Sewage treatment aeration system energy-saving control method and system based on working condition adaptation

Abstract

The invention discloses an energy-saving control method and system for a sewage treatment aeration system based on working condition adaptation, and relates to the technical field of sewage treatment energy conservation. According to the method, through full-process substance trajectory analysis, operating environments are divided into four types of high-temperature sunny days, high-temperature rainy days, low-temperature sunny days and low-temperature rainy days, and COD removal rates of all sections of a biochemical pool under different working conditions are quantified; a theoretical oxygen demand dynamic calculation model is constructed based on the principle of conservation of substances, and the actual oxygenation amount is monitored in real time in combination with an intelligent aeration monitor; a staged aeration optimization strategy is adopted, and the aeration rate is adjusted in sequence, so that DO is maintained at 1.0-2.0 mg / L; and energy-saving effect quantification and feedback adjustment are realized by monitoring indexes in real time. The device comprises an intelligent monitoring module, a working condition adaptation calculation module, a subsection control execution module and a data feedback module. The method solves the problems of poor working condition adaptability, extensive calculation of oxygen transfer efficiency and the like of a traditional method, and realizes accurate energy saving of an aeration system and stable and standard water quality.

Description

Technical Field

[0001] This invention relates to the field of energy-saving technology in wastewater treatment, and in particular to an energy-saving control method and system for wastewater treatment aeration systems based on operating conditions. Background Technology

[0002] In wastewater treatment, the removal of pollutants relies on the biochemical metabolism of microorganisms. This process requires aeration to provide electron acceptors. As the core component of wastewater treatment, the aeration system accounts for approximately 45% to 75% of the plant's energy consumption. Insufficient aeration can affect nitrification, leading to substandard effluent quality; excessive aeration, on the other hand, wastes energy and may damage the sludge structure.

[0003] Traditional aeration control methods have several drawbacks. First, they lack adaptability to operating conditions. Using fixed dissolved oxygen thresholds (e.g., 2 mg / L~3 mg / L) fails to consider the dynamic impact of environmental factors such as temperature and rainfall on microbial activity and pollutant removal efficiency, leading to a 20%-30% deviation between the actual aeration volume and the actual demand. Second, oxygen transfer efficiency calculations are crude. Assuming an oxygen transfer efficiency (OTE) as a constant and ignoring the effects of water quality, water temperature, and aerator blockage, the calculated actual oxygenation volume often deviates significantly, frequently resulting in over-aeration (e.g., actual oxygenation volume exceeding 1.5 times the theoretical value). Third, the control strategy is simplistic, lacking a segmented aeration optimization mechanism. It cannot dynamically adjust the aeration volume based on differences in oxygen demand along the aerobic tank, resulting in significant energy waste. While existing technologies such as fuzzy logic control and dynamic alpha factor models offer improvements, they have not yet formed a systematic solution integrating operating condition analysis, real-time monitoring, and precise calculation. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides an energy-saving control method and system for wastewater treatment aeration systems based on operating conditions. By constructing a theoretical oxygen demand model that considers operating conditions such as temperature and rainfall, and combining it with real-time oxygen transfer efficiency monitoring, the aeration volume can be precisely controlled, solving the problem of over-aeration, reducing energy consumption, and improving water quality stability.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: An energy-saving control method for a wastewater treatment aeration system based on operating condition adaptation includes the following steps: S1. Full-process material trajectory analysis and operating condition classification: Sampling points are set up in each process section of the wastewater treatment plant, and water quality data are collected according to the set period to analyze the migration trajectory of pollutants; the operating environment is divided into four categories: high temperature sunny day, high temperature rainy day, low temperature sunny day, and low temperature rainy day, and the COD removal rate of each section of the biological treatment tank under different operating conditions is quantified. S2. Construction of a dynamic calculation model for theoretical oxygen demand (TOD): Based on the principle of conservation of mass, a TOD calculation formula is established, which integrates the oxygen demand of aerobic COD degradation by heterotrophic bacteria, the oxygen demand of nitrification reaction by autotrophic bacteria, and the consumption of nitrate nitrogen by the denitrification process. S3. Real-time monitoring of actual oxygenation rate (OTR): An intelligent aeration monitor is used to collect the exhaust gas from the aeration tank through the gas collection hood, detect the oxygen partial pressure difference between the exhaust gas and the ambient air, and calculate the real-time oxygen transfer efficiency (OTE); simultaneously monitor parameters such as water temperature (T), dissolved oxygen (DO), and salinity, convert the OTE to the standard oxygen transfer efficiency (SOTE), and calculate the actual oxygenation rate of each aeration section. S4. Segmented Aeration Optimization Strategy: Comparing TOD and OTR, when OTR>TOD, the aeration rate is gradually reduced in a set order until the sum of the oxygenation rates of each segment equals TOD; segmented control technology is adopted to divide the aerobic tank into multiple aeration zones. Based on the real-time calculated recommended aeration rate, the opening of the aerators in each zone is dynamically adjusted through the control cabinet to keep dissolved oxygen (DO) within the optimized range. S5. Energy-saving effect quantification and feedback adjustment: Real-time monitoring of indicators such as aeration volume per unit water volume and fan power consumption. When the COD and ammonia nitrogen concentration in the effluent fluctuate beyond the set value, the model parameter calibration is automatically triggered, and the database of COD removal rate and oxygen transfer efficiency under different working conditions is updated.

[0006] Furthermore, in S1, the number of sampling points is several, covering each process section including influent, anaerobic tank, anoxic tank, aerobic tank, and effluent; the set cycle is 4 hours; water temperature >15℃ is defined as high temperature, and daily rainfall ≥2mm is defined as rainy day.

[0007] Furthermore, in S2, the formula for calculating the theoretical oxygen demand (TOD) is as follows: (1) (2) (3) (4) (5) (6) In the formula: 4.57 represents the mass of oxygen required to oxidize one kilogram of ammonia nitrogen during nitrification. The oxygen demand (kg / d) corresponding to the residual NO3-N in the total effluent. Inlet flow rate (m) 3 / d), The TN concentration in the effluent (mg / L) The concentration of NH3-N in the effluent (mg / L); The oxygen demand (kg / d) for the denitrification of COD by heterotrophic bacteria in anoxic conditions. The COD removal rate (%) in the anaerobic tank. The COD removal rate (%) in the anoxic tank. The influent COD concentration (mg / L) The COD concentration of the effluent (mg / L); The oxygen demand (kg / d) corresponding to the NO3-N consumption for heterotrophic bacteria in anaerobic denitrification. The oxygen demand (kg / d) for autotrophic bacteria to oxidize NH3-N to NO3-N. The oxygen demand (kg / d) for heterotrophic bacteria to aerobicly degrade COD. COD removal rate (%) in the aerobic tank; COD removal rate of biological treatment tank under different operating conditions The calculation formula for (%) is as follows: (7) Combining formulas (1) to (7), we get: (8).

[0008] Furthermore, in S3, the formula for calculating the oxygenation capacity OTR (kg / d) is as follows: (9) (10) (11) (12) In the formula: OTE Oxygen transfer efficiency (%) The percentage of oxygen in the air (%). The percentage of oxygen in the exhaust gas (%) α This represents the ratio of oxygen mass transfer efficiency between wastewater and clean water. SOTE Standard oxygen transfer efficiency (%). The dissolved oxygen concentration (mg / L) in saturated water at 20℃. β This is the ratio of the saturated dissolved oxygen concentration of wastewater to that of clean water. T This represents the actual water temperature (°C). for T Dissolved oxygen concentration (mg / L) in water at ℃. DO This represents the actual dissolved oxygen concentration (mg / L). θ Temperature coefficient; OTR i For the first i Oxygenation rate per section (kg / d) iThe numbers 1 to 6 represent the front, middle, and rear sections of aerobic tanks A and B, respectively. The density of oxygen under standard conditions (kg / m³) 3 ), For the first i Aeration rate of section (m) 3 / min).

[0009] Furthermore, in S4, the SOTE value under different aeration rates can be confirmed through aerator testing experiments: (13) In the formula: AFR is the air flow rate of a single aerator (m3 / h), and H is the actual water depth of the aerobic tank (m). , These are the parameters for fitting the oxygen transfer performance curve of the aerator in clear water.

[0010] Combining formulas (10) and (13), we can obtain: (14) Since the α coefficient is mainly related to water quality and is not affected by the aeration rate, the coefficient calculated by this formula can be combined with formula (13) to predict the α·SOTE corresponding to different aeration rates, and then predict the OTR corresponding to different aeration rates.

[0011] The method for calculating the recommended aeration rate is as follows: When the actual oxygen supply (OTR) is less than or equal to the theoretical oxygen demand (TOD), since the effluent can already stably meet the standards, the recommended aeration rate is the actual aeration rate; when the actual oxygen supply (OTR) is greater than the theoretical oxygen demand (TOD), the recommended aeration rate is calculated as follows: (15) (16) (17) In the formula: Recommended oxygenation amount (kg / d) for the i-th segment; Let be the recommended aeration rate (m3 / min) for the i-th segment, and Ni be the number of aerators in the i-th segment. The recommended total aeration rate is (m³ / min).

[0012] Furthermore, in S3, each aeration section includes the front, middle, and rear sections of the aerobic tank; the intelligent aeration monitoring instrument consists of an air collection hood, an air guide pipe, and a detector.

[0013] Furthermore, in S4, the setting sequence is "rear section → middle section → front section"; the segmented control technology adopts a magnetic levitation centrifugal blower; the aerobic tank is divided into 6 aeration zones, namely the front, middle and rear sections of tanks A and B respectively; the optimization range is 1.0-2.0 mg / L; and the control cabinet is a PLC control cabinet.

[0014] Furthermore, in S5, the set value is 10%.

[0015] This invention also provides an energy-saving control system for a wastewater treatment aeration system based on operating condition adaptation, using the energy-saving control method described above, including: Intelligent monitoring module: includes multiple water quality sensors and a gas collection hood type exhaust gas analyzer, which collects water quality and aeration parameters in real time and transmits the data to the cloud server; Operating condition adaptation calculation module: It has a built-in theoretical oxygen demand calculation model and oxygen transfer efficiency dynamic correction algorithm. It calls the corresponding biochemical reaction parameters according to the real-time operating conditions and outputs the suggested aeration rate. Segmented control execution module: Composed of magnetic levitation centrifugal blower, electric regulating valve and control cabinet, it supports independent aeration control of front, middle and rear sections, and dynamically adjusts the opening of aerators in each area according to the recommended aeration volume. Data feedback module: Compares actual operating data with theoretical calculations, automatically calibrates model parameters, and generates an energy-saving effect analysis report.

[0016] Furthermore, the intelligent monitoring module includes 17 sets of water quality sensors, including COD, NH3-N, TN, DO, and water temperature sensors; the data is transmitted to a cloud server for storage and subsequent analysis.

[0017] Compared with the prior art, the present invention has the following beneficial effects: 1. Through full-process material trajectory analysis, the system quantifies the dynamic impact of environmental factors such as temperature and rainfall on the COD removal rate of each stage of the biological treatment tank, solving the problem that fixed parameters in traditional control methods are difficult to adapt to changes in operating conditions. The theoretical oxygen demand calculation model can call the corresponding biochemical reaction parameters according to real-time operating conditions, ensuring that the oxygen demand calculation fits the actual operating conditions and avoiding deviations in oxygen demand assessment caused by differences in operating conditions.

[0018] 2. The system employs an intelligent aeration monitoring instrument to acquire the oxygen transfer efficiency (OTE) in real time and converts it into the standard oxygen transfer efficiency (SOTE) using a dynamic correction algorithm, overcoming the limitation of treating oxygen transfer efficiency as a constant in traditional methods. Simultaneously, the system can monitor the impact of parameters such as water temperature, dissolved oxygen, and salinity on oxygen transfer, making the calculation of actual oxygenation more accurate and providing reliable data support for aeration control.

[0019] 3. By dividing the aeration zones and dynamically adjusting the aeration volume in each zone, the system can achieve precise oxygen supply based on the differences in oxygen demand along the aerobic tank. When the actual oxygen supply exceeds the theoretical oxygen demand, the aeration volume is gradually adjusted in the order of "rear section → middle section → front section," which ensures that the biochemical reaction proceeds fully while avoiding over-aeration and reducing energy waste.

[0020] 4. By monitoring energy-saving indicators (such as aeration rate per unit water volume and fan power consumption) and water quality parameters (such as effluent COD and ammonia nitrogen concentration) in real time, the system can automatically trigger model calibration to ensure stable effluent water quality while saving energy and reducing consumption. The feedback adjustment mechanism enables the system to continuously adapt to changes in operating conditions and maintain a high-efficiency operating state in the long term.

[0021] 5. This invention integrates functions such as operating condition analysis, real-time monitoring, precise calculation and dynamic control, forming a complete energy-saving control system for aeration systems. It makes up for the shortcomings of single control strategies in existing technologies and provides wastewater treatment plants with a systematic energy-saving solution that can be directly applied. Attached Figure Description

[0022] The present invention will be further described below with reference to the accompanying drawings and embodiments: Figure 1 This is a flow chart of the wastewater treatment process. Figure 2 The data for effluent COD and ammonia nitrogen from September 18, 2023 to February 27, 2024 are for embodiments of the present invention. Figure 3 This is a distribution diagram of sampling points throughout the entire process of an embodiment of the present invention; Figure 4 This is the result of the change in the trajectory of matter on a hot, sunny day according to an embodiment of the present invention; Figure 5 This is a result of the change in the trajectory of matter during a high-temperature rainy day according to an embodiment of the present invention; Figure 6 This is the result of the change in the trajectory of matter under low temperature and clear weather in an embodiment of the present invention; Figure 7 This is the result of the change in the trajectory of matter during low-temperature rainy weather according to an embodiment of the present invention; Figure 8 The oxygen transfer performance curve of the aerator in clear water was measured for an embodiment of the present invention; Figure 9 This invention provides a comparison of oxygen demand testing in various embodiments. Figure 10 This is a curve showing the relationship between blower air volume and pollutant load in an embodiment of the present invention. Figure 11 The figure shows the blower air volume and monthly average energy consumption curves in an embodiment of the present invention. Figure 12 This is an evaluation index curve of aeration efficiency in an embodiment of the present invention; Figure 13 For the embodiments of the present invention, a quantitative analysis comparing the aeration volume with the actual aeration volume is proposed; Figure 14 The optimized influent flow rate and aeration rate of the aeration system in this embodiment of the invention; Figure 15 The unit power consumption of the blower after optimization of the aeration system in this embodiment of the invention. Detailed Implementation

[0023] The technical solutions of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0024] Under normal operating conditions, temperature is a limiting factor affecting the biological activity and structure of activated sludge in wastewater treatment plants, while rainfall affects influent water quality. Both temperature and weather significantly impact the pollutant removal efficiency of wastewater treatment plants. Therefore, before calculating the theoretical oxygen demand, it is essential to fully analyze the differences and patterns in the pollutant removal capacity of wastewater treatment biochemical systems under different operating environments. This invention classifies temperature into high and low temperatures, and weather into sunny and rainy days. A water temperature above 15℃ is defined as high-temperature weather, and daily rainfall above 2mm is defined as rainy weather. According to the law of conservation of mass, the amount of matter input into the wastewater treatment system should equal the sum of the amount of matter output from the system and the amount of waste generated within the system. The main elements input into the wastewater treatment system are C, N, and P, which then leave the system after being processed by various structures and process units. Therefore, sampling points can be set up at each process stage to sample and analyze the changes in water quality and material trajectories throughout the entire wastewater treatment process.

[0025] Theoretical Oxygen Demand Calculation Principle Theoretical oxygen demand (TOD) is the sum of the oxygen demand for aerobic COD degradation by heterotrophic bacteria and the oxygen demand for nitrification by autotrophic bacteria. Of the NO3-N produced during nitrification, a portion is consumed by the heterotrophic bacteria in the anoxic denitrification process, acting as an electron acceptor for COD degradation; the corresponding oxygen demand is equal to the oxygen demand for COD degradation by the heterotrophic bacteria in anoxic denitrification. The other portion flows out with the effluent. Considering the differences in pollutant removal efficiency of the biological treatment tank under different operating conditions, and combining historical monitoring data of the influent and effluent, the formula for calculating TOD (kg / d) is as follows: (1); (2); (3); (4); (5); (6); In the formula: 4.57 represents the mass of oxygen required to oxidize one kilogram of ammonia nitrogen during nitrification. The oxygen demand (kg / d) corresponding to the residual NO3-N in the total effluent. Inlet flow rate (m) 3 / d), The TN concentration in the effluent (mg / L) The concentration of NH3-N in the effluent (mg / L); The oxygen demand (kg / d) for the denitrification of COD by heterotrophic bacteria in anoxic conditions. The COD removal rate (%) in the anaerobic tank. The COD removal rate (%) in the anoxic tank. The influent COD concentration (mg / L) The COD concentration of the effluent (mg / L); The oxygen demand (kg / d) corresponding to the NO3-N consumption for heterotrophic bacteria in anaerobic denitrification. The oxygen demand (kg / d) for autotrophic bacteria to oxidize NH3-N to NO3-N. The oxygen demand (kg / d) for heterotrophic bacteria to aerobicly degrade COD. The COD removal rate (%) of the aerobic tank.

[0026] COD removal rate of biological treatment tank under different operating conditions The calculation formula for (%) is as follows: (7); Combining formulas (1) to (7), we get: (8).

[0027] Principle of Actual Oxygen Supply Calculation Oxygenation capacity (OTR) represents the amount of oxygen supplied to the aeration system of a wastewater treatment plant's aeration tank per unit time. The oxygenation performance parameters of aerators in wastewater treatment plants are usually obtained during clean water tests, which significantly differ from the actual oxygenation performance of the aeration system during operation, and real-time oxygen transfer efficiency cannot be obtained. This invention uses an intelligent aeration monitoring instrument to monitor the relative difference between the oxygen composition of the air entering the aeration tank and the oxygen composition of the gas escaping the aeration tank, thereby obtaining the real-time actual oxygen transfer efficiency (OTE) of the wastewater treatment plant's blower aeration system. Simultaneously, it monitors the CO2 content escaping from the aeration tank, as well as ambient air humidity and temperature, displaying the data locally and transmitting it to a cloud server. The monitoring instrument consists of a gas collection hood, a gas guide pipe, and a detector. The detector first measures the partial pressure of oxygen in the ambient air, then measures the partial pressure of oxygen in the exhaust gas collected by the gas collection hood. The oxygen transfer efficiency (OTE) of the aeration system is calculated based on the difference between the partial pressure of oxygen in the exhaust gas and the air. Because the testing environment (including DO, water temperature, salinity, etc.) varies, the measured OTE cannot be directly used to calculate the actual oxygenation rate (OTR). It is necessary to first convert the OTE to α·SOTE. The actual total oxygenation rate is the sum of the oxygenation rates in the initial, middle, and final stages of the aerobic tank. The formula for calculating OTR (kg / d) is as follows: (9); (10); (11); (12); In the formula: OTE Oxygen transfer efficiency (%) The percentage of oxygen in the air (%). The percentage of oxygen in the exhaust gas (%) α This represents the ratio of oxygen mass transfer efficiency between wastewater and clean water. SOTE Standard oxygen transfer efficiency (%). The dissolved oxygen concentration (mg / L) in saturated water at 20℃. β This is the ratio of the saturated dissolved oxygen concentration of wastewater to that of clean water. T This represents the actual water temperature (°C). for T Dissolved oxygen concentration (mg / L) in water at ℃. DO This represents the actual dissolved oxygen concentration (mg / L). θ Temperature coefficient; OTR i For the first i Oxygenation rate per unit area (kg / d), this invention i The numbers 1 to 6 represent the front, middle, and rear sections of aerobic tanks A and B, respectively. The density of oxygen under standard conditions (kg / m³) 3 ), For the firsti Aeration rate of section (m) 3 / min).

[0028] Suggested principles for calculating aeration volume Through aerator testing experiments, the SOTE values ​​under different aeration rates can be confirmed: (13); In the formula: AFR The air flow rate of a single aerator (m³) 3 / h), H This represents the actual water depth (m) of the aerobic tank. , These are the parameters for fitting the oxygen transfer performance curve of the aerator in clear water.

[0029] Combining formulas (10) and (13), we can obtain: (14).

[0030] Since the α coefficient is mainly related to water quality and is not affected by the aeration rate, the coefficient calculated by this formula can be combined with formula (13) to predict the α·SOTE corresponding to different aeration rates, and then predict the OTR corresponding to different aeration rates.

[0031] The method for calculating the recommended aeration rate is as follows: When the actual oxygen supply (OTR) is less than or equal to the theoretical oxygen demand (TOD), since the effluent can already stably meet the standards, the recommended aeration rate is the actual aeration rate; when the actual oxygen supply (OTR) is greater than the theoretical oxygen demand (TOD), the recommended aeration rate is calculated as follows: (15); (16); (17).

[0032] In the formula: For the first i Recommended oxygenation amount (kg / d) for this section; For the first i Recommended aeration rate (m³) for this section 3 / min), N i For the first i Number of aerators in a section (units); Recommended total aeration volume (m³) 3 / min).

[0033] When the actual oxygenation rate (OTR) is greater than the theoretical oxygen demand (TOD), the aeration rate of the later, middle, and earlier stages is reduced sequentially until the sum of the recommended oxygenation rates of each stage equals the TOD, and the recommended total aeration rate is finally obtained.

[0034] The method will now be verified and analyzed through specific embodiments: Project Background: The wastewater treatment plant is located in Anhui Province, with a wastewater treatment capacity of 80,000 m³ / d. It adopts the A2O process, and the process route is as follows: Figure 1 As shown in Table 1, the emission standards comply with the Class A emission standard of the "Emission Standard of Pollutants for Urban Wastewater Treatment Plants" (GB18918-2002) and the "Emission Limits of Major Water Pollutants for Urban Wastewater Treatment Plants and Industrial Sectors in Chaohu Lake Basin" (DB34 / 2710-2016). The designed effluent water quality indicators are shown in Table 1.

[0035] Table 1. Effluent Water Quality Indicators

[0036] The plant has two sets of biological treatment tanks, A and B, each containing a selection tank, anaerobic tank, anoxic tank, and aerobic tank. Dissolved oxygen in the aerobic tank is maintained at approximately 1.0-2.0 mg / L by adjusting the blower airflow. The biological treatment tanks are equipped with 2600 tubular microporous aerators and 30 underwater propellers. The blower room has four magnetic levitation centrifugal blowers, each with an installed power of 213 kW, an airflow of 122 m³ / min, and a pressure boost of 75 kPa. Data on effluent COD and ammonia nitrogen from September 18, 2023 to February 27, 2024 (…) Figure 2 As can be seen, the effluent consistently met the standards and was far below the limit during this period, indicating that the plant had sufficient or even excessive oxygenation and had great potential for energy saving through aeration.

[0037] Analysis of changes in material trajectory: To investigate the pollutant removal efficiency of the biological treatment tank under different operating conditions, full-process sampling was conducted for 10 days each under high-temperature sunny, high-temperature rainy, low-temperature sunny, and low-temperature rainy conditions, with a sampling period of 4 hours. The average values ​​of the test results were used to analyze the changes in influent and effluent water quality and material trajectories under different environments. A total of 17 sampling points were set up, including influent, pretreatment, anaerobic tank, anoxic tank, aerobic tank, secondary sedimentation tank, high sedimentation tank, effluent, internal and external recirculation, and excess sludge. The sampling points are listed below. Figure 3 As shown.

[0038] Based on the analysis data from sampling points throughout the entire process, the results of material trajectory changes under different operating environments were obtained, such as... Figures 4-7 As shown.

[0039] from Figures 4-7It is evident that the aerobic tank is the core component for COD removal in the wastewater treatment process. Within the aerobic tank, numerous aerobic microorganisms convert COD from organic matter into CO2 and H2O through respiration, consuming a significant amount of carbon. Under different operating conditions, the COD removal capacity of the aerobic tank varies significantly, with the highest removal rate reaching 62.0% and the lowest only 28.2% during the experiment. This indicates that environmental factors such as temperature and rainfall have a substantial impact on the pollution removal efficiency of the aerobic tank. Through in-depth analysis of material trajectory changes, the COD removal rates of each stage of the biological treatment tank under different operating conditions were obtained, as detailed in Table 2. The COD removal rate of the biological treatment tank will be used as the basis for calculating the theoretical oxygen demand.

[0040] Table 2 COD removal rate of each section of the biological treatment tank under different operating conditions

[0041] Comparative analysis of theoretical oxygen demand and actual oxygen supply: An aerator test experiment was conducted on the tubular aerators installed in the aerobic tank of a wastewater treatment plant, and the oxygen transfer performance curve of the aerator in clear water was measured as follows: Figure 8 As shown, the horizontal axis represents the airflow rate of a single aerator, and the vertical axis represents the standard oxygen transfer efficiency per unit water depth. The submersion depth of the aerator pipe is 2.1m. The fitted result is... =3.873、 =-0.342.

[0042] Based on production operation monitoring and testing data, material trajectory change analysis, and aerator oxygen transfer performance test results, the theoretical oxygen demand (TOD) and actual oxygen supply rate (OTR) can be calculated. Figure 9 As shown, the theoretical oxygen demand range for this plant during this period was 2661~11799 kg / d, with an average of 7059 kg / d; the actual oxygen supply range was 7362~14785 kg / d, with an average of 10512 kg / d, which is about 1.5 times the average theoretical oxygen demand. The actual oxygen supply can reach more than 3 times the theoretical oxygen demand, indicating obvious over-aeration.

[0043] Quantitative analysis of the potential of solar terms: Figure 10 The data shows that the blower airflow trend is basically synchronized with the changes in influent ammonia nitrogen and COD loads. From February to March 2024, the influent COD load surged by approximately 140%, but the airflow only increased by about 27%. This is because the surge in COD was mainly degraded by microorganisms in the anaerobic and anoxic tanks, and the amount of COD entering the aerobic tank requiring oxygen was limited, resulting in a significantly lower increase in airflow than in COD load.

[0044] Figure 11The data shows that the blower air volume and the monthly average energy consumption trend are highly consistent. From September 2023 to January 2024, although the NH3-N load showed a downward trend, the air volume and the average energy consumption of the blower continued to increase, and the air-to-water ratio, the air-to-ammonia-to-nitrogen ratio, and the blower's power consumption per unit also increased overall (see...). Figure 12 This phenomenon, besides being influenced by human-controlled airflow, may also be affected by seasonal temperature drops. Decreasing water temperature significantly inhibits microbial activity and slows down pollutant degradation. To maintain treatment effectiveness, wastewater treatment plants typically increase sludge concentration to increase microbial biomass, while simultaneously increasing airflow to raise dissolved oxygen levels and meet the growth requirements of the microorganisms.

[0045] From February to April 2024, the NH3-N load gradually increased, and the fan airflow increased accordingly. Compared to the ammonia nitrogen load of 1386.27 kg / d in January 2024, it increased to 1781.84 kg / d in April. The gas-to-ammonia-to-nitrogen ratio was 0.16 m³ / gNH3-N in both months. However, the effluent ammonia-to-nitrogen concentration in April was 0.17 mg / L, lower than the 0.27 mg / L in January, indicating better airflow control in April, balancing water quality and energy conservation. From September 2023 to April 2024, the plant's average gas-to-water ratio, gas-to-ammonia-to-nitrogen ratio, and fan power consumption were 2.76, 0.13 m³ / gNH3-N, and 0.082 kW·h / m³, respectively. Monthly data comparisons show that there is still room for optimization in airflow control.

[0046] like Figure 13 As shown, the recommended aeration rates for each time period were calculated using the above method. During this period, the recommended aeration rate for this water purification plant was 26,479~250,944 m³ / d, with an average of 125,317 m³ / d; the actual aeration rate was 81,960~282,636 m³ / d, with an average of 166,458 m³ / d. Based on this, the air-saving potential of the aeration system is approximately 24.7%.

[0047] To verify the optimization potential of the aeration system, the operating data of the plant from March to November 2024 were compared. March to July served as the control group, while August to November used an intelligent aeration monitoring system to control the air volume as the experimental group. Figure 14 and Figure 15 It can be seen that when the daily water treatment volume and pollutant concentration are basically stable, the monthly average air volume of the blowers in the control group and the experimental group are 8.5689 million m³ and 5.5175 million m³, respectively. The aeration volume per unit water volume decreased from 3.85 m³ to 2.51 m³, a decrease of 34.8%; the power consumption per blower decreased from 0.089 kW·h / m³ to 0.061 kW·h / m³, a decrease of 31.5%.

[0048] in conclusion: This invention quantifies the impact of different environmental conditions (temperature, rainfall) on the COD removal rate of each stage of the biochemical tank through full-process material trajectory analysis, and constructs a theoretical oxygen demand calculation model based on actual operating conditions. This solves the problem that traditional empirical formulas do not take into account differences in operating conditions and significantly improves the accuracy of oxygen demand calculation.

[0049] A method for real-time calculation of actual oxygenation based on an intelligent aeration monitoring instrument was developed, which dynamically obtains the oxygen transfer efficiency and oxygen mass transfer coefficient correction values, and reveals the differences in oxygen transfer performance along the aerobic tank and the spatiotemporal variation law of the coefficient, providing data support for precise aeration control.

[0050] Quantitative analysis shows that the actual oxygenation volume of the plant averages 1.5 times the theoretical oxygen demand, indicating a significant over-aeration problem and a potential energy-saving rate of 24.7%. Through optimization of the intelligent aeration system, the aeration volume per unit water volume decreased by 34.8%, and the power consumption per blower decreased by 31.5%, achieving a synergistic effect of energy saving and water quality compliance. The working condition-adaptive oxygen demand calculation method and intelligent aeration control method proposed in this invention provide theoretical and engineering practice references for precise energy saving in wastewater treatment plant aeration systems.

[0051] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. An energy-saving control method for a wastewater treatment aeration system based on operating condition adaptation, characterized in that, Includes the following steps: S1. Full-process material trajectory analysis and operating condition classification: Sampling points are set up in each process section of the wastewater treatment plant, water quality data are collected at a set period, and the migration trajectory of pollutants is analyzed. The operating environment was divided into four categories: high temperature sunny day, high temperature rainy day, low temperature sunny day, and low temperature rainy day. The COD removal rate of each section of the biological tank under different operating conditions was quantified. S2. Construction of a dynamic calculation model for theoretical oxygen demand (TOD): Based on the principle of conservation of mass, a TOD calculation formula is established, which integrates the oxygen demand of aerobic COD degradation by heterotrophic bacteria, the oxygen demand of nitrification reaction by autotrophic bacteria, and the consumption of nitrate nitrogen by the denitrification process. S3. Real-time monitoring of actual oxygenation rate (OTR): An intelligent aeration monitor is used to collect the exhaust gas from the aeration tank through the gas collection hood, detect the oxygen partial pressure difference between the exhaust gas and the ambient air, and calculate the real-time oxygen transfer efficiency (OTE); simultaneously monitor parameters such as water temperature (T), dissolved oxygen (DO), and salinity, convert the OTE to the standard oxygen transfer efficiency (SOTE), and calculate the actual oxygenation rate of each aeration section. S4. Segmented aeration optimization strategy: Compare TOD and OTR. When OTR > TOD, gradually reduce the aeration volume in the set order until the sum of the oxygenation volumes of each segment equals TOD. The aerobic tank is divided into multiple aeration zones using segmented control technology. Based on the real-time calculated recommended aeration rate, the opening of the aerators in each zone is dynamically adjusted through the control cabinet to maintain dissolved oxygen (DO) within the optimized range. S5. Energy-saving effect quantification and feedback adjustment: Real-time monitoring of indicators such as aeration volume per unit water volume and fan power consumption. When the COD and ammonia nitrogen concentration in the effluent fluctuate beyond the set value, the model parameter calibration is automatically triggered, and the database of COD removal rate and oxygen transfer efficiency under different working conditions is updated.

2. The energy-saving control method for a wastewater treatment aeration system based on operating condition adaptation as described in claim 1, characterized in that, In S1, the number of sampling points is several, covering the influent, anaerobic tank, anoxic tank, aerobic tank, and effluent process sections; the set cycle is 4 hours; water temperature >15℃ is defined as high temperature, and daily rainfall ≥2mm is defined as rainy day.

3. The energy-saving control method for a wastewater treatment aeration system based on operating condition adaptation as described in claim 1, characterized in that, In S2, the formula for calculating the theoretical oxygen demand (TOD) is as follows: （1）； （2）； （3）； （4）； （5）； （6）； In the formula: the coefficient 4.57 represents the mass of oxygen required to oxidize one kilogram of ammonia nitrogen during nitrification. The oxygen demand (kg / d) corresponding to the residual NO3-N in the total effluent. Inlet flow rate (m) 3 / d), The TN concentration in the effluent (mg / L) The concentration of NH3-N in the effluent (mg / L); The oxygen demand (kg / d) for the denitrification of COD by heterotrophic bacteria in anoxic conditions. The COD removal rate (%) in the anaerobic tank. The COD removal rate (%) in the anoxic tank. The influent COD concentration (mg / L) The COD concentration of the effluent (mg / L); The oxygen demand (kg / d) corresponding to the NO3-N consumption for heterotrophic bacteria in anaerobic denitrification. The oxygen demand (kg / d) for autotrophic bacteria to oxidize NH3-N to NO3-N. The oxygen demand (kg / d) for heterotrophic bacteria to aerobicly degrade COD. COD removal rate (%) in the aerobic tank; COD removal rate of biological treatment tank under different operating conditions The calculation formula for (%) is as follows: （7）； Combining formulas (1) to (7), we get: （8）。 4. The energy-saving control method for a wastewater treatment aeration system based on operating condition adaptation as described in claim 3, characterized in that, In S3, the formula for calculating the oxygenation capacity OTR (kg / d) is as follows: （9）； （10）； （11）； （12）； In the formula: OTE Oxygen transfer efficiency (%) The percentage of oxygen in the air (%). The percentage of oxygen in the exhaust gas (%) α This represents the ratio of oxygen mass transfer efficiency between wastewater and clean water. SOTE Standard oxygen transfer efficiency (%). The dissolved oxygen concentration (mg / L) in saturated water at 20℃. β This is the ratio of the saturated dissolved oxygen concentration of wastewater to that of clean water. T This represents the actual water temperature (°C). for T Dissolved oxygen concentration (mg / L) in water at ℃. DO This represents the actual dissolved oxygen concentration (mg / L). θ Temperature coefficient; OTR i For the first i Oxygenation rate per section (kg / d) i The numbers 1 to 6 represent the front, middle, and rear sections of aerobic tanks A and B, respectively. The density of oxygen under standard conditions (kg / m³) 3 ), For the first i Aeration rate of section (m) 3 / min).

5. The energy-saving control method for a wastewater treatment aeration system based on operating condition adaptation as described in claim 1, characterized in that, In S4, the SOTE value under different aeration rates can be confirmed through aerator testing experiments: （13）； In the formula: AFR is the air flow rate of a single aerator (m3 / h), and H is the actual water depth of the aerobic tank (m). , These are the parameters for fitting the oxygen transfer performance curve of the aerator in clear water. Combining formulas (10) and (13), we can obtain: （14）； Since the α coefficient is mainly related to water quality and is not affected by the aeration rate, the coefficient calculated by this formula can be combined with formula (13) to predict the α·SOTE corresponding to different aeration rates, and then predict the OTR corresponding to different aeration rates. The method for calculating the recommended aeration rate is as follows: When the actual oxygen supply (OTR) is less than or equal to the theoretical oxygen demand (TOD), since the effluent can already stably meet the standards, the recommended aeration rate is the actual aeration rate; when the actual oxygen supply (OTR) is greater than the theoretical oxygen demand (TOD), the recommended aeration rate is calculated as follows: （15）； （16）； （17）； In the formula: Recommended oxygenation amount (kg / d) for the i-th segment; Let be the recommended aeration rate (m3 / min) for the i-th segment, and Ni be the number of aerators in the i-th segment. The recommended total aeration rate is (m³ / min).

6. The energy-saving control method for a wastewater treatment aeration system based on operating condition adaptation as described in claim 1, characterized in that, In S3, each aeration section includes the front, middle and rear sections of the aerobic tank; the intelligent aeration monitoring instrument consists of an air collection hood, an air guide pipe and a detector.

7. The energy-saving control method for a wastewater treatment aeration system based on operating condition adaptation as described in claim 1, characterized in that, In S4, the setting sequence is "rear section → middle section → front section"; the segmented control technology adopts a magnetic levitation centrifugal blower; the aerobic tank is divided into 6 aeration zones, namely the front, middle and rear sections of tanks A and B respectively; the optimization range is 1.0-2.0 mg / L; the control cabinet is a PLC control cabinet.

8. The energy-saving control method for a wastewater treatment aeration system based on operating condition adaptation as described in claim 1, characterized in that, In S5, the set value is 10%.

9. An energy-saving control system for a wastewater treatment aeration system based on operating condition adaptation, characterized in that, Using the energy-saving control method as described in any one of claims 1 to 8, comprising: Intelligent monitoring module: includes multiple water quality sensors and a gas collection hood type exhaust gas analyzer, which collects water quality and aeration parameters in real time and transmits the data to the cloud server; Operating condition adaptation calculation module: It has a built-in theoretical oxygen demand calculation model and oxygen transfer efficiency dynamic correction algorithm. It calls the corresponding biochemical reaction parameters according to the real-time operating conditions and outputs the suggested aeration rate. Segmented control execution module: Composed of magnetic levitation centrifugal blower, electric regulating valve and control cabinet, it supports independent aeration control of front, middle and rear sections, and dynamically adjusts the opening of aerators in each area according to the recommended aeration volume. Data feedback module: Compares actual operating data with theoretical calculations, automatically calibrates model parameters, and generates an energy-saving effect analysis report.

10. The energy-saving control system for a wastewater treatment aeration system based on operating condition adaptation as described in claim 9, characterized in that, The intelligent monitoring module includes 17 sets of water quality sensors, including COD, NH3-N, TN, DO, and water temperature sensors; the data is transmitted to a cloud server for storage and subsequent analysis.

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