status.

[0044] In one example, the comprehensive state is represented by a state parameter. Accordingly, determining whether the compressed air station has an abnormality based on the comprehensive state includes: determining whether the state parameter is within a corresponding parameter range; if not, determining that the compressed air station has an abnormal state.

[0045] Among them, the parameter range corresponding to the state parameter is preset.

[0046] Furthermore, in the case where the state parameters include multiple ones, it is necessary to determine whether each state parameter is within the corresponding parameter range; if there is a state parameter that is not within the corresponding parameter range, it is determined that the compressed air station has an abnormal state. In addition, considering that the meanings and calculation methods of different state parameters are different, the parameter ranges corresponding to different state parameters are set separately.

[0047] In another example, the comprehensive status is represented by the status of different equipment in the compressed air station. Accordingly, determining whether there is an abnormality in the compressed air station based on the comprehensive status includes: determining whether the equipment status of each device matches; and determining that there is an abnormality in the compressed air station when there are devices with mismatched equipment status.

[0048] Among them, the status matching relationship between different devices is preset.

[0049] Step 105, when it is determined that the compressed air station has an abnormality, the abnormality handling process is automatically executed.

[0050] The exception handling process is pre-set. In one example, the exception handling process includes an alarm process. Specifically, the alarm process can be executed by sending alarm prompt information to the background staff, controlling the alarm equipment corresponding to the compressed air station, etc., to prompt the staff to handle the equipment abnormality.

[0051] Furthermore, the automatic execution of the abnormality handling process also includes: determining the risk value of the compressed air station; when the risk value is greater than the preset risk value threshold, controlling the compressed air station to stop working. The risk value can be determined based on the comprehensive state, for example: when the comprehensive state includes state parameters, the risk value can be determined based on the state parameters and the corresponding parameter range, or the risk value can be directly determined based on the operating data, for example: the operating data includes working pressure, and the greater the working pressure, the higher the corresponding risk value. This can help reduce the safety risks caused by abnormalities in compressed air stations.

[0052] Furthermore, when the risk value is less than or equal to the risk value threshold, it is determined whether the difference between the risk value and the risk value threshold is less than the preset risk difference threshold; when the difference is less than the risk difference threshold, the air supply of the compressed air station is reduced, and the risk value is continuously monitored to see whether it is greater than the risk value threshold. This can help avoid safety risks caused by air station abnormalities.

[0053] The implementation principle of a cogeneration air compressor intelligent control method in an embodiment of the present application is: obtain the operating data of each air compressor; obtain the monitoring data collected by the monitoring component set in the compressed air station; input the operating data and the monitoring data into the dynamic simulation model corresponding to the compressed air station to obtain the comprehensive state of the compressed air station, and the dynamic simulation model corresponds to the physical structure of the compressed air station; determine whether there is an abnormality in the compressed air station based on the comprehensive state; when it is determined that there is an abnormality in the compressed air station, automatically execute the abnormality handling process. By adopting the above technical solution, the comprehensive state of the compressed air station can be determined based on the operating data of the air compressor and the data collected by the monitoring component, and when it is determined that there is an abnormality in the compressed air station based on the comprehensive state, the abnormality handling process is automatically executed. In this way, the overall operating state of the compressed air station can be simulated and monitored in combination with different data, and the abnormality handling can be automatically performed when an abnormality is detected, which can help improve the safety of the overall operation of the compressed air station.

[0054] In addition, since the state of the compressed air station can be dynamically simulated based on the dynamic simulation model, this can help to correlate the states of different equipment and pipelines in the compressed air station, so that the determined comprehensive state can better reflect the actual situation of the compressed air station, which can help improve the accuracy of abnormal monitoring.

[0055] In some embodiments, the monitoring data includes equipment monitoring data collected by a monitoring component disposed on the equipment to be monitored in the compressed air station.

[0056] Accordingly, reference Figure 2 , step 103, inputting the operation data and the monitoring data into the dynamic simulation model corresponding to the compressed air station to obtain the comprehensive state of the compressed air station, including the following steps: Step 201 : inputting the operation data and the equipment monitoring data into the dynamic simulation model to update the equipment parameters of each air compressor and the equipment to be monitored in the dynamic simulation model.

