CN-122022002-A - Cloud computing evaluation method and system for comprehensive work transmission efficiency of compressed air station

Abstract

The application relates to the technical field of energy efficiency evaluation, in particular to a cloud computing evaluation method and a cloud computing evaluation system for comprehensive work transmission efficiency of a compressed air station, wherein the method comprises the steps of acquiring operation information of the compressed air station, wherein the operation information comprises equipment parameters, pipe network data and environmental parameters; the method comprises the steps of obtaining an initial efficiency rate value based on equipment parameters, pipe network data and environmental parameters, marking a compressed air station as an inefficient operation station if the initial efficiency rate value is lower than a first efficiency threshold value, obtaining system configuration information corresponding to the inefficient operation station based on the compressed air station, analyzing the operation information based on the system configuration information and obtaining efficiency correction coefficients, obtaining a target efficiency rate value based on the initial efficiency rate value and the efficiency correction coefficients, and generating an efficiency optimization suggestion if the target efficiency rate value is lower than the first efficiency threshold value. The method is beneficial to improving the integrity, suitability and accuracy of the comprehensive work efficiency assessment of the compressed air station, and strengthening the pertinence of the optimization suggestion.

Inventors

• WANG QICHANG
• LIU JIANQIANG

Assignees

• 深圳气佬板节能技术有限公司

Dates

Publication Date

20260512

Application Date

20251224

Claims (10)

