Distributed control photocatalytic method and system for large-scale industrial water treatment

Abstract

The application is suitable for the technical field of industrial water treatment, and provides a distributed control photocatalysis method and system for large-scale industrial water treatment. The method comprises the following steps: configuring an initial temperature set point for each photocatalysis reaction unit and collecting multi-dimensional operation data; generating a temperature control instruction based on the data and the set point, in combination with a temperature difference value and a change trend; synchronously collecting operation state data after the instruction is executed; generating a global optimization strategy containing a dynamic temperature set point and an intelligent hydraulic routing instruction based on all unit data; and updating the set point and adjusting water inlet distribution. The scheme realizes distributed collaborative optimization, improves the treatment efficiency, reduces the energy consumption, and is suitable for large-scale industrial water treatment scenes.

Description

Technical Field

[0001] This invention belongs to the field of industrial water treatment technology, and particularly relates to a distributed controlled photocatalysis method and system for large-scale industrial water treatment. Background Technology

[0002] With the continuous expansion of industrial production, the discharge of industrial wastewater is increasing daily. Its complex composition and high pollutant concentration pose a serious threat to the ecological environment and water resource security. Developing efficient and stable industrial water treatment technologies has become a key focus for the industry. Photocatalysis technology, with its advantages of deep degradation of organic pollutants, no secondary pollution, and mild reaction conditions, is increasingly widely used in industrial water treatment. To meet the treatment needs of large-scale industrial wastewater, distributed control systems composed of multiple photocatalytic reaction units are gradually becoming the mainstream development trend. These systems increase treatment capacity through decentralized layout, while relying on precise control technology to achieve coordinated operation of each unit, thereby controlling energy consumption while ensuring water treatment efficiency.

[0003] The existing system's unified temperature setpoint cannot adapt to the optimal activity temperature requirements of different reaction units due to differences in catalyst characteristics and inlet water temperature, which can easily lead to insufficient catalyst activity or overheating deactivation in some units. The multi-dimensional operation data collection is incomplete, and relying on only a few parameters is insufficient to fully reflect the unit's operating status, resulting in a lack of precise basis for temperature regulation and a tendency for over- or under-regulation. There is a lack of a global cooling energy consumption prediction and optimization mechanism based on the operating status of each unit, resulting in large fluctuations in total cooling energy consumption and low energy utilization efficiency. The inlet water distribution method is fixed and is not dynamically adapted in conjunction with the light intensity adjustment or cooling system operating status of each unit, resulting in energy waste. Furthermore, the lack of effective coordination among units in the distributed architecture makes it difficult to improve overall operating efficiency. Summary of the Invention

[0004] The purpose of this invention is to provide a distributed controlled photocatalysis method for large-scale industrial water treatment, aiming to solve the technical problems of the prior art as identified in the background section.

[0005] This invention is implemented as follows: a distributed controlled photocatalysis method for large-scale industrial water treatment, the method comprising:

[0006] An initial temperature setpoint was configured for each photocatalytic reaction unit, and multi-dimensional operational data for each photocatalytic reaction unit was collected.

[0007] Based on the multi-dimensional operating data and the initial temperature setpoint, control commands for adjusting the temperature of the corresponding photocatalytic reaction unit are generated according to the difference between the current internal temperature of the reactor and the initial temperature setpoint and the trend of the difference.

[0008] During the execution of the control command, the operating status data of each photocatalytic reaction unit is collected synchronously after the control command is executed;

[0009] Based on the operating status data of all photocatalytic reaction units, a global optimization strategy is generated, which includes updated dynamic temperature setpoint instructions and intelligent hydraulic routing instructions.

[0010] The updated dynamic temperature setpoint command is updated to the initial temperature setpoint, and the intelligent hydraulic routing command is sent to the water inlet distribution valve group to adjust the water inlet distribution of each photocatalytic reaction unit.

[0011] As a further aspect of the present invention, configuring an initial temperature setpoint for each photocatalytic reaction unit and collecting multi-dimensional operational data for each photocatalytic reaction unit specifically includes:

[0012] The optimal activity temperature range is determined based on the characteristics of the catalyst material, and an initial temperature setpoint is configured for each photocatalytic reaction unit within the optimal activity temperature range.

[0013] The system collects the inlet flow rate and temperature of the inlet pipe, and simultaneously collects the internal temperature of the reactor in real time. The system also collects the current light intensity of the ultraviolet lamp through the power meter that is equipped with the ultraviolet lamp.

[0014] The collected data, including reactor internal temperature, current UV lamp intensity, influent flow rate, and influent temperature, are packaged into multi-dimensional operational data.

[0015] The multi-dimensional operating data includes the reactor internal temperature, the current light intensity of the ultraviolet lamp, the influent flow rate, and the influent temperature.

[0016] As a further embodiment of the present invention, the generation of control commands for adjusting the temperature of the corresponding photocatalytic reaction unit includes:

[0017] The negative deviation threshold is determined based on the catalyst minimum activation temperature, the positive deviation threshold is determined based on the catalyst tolerance limit, and a sliding time window is set for the internal temperature of the reactor.

[0018] Calculate the real-time difference between the current internal temperature of the reactor and the initial temperature setpoint, and calculate the trend of the difference change according to the length of the sliding time window;

[0019] When the real-time difference exceeds the negative deviation threshold and the corresponding trend of the difference change is negative, the increase in the light intensity of the ultraviolet lamp is calculated based on the real-time difference, and a corresponding light intensity increase control command is generated. The increase is proportional to the real-time difference.

[0020] When the real-time difference exceeds the positive deviation threshold and the corresponding trend of the difference change is positive, the reduction rate of the UV lamp light intensity and the increase rate of the cooling system valve opening are calculated based on the real-time difference, and corresponding joint adjustment control commands are generated.

[0021] As a further aspect of the present invention, the synchronous acquisition control command, after which the operating status data of each photocatalytic reaction unit is executed, includes:

[0022] The control command is issued to drive the light intensity adjustment module of the ultraviolet lamp and the valve adjustment of the cooling system;

[0023] After executing the control command, the real-time reaction temperature and real-time inlet water temperature inside the reactor are continuously collected;

[0024] The instantaneous heat load is calculated based on the inlet flow rate, real-time reaction temperature, and the difference between the real-time inlet temperature and the inlet temperature in the multi-dimensional operating data.

[0025] As a further aspect of the present invention, the generation of the global optimization strategy includes:

[0026] The system periodically receives operating status data uploaded by all photocatalytic reaction units and analyzes it to obtain the real-time reaction temperature and instantaneous heat load of each photocatalytic reaction unit.

[0027] Based on the instantaneous heat load data of all photocatalytic reaction units, the total cooling energy consumption in the next 15 minutes is predicted. With the goal of mitigating the total cooling energy consumption, the dynamic temperature setpoint is calculated and used as the updated dynamic temperature setpoint command.

[0028] Based on the real-time reaction temperature, light intensity regulation, and cooling system status of each photocatalytic reaction unit, low-temperature inlet water that needs to be heated is directed to the photocatalytic reaction unit in the heating state, and high-temperature inlet water that needs to be cooled is directed to the photocatalytic reaction unit in the cooling state, generating intelligent hydraulic routing instructions.

[0029] As a further aspect of the present invention, the adjustment of the water inlet distribution of each photocatalytic reaction unit includes:

[0030] The updated dynamic temperature setpoint command is sent to the corresponding photocatalytic reaction unit, overwriting the original initial temperature setpoint, and used as the temperature control reference for the next control cycle.

[0031] The intelligent hydraulic routing command is sent to the water inlet distribution valve group to adjust the opening of the cooling system valves of each branch, thereby realizing the dynamic adjustment of the water inlet distribution of each photocatalytic reaction unit.

[0032] Another object of the present invention is to provide a distributed controlled photocatalytic system for large-scale industrial water treatment, the system comprising:

[0033] The data acquisition module is used to configure an initial temperature setpoint for each photocatalytic reaction unit and to collect multi-dimensional operating data for each photocatalytic reaction unit. The multi-dimensional operating data includes the internal temperature of the reactor, the current light intensity of the ultraviolet lamp, the influent flow rate, and the influent temperature.