[0057] Among them, the equipment parameters are used to record the working status of the equipment. In actual implementation, since the working modes corresponding to different types of equipment may be different, the types of equipment parameters corresponding to different types of equipment are set separately. For example: the equipment data of the air compressor may include working pressure, volume flow, power, speed, working temperature, etc.; the equipment data of the gas tank may include air pressure value, air intake speed, air outlet speed, etc.; the equipment data of the dryer may include air intake temperature, air outlet temperature, etc.

[0058] Step 202: Determine the comprehensive status of the compressed air station based on the equipment parameters of each air compressor and the equipment to be monitored.

[0059] Specifically, the comprehensive state is represented by state parameters. At this time, the method of determining the state parameters based on the equipment parameters can be analogous to the method of determining the state parameters based on the operation data and the monitoring data in step 103, which will not be repeated here.

[0060] Furthermore, the comprehensive state of the compressed air station is determined based on the equipment parameters of each air compressor and the equipment parameters of the equipment to be monitored, including: determining the equipment parameters of the reference equipment in the dynamic simulation model based on the equipment parameters of each air compressor and the equipment parameters of the equipment to be monitored; determining the comprehensive state of the compressed air station based on the equipment parameters of each air compressor, the equipment to be monitored and the reference equipment.

[0061] The reference device is different from the air compressor and the device to be monitored, and there is an association relationship between the reference device and the air compressor and / or the device to be monitored. In this embodiment, the corresponding mode of device parameters between the devices with association relationship is preset in the dynamic simulation model.

[0062] In the above technical scheme, the equipment parameters of the reference device can be determined by the equipment parameters of the air compressor and the equipment parameters of the device to be monitored, and the comprehensive status can be determined in combination with the equipment parameters of the reference device. This can help enrich the dimensions of the data used to determine the comprehensive status without adding monitoring components, and further help improve the reference value of the determined comprehensive status.

[0063] In one example, reference Figure 3 Taking a cogeneration system as an example, in which the air compressor, primary gas tank, dryer, secondary gas tank and gas-using equipment are connected in sequence, the secondary gas tank can be determined as the equipment to be monitored, and the primary gas tank dryer can be determined as the reference equipment. In this way, the equipment parameters of the primary gas tank and the dryer can be predicted and updated based on the equipment parameters of the air compressor and the secondary gas tank.

[0064] In the above embodiment, since the monitoring data includes equipment monitoring data, and the equipment parameters of the air compressor and the equipment to be monitored can be updated based on the operation data and the equipment monitoring data, and the comprehensive status of the compressed air station is determined based on the equipment parameters of the air compressor and the equipment to be monitored, such a comprehensive status can comprehensively reflect the conditions of different equipment in the compressed air station, which can help to improve the accuracy of the determined comprehensive status.

[0065] Further, in some embodiments, the monitoring data includes pipeline monitoring data collected by a monitoring component disposed on a pipeline of a compressed air station. Figure 4 , step 202, determining the comprehensive status of the compressed air station based on the equipment parameters of each air compressor and the equipment to be monitored, including the following steps: Step 301: determine the equipment status of the compressed air station based on the equipment parameters of each air compressor and the equipment to be monitored.

[0066] In one example, the equipment status is represented by the equipment power consumption. Accordingly, the equipment status of the compressed air station is determined based on the equipment parameters of each air compressor and the equipment to be monitored, including: estimating the equipment power consumption based on the equipment parameters of each air compressor and the equipment to be monitored. Specifically, the power consumption of different equipment is estimated based on the equipment parameters corresponding to different equipment; and the equipment power consumption is determined based on the power consumption of different equipment.

[0067] In another example, the equipment status is represented by an equipment status level, and the equipment status of the compressed air station is determined based on the equipment parameters of each air compressor and the detection equipment, including: determining the status parameters of the compressed air station based on the equipment parameters of each air compressor and the detection equipment; determining the equipment status level corresponding to the parameter interval to which the status parameter belongs as the equipment status.