1. 1. A cloud computing and evaluating method for comprehensive work efficiency of a compressed air station is characterized by comprising the following steps: Acquiring operation information of a compressed air station, wherein the operation information comprises equipment parameters, pipe network data and environment parameters; acquiring an initial power transmission efficiency value based on the equipment parameters, the pipe network data and the environmental parameters; If the initial efficiency rate value is below a first efficiency threshold, marking the compressed air station as an inefficient operation station; Acquiring system configuration information corresponding to the low-efficiency operation site based on the compressed air station; analyzing the operation information and acquiring an efficiency correction coefficient based on the system configuration information; Acquiring a target efficiency rate value based on the initial efficiency rate value and the efficiency correction coefficient; and if the target efficiency rate value is lower than a first efficiency threshold value, generating an efficiency optimization suggestion.
2. 2. The cloud computing assessment method for comprehensive power efficiency of a compressed air station according to claim 1, wherein the obtaining an initial power efficiency value based on the equipment parameter, the pipe network data and the environmental parameter comprises: Acquiring key pipe network nodes based on the pipe network data; Monitoring the pressure flow of the key pipe network node to obtain a node characteristic parameter; acquiring abnormal nodes based on the key pipe network nodes and the node characteristic parameters; Calculating pipe network abnormal duty ratio data based on the key pipe network nodes and the abnormal nodes; calculating an equipment operation load rate based on the equipment parameters; determining an environmental temperature and humidity influence coefficient based on the environmental parameters; and combining the equipment operation load rate, the environmental temperature and humidity influence coefficient and the pipe network abnormal duty ratio data to obtain an initial power transmission efficiency value.
3. 3. The cloud computing assessment method for comprehensive work efficiency of a compressed air station according to claim 1, wherein the analyzing the operation information and obtaining an efficiency correction coefficient based on the system configuration information comprises: Judging whether an inefficient association factor exists or not based on the system configuration information; If the low-efficiency association factors exist, acquiring characteristic data corresponding to the low-efficiency association factors; if the characteristic data exceeds the corresponding characteristic threshold value, judging whether the low-efficiency operation site is in a full-load operation state or not based on the equipment parameters; If the low-efficiency operation site is in a full-load operation state, acquiring equipment linkage information; judging whether efficiency correction is needed or not based on the equipment linkage information; and if the efficiency correction is needed, acquiring an efficiency correction coefficient.
4. 4. The cloud computing assessment method for comprehensive work efficiency of a compressed air station according to claim 3, wherein the determining whether the inefficiency related factor exists based on the system configuration information comprises: acquiring historical operation data corresponding to the low-efficiency operation site; extracting efficiency fluctuation reasons of different time periods based on the historical operation data; counting the occurrence frequency corresponding to the efficiency fluctuation reason; and if the occurrence frequency exceeds a preset frequency threshold, judging that the inefficiency related factor exists.
5. 5. The cloud computing and evaluating method for comprehensive work efficiency of a compressed air station according to claim 4, further comprising, after said counting of the occurrence frequency corresponding to the cause of the fluctuation in efficiency: if the occurrence frequency does not exceed the preset frequency threshold, judging that the low-efficiency operation site is in a continuous operation mode or an intermittent operation mode based on the system configuration information; If the low-efficiency operation site is in the continuous operation mode, acquiring the equipment aging degree and the maintenance period; If the equipment aging degree and the maintenance period have significant influence on the operation information, judging that an inefficient association factor exists; if the low-efficiency operation site is in the intermittent operation mode, acquiring start-stop transition time corresponding to the low-efficiency operation site; Calculating the energy consumption loss rate of the transition stage based on the start-stop transition time; And if the energy consumption loss rate exceeds a second efficiency threshold, judging that an inefficiency related factor exists.
6. 6. The cloud computing assessment method for comprehensive work efficiency of a compressed air station according to claim 3, wherein the equipment linkage information comprises equipment start-stop time sequence, pressure matching degree and energy consumption synergy, and the judging whether efficiency correction is needed based on the equipment linkage information comprises the following steps: acquiring rated output power and actual output power of each device based on the device parameters, and calculating a target deviation rate based on the rated output power and the actual output power; if the target deviation rate is within the preset deviation range, judging whether the pressure matching degree is a first matching grade or not; If the first matching grade is the first matching grade and the second matching grade is not changed within the preset time period, judging that efficiency correction is needed; If the first matching grade is the first matching grade and the preset duration is changed into the second matching grade, analyzing the equipment start-stop time sequence and acquiring the response time difference of the adjacent equipment; if the response time difference is smaller than a preset time difference threshold and the energy consumption synergy is in a preset synergy state, judging that efficiency correction is not needed; if the target deviation rate exceeds the preset deviation range, carrying out conflict analysis on the equipment linkage information, and establishing a corresponding relation between the equipment linkage information and the influence of efficiency; determining the efficiency influence of all linkage information based on the corresponding relation, and acquiring a conflict relation; if the conflict relation is the in-equipment conflict, acquiring a conflict coefficient; And comparing the conflict coefficient with a preset coefficient threshold value, generating a comparison result, and judging whether efficiency correction is needed or not based on the comparison result.
7. 7. The cloud computing and evaluating method for comprehensive work efficiency of a compressed air station according to claim 6, wherein after determining efficiency effects of all linkage information based on the correspondence, obtaining the conflict relationship, further comprises: If the conflict relation is the conflict between the devices, determining the operation priority of each device based on the device parameters, and calculating the influence weight corresponding to the linkage information based on the operation priority of the device; If the first target equipment with the maximum influence weight and the highest running stability exists, judging whether efficiency correction is needed or not based on linkage information of the first target equipment; if the equipment is not available, calculating the comprehensive score of each equipment by combining the influence weight and the running stability; Judging whether efficiency correction is needed or not based on linkage information of the equipment with the highest comprehensive score; If a plurality of second target devices with the highest comprehensive scores exist and the scores are the same, acquiring an operation efficiency curve of the second target devices after the last maintenance; acquiring linkage information of target equipment based on the slope change trend of the efficiency curve; and judging whether efficiency correction is needed or not based on the linkage information of the target equipment.
8. 8. The cloud computing assessment method for comprehensive work efficiency of a compressed air station according to claim 3, wherein if efficiency correction is required, obtaining an efficiency correction coefficient comprises: If efficiency correction is needed, screening key influence parameters in equipment linkage information, including start-stop response delay values, pressure fluctuation amplitude and energy consumption deviation amount, based on the efficiency correction judging result; Acquiring a historical high-efficiency operation record of the low-efficiency operation site under the same environmental parameters, and extracting a parameter reference value in the record; Calculating a deviation percentage based on the key influence parameter and the parameter reference value; Acquiring a sensitivity coefficient of key influence parameters to the work transmission efficiency; And obtaining an efficiency correction coefficient based on the deviation percentage and the sensitivity coefficient.
9. 9. The cloud computing assessment method for comprehensive power efficiency of a compressed air station according to claim 1, wherein the efficiency optimization suggestions comprise a targeted pipe network optimization suggestion, a device dynamic adjustment suggestion and a system reconstruction suggestion, and the generating the efficiency optimization suggestion if the target power efficiency value is lower than a first efficiency threshold comprises: if the target efficiency rate value is lower than the first efficiency threshold value, calculating the absolute value of the difference value between the target efficiency rate value and the first efficiency threshold value, and dividing the optimization grade according to a difference interval; if the optimization is low-level optimization, extracting an anomaly type with the highest occupancy rate in the pipe network anomaly occupancy rate data, and generating a targeted pipe network optimization suggestion; If the optimization is medium-level optimization, generating a device dynamic adjustment suggestion by combining a fluctuation peak period of the device operation load rate and a change rule of an environmental temperature and humidity influence coefficient; if the optimization is high-level optimization, integrating a conflict analysis result of equipment linkage information and a time sequence optimization feasibility evaluation to generate a system reconstruction suggestion.
10. 10. The cloud computing and evaluating system for the comprehensive work conveying efficiency of the compressed air station is characterized by comprising the following components: the information acquisition module is used for acquiring operation information of the compressed air station, wherein the operation information comprises equipment parameters, pipe network data and environmental parameters; The initial evaluation module is used for acquiring an initial power transmission efficiency value based on the equipment parameters, the pipe network data and the environment parameters; the station marking module is used for marking the compressed air station as an inefficient operation station if the initial efficiency rate value is lower than a first efficiency threshold value; the configuration acquisition module is used for acquiring system configuration information corresponding to the low-efficiency operation site based on the compressed air station; The correction calculation module is used for analyzing the operation information and acquiring an efficiency correction coefficient based on the system configuration information; The target evaluation module is used for acquiring a target efficiency rate value based on the initial efficiency rate value and the efficiency correction coefficient; and the suggestion generation module is used for generating an efficiency optimization suggestion if the target efficiency rate value is lower than a first efficiency threshold value.

Description

Cloud computing evaluation method and system for comprehensive work transmission efficiency of compressed air station Technical Field The application relates to the technical field of energy efficiency evaluation, in particular to a cloud computing evaluation method and system for comprehensive work efficiency of a compressed air station. Background In the field of industrial production, a compressed air station is a core infrastructure for providing a power source, and the comprehensive work efficiency of the compressed air station is directly related to the energy consumption cost, production continuity and equipment service life of an enterprise. The efficient comprehensive work efficiency can not only reduce industrial energy consumption and carbon emission, but also ensure the stable operation of downstream gas equipment, so that the comprehensive work efficiency of the compressed air station is evaluated scientifically and accurately, and the comprehensive work efficiency is a key link of industrial energy efficiency management. Currently, comprehensive work efficiency assessment of a compressed air station is mainly realized through modes of manually counting equipment parameters, monitoring pipe network pressure and the like, so that whether the operation efficiency of a station body reaches the standard is judged, and a basis is provided for subsequent energy efficiency optimization. However, due to the complex operating environment of the compressed air station, various factors such as linkage of a plurality of devices, pipe network layout difference, environmental temperature and humidity fluctuation and the like are involved, and the traditional evaluation mode has obvious limitation. The system configuration characteristics of the compressed air station, such as the difference between continuous operation and intermittent operation modes, the rationality of equipment linkage logic and the like, are not considered in some evaluations, so that the deviation between an evaluation result and the actual operation efficiency is larger. Under the condition, the traditional evaluation may not only misjudge the inefficient operation site and fail to accurately position the effective problem root, but also cause the follow-up optimization suggestion to lack pertinence due to lack of a scientific efficiency correction mechanism, thereby further causing the problems of aggravation of energy waste, increase of equipment maintenance cost and the like. Disclosure of Invention In order to help to improve the integrity, suitability and accuracy of the comprehensive work efficiency evaluation of the compressed air station and strengthen the pertinence of optimization suggestions, the application provides a cloud computing evaluation method and a cloud computing evaluation system of the comprehensive work efficiency of the compressed air station. In a first aspect, the application provides a cloud computing and evaluating method for comprehensive work efficiency of a compressed air station, which adopts the following technical scheme: a cloud computing assessment method for comprehensive work efficiency of a compressed air station comprises the following steps: Acquiring operation information of a compressed air station, wherein the operation information comprises equipment parameters, pipe network data and environment parameters; acquiring an initial power transmission efficiency value based on the equipment parameters, the pipe network data and the environmental parameters; If the initial efficiency rate value is below a first efficiency threshold, marking the compressed air station as an inefficient operation station; Acquiring system configuration information corresponding to the low-efficiency operation site based on the compressed air station; analyzing the operation information and acquiring an efficiency correction coefficient based on the system configuration information; Acquiring a target efficiency rate value based on the initial efficiency rate value and the efficiency correction coefficient; and if the target efficiency rate value is lower than a first efficiency threshold value, generating an efficiency optimization suggestion. Optionally, the obtaining the initial power efficiency rate based on the equipment parameter, the pipe network data, and the environmental parameter includes: Acquiring key pipe network nodes based on the pipe network data; Monitoring the pressure flow of the key pipe network node to obtain a node characteristic parameter; Based on the key pipe network node and the node characteristic parameters, obtaining an abnormal node, wherein the node corresponding to the node characteristic parameters beyond the conventional range is used as the abnormal node Calculating pipe network abnormal duty ratio data based on the key pipe network nodes and the abnormal nodes; calculating an equipment operation load rate based on the equipment parameters; determining an environmental temperatur