[0034] The temperature control command generation module is used to generate control commands for adjusting the temperature of the corresponding photocatalytic reaction unit based on the multi-dimensional operating data and the initial temperature setpoint, according to the difference between the current internal temperature of the reactor and the initial temperature setpoint and the trend of the difference.

[0035] The operation status data synchronous acquisition module is used to synchronously acquire the operation status data of each photocatalytic reaction unit after the control command is executed during the execution of the control command. The operation status data includes real-time reaction temperature and instantaneous heat load.

[0036] The global optimization strategy generation module is used to generate a global optimization strategy based on the operating status data of all photocatalytic reaction units. The global optimization strategy includes updated dynamic temperature setpoint instructions and intelligent hydraulic routing instructions.

[0037] The instruction issuing module is used to update the updated dynamic temperature setpoint instruction to the initial temperature setpoint and send the intelligent hydraulic routing instruction to the water inlet distribution valve group to adjust the water inlet distribution of each photocatalytic reaction unit.

[0038] As a further embodiment of the present invention, the temperature control command generation module includes:

[0039] The deviation threshold setting unit is used to determine the negative deviation threshold based on the minimum catalyst activation temperature, determine the positive deviation threshold based on the catalyst tolerance limit, and set a sliding time window for the internal temperature of the reactor.

[0040] The trend analysis unit is used to calculate the real-time difference between the current internal temperature of the reactor and the initial temperature setpoint, and to calculate the trend of the difference change according to the length of the sliding time window.

[0041] A light intensity control command generation unit is used to calculate the increase in light intensity of the ultraviolet lamp tube based on the real-time difference when the real-time difference exceeds the negative deviation threshold and the corresponding change trend of the difference is negative, and generate a corresponding light intensity increase control command, wherein the increase is proportional to the real-time difference.

[0042] The joint control command generation unit is used to calculate the reduction rate of the ultraviolet lamp light intensity and the increase rate of the cooling system valve opening based on the real-time difference when the real-time difference exceeds the positive deviation threshold and the corresponding difference change trend is positive, and generate corresponding joint adjustment control commands.

[0043] As a further embodiment of the present invention, the operating status data synchronization acquisition module includes:

[0044] A control command issuing unit is used to issue the control command to drive the light intensity adjustment unit of the ultraviolet lamp tube, which is used to adjust the valve of the cooling system.

[0045] The real-time temperature data acquisition unit is used to continuously acquire the real-time reaction temperature and real-time inlet water temperature inside the reactor after executing the control command.

[0046] The instantaneous heat load calculation unit is used to calculate the instantaneous heat load based on the inlet water flow rate, real-time reaction temperature, and the difference between the real-time inlet water temperature and the inlet water temperature in the multi-dimensional operating data.

[0047] As a further embodiment of the present invention, the global optimization strategy generation module includes:

[0048] The operation status data analysis unit is used to periodically receive the operation status data uploaded by all photocatalytic reaction units and analyze it to obtain the real-time reaction temperature and instantaneous heat load of each photocatalytic reaction unit.

[0049] The dynamic temperature setpoint calculation unit is used to predict the total cooling energy consumption in the next 15 minutes based on the instantaneous heat load data of all photocatalytic reaction units. With the goal of balancing the total cooling energy consumption, it calculates the dynamic temperature setpoint as the updated dynamic temperature setpoint instruction.

[0050] The intelligent hydraulic routing instruction generation unit is used to generate intelligent hydraulic routing instructions based on the real-time reaction temperature, light intensity adjustment, and cooling system status of each photocatalytic reaction unit. It directs low-temperature inlet water that needs to be heated to photocatalytic reaction units that are in a heated state, and directs high-temperature inlet water that needs to be cooled to photocatalytic reaction units that are in a cooled state.