[0068] The parameter interval is obtained by dividing the value range of the status parameter, and the device status levels corresponding to different parameter intervals are preset.

[0069] Specifically, the method of determining the state parameters based on the equipment parameters can be analogous to the method of determining the state parameters based on the operation data and the monitoring data in step 103, which will not be repeated here.

[0070] Furthermore, when there are multiple status parameters, since the value ranges of different status parameters are different, the parameter interval division methods corresponding to different status parameters are also different. In the actual implementation process, it is necessary to determine the device status level corresponding to each status parameter and set the highest device status level corresponding to each status parameter as the device status.

[0071] Step 302, determining the pipeline status of the compressed air station based on the pipeline monitoring data.

[0072] Optionally, the pipeline status is represented by a pipeline status level. Accordingly, determining the pipeline status of the compressed air station based on the pipeline monitoring data includes: determining the pipeline status as the pipeline status according to the pipeline status level corresponding to the data interval to which the pipeline monitoring data belongs.

[0073] The data interval is obtained by dividing the value range of the pipeline monitoring data, and the pipeline status levels corresponding to different data intervals are preset.

[0074] Furthermore, when multiple pipelines are monitored simultaneously, since the actual conditions of different pipelines may be different, the data intervals corresponding to different pipeline monitoring data may also be different. In the actual implementation process, it is necessary to determine the pipeline status level corresponding to each pipeline monitoring data, and determine the highest pipeline status level corresponding to each pipeline monitoring data as the pipeline status.

[0075] Step 303, determine whether the device status matches the pipeline status.

[0076] In one example, the device state is represented by the device power consumption, and the pipeline state is represented by the pipeline state level. At this time, determining whether the device state matches the pipeline state includes: determining whether the device power consumption is in the power consumption interval corresponding to the pipeline state level; if so, determining that the device state matches the pipeline state; if not, determining that the device state does not match the pipeline state.

[0077] Among them, the power consumption range corresponding to the pipeline status level is preset.

[0078] In another example, the device state is represented by a device state level, and the pipeline state is identified by a pipeline state level. At this time, determining whether the device state matches the pipeline state includes: determining whether the device state level matches the pipeline state level; if so, determining that the device state matches the pipeline state; if not, determining that the device state does not match the pipeline state.

[0079] Among them, the matching relationship between the device status and the pipeline status is preset.

[0080] Step 304: When the equipment status matches the pipeline status, the comprehensive status of the compressed air station is determined based on the equipment parameters of each air compressor and the equipment to be monitored.

[0081] Specifically, the method of determining the comprehensive status of the compressed air station based on the equipment parameters of each air compressor and the equipment to be monitored is shown in step 202, and this embodiment will not be repeated here.

[0082] In actual implementation, the pipeline monitoring data can be further combined in the process of determining the comprehensive state, that is, the comprehensive state can be determined based on the equipment parameters of each air compressor and the equipment to be monitored and the pipeline monitoring data. In this way, the comprehensive state can not only reflect the conditions of different equipment, but also the conditions of the pipeline, so that the comprehensive state can more comprehensively reflect the actual situation of the compressed air station, which can help improve the accuracy of the abnormal judgment results. The method of determining the comprehensive state based on equipment parameters and pipeline monitoring data can be analogous to the method of determining the state parameters based on operation data and monitoring data in step 103, which will not be repeated here.

[0083] Optionally, when the device status matches the pipeline status, it can be further determined whether to correct the device status; when it is determined that the device status should be corrected, the step of correcting the device status is performed to make the device status match the pipeline status; when it is determined that the device status should not be corrected, it is directly determined that there is an abnormality in the compressed air station.

[0084] In the actual implementation process, it is found that the reason why the device status does not match the pipeline status may be that the device control method is unreasonable or the pipeline is damaged. In the case of unreasonable device control method, the device can be adjusted to make the device status match the pipeline status. Therefore, when it is determined that the device status does not match the pipeline status, further judgment can be made.

[0085] In the above technical solution, when it is determined that the device state does not match the pipeline state, it is determined whether to correct the device state, and when it is determined that the device state should be corrected, the device state is corrected so that the device state matches the pipeline state, which can help improve the efficiency and accuracy of abnormality judgment.

[0086] In one example, the device state is represented by the device power consumption, and determining whether to correct the device state includes: determining whether the device power consumption is less than the lower limit of the power consumption range corresponding to the pipeline state level; if so, determining to correct the device state; if not, determining not to correct the device state.

[0087] Accordingly, the step of correcting the equipment status is performed, including: increasing the output power of the compressed air station.

[0088] In the above implementation, the pipeline status can be determined in combination with the pipeline monitoring data, and when the equipment status matches the pipeline status, the comprehensive status of the compressed air station is determined based on the equipment parameters of the air compressor and the equipment to be detected. This can help ensure the validity of the equipment parameters used to determine the comprehensive status, and can help ensure the accuracy of the determined comprehensive status.

[0089] In some embodiments, reference Figure 5 The cogeneration air compressor intelligent control method provided in this embodiment also includes: Step 401, predicting the gas consumption of the gas-consuming equipment connected to the compressed air station to obtain the predicted gas consumption.

[0090] Optionally, the gas-consuming equipment includes power generation equipment, and historical power generation changes of the power generation equipment are obtained; the power generation of the power generation equipment is predicted based on the historical power generation changes to obtain predicted power generation; and the predicted gas consumption corresponding to the power generation equipment is determined based on the predicted power generation.

[0091] Among them, the corresponding relationship between power generation and gas consumption is pre-set according to the nature of the power generation equipment.

[0092] In one example, historical power generation changes are counted on a daily basis, that is, the changes in historical power generation in different time periods of each day are observed, and accordingly, the power generation of the power generation equipment is predicted based on the historical power generation changes, including: predicting the power generation of the power generation equipment in at least one subsequent time period based on the historical power generation changes to obtain the predicted power generation.

[0093] The length of the time period is preset. In principle, the time period should not be too long, as a long time period will result in a lack of real-time prediction of gas consumption. At the same time, the time period should not be too short, as a short time period will reduce the accuracy of a single prediction result. Therefore, it is necessary to select an appropriate time period length according to the actual situation, such as half an hour or one hour.

[0094] Since the power generation of power generation equipment may change with changes in factors such as electricity demand and power storage capacity, and the power generation will affect the gas consumption, in the above technical scheme, the power generation is predicted by the historical changes in power generation, and the predicted gas consumption is determined based on the predicted power generation, which can help to achieve accurate estimation of gas consumption.

[0095] Step 402: Adjust the control strategy of the compressed air station based on the predicted gas consumption.

[0096] Among them, the control strategy includes the control strategy of the air compressor. Specifically, the control strategy includes controlling the volume flow of the air compressor. Furthermore, when there are more than two air compressors, the control strategy can control different air compressors separately. For example, when the predicted gas consumption is low, some air compressors are controlled to work and the remaining air compressors are on standby. This can help put the air compressors in a suitable working state, which can help reduce the overall energy consumption of the compressed air station.

[0097] Furthermore, after adjusting the control strategy of the compressed air station based on the predicted gas consumption, it also includes: determining whether the control strategy of the compressed air station matches the control strategy of the heat recovery system corresponding to the compressed air station; if the control strategy of the compressed air station does not match the control strategy of the heat recovery system, adjusting the control strategy of the heat recovery system based on the control strategy of the compressed air station. In this way, the control strategy of the heat recovery system can be adjusted based on the control strategy of the compressed air station, which can help to match the working strategy of the heat recovery system with the control strategy of the compressed air station, and further help to improve the heat recovery rate of the heat recovery system.

[0098] In one example, determining whether a control strategy of a compressed air station matches a control strategy of a heat recovery system corresponding to the compressed air station includes: determining whether the compressed air station turns on or off an air compressor; and determining that the control strategy of the compressed air station does not match the control strategy of the heat recovery system when the compressed air station turns on or off the air compressor.

[0099] Accordingly, the control strategy of the heat recovery system is adjusted based on the control strategy of the compressed air station, including: when the air compressor is turned on, the recovery equipment corresponding to the air compressor in the heat recovery system is controlled to work; when the air compressor is turned off, the recovery equipment corresponding to the air compressor in the heat recovery system is controlled to shut down.

[0100] Furthermore, when the compressed air station does not turn on or off the air compressor, for each turned-on air compressor, determine whether the volume flow change amplitude of the air compressor is greater than a preset change amplitude threshold; if so, it is determined that the control strategy of the compressed air station does not match the control strategy of the heat recovery system.

[0101] Accordingly, the control strategy of the heat recovery system is adjusted based on the control strategy of the compressed air station, including: adjusting the working parameters of the recovery equipment corresponding to the air compressor whose volume flow rate change amplitude is greater than the preset change amplitude, and the specific adjustment direction is consistent with the change direction of the volume flow rate.

[0102] In the above embodiment, the gas consumption of the gas-consuming equipment can be predicted, and the control strategy of the compressed air station can be adjusted based on the predicted gas consumption. This can help improve the matching degree between the gas production of the compressed air station and the demand of the gas-consuming equipment, thereby helping to avoid the problems of insufficient gas production and excessive gas production, and further help to improve the accuracy of the compressed air station control, and also improve the energy efficiency of the compressed air station.

[0103] The present application also provides an intelligent control type cogeneration air compression system. Figure 6 The intelligent control cogeneration air compression system includes at least one air compressor 510, at least one monitoring component 520, and a control device 530 connected to the air compressor device 510 and the monitoring component 520 by signal. The control device 530 is used to execute the cogeneration air compression intelligent control method provided by the above method embodiment.

[0104] The monitoring component 520 may be a temperature monitoring component, a vibration monitoring component, a flow monitoring component, or other equipment that can monitor data. This embodiment does not limit the type of the monitoring component 520 .

[0105] In one example, the air compressor 510 is a screw air compressor.

[0106] In actual implementation, the control device 530 can also be connected to other device signals in the cogeneration system, such as: connected to the hot air blower and the heat recovery system signal, which can help to achieve comprehensive control of the cogeneration system.

[0107] The present application also provides an electronic device. Figure 7 As shown, Figure 7 The electronic device 600 shown includes: a processor 601 and a memory 603. The processor 601 and the memory 603 are connected, such as through a bus 602. Optionally, the electronic device 600 may also include a transceiver 604. It should be noted that in actual applications, the transceiver 604 is not limited to one, and the structure of the electronic device 600 does not constitute a limitation on the embodiments of the present application.

[0108] Processor 601 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It may implement or execute various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 601 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, and the like.

[0109] The bus 602 may include a path to transmit information between the above components. The bus 602 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 602 may be divided into an address bus, a data bus, etc. For ease of representation, Figure 7 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0110] The memory 603 may be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program codes in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0111] The memory 603 is used to store the application code for executing the solution of the present application, and the execution is controlled by the processor 601. The processor 601 is used to execute the application code stored in the memory 603 to implement the contents shown in the above method embodiment.

[0112] The electronic devices include, but are not limited to, mobile terminals such as mobile phones, laptop computers, PDAs (personal digital assistants), PADs (tablet computers), etc., and fixed terminals such as digital TVs, desktop computers, etc. It can also be a server terminal, etc. Figure 7 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0113] It should be understood that although the steps in the flowchart of the accompanying drawings are shown in sequence according to the instructions of the arrows, these steps are not necessarily performed in the order indicated by the arrows. Unless otherwise clearly stated in this document, the execution of these steps is not strictly limited in order and can be performed in other orders.

[0114] The above are only some implementation methods of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A cogeneration air compressor intelligent control method, characterized in that: Used in a compressed air station, the compressed air station comprising at least one air compressor, the method comprising: Acquiring the operating data of each of the air compressors; Acquiring monitoring data collected by a monitoring component provided in the compressed air station; Inputting the operating data and the monitoring data into a dynamic simulation model corresponding to the compressed air station to obtain a comprehensive state of the compressed air station, wherein the dynamic simulation model corresponds to the physical structure of the compressed air station; determining whether the compressed air station has an abnormality based on the comprehensive status; When it is determined that the compressed air station has an abnormality, the abnormality handling process is automatically executed.

2. The method according to claim 1, characterized in that The monitoring data includes equipment monitoring data collected by a monitoring component disposed on the equipment to be monitored at the compressed air station; The step of inputting the operation data and the monitoring data into a dynamic simulation model corresponding to the compressed air station to obtain a comprehensive state of the compressed air station includes: Inputting the operation data and the equipment monitoring data into the dynamic simulation model to update the equipment parameters of each of the air compressors and the equipment to be monitored in the dynamic simulation model; The comprehensive status of the compressed air station is determined based on the equipment parameters of each of the air compressors and the equipment to be monitored.

3. The method according to claim 2, characterized in that Determining the comprehensive status of the compressed air station based on the status of each of the air compressors and the equipment to be monitored includes: Determine the equipment parameters of the reference equipment in the dynamic simulation model based on the equipment parameters of each of the air compressors and the equipment parameters of the equipment to be monitored, wherein the reference equipment is different from the air compressor and the equipment to be monitored, and there is an association relationship between the reference equipment and the air compressor and / or the equipment to be monitored; The comprehensive status of the compressed air station is determined based on the equipment parameters of each of the air compressors, the equipment to be monitored and the reference equipment.

4. The method according to claim 2, characterized in that: The monitoring data includes pipeline monitoring data collected by a monitoring component arranged on a pipeline of the compressed air station; the comprehensive state of the compressed air station is determined based on the equipment parameters of each of the air compressors and the equipment to be monitored, including: Determining the equipment status of the compressed air station based on the equipment parameters of each of the air compressors and the equipment to be monitored; determining a pipeline status of the compressed air station based on the pipeline monitoring data; determining whether the device state matches the pipeline state; In the case where the equipment status matches the pipeline status, the comprehensive status of the compressed air station is determined based on the equipment parameters of each of the air compressors and the equipment to be monitored.

5. The method according to claim 4, characterized in that After determining whether the device state matches the pipeline state, the method further includes: In the case where the device state matches the pipeline state, determining whether to modify the device state; In the case where it is determined that the device state is to be corrected, a step of correcting the device state is performed so that the device state matches the pipeline state; When it is determined that the equipment status is not to be corrected, it is directly determined that an abnormality exists in the compressed air station.

6. The method according to claim 1, characterized in that The method further comprises: Predicting the gas consumption of the gas-consuming equipment connected to the compressed air station to obtain the predicted gas consumption; The control strategy of the compressed air station is adjusted based on the predicted gas consumption.

7. The method according to claim 6, characterized in that The gas-consuming equipment includes power generation equipment, and the gas consumption of the gas-consuming equipment connected to the compressed air station is predicted to obtain the predicted gas consumption, including: Obtaining historical power generation changes of the power generation equipment; Predicting the power generation of the power generation equipment based on the historical power generation change to obtain predicted power generation; The predicted gas consumption corresponding to the power generation equipment is determined based on the predicted power generation.

8. The method according to claim 6, characterized in that After the control strategy of the compressed air station is adjusted based on the predicted gas consumption, the method further includes: Determining whether a control strategy of the compressed air station matches a control strategy of a heat recovery system corresponding to the compressed air station; In the case where the control strategy of the compressed air station does not match the control strategy of the heat recovery system, the control strategy of the heat recovery system is adjusted based on the control strategy of the compressed air station.

9. An intelligent controlled cogeneration air compression system, characterized in that: The system includes a compressed air station, which includes at least one air compressor, at least one monitoring component, and a control device connected to the air compressor and the monitoring component by signal, and the control device is used to execute the cogeneration air compressor intelligent control method described in any one of claims 1-8.

10. An electronic device, characterized in that: The electronic device comprises: at least one processor; Memory; At least one application, wherein at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute the cogeneration air compression intelligent control method as described in any one of claims 1 to 8.

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