Energy efficiency optimization analysis method for sewage treatment

Abstract

The invention discloses an energy efficiency optimization analysis method for sewage treatment, and particularly relates to the field of sewage energy efficiency data processing and signal transmission processing. Comprising the steps of data source signal integrity detection, input preparation of a three-dimensional evaluation model, three-dimensional analysis of energy efficiency data, generation of an energy efficiency evaluation value, comparison of the energy efficiency evaluation value and an energy efficiency threshold value, screening of a model sewage treatment plant and the like. Through signal integrity detection and a dynamic adjustment mechanism of data acquisition frequency, the data quality in the energy efficiency evaluation process is improved, so that the overall precision of energy efficiency evaluation is improved; under the support of system real-time monitoring and data quality control, high-reliability data sources can be effectively screened for evaluation and analysis, so that the energy efficiency evaluation result is more suitable for actual conditions and operation requirements.

Description

Technical Field

[0001] The present invention relates to the technical field of sewage energy efficiency data processing and signal transmission processing, and more specifically, to an energy efficiency optimization analysis method for sewage treatment. Background Art

[0002] At present, there are various wastewater treatment technologies, including physical treatment, chemical treatment and biological treatment. However, these traditional methods still have limitations in terms of treatment efficiency, energy consumption and pollutant removal rate. The wastewater treatment plant energy efficiency optimization analysis method, device, equipment and storage medium with publication number CN118350541A discloses energy efficiency evaluation of a target wastewater treatment plant to obtain energy efficiency data of the target wastewater treatment plant; if the size of the energy efficiency data is less than or equal to a preset threshold, a model wastewater treatment plant is matched from the geographical area to which the target wastewater treatment plant belongs; the important coefficients of various energy efficiency decision units of the target wastewater treatment plant relative to any model wastewater treatment plant are calculated; according to the important coefficients of various energy efficiency decision units of the target wastewater treatment plant relative to any model wastewater treatment plant, an energy efficiency optimization analysis is performed on the target wastewater treatment plant to obtain an energy efficiency optimization strategy; The above solutions still have shortcomings in signal transmission stability and real-time data monitoring when processing energy efficiency data, which is a pain point in the industry and it is difficult to ensure continuous high-quality processing results; Regarding the problem of insufficient signal transmission stability, the existing technology is easily affected by environmental conditions or unstable data acquisition frequency during long-term continuous operation, resulting in inaccurate data, which ultimately affects the energy efficiency and treatment effect of sewage treatment; the instability of signal transmission is particularly prominent when multiple devices are working together, and traditional solutions have failed to effectively solve this defect in terms of processing efficiency, signal integrity and real-time performance. Summary of the invention

[0003] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides an energy efficiency optimization analysis method for sewage treatment. Through signal integrity detection and a dynamic adjustment mechanism of data acquisition frequency, the data quality in the energy efficiency evaluation process is improved, thereby improving the overall accuracy of the energy efficiency evaluation to solve the problems raised in the above-mentioned background technology.

[0004] To achieve the above object, the present invention provides the following technical solution: a method for optimizing energy efficiency for sewage treatment, comprising: Before conducting energy efficiency evaluation, the data source for energy efficiency evaluation is tested for signal integrity. When the signal strength of the corresponding data source is lower than the signal strength threshold preset by the system, and the data acquisition frequency deviates from the data acquisition frequency range threshold preset by the system, an alarm is triggered and the use of the data is suspended; otherwise, the data source used for energy efficiency evaluation is used as an input value to the three-dimensional evaluation model; Obtain energy efficiency data of the target sewage treatment plant that has passed the signal integrity test, conduct energy efficiency evaluation on the energy efficiency data of the target sewage treatment plant through a three-dimensional evaluation model, and generate an energy efficiency evaluation value; The energy efficiency data includes three dimensions: energy consumption and pollutant reduction efficiency, resource recovery and reuse efficiency, and operation and management efficiency. The energy consumption and pollutant reduction benefit dimensions of the energy efficiency data include the annual total electricity input of the target sewage treatment plant, the annual total COD reduction output, the annual total BOD5 reduction output, the annual total ammonia reduction output, the annual total nitrogen reduction output, and the annual total phosphorus reduction output; The resource recovery and reuse efficiency dimension of the energy efficiency data includes the biodiversity index, carbon footprint, and annual ecological restoration investment of the target wastewater treatment plant; The dimensions of operation and management efficiency of energy efficiency data include automation degree, technology application rate and signal detection accuracy; If the energy efficiency evaluation value is lower than or equal to the preset energy efficiency evaluation value threshold, a model sewage treatment plant that meets the conditions is selected from the geographical area to which the target sewage treatment plant belongs; Then, the relative impact coefficients of various energy efficiency decision-making units of the target sewage treatment plant relative to the model sewage treatment plant are calculated to evaluate their relative efficiency; Finally, based on the calculated relative impact coefficient, an energy efficiency optimization analysis is conducted on the target sewage treatment plant, and a targeted energy efficiency optimization strategy is formulated.