[0051] The beneficial effects of this invention are:

[0052] This invention provides a distributed control photocatalysis method and system for large-scale industrial water treatment. By configuring personalized initial temperature setpoints for each photocatalytic reaction unit based on catalyst characteristics, it solves the problem of poor adaptability of uniform setpoints, ensuring that each unit is in a highly efficient activity range from startup. It comprehensively collects multi-dimensional operational data, including reactor internal temperature, current UV lamp intensity, influent flow rate, and influent temperature, providing a complete basis for temperature regulation and avoiding blind adjustments. Based on catalyst characteristics, it sets deviation thresholds and analyzes the trend of difference changes using a sliding time window to generate targeted adjustment commands, ensuring temperature stability within a safe activity range and reducing the risk of catalyst deactivation. By calculating instantaneous heat load to predict future total cooling energy consumption, it generates dynamic temperature setpoints with the goal of mitigating energy consumption. Simultaneously, it formulates intelligent hydraulic routing commands based on unit operating status to adjust influent allocation, achieving inter-unit state complementarity and efficient energy utilization. The dynamic temperature setpoint update and influent allocation adjustment form a closed-loop control, enabling the system to continuously adapt to operating condition fluctuations. Under the distributed architecture, it ensures independent and efficient operation of each unit while improving overall water treatment efficiency and stability through global collaborative optimization, effectively reducing long-term energy consumption and maintenance costs. Attached Figure Description

[0053] Figure 1 A flowchart of a distributed controlled photocatalysis method for large-scale industrial water treatment provided in an embodiment of the present invention;

[0054] Figure 2 This is a flowchart illustrating the process of collecting multi-dimensional operational data for each photocatalytic reaction unit, as provided in an embodiment of the present invention.

[0055] Figure 3 A flowchart for generating control commands for adjusting the temperature of the corresponding photocatalytic reaction unit is provided for embodiments of the present invention;

[0056] Figure 4 A flowchart illustrating the operating status data of each photocatalytic reaction unit after the execution of the synchronous acquisition control command, provided in an embodiment of the present invention;

[0057] Figure 5 A flowchart for generating a global optimization strategy provided in an embodiment of the present invention;

[0058] Figure 6 A flowchart for adjusting the water inlet distribution of each photocatalytic reaction unit provided in an embodiment of the present invention;

[0059] Figure 7 This is a structural block diagram of a distributed control photocatalytic system for large-scale industrial water treatment provided in an embodiment of the present invention.

[0060] Figure 8 This is a structural block diagram of the temperature control command generation module provided in an embodiment of the present invention;

[0061] Figure 9 This is a structural block diagram of the operation status data synchronization acquisition module provided in an embodiment of the present invention;

[0062] Figure 10 This is a structural block diagram of the global optimization strategy generation module provided in an embodiment of the present invention. Detailed Implementation

[0063] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0064] Figure 1 A flowchart of a distributed controlled photocatalysis method for large-scale industrial water treatment provided in an embodiment of the present invention is shown below. Figure 1 As shown, the method includes:

[0065] S100 configures an initial temperature setpoint for each photocatalytic reaction unit and collects multi-dimensional operating data for each photocatalytic reaction unit;

[0066] When configuring the initial temperature setpoint, it is necessary to first determine the optimal activity temperature range based on the characteristics of the catalyst material. In large-scale industrial water treatment scenarios, the system typically contains multiple photocatalytic reaction units. The catalysts in different units may have slightly different temperature adaptation ranges due to differences in type, preparation batch, or installation environment. Therefore, it is necessary to define the optimal activity temperature range for each unit's catalyst characteristics separately, and then select the initial temperature setpoint within this range. During the selection process, both catalyst activity stability and system start-up efficiency must be considered. Usually, the middle region of the optimal activity temperature range is selected as the initial temperature setpoint. This avoids activity fluctuations caused by the temperature approaching the range boundary and ensures that the unit quickly enters a highly efficient reaction state after startup.

[0067] In the multi-dimensional operational data collection phase, four key parameters need to be acquired simultaneously: reactor internal temperature, current UV lamp intensity, influent flow rate, and influent temperature. Reactor internal temperature directly reflects whether the reaction environment matches the catalyst activity requirements and serves as the basis for subsequent temperature adjustments. The current UV lamp intensity determines the excitation intensity of the photocatalytic reaction, affecting the pollutant degradation rate. Influent flow rate is related to the unit's processing load; changes in flow rate lead to changes in reaction contact time. Influent temperature directly affects the reactor's internal thermal balance and is closely related to subsequent heat load calculations and cooling system adjustments. In large-scale industrial water treatment systems, the influent conditions and lamp aging levels of each reaction unit may differ. A single parameter cannot comprehensively determine the unit's operational status; therefore, it is necessary to simultaneously collect all four parameters and package them into multi-dimensional operational data to ensure that the operational status of each unit can be accurately characterized.

[0068] S200, based on the multi-dimensional operating data and the initial temperature setpoint, and according to the difference between the current internal temperature of the reactor and the initial temperature setpoint and the trend of the difference, a control command is generated to adjust the temperature of the corresponding photocatalytic reaction unit.

[0069] The minimum activation temperature refers to the lowest temperature required for the catalyst to initiate a photocatalytic reaction.

[0070] In large-scale industrial water treatment systems, the catalysts in each photocatalytic reaction unit differ in their minimum activation temperature and tolerance limit due to variations in preparation processes and composition. Determining a negative deviation threshold based on the minimum activation temperature ensures that the temperature does not fall below the catalyst's effective activation lower limit, while determining a positive deviation threshold based on the tolerance limit prevents the temperature from exceeding the catalyst's safe operating upper limit. This design adapts to the heterogeneity of units in a distributed system, ensuring that each unit has a temperature safety boundary consistent with its own catalyst characteristics. The sliding time window is designed to address instantaneous fluctuations in temperature data in industrial scenarios. Brief changes in influent flow rate and temporary fluctuations in water concentration can trigger accidental temperature jumps within the reactor. A fixed-length time window (containing the time interval of multiple consecutive sampling points) smooths out short-term disturbances, focuses on the overall trend of temperature difference changes, and avoids unnecessary adjustments triggered by accidental fluctuations, ensuring the objectivity of adjustment decisions.

[0071] Calculating the real-time difference between the current internal temperature of the reactor and the initial temperature setpoint allows for direct understanding of the temperature deviation of a single unit. Furthermore, by combining the length of the sliding time window to calculate the trend of the difference, it is possible to determine whether the deviation is temporary or persistent. If the difference only exceeds the threshold once but the trend is stable, it may be a short-term disturbance. If the difference exceeds the threshold and the trend is consistent with the direction of deviation, it indicates that the temperature is continuously deviating from the safe range.

[0072] When the real-time difference exceeds the negative deviation threshold and the trend is negative, the temperature is continuously below the effective operating range of the catalyst. At this time, a control command is generated by calculating the increase in UV lamp light intensity. The heat generation effect brought about by the increase in light intensity is used to raise the reactor temperature, so that the catalyst can quickly recover its activity. When the real-time difference exceeds the positive deviation threshold and the trend is positive, the temperature is continuously exceeding the safe range. A single adjustment method may not be able to cool down in time. Therefore, it is necessary to simultaneously calculate the decrease in UV lamp light intensity and the increase in the opening ratio of the cooling system valves. By combining the reduction of heat generation and the enhancement of heat dissipation, the temperature can be quickly pulled back to the safe range.

[0073] In large-scale chemical wastewater treatment systems, some units treating low-concentration organic wastewater may experience a drop in ambient temperature, causing the reactor's internal temperature to remain below the initial temperature setpoint. If the difference exceeds the negative threshold and the trend is negative, the system will calculate the light intensity increase based on the real-time difference and generate a light intensity increase command. Meanwhile, units treating high-concentration recalcitrant wastewater experience intense exothermic reactions, resulting in a persistently high temperature with a positive trend. In such cases, the system will generate a combined command to reduce light intensity and increase the opening of cooling valves, ensuring that units under different operating conditions can obtain an appropriate temperature regulation scheme.

[0074] S300, during the execution of the control command, the operating status data of each photocatalytic reaction unit after the execution of the control command are collected synchronously;

[0075] In large-scale industrial water treatment systems, reaction units are deployed in a dispersed manner and may bear different water treatment loads. Therefore, it is crucial to ensure that command issuance is targeted and timely, avoiding confusion or delays between different units, and ensuring that each unit can promptly initiate adjustment actions based on its previous temperature deviations. For example, in a large-scale system treating mixed industrial wastewater, some units may execute a light intensity increase command because their temperature is below the negative deviation threshold, while other units may execute a combined command to decrease light intensity and increase valve opening because their temperature exceeds the positive deviation threshold. The corresponding commands are then issued to the dedicated adjustment modules of each unit to ensure precise initiation of adjustment actions.

[0076] After the command is executed, the real-time reaction temperature and real-time inlet water temperature inside the reactor are continuously collected. The real-time reaction temperature directly reflects the initial effect of the regulation command, such as whether the temperature rises as expected after the light intensity is increased, or whether the temperature drops as expected after the valve opening is increased; the real-time inlet water temperature is compared with the inlet water temperature in the previous multi-dimensional operation data to determine whether the inlet water temperature has fluctuated, so as to avoid the interference of changes in the inlet water temperature on the judgment of the effect of the regulation command.

[0077] If any unit executes the command to increase the opening of the cooling valve and the real-time temperature does not decrease significantly, and continuous data collection reveals that the real-time inlet water temperature has increased compared to before, it can be determined that the slow temperature decrease is not due to a problem with the command execution, but rather due to fluctuations in the inlet water temperature.

[0078] Based on this, the instantaneous heat load is calculated by combining the influent flow rate, the real-time reaction temperature, and the difference between the real-time influent temperature. The influent flow rate determines the total amount of water entering the unit per unit time and is the basis for calculating heat changes; the difference between the real-time reaction temperature and the real-time influent temperature reflects the temperature change of the water within the reaction unit. Combined with the density and specific heat capacity of water, the heat generation or consumption of the unit per unit time can be quantified.

[0079] S400 generates a global optimization strategy based on the operating status data of all photocatalytic reaction units. The global optimization strategy includes updated dynamic temperature setpoint instructions and intelligent hydraulic routing instructions.

[0080] When periodically receiving operational status data, a reasonable receiving period should be set to ensure that the data can reflect the dynamic changes of the unit in a timely manner, while avoiding excessive data transmission that would increase the system's computational load. Typically, the receiving period is set to 1 minute, taking into account the reaction cycle and data update requirements of the industrial water treatment system, to ensure that the operational status data of each unit can be synchronized in real time.

[0081] After receiving the data, the real-time reaction temperature and instantaneous heat load of each unit are extracted. The real-time reaction temperature is directly related to the catalyst activity state, allowing us to determine whether the unit's current temperature is within the high-efficiency reaction range. The instantaneous heat load quantifies the heat change per unit time, providing a direct reflection of the unit's thermal management needs. Combining these two metrics allows for a comprehensive understanding of the operational status of each unit. In a large-scale chemical industrial park's water treatment system, which contains dozens of photocatalytic reaction units, some units treat high-concentration organic wastewater, exhibiting significant exothermic reactions and high instantaneous heat loads, with real-time reaction temperatures approaching the upper limit of the setpoint. Other units treat low-concentration wastewater, with less exothermic reactions and lower instantaneous heat loads, with real-time reaction temperatures falling within the middle range of the setpoint. By periodically analyzing this data, the differentiated states of all units can be monitored simultaneously, providing a complete data foundation for subsequent global optimization.

[0082] When predicting total cooling energy consumption for the next 15 minutes based on instantaneous heat load data, a predictive model needs to be built based on historical heat load variation patterns. In industrial water treatment systems, parameters such as influent flow rate and water concentration exhibit a certain degree of continuity in changes within a short period of 15 minutes. This pattern is captured by a time series model trained using historical data to accurately estimate future total cooling energy consumption. When calculating the dynamic temperature setpoint, the core objective is to smooth out total cooling energy consumption and avoid drastic fluctuations. If the predicted future total cooling energy consumption is significantly higher than the historical average, the setpoint will be adjusted according to the instantaneous heat load of different units: for units with high instantaneous heat load and large cooling demand, the temperature setpoint will be appropriately lowered to a reasonable range within the optimal activity range of the catalyst to reduce cooling pressure; for units with low instantaneous heat load and small cooling demand, the setpoint will be fine-tuned to maintain catalyst activity without excessive cooling. Through the coordinated adjustment of the setpoints of each unit, the total cooling energy consumption is maintained within a stable range.

[0083] When generating intelligent hydraulic routing commands, it is necessary to comprehensively consider the real-time response temperature, light intensity adjustment status, and cooling system status of each unit. The light intensity adjustment status can determine whether a unit is in heating mode, while the cooling system status can determine whether a unit is in cooling mode. Low-temperature inlet water requiring heating is directed to units in heating mode. This low-temperature inlet water absorbs the heat generated by the unit's reaction, helping the unit maintain a stable temperature and avoiding increased energy consumption due to overheating, without requiring additional heating equipment to be activated. Conversely, high-temperature inlet water requiring cooling is directed to units in cooling mode. This high-temperature inlet water can be cooled by the unit's cooling system, reducing the additional load on the cooling system and avoiding waste of cooling resources. For example, if some units in the system are executing a light intensity increase command, and their real-time response temperature is slightly lower than the set point, directing low-temperature inlet water to these units will allow the water to absorb heat and rise in temperature, allowing the units to maintain their temperature without further increasing the light intensity. Similarly, if some units are executing a cooling valve opening increase command, and their real-time response temperature is slightly higher than the set point, directing high-temperature inlet water to these units will cool them while also reducing the operating pressure on the unit's cooling system.

[0084] S500, update the updated dynamic temperature setpoint command to the initial temperature setpoint, and send the intelligent hydraulic routing command to the water inlet distribution valve group to adjust the water inlet distribution of each photocatalytic reaction unit.

[0085] When updating the dynamic temperature setpoint, the updated dynamic temperature setpoint command is precisely sent to the corresponding photocatalytic reaction unit, directly overriding the original initial temperature setpoint, and using this as the temperature control reference for the next control cycle. The initial temperature setpoint is only a reference value when the unit starts up. However, in actual operation, the influent water temperature, water concentration, ambient temperature, and other operating conditions will continuously change. If the initial temperature setpoint is used for a long time, it may cause the unit temperature to deviate from the optimal activity range of the catalyst, or cause fluctuations in total cooling energy consumption. For example, in the water treatment system of a large chemical industrial park, the influent water temperature generally rises during the day due to high production load. The original initial temperature setpoint of some units may lead to a surge in cooling demand. By sending the updated dynamic temperature setpoint, the temperature reference of these units can be appropriately adjusted upward to a reasonable range within the optimal activity range of the catalyst, reducing cooling pressure while maintaining reaction efficiency. At night, when the influent water temperature drops, the dynamic temperature setpoint can be appropriately adjusted downward to avoid a decrease in catalyst activity due to excessively low temperature, ensuring that the temperature control reference of each unit is always adapted to the current global operating conditions.

[0086] In adjusting the water inlet distribution, intelligent hydraulic routing commands need to be sent to the water inlet distribution valve group. Dynamic adjustment of the water inlet distribution is achieved by regulating the opening of the cooling system valves in each branch. In large-scale systems, the operating states of each photocatalytic reaction unit differ; some units are in a heating state, while others are in a cooling state. A fixed water inlet distribution method would lead to energy waste. Low-temperature inlet water entering a cooling unit requires additional heating, while high-temperature inlet water entering a heating unit requires additional cooling. By adjusting the valve opening, more low-temperature inlet water can be directed to units in a heating state. The low-temperature inlet water absorbs heat from the unit's reaction while its own temperature rises, thus helping heating units maintain temperature stability without requiring further increases in light intensity and reducing the additional heating demand for low-temperature inlet water. Conversely, more high-temperature inlet water can be directed to units in a cooling state. The high-temperature inlet water is cooled by the cooling system, simultaneously reducing the cooling load on cooling units without requiring further increases in valve opening.

[0087] like Figure 2 As shown, the process of configuring an initial temperature setpoint for each photocatalytic reaction unit and collecting multi-dