Wastewater treatment energy consumption management system and method based on data analysis

Abstract

The invention relates to the technical field of water replenishing and cleaning, and discloses a waste water treatment energy consumption management system and method based on data analysis. Energy consumption data and equipment operation data in the waste water treatment process are collected in real time through a data collection module, and then a communication protocol suitable for an industrial environment is selected through a data transmission module; according to the method, the reliability and the real-time performance of data transmission are ensured, the transmitted data are encrypted, the data security is ensured, data leakage and tampering are prevented, real-time synchronization of the data is realized, and the data processing and analyzing module can obtain the latest energy consumption data, and then the latest energy consumption data are transmitted to the data processing and analyzing module through the data processing and analyzing module. According to the method, data of different sources and different formats are integrated into a unified data format, subsequent analysis is facilitated, then the processed data are analyzed, and based on real-time energy consumption data and an equipment operation state, a wastewater treatment process and equipment operation parameters are dynamically adjusted, so that optimal management of energy consumption is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of water replenishment and cleaning, and in particular to a wastewater treatment energy consumption management system and method based on data analysis. Background Art

[0002] Industrial wastewater refers to wastewater, sewage and waste liquid generated in the industrial production process, which contains industrial production materials, intermediates and products lost with the water, as well as pollutants generated in the production process. It is characterized by complex types, great difficulty in treatment, great pollution hazards, complex composition and high requirements for treatment technology.

[0003] Zero-discharge treatment of industrial wastewater refers to the process of water quality conditioning such as sedimentation, filtration, coagulation, flocculation, corrosion inhibition, and scale inhibition through a series of water treatment equipment, using physical, chemical, biological, integrated membrane treatment, evaporation crystallization and other means. The current industrial wastewater treatment system generally lacks comprehensive and real-time monitoring of energy consumption data. Most systems only focus on the wastewater treatment effect, but ignore the importance of energy consumption management, resulting in incomplete collection of energy consumption data and difficulty in refined management. In order to improve the wastewater treatment effect, reduce operating costs, and achieve sustainable development, it is necessary to carry out in-depth improvements and optimizations on these issues. The patent of this invention aims to provide an industrial wastewater treatment energy consumption management system and method based on data analysis, which can achieve energy consumption reduction and energy efficiency improvement in the wastewater treatment process through real-time monitoring, data analysis and intelligent decision-making. Summary of the invention

[0004] The purpose of the present invention is to provide a wastewater treatment energy consumption management system and method based on data analysis to solve the above-mentioned technical problems.

[0005] A wastewater treatment energy consumption management system based on data analysis, the system includes a data acquisition module, a data transmission module, a data processing and analysis module and an intelligent decision-making module;

[0006] The data acquisition module includes an energy consumption data monitoring unit and an equipment status monitoring unit;

[0007] The energy consumption data monitoring unit is used to deploy high-precision sensors at various stages of the wastewater treatment process to monitor the power consumption, water consumption and drug consumption parameters in the wastewater treatment process;

[0008] The equipment status monitoring unit is used to monitor the performance parameters of the equipment during operation;

[0009] The data transmission module is used to select a communication protocol suitable for the industrial environment, encrypt the transmitted data, and transmit the data to the data processing and analysis module in real time and synchronously;

[0010] The data processing and analysis module is used to process the data transmitted by the data transmission module and analyze the processed data;

[0011] The intelligent decision-making module is used to generate an energy consumption management strategy according to the analysis results of the data processing and analysis module.

[0012] As a further description of the solution of the present invention, the working process of the energy consumption data monitoring unit includes:

[0013] The sewage treatment process is divided into n treatment levels according to the pollution degree of the sewage to be treated, and the energy consumption data at different treatment levels are collected;

[0014] Obtain the data of electricity consumption, water consumption and drug consumption over time at different treatment levels;

[0015] According to the data of electricity consumption changing over time, water consumption changing over time and drug consumption changing over time under different treatment levels, the function of electricity consumption changing over time, water consumption changing over time and drug consumption changing over time are fitted.

[0016] As a further description of the solution of the present invention, the working process of the equipment status monitoring unit includes:

[0017] Number all devices in the following order: 1, 2, ..., m;

[0018] Obtain key performance parameter data of all equipment separately.

[0019] As a further description of the solution of the present invention, the working process of the data processing and analysis module includes:

[0020] The energy consumption coefficient mathematical model is constructed based on the time-varying functions of electricity consumption, water consumption and drug consumption under different treatment levels. The expression is:

[0021] k=k1*A E +k2*A W +k3*A M ;

[0022] In the formula, k is the system energy consumption coefficient, A E A is the parameter affecting power consumption. W is the water consumption influencing parameter, A M is the influencing parameter of drug consumption, k1, k2 and k3 are the corresponding weight coefficients respectively.

[0023] As a further description of the solution of the present invention, the power consumption influencing parameter A E The mathematical expression is as follows:

[0024]

[0025] The water consumption affects the parameter A W The mathematical expression is as follows:

[0026]

[0027] The drug consumption affects the parameter A W The mathematical expression is as follows:

[0028]

[0029] Where n is the number of processing levels, i∈[1,n]; t i1 is the initial time point corresponding to the i-th sewage treatment level, t i2 is the end time point corresponding to the i-th sewage treatment level; E i (t) is the actual function of the power consumption of the i-th sewage treatment level over time, E i0 (t) is the preset standard function of the power consumption of the i-th sewage treatment level over time, α i is the power consumption weight coefficient corresponding to the i-th sewage treatment level, ΔE ith is the reference value of power consumption for the i-th sewage treatment level; W i (t) is the actual function of water consumption of the ith sewage treatment level over time, W i0 (t) is the standard function of water consumption of the preset i-th sewage treatment level over time, β i is the water consumption weight coefficient corresponding to the i-th sewage treatment level, ΔW ith is the water consumption reference value of the i-th sewage treatment level; M i (t) is the actual function of the drug consumption of the i-th sewage treatment level over time, M i0 (t) is the standard function of the drug consumption of the preset i-th sewage treatment level over time, γ i is the drug consumption weight coefficient corresponding to the i-th sewage treatment level, ΔM ith is the reference value of drug consumption for the i-th sewage treatment level;

[0030] A E , A W and A M Substitute the energy consumption coefficient into the mathematical model to obtain the energy consumption coefficient.

[0031] As a further description of the solution of the present invention, the working process of the data processing and analysis module also includes:

[0032] Obtain the time-varying data of key performance parameters of all equipment;

[0033] The mathematical model of equipment utilization coefficient is constructed based on the data of changes in key performance parameters of all equipment over time. The expression is:

[0034]

[0035] In the formula, q is the number of key parameters collected by the jth device, h belongs to q, T h The actual data collected for the hth parameter item of the jth device, T h0 Preset standard data for the hth parameter item of the jth device, θ h is the weight coefficient of the hth parameter item of the jth device, is the utilization coefficient of the jth device; σ is the utilization coefficient of the system equipment, μ j is the weight coefficient of the utilization coefficient of the j-th device.

[0036] As a further description of the solution of the present invention, the working process of the intelligent decision-making module includes:

[0037] A W , A W and A M Compare with corresponding preset thresholds respectively;

[0038] If one of the influencing parameters does not meet the threshold condition, the influencing parameter item is adjusted;

[0039] Calculate the usage coefficients of the m devices respectively and compare them with the corresponding preset thresholds;

[0040] If the influencing parameter of one of the devices does not meet the threshold condition, the device is adjusted.

[0041] As a further description of the solution of the present invention, the working process of the intelligent decision-making module also includes:

[0042] A E , A W and A M Compare with corresponding preset thresholds respectively;

[0043] If all influencing parameters meet the corresponding threshold conditions, the system energy consumption coefficient ρ is compared with the preset system energy consumption coefficient threshold ρ th Make comparisons;

[0044] If ρ ≥ ρ th , then the overall energy consumption of the system is judged to be abnormal. If ρ<ρ th , then it is judged that the overall energy consumption of the system is normal;

[0045] Compare the utilization coefficients of the m devices with the corresponding preset thresholds;

[0046] If the influencing parameters of all devices meet the threshold conditions, the system equipment utilization coefficient σ is compared with the preset system equipment utilization coefficient threshold σ th Make comparisons;

[0047] If σ≥σ th , then it is judged that the overall equipment usage of the system is abnormal. If σ<σ th , it is judged that the overall equipment of the system is in normal use.

[0048] As a further description of the solution of the present invention, the working process of the intelligent decision-making module also includes:

[0049] If the overall equipment usage of the system is abnormal, and the overall energy consumption of the system is abnormal, the equipment operating parameters lead to abnormal energy consumption, and the equipment parameters should be adjusted;

[0050] If the overall equipment of the system is used normally but the overall energy consumption of the system is abnormal, then the wastewater treatment process causes the abnormal energy consumption and the wastewater treatment process should be adjusted.

[0051] A wastewater treatment energy consumption management method based on data analysis, wherein the method is applicable to a wastewater treatment energy consumption management system based on data analysis.

[0052] Beneficial effects of the present invention:

[0053] The present invention collects energy consumption data and equipment operation data in the wastewater treatment process in real time through a data acquisition module, then selects a communication protocol suitable for an industrial environment through a data transmission module to ensure the reliability and real-time performance of data transmission, encrypts the transmitted data to ensure data security, prevents data leakage and tampering, and sets a data cache mechanism during the transmission process to avoid data loss due to network fluctuations, achieves real-time synchronization of data, ensures that a data processing and analysis module can obtain the latest energy consumption data, then removes duplicate, erroneous and invalid data through the data processing and analysis module to ensure data accuracy and consistency, integrates data from different sources and in different formats into a unified data format to facilitate subsequent analysis, then analyzes the processed data, and dynamically adjusts the wastewater treatment process and equipment operation parameters based on real-time energy consumption data and equipment operation status to achieve optimal management of energy consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] The present invention will be further described below in conjunction with the accompanying drawings.

[0055] Figure 1 It is a partial structural diagram of the wastewater treatment energy consumption management system based on data analysis provided by the present invention. DETAILED DESCRIPTION

[0056] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0057] See also Figure 1 As shown, the present invention is a wastewater treatment energy consumption management system based on data analysis, the system includes a data acquisition module, a data transmission module, a data processing and analysis module and an intelligent decision-making module;

[0058] The data acquisition module includes an energy consumption data monitoring unit and an equipment status monitoring unit;

[0059] The energy consumption data monitoring unit is used to deploy high-precision sensors at various stages of the wastewater treatment process to monitor the power consumption, water consumption and drug consumption parameters in the wastewater treatment process;

[0060] The equipment status monitoring unit is used to monitor the performance parameters of the equipment during operation;

[0061] The data transmission module is used to select a communication protocol suitable for the industrial environment, encrypt the transmitted data, and transmit the data to the data processing and analysis module in real time and synchronously;

[0062] The data processing and analysis module is used to process the data transmitted by the data transmission module and analyze the processed data;

[0063] The intelligent decision-making module is used to generate an energy consumption management strategy according to the analysis results of the data processing and analysis module.

[0064] Through the above technical scheme, the present invention collects energy consumption data and equipment operation data in the wastewater treatment process in real time through the data acquisition module, and then selects a communication protocol suitable for the industrial environment, such as MQTT, OPCUA, etc., through the data transmission module to ensure the reliability and real-time performance of data transmission, encrypts the transmitted data, ensures data security, prevents data leakage and tampering, and sets a data cache mechanism during the transmission process to avoid data loss due to network fluctuations, realizes real-time synchronization of data, ensures that the data processing and analysis module can obtain the latest energy consumption data, and then removes duplicate, erroneous and invalid data through the data processing and analysis module to ensure data accuracy and consistency, integrates data from different sources and in different formats into a unified data format for subsequent analysis, and then analyzes the processed data, dynamically adjusts the wastewater treatment process and equipment operation parameters based on real-time energy consumption data and equipment operation status, and realizes optimal management of energy consumption.

[0065] The working process of the energy consumption data monitoring unit includes:

[0066] The sewage treatment process is divided into n treatment levels according to the pollution degree of the sewage to be treated, and the energy consumption data at different treatment levels are collected;

[0067] Obtain the data of electricity consumption, water consumption and drug consumption over time at different treatment levels;

[0068] According to the data of electricity consumption changing over time, water consumption changing over time and drug consumption changing over time under different treatment levels, the function of electricity consumption changing over time, water consumption changing over time and drug consumption changing over time are fitted.

[0069] The working process of the data processing and analysis module includes:

[0070] The energy consumption coefficient mathematical model is constructed based on the time-varying functions of electricity consumption, water consumption and drug consumption under different treatment levels. The expression is:

[0071] ρ=k1*A E +k2*A M +k3*A M ;

[0072] Where ρ is the system energy consumption coefficient, A E A is the parameter affecting power consumption. W is the water consumption influencing parameter, A M is the influencing parameter of drug consumption, k1, k2 and k3 are the corresponding weight coefficients respectively.

[0073] The power consumption affects the parameter A E The mathematical expression is as follows:

[0074]

[0075] The water consumption affects the parameter A W The mathematical expression is as follows:

[0076]

[0077] The drug consumption affects the parameter A W The mathematical expression is as follows:

[0078]

[0079] Where n is the number of processing levels, i∈[1,n]; t i1 is the initial time point corresponding to the i-th sewage treatment level, t i2 is the end time point corresponding to the i-th sewage treatment level; Ei (t) is the actual function of the power consumption of the i-th sewage treatment level over time, E i0 (t) is the preset standard function of the power consumption of the i-th sewage treatment level over time, α i is the power consumption weight coefficient corresponding to the i-th sewage treatment level, ΔE ith is the reference value of power consumption for the i-th sewage treatment level; W i (t) is the actual function of water consumption of the ith sewage treatment level over time, W i0 (t) is the standard function of water consumption of the preset i-th sewage treatment level over time, β i is the water consumption weight coefficient corresponding to the i-th sewage treatment level, ΔW ith is the water consumption reference value of the i-th sewage treatment level; M i (t) is the actual function of the drug consumption of the i-th sewage treatment level over time, M i0 (t) is the standard function of the drug consumption of the preset i-th sewage treatment level over time, γ i is the drug consumption weight coefficient corresponding to the i-th sewage treatment level, ΔM ith is the reference value of drug consumption for the i-th sewage treatment level;

[0080] A E , A W and A M Substitute the energy consumption coefficient into the mathematical model to obtain the energy consumption coefficient.

[0081] The working process of the intelligent decision-making module includes:

[0082] A E , A W and A M Compare with corresponding preset thresholds respectively;

[0083] If one of the influencing parameters does not meet the threshold condition, the influencing parameter item is adjusted;

[0084] The working process of the intelligent decision-making module also includes:

[0085] A E , A W and A M Compare with corresponding preset thresholds respectively;

[0086] If all influencing parameters meet the corresponding threshold conditions, the system energy consumption coefficient ρ is compared with the preset system energy consumption coefficient threshold ρ th Make comparisons;

[0087] If ρ ≥ ρ th , then the overall energy consumption of the system is judged to be abnormal. If ρ<ρth , then it is judged that the overall energy consumption of the system is normal.

[0088] Through the above technical scheme, this embodiment divides the sewage treatment process into n treatment levels according to the different pollution degrees of the treated sewage, obtains the energy consumption data of the sewage treatment process at each level, calculates the power consumption influencing parameters, water consumption influencing parameters and drug consumption influencing parameters according to the acquired energy consumption data, compares the power consumption influencing parameters, water consumption influencing parameters and drug consumption influencing parameters with the corresponding preset thresholds, if one of the influencing parameters does not meet the threshold condition, adjusts the influencing parameter item, if all the influencing parameters meet the corresponding threshold condition, substitutes the power consumption influencing parameters, water consumption influencing parameters and drug consumption influencing parameters into the energy consumption utilization coefficient mathematical model to calculate the energy consumption utilization coefficient, and compares the system energy consumption utilization coefficient with the preset system energy consumption utilization coefficient threshold; if the system energy consumption utilization coefficient is greater than or equal to the preset system energy consumption utilization coefficient threshold, it is judged that the overall energy consumption utilization of the system is abnormal, otherwise, it is judged that the overall energy consumption utilization of the system is normal.

[0089] The working process of the equipment status monitoring unit includes:

[0090] Number all devices in the following order: 1, 2, ..., m;

[0091] Obtain key performance parameter data of all equipment separately.

[0092] The working process of the data processing and analysis module also includes:

[0093] Obtain the time-varying data of key performance parameters of all equipment;

[0094] The mathematical model of equipment utilization coefficient is constructed based on the data of changes in key performance parameters of all equipment over time. The expression is:

[0095]

[0096] In the formula, q is the number of key parameters collected by the jth device, h belongs to q, T h The actual data collected for the hth parameter item of the jth device, T h0 Preset standard data for the hth parameter item of the jth device, θ h is the weight coefficient of the hth parameter item of the jth device, is the utilization coefficient of the jth device; σ is the utilization coefficient of the system equipment, μ j is the weight coefficient of the utilization coefficient of the j-th device.

[0097] Calculate the usage coefficients of the m devices respectively and compare them with the corresponding preset thresholds;

[0098] If the influencing parameter of one of the devices does not meet the threshold condition, the device is adjusted.

[0099] Compare the utilization coefficients of the m devices with the corresponding preset thresholds;

[0100] If the influencing parameters of all devices meet the threshold conditions, the system equipment utilization coefficient σ is compared with the preset system equipment utilization coefficient threshold σ th Make comparisons;

[0101] If σ≥σ th , then it is judged that the overall equipment usage of the system is abnormal. If σ<σ th , it is judged that the overall equipment of the system is in normal use.

[0102] Through the above calculation scheme, this embodiment numbers all processing devices, obtains the key performance parameter data of all devices respectively, calculates the equipment usage coefficient of all devices according to the obtained data, and compares it with the corresponding preset threshold value. If the influencing parameter of one of the devices does not meet the threshold condition, the current device fails, and the device is adjusted. If the influencing parameters of all devices meet the threshold condition, the system equipment usage coefficient is calculated, and the system equipment usage coefficient is compared with the preset system equipment usage coefficient threshold; if the system equipment usage coefficient is greater than or equal to the preset system equipment usage coefficient threshold, it is judged that the overall system equipment usage is abnormal; otherwise, it is judged that the overall system equipment usage is normal.

[0103] When all single energy consumption influencing parameters meet the corresponding threshold conditions and all influencing parameters of single devices meet the threshold conditions, the working process of the intelligent decision-making module further includes:

[0104] If the overall equipment usage of the system is abnormal, and the overall energy consumption of the system is abnormal, the equipment operating parameters lead to abnormal energy consumption, and the equipment parameters should be adjusted;

[0105] If the overall equipment of the system is used normally but the overall energy consumption of the system is abnormal, then the wastewater treatment process causes the abnormal energy consumption and the wastewater treatment process should be adjusted.

[0106] A wastewater treatment energy consumption management method based on data analysis, wherein the method is applicable to a wastewater treatment energy consumption management system based on data analysis.

[0107] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A wastewater treatment energy consumption management system based on data analysis, characterized in that: The system includes a data acquisition module, a data transmission module, a data processing and analysis module and an intelligent decision-making module; The data acquisition module includes an energy consumption data monitoring unit and an equipment status monitoring unit; The energy consumption data monitoring unit is used to deploy high-precision sensors at various stages of the wastewater treatment process to monitor the power consumption, water consumption and drug consumption parameters in the wastewater treatment process; The equipment status monitoring unit is used to monitor the performance parameters of the equipment during operation; The data transmission module is used to select a communication protocol suitable for the industrial environment, encrypt the transmitted data, and transmit the data to the data processing and analysis module in real time and synchronously; The data processing and analysis module is used to process the data transmitted by the data transmission module and analyze the processed data; The intelligent decision-making module is used to generate an energy consumption management strategy according to the analysis results of the data processing and analysis module.

2. The wastewater treatment energy consumption management system based on data analysis according to claim 1 is characterized in that: The working process of the energy consumption data monitoring unit includes: The sewage treatment process is divided into n treatment levels according to the pollution degree of the sewage to be treated, and the energy consumption data at different treatment levels are collected; Obtain the data of electricity consumption, water consumption and drug consumption over time at different treatment levels; According to the data of electricity consumption changing over time, water consumption changing over time and drug consumption changing over time under different treatment levels, the function of electricity consumption changing over time, water consumption changing over time and drug consumption changing over time are fitted.

3. The wastewater treatment energy consumption management system based on data analysis according to claim 2 is characterized in that: The working process of the equipment status monitoring unit includes: Number all devices in the following order: 1, 2, ..., m; Obtain key performance parameter data of all equipment separately.

4. The wastewater treatment energy consumption management system based on data analysis according to claim 3 is characterized in that: The working process of the data processing and analysis module includes: The energy consumption coefficient mathematical model is constructed based on the time-varying functions of electricity consumption, water consumption and drug consumption under different treatment levels. The expression is: ρ=k1*A E +k2*A W +k3*A M ; Where ρ is the system energy consumption coefficient, A E A is the parameter affecting power consumption. W is the water consumption influencing parameter, A M is the influencing parameter of drug consumption, k1, k2 and k3 are the corresponding weight coefficients respectively.

5. The wastewater treatment energy consumption management system based on data analysis according to claim 4 is characterized in that: The power consumption affects the parameter A E The mathematical expression is as follows: The water consumption affects the parameter A W The mathematical expression is as follows: The drug consumption affects the parameter A W The mathematical expression is as follows: Where n is the number of processing levels, i∈[1,n]; t i1 is the initial time point corresponding to the i-th sewage treatment level, t i2 is the end time point corresponding to the i-th sewage treatment level; E i (t) is the actual function of the power consumption of the i-th sewage treatment level over time, E i0 (t) is the preset standard function of the power consumption of the i-th sewage treatment level over time, α i is the power consumption weight coefficient corresponding to the i-th sewage treatment level, ΔE ith is the reference value of power consumption for the i-th sewage treatment level; W i (t) is the actual function of water consumption of the ith sewage treatment level over time, W i0 (t) is the standard function of water consumption of the preset i-th sewage treatment level over time, β i is the water consumption weight coefficient corresponding to the i-th sewage treatment level, ΔW ith is the water consumption reference value of the i-th sewage treatment level; M i (t) is the actual function of the drug consumption of the i-th sewage treatment level over time, M i0 (t) is the standard function of the drug consumption of the preset i-th sewage treatment level over time, γ i is the drug consumption weight coefficient corresponding to the i-th sewage treatment level, ΔM ith is the reference value of drug consumption for the i-th sewage treatment level; A E , A W and A M Substitute the energy consumption coefficient into the mathematical model to obtain the energy consumption coefficient.

6. The wastewater treatment energy consumption management system based on data analysis according to claim 5 is characterized in that: The working process of the data processing and analysis module also includes: Obtain the time-varying data of key performance parameters of all equipment; The mathematical model of equipment utilization coefficient is constructed based on the data of changes in key performance parameters of all equipment over time. The expression is: In the formula, q is the number of key parameters collected by the jth device, h belongs to q, T h The actual data collected for the hth parameter item of the jth device, T h0 Preset standard data for the hth parameter item of the jth device, θ h is the weight coefficient of the hth parameter item of the jth device, is the utilization coefficient of the jth device; σ is the utilization coefficient of the system equipment, μ j is the weight coefficient of the utilization coefficient of the j-th device.

7. The wastewater treatment energy consumption management system based on data analysis according to claim 6 is characterized in that: The working process of the intelligent decision-making module includes: A E , A W and A M Compare with corresponding preset thresholds respectively; If one of the influencing parameters does not meet the threshold condition, the influencing parameter item is adjusted; Calculate the usage coefficients of the m devices respectively and compare them with the corresponding preset thresholds; If the influencing parameter of one of the devices does not meet the threshold condition, the device is adjusted.

8. The wastewater treatment energy consumption management system based on data analysis according to claim 7 is characterized in that: The working process of the intelligent decision-making module also includes: A E , A W and A M Compare with corresponding preset thresholds respectively; If all influencing parameters meet the corresponding threshold conditions, the system energy consumption coefficient ρ is compared with the preset system energy consumption coefficient threshold ρ th Make comparisons; If ρ ≥ ρ th , then the overall energy consumption of the system is judged to be abnormal. If ρ<ρ th , then it is judged that the overall energy consumption of the system is normal; Compare the utilization coefficients of the m devices with the corresponding preset thresholds; If the influencing parameters of all devices meet the threshold conditions, the system equipment utilization coefficient σ is compared with the preset system equipment utilization coefficient threshold σ th Make comparisons; If σ≥σ th , then it is judged that the overall equipment usage of the system is abnormal. If σ<σ th , it is judged that the overall equipment of the system is in normal use.

9. The wastewater treatment energy consumption management system based on data analysis according to claim 8 is characterized in that: The working process of the intelligent decision-making module also includes: If the overall equipment usage of the system is abnormal, and the overall energy consumption of the system is abnormal, the equipment operating parameters lead to abnormal energy consumption, and the equipment parameters should be adjusted; If the overall equipment of the system is used normally but the overall energy consumption of the system is abnormal, then the wastewater treatment process causes the abnormal energy consumption and the wastewater treatment process should be adjusted.

10. A method for managing energy consumption in wastewater treatment based on data analysis, characterized in that: The method is applicable to the wastewater treatment energy consumption management system based on data analysis as described in any one of claims 1-9.

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