[0005] In a preferred embodiment, for signal integrity detection, when the signal strength S is lower than a preset threshold , and the data acquisition frequency F deviates from the preset range When the alarm is triggered, the use of data is suspended; The judgment conditions are:

[0006] Where S represents the current signal strength. If the signal strength is too low, data transmission may fail. is the signal strength threshold set by the system; F is the frequency of data collection, indicating the number of times data is collected per second; Indicates the preset data collection frequency range.

[0007] In a preferred embodiment, energy efficiency data consisting of three dimensions is obtained; dimension one includes energy consumption and pollutant reduction benefit dimensions; The proposed annual total electricity consumption is E; the proposed annual total COD reduction output is ; The total annual BOD5 reduction output is planned to be ;

[0008]

[0009]

[0010]

[0011]

[0012] in is the unit price of electricity, which indicates the cost per kilowatt-hour of electricity; is the electricity consumption time, which indicates the total electricity usage time of the sewage treatment plant in one year; is the COD concentration before sewage treatment, indicating the pollutant content before treatment; is the COD concentration after sewage treatment, indicating the pollutant content after treatment; is the COD treatment efficiency, Reflects the COD removal capacity of the treatment facility; is the BOD5 concentration before sewage treatment; is the BOD5 concentration after sewage treatment; It is the BOD5 treatment efficiency; The total annual ammonia reduction is planned to be ; The annual total nitrogen reduction output is planned to be ; Planned annual total phosphorus reduction output ;

[0013]

[0014]

[0015]

[0016]

[0017]

[0018] in is the ammonia nitrogen concentration before sewage treatment; is the ammonia nitrogen concentration after sewage treatment; is the ammonia nitrogen treatment efficiency; is the nitrogen concentration before sewage treatment; is the nitrogen concentration after sewage treatment; represents the ammonia treatment efficiency; is the phosphorus concentration before sewage treatment; is the phosphorus concentration after sewage treatment; is the phosphorus treatment efficiency; The comprehensive evaluation formula for energy consumption and pollutant reduction benefits in dimension 1 is proposed as follows: ; It means that by subtracting the initial and final concentrations of various pollutants, the total amount of pollutants reduced is calculated and compared with the total electricity E to reflect the energy efficiency;

[0019] The proposed comprehensive income is ;

[0020] in is the total cost; the above formula is used to evaluate the relationship between the economic benefits brought by energy efficiency and the input cost.

[0021] In a preferred embodiment, Dimension 2 of energy efficiency data includes the resource recovery and reuse efficiency dimension; The proposed biodiversity index is ;

[0022]

[0023] Among them, S is species richness, which indicates the number of species in the ecosystem around the sewage treatment plant; H represents species evenness, which reflects the uniformity of the distribution of species; is the number of the i-th species, N is the total number of all species; Q represents the habitat quality score, which is obtained through ecological surveys and is used to assess the health of the habitat; K is a normalization constant used to adjust the index to the standard range to ensure that the biodiversity index is between 0 and 1; The proposed carbon footprint is CF;

[0024] in It is the annual CO2 emission, which is used to reflect the greenhouse gas emission in the sewage treatment process; represents the carbon emission factor associated with energy consumption, which represents the carbon dioxide produced per unit of electrical energy; The proposed annual environmental protection investment fund is EPI;

[0025] in It is the annual expenditure for the maintenance of facilities; Annual expenditure for the introduction of new technology; Environmental protection training expenses, annual expenditure; The resource recovery and reuse efficiency dimensions are comprehensively evaluated through the biodiversity index BI, carbon footprint CF and annual environmental protection investment EPI; the resource recovery efficiency is proposed to be ; Propose a resource utilization assessment for ;

[0026] The above formula is used to combine biodiversity, environmental protection input and carbon footprint, and standardize the evaluation of resource recovery and reuse efficiency through electricity input E;

[0027] in The definition is the reuse rate, which is used to reflect the proportion of sewage reuse. The reuse rate represents the ratio of the amount of water that can be reused in the treatment process to the total amount of treated water. Defined as the waste generation rate, the waste generation rate represents the ratio of the amount of waste generated during sewage treatment to the total sewage treatment volume.

[0028] In a preferred embodiment, the third dimension of energy efficiency data includes the dimension of operation and management efficiency; The proposed automation degree is A; the proposed technology application rate is T; the proposed signal detection accuracy rate is SD;

[0029]

[0030]

[0031] in is the number of automated equipment, indicating the number of equipment with automated functions in the sewage treatment system; is the total number of equipment, indicating the total number of all equipment in the sewage treatment plant; The ratio of new technology use indicates the application ratio of newly introduced technologies in sewage treatment; The ratio of traditional technology used is the ratio of the original technology used in sewage treatment. It is the total application of all technologies, including new technologies and traditional technologies; is the number of correct detections, which indicates the total number of successful signal recognition; is the total number of signal detections, indicating the total number of all detection attempts; A comprehensive evaluation of the operation and management efficiency dimensions is conducted based on the automation degree A, technology application rate T and signal detection accuracy SD; the operation management efficiency is proposed as ;

[0032] The above formula averages the degree of automation, technology application rate and signal detection accuracy to evaluate the overall operation and management efficiency.

[0033] In a preferred embodiment, a comprehensive energy efficiency evaluation is performed based on energy efficiency data in three dimensions; The proposed comprehensive energy efficiency evaluation value is ; Comprehensive evaluation formula:

[0034] The above formula is used to combine the energy consumption and pollutant reduction benefit dimensions, resource recovery and reuse efficiency dimensions, and operation and management efficiency dimensions to form a comprehensive energy efficiency evaluation value. The comprehensive energy efficiency evaluation value is used to reflect the overall energy efficiency performance.

[0035] In a preferred embodiment, the conditions for screening the model sewage treatment plant are as follows: If the comprehensive energy efficiency evaluation value Lower than or equal to the preset threshold , then select qualified model sewage treatment plants from the geographical area where the target sewage treatment plant belongs; Judgment conditions: .

[0036] In a preferred embodiment, the relative influence coefficient is calculated to calculate the relative influence coefficient RIC of each energy efficiency decision unit of the target sewage treatment plant relative to the model sewage treatment plant:

[0037] in It is the comprehensive energy efficiency evaluation value of the model sewage treatment plant, which is used to compare and evaluate the relative performance of the target sewage treatment plant; Next, an energy efficiency optimization analysis is carried out; based on the calculated relative impact coefficient, the strengths and weaknesses of the target sewage treatment plant in terms of energy efficiency are identified, analyzed, and ultimately a targeted energy efficiency optimization strategy is formulated.

[0038] In a preferred embodiment, the detection frequency of the proposed initial signal integrity detection is , according to the selection criteria of model sewage treatment plants Dynamically adjust the pass rate The value of

[0039] The proposed energy efficiency pass rate is , Used to reflect the energy efficiency performance of the target sewage treatment plant; according to and Comparison results and pass rate To dynamically adjust the detection frequency ;when If the energy efficiency passing rate If the energy efficiency is lower than the preset threshold, the detection frequency will be increased. When When, and the energy efficiency pass rate If the energy efficiency pass rate is higher than the preset threshold, the detection frequency will be reduced. The value of Dynamically update the detection frequency through the dynamic frequency adjustment formula ;

[0040] in is the current detection frequency; It is an adjustment coefficient used to control the variation of the detection frequency.

[0041] Technical effects and advantages of the present invention: Through the signal integrity detection and dynamic adjustment mechanism of data acquisition frequency, the data quality in the energy efficiency evaluation process is improved, thereby improving the overall accuracy of energy efficiency evaluation; with the support of real-time system monitoring and data quality control, highly reliable data sources can be effectively screened for evaluation and analysis, making the energy efficiency evaluation results more in line with actual conditions and operational requirements; Through automatic signal strength and frequency detection, the frequency of signal detection is dynamically adjusted, so that the detection frequency is increased when the data is unstable and reduced when the signal is stable, to achieve optimal allocation of signal detection resources; Dynamic frequency adjustment and real-time data monitoring enable the system to quickly respond to changes in external conditions when facing different processing scenarios. Through this mechanism, abnormal signals can be discovered and adjusted in a timely manner during the energy efficiency evaluation process, effectively avoiding evaluation errors caused by abnormal signals. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0043] 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.

[0044] Refer to the instruction manual Figure 1, a method for optimizing energy efficiency for sewage treatment according to an embodiment of the present invention comprises: Before conducting energy efficiency evaluation, the data source for energy efficiency evaluation is tested for signal integrity. When the signal strength of the corresponding data source is lower than the signal strength threshold preset by the system, and the data acquisition frequency deviates from the data acquisition frequency range threshold preset by the system, an alarm is triggered and the use of the data is suspended; otherwise, the data source used for energy efficiency evaluation is used as an input value to the three-dimensional evaluation model; Obtain energy efficiency data of the target sewage treatment plant that has passed the signal integrity test, conduct energy efficiency evaluation on the energy efficiency data of the target sewage treatment plant through a three-dimensional evaluation model, and generate an energy efficiency evaluation value; The energy efficiency data includes three dimensions: energy consumption and pollutant reduction efficiency, resource recovery and reuse efficiency, and operation and management efficiency. The energy consumption and pollutant reduction benefit dimensions of the energy efficiency data include the annual total electricity input of the target sewage treatment plant, the annual total COD reduction output, the annual total BOD5 reduction output, the annual total ammonia reduction output, the annual total nitrogen reduction output, and the annual total phosphorus reduction output; The resource recovery and reuse efficiency dimension of the energy efficiency data includes the biodiversity index, carbon footprint, and annual ecological restoration investment of the target wastewater treatment plant; The dimensions of operation and management efficiency of energy efficiency data include automation degree, technology application rate and signal detection accuracy; If the energy efficiency evaluation value is lower than or equal to the preset energy efficiency evaluation value threshold, a model sewage treatment plant that meets the conditions is selected from the geographical area to which the target sewage treatment plant belongs; Then, the relative impact coefficients of various energy efficiency decision-making units of the target sewage treatment plant relative to the model sewage treatment plant are calculated to evaluate their relative efficiency; Finally, based on the calculated relative impact coefficient, an energy efficiency optimization analysis is conducted on the target sewage treatment plant, and a targeted energy efficiency optimization strategy is formulated.

[0045] For signal integrity detection, when the signal strength S is lower than the preset threshold , and the data acquisition frequency F deviates from the preset range When the alarm is triggered, the use of data is suspended; The judgment conditions are:

[0046] Where S represents the current signal strength. If the signal strength is too low, data transmission may fail. The signal strength threshold set by the system is determined through historical data analysis to ensure the reliability of signal transmission; F is the frequency of data collection, indicating the number of times data is collected per second; Indicates the preset data acquisition frequency range, defining the frequency limit within which the system can effectively process and update data.

[0047] Obtain energy efficiency data consisting of three dimensions; Dimension 1 includes energy consumption and pollutant reduction benefits; The proposed annual total electricity consumption is E; the proposed annual total COD reduction output is ; The total annual BOD5 reduction output is planned to be ;

[0048]

[0049]

[0050]

[0051]

[0052] in is the unit price of electricity, which indicates the cost per kilowatt-hour of electricity; is the electricity consumption time, which indicates the total electricity usage time of the sewage treatment plant in one year; is the COD concentration before sewage treatment, indicating the pollutant content before treatment; is the COD concentration after sewage treatment, indicating the pollutant content after treatment; is the COD treatment efficiency, usually expressed as a percentage, Reflects the COD removal capacity of the treatment facility; is the BOD5 concentration before sewage treatment; is the BOD5 concentration after sewage treatment; It is the BOD5 treatment efficiency; The total annual ammonia reduction is planned to be ; The annual total nitrogen reduction output is planned to be ; Planned annual total phosphorus reduction output ;

[0053]

[0054]

[0055]

[0056]

[0057]

[0058] in is the ammonia nitrogen concentration before sewage treatment; is the ammonia nitrogen concentration after sewage treatment; is the ammonia nitrogen treatment efficiency; is the nitrogen concentration before sewage treatment; is the nitrogen concentration after sewage treatment; represents the ammonia treatment efficiency; is the phosphorus concentration before sewage treatment; is the phosphorus concentration after sewage treatment; is the phosphorus treatment efficiency; The comprehensive evaluation formula for energy consumption and pollutant reduction benefits in dimension 1 is proposed as follows: ; It means that by subtracting the initial and final concentrations of various pollutants, the total amount of pollutants reduced is calculated and compared with the total electricity E to reflect the energy efficiency;

[0059] The proposed comprehensive income is ;

[0060] in is the total cost, including equipment maintenance, personnel costs, etc.; the above formula is used to evaluate the relationship between the economic benefits brought by energy efficiency and the input cost.

[0061] Dimension 2 of energy efficiency data includes the resource recovery and reuse efficiency dimension; The proposed biodiversity index is BI;

[0062]

[0063] Among them, S is species richness, which indicates the number of species in the ecosystem around the sewage treatment plant; H represents species evenness, which reflects the uniformity of the distribution of species; It is is the number of species, N is the total number of all species; Q represents the habitat quality score, which is obtained through ecological surveys and is used to assess the health of the habitat; K is a normalization constant used to adjust the index to the standard range to ensure that the biodiversity index is between 0 and 1; The proposed carbon footprint is CF;

[0064] in It is the annual CO2 emission, which is used to reflect the greenhouse gas emission in the sewage treatment process; represents the carbon emission factor associated with energy consumption, which represents the carbon dioxide produced per unit of electrical energy; The proposed annual environmental protection investment fund is EPI;

[0065] in It is the annual expenditure for the maintenance of facilities; Annual expenditure for the introduction of new technology; Environmental protection training expenses, annual expenditure; The resource recovery and reuse efficiency dimensions are comprehensively evaluated through the biodiversity index BI, carbon footprint CF and annual environmental protection investment EPI; the resource recovery efficiency is proposed to be ; Propose a resource utilization assessment for ;

[0066] The above formula is used to combine biodiversity, environmental protection input and carbon footprint, and standardize the evaluation of resource recovery and reuse efficiency through electricity input E;

[0067] in The definition is the reuse rate, which is used to reflect the proportion of sewage reuse. The reuse rate represents the ratio of the amount of water that can be reused in the treatment process to the total amount of treated water. Defined as the waste generation rate, the waste generation rate represents the ratio of the amount of waste generated during sewage treatment to the total sewage treatment volume.

[0068] Dimension three of energy efficiency data includes the operational and management efficiency dimension; The proposed automation degree is A; the proposed technology application rate is T; the proposed signal detection accuracy rate is SD;

[0069]

[0070]

[0071] in is the number of automated equipment, indicating the number of equipment with automated functions in the sewage treatment system; is the total number of equipment, indicating the total number of all equipment in the sewage treatment plant; The ratio of new technology use indicates the application ratio of newly introduced technologies in sewage treatment; The ratio of traditional technology used is the ratio of the original technology used in sewage treatment. It is the total application of all technologies, including new technologies and traditional technologies; is the number of correct detections, which indicates the total number of successful signal recognition; is the total number of signal detections, indicating the total number of all detection attempts; A comprehensive evaluation of the operation and management efficiency dimensions is conducted based on the automation degree A, technology application rate T and signal detection accuracy SD; the operation management efficiency is proposed as ;

[0072] The above formula averages the degree of automation, technology application rate and signal detection accuracy to evaluate the overall operation and management efficiency.

[0073] Comprehensive energy efficiency evaluation based on energy efficiency data in three dimensions; The proposed comprehensive energy efficiency evaluation value is ; Comprehensive evaluation formula:

[0074] The above formula is used to combine the energy consumption and pollutant reduction benefit dimensions, resource recovery and reuse efficiency dimensions, and operation and management efficiency dimensions to form a comprehensive energy efficiency evaluation value. The comprehensive energy efficiency evaluation value is used to reflect the overall energy efficiency performance.

[0075] Judgment on the criteria for selecting model sewage treatment plants: If the comprehensive energy efficiency evaluation value Lower than or equal to the preset threshold , then select qualified model sewage treatment plants from the geographical area where the target sewage treatment plant belongs; Judgment conditions: .

[0076] Calculate the relative impact coefficients, and calculate the relative impact coefficients (RIC) of each energy efficiency decision-making unit of the target sewage treatment plant relative to the model sewage treatment plant:

[0077] in It is the comprehensive energy efficiency evaluation value of the model sewage treatment plant, which is used to compare and evaluate the relative performance of the target sewage treatment plant; Next, an energy efficiency optimization analysis is carried out; based on the calculated relative impact coefficient, the strengths and weaknesses of the target sewage treatment plant in terms of energy efficiency are identified, analyzed, and ultimately a targeted energy efficiency optimization strategy is formulated.

[0078] The proposed detection frequency of the initial signal integrity detection is , according to the selection criteria of model sewage treatment plants Dynamically adjust the pass rate The value of

[0079] The proposed energy efficiency pass rate is , Used to reflect the energy efficiency performance of the target sewage treatment plant; according to and Comparison results and pass rate To dynamically adjust the detection frequency ;when If the energy efficiency passing rate If the energy efficiency is lower than the preset threshold, the detection frequency will be increased. value to perform signal integrity checks more frequently; when When, and the energy efficiency pass rate If the energy efficiency pass rate is higher than the preset threshold, the detection frequency will be reduced. to save system resources; Dynamically update the detection frequency through the dynamic frequency adjustment formula ;

[0080] in is the current detection frequency; It is the adjustment coefficient used to control the variation of the detection frequency. It usually takes a value between 0 and 1. The larger the value, the greater the frequency adjustment amplitude. is the energy efficiency pass rate, if the pass rate If lower, The value of is large, resulting in Increase; on the contrary, if Higher, reduce.

[0081] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for optimizing energy efficiency for sewage treatment, characterized in that: include: Before conducting energy efficiency evaluation, the data source for energy efficiency evaluation is tested for signal integrity. When the signal strength of the corresponding data source is lower than the signal strength threshold preset by the system, and the data acquisition frequency deviates from the data acquisition frequency range threshold preset by the system, an alarm is triggered and the use of the data is suspended; otherwise, the data source used for energy efficiency evaluation is used as an input value to the three-dimensional evaluation model; Obtain energy efficiency data of the target sewage treatment plant that has passed the signal integrity test, conduct energy efficiency evaluation on the energy efficiency data of the target sewage treatment plant through a three-dimensional evaluation model, and generate an energy efficiency evaluation value; The energy efficiency data includes three dimensions: energy consumption and pollutant reduction efficiency, resource recovery and reuse efficiency, and operation and management efficiency. The energy consumption and pollutant reduction benefit dimensions of the energy efficiency data include the annual total electricity input of the target sewage treatment plant, the annual total COD reduction output, the annual total BOD5 reduction output, the annual total ammonia reduction output, the annual total nitrogen reduction output, and the annual total phosphorus reduction output; The resource recovery and reuse efficiency dimension of the energy efficiency data includes the biodiversity index, carbon footprint, and annual ecological restoration investment of the target wastewater treatment plant; The dimensions of operation and management efficiency of energy efficiency data include automation degree, technology application rate and signal detection accuracy; If the energy efficiency evaluation value is lower than or equal to the preset energy efficiency evaluation value threshold, a model sewage treatment plant that meets the conditions is selected from the geographical area to which the target sewage treatment plant belongs; Then, the relative impact coefficients of various energy efficiency decision-making units of the target sewage treatment plant relative to the model sewage treatment plant are calculated to evaluate their relative efficiency; Finally, based on the calculated relative impact coefficient, the target sewage treatment plant is analyzed for energy efficiency optimization and targeted energy efficiency optimization strategies are formulated; For signal integrity detection, when the signal strength S is lower than the preset threshold , and the data acquisition frequency F deviates from the preset range When the alarm is triggered, the use of data is suspended; The judgment conditions are: Where S represents the current signal strength. If the signal strength is too low, data transmission may fail. is the signal strength threshold set by the system; F is the frequency of data collection, indicating the number of times data is collected per second; Indicates the preset data acquisition frequency range; Obtain energy efficiency data consisting of three dimensions; Dimension 1 includes energy consumption and pollutant reduction benefits; The proposed annual total electricity consumption is E; the proposed annual total COD reduction output is ; The total annual BOD5 reduction output is planned to be ; in is the unit price of electricity, which indicates the cost per kilowatt-hour of electricity; is the electricity consumption time, which indicates the total electricity usage time of the sewage treatment plant in one year; is the COD concentration before sewage treatment, indicating the pollutant content before treatment; is the COD concentration after sewage treatment, indicating the pollutant content after treatment; is the COD treatment efficiency, Reflects the COD removal capacity of the treatment facility; is the BOD5 concentration before sewage treatment; is the BOD5 concentration after sewage treatment; It is the BOD5 treatment efficiency; The total annual ammonia reduction is planned to be ; The proposed annual total nitrogen reduction output is ; Planned annual total phosphorus reduction output ; in is the ammonia nitrogen concentration before sewage treatment; is the ammonia nitrogen concentration after sewage treatment; is the ammonia nitrogen treatment efficiency; is the nitrogen concentration before sewage treatment; is the nitrogen concentration after sewage treatment; represents the ammonia treatment efficiency; is the phosphorus concentration before sewage treatment; is the phosphorus concentration after sewage treatment; is the phosphorus treatment efficiency; The comprehensive evaluation formula for energy consumption and pollutant reduction benefits in dimension 1 is proposed as follows: ; It means that by subtracting the initial and final concentrations of various pollutants, the total amount of pollutants reduced is calculated and compared with the total electricity E to reflect the energy efficiency; The proposed comprehensive income is ; in is the total cost; the above formula is used to evaluate the relationship between the economic benefits brought by energy efficiency and the input cost; Dimension 2 of energy efficiency data includes the resource recovery and reuse efficiency dimension; The proposed biodiversity index is ; Among them, S is species richness, which indicates the number of species in the ecosystem around the sewage treatment plant; H represents species evenness, which reflects the uniformity of the distribution of species; It is is the number of species, N is the total number of all species; Q represents the habitat quality score, which is obtained through ecological surveys and is used to assess the health of the habitat; K is a normalization constant used to adjust the index to the standard range to ensure that the biodiversity index is between 0 and 1; The proposed carbon footprint is CF; in It is the annual CO2 emission, which is used to reflect the greenhouse gas emission in the sewage treatment process; represents the carbon emission factor associated with energy consumption, which represents the carbon dioxide produced per unit of electrical energy; The annual environmental protection investment is planned to be ; in It is the annual expenditure for the maintenance of facilities; Annual expenditure for the introduction of new technology; Environmental protection training expenses, annual expenditure; Through the Biodiversity Index , Carbon Footprint and annual environmental protection investment Comprehensively evaluate the resource recovery and reuse efficiency dimensions; propose resource recovery efficiency as ; Propose a resource utilization assessment for ; The above formula is used to combine biodiversity, environmental protection investment and carbon footprint, through electricity investment Conduct standardized assessments of resource recovery and reuse efficiency; in The definition is the reuse rate, which is used to reflect the proportion of sewage reuse. The reuse rate represents the ratio of the amount of water that can be reused in the treatment process to the total amount of treated water. Defined as the waste generation rate, the waste generation rate represents the ratio of the amount of waste generated during sewage treatment to the total sewage treatment volume; Dimension three of energy efficiency data includes the operational and management efficiency dimension; The proposed automation level is ; The proposed technology application rate is ; The proposed signal detection accuracy is ; in is the number of automated equipment, indicating the number of equipment with automated functions in the sewage treatment system; is the total number of equipment, indicating the total number of all equipment in the sewage treatment plant; The ratio of new technology use indicates the application ratio of newly introduced technologies in sewage treatment; The ratio of traditional technology used is the ratio of the original technology used in sewage treatment. It is the total application of all technologies, including new technologies and traditional technologies; is the number of correct detections, which indicates the total number of successful signal recognition; is the total number of signal detections, indicating the total number of all detection attempts; Based on the degree of automation , technology application rate And signal detection accuracy Comprehensively evaluate the dimensions of operation and management efficiency; propose operation and management efficiency as ; The above formula averages the degree of automation, technology application rate and signal detection accuracy to evaluate the overall operation and management efficiency.

2. The method for energy efficiency optimization analysis of sewage treatment according to claim 1, characterized in that: Comprehensive energy efficiency evaluation based on energy efficiency data in three dimensions; The proposed comprehensive energy efficiency evaluation value is ; Comprehensive evaluation formula: The above formula is used to combine the energy consumption and pollutant reduction benefit dimensions, resource recovery and reuse efficiency dimensions, and operation and management efficiency dimensions to form a comprehensive energy efficiency evaluation value. The comprehensive energy efficiency evaluation value is used to reflect the overall energy efficiency performance.

3. The method for optimizing energy efficiency for sewage treatment according to claim 2, characterized in that: Judgment on the criteria for selecting model sewage treatment plants: If the comprehensive energy efficiency evaluation value Lower than or equal to the preset threshold , then select qualified model sewage treatment plants from the geographical area where the target sewage treatment plant belongs; Judgment conditions: .

4. The method for optimizing energy efficiency for sewage treatment according to claim 3, characterized in that: Calculate the relative impact coefficients of the target sewage treatment plant relative to the model sewage treatment plant's energy efficiency decision-making units : in It is the comprehensive energy efficiency evaluation value of the model sewage treatment plant, which is used to compare and evaluate the relative performance of the target sewage treatment plant; Next, an energy efficiency optimization analysis is carried out; based on the calculated relative impact coefficient, the strengths and weaknesses of the target sewage treatment plant in terms of energy efficiency are identified, analyzed, and ultimately a targeted energy efficiency optimization strategy is formulated.

5. The method for energy efficiency optimization analysis for sewage treatment according to claim 4, characterized in that: The proposed detection frequency of the initial signal integrity detection is , according to the selection criteria of model sewage treatment plants Dynamically adjust the pass rate The value of The proposed energy efficiency pass rate is , Used to reflect the energy efficiency performance of the target sewage treatment plant; according to and Comparison results and pass rate To dynamically adjust the detection frequency ;when If the energy efficiency passing rate If the energy efficiency is lower than the preset threshold, the detection frequency will be increased. When When, and the energy efficiency pass rate If the energy efficiency pass rate is higher than the preset threshold, the detection frequency will be reduced. The value of Dynamically update the detection frequency through the dynamic frequency adjustment formula ; in is the current detection frequency; It is an adjustment coefficient used to control the variation of the detection frequency.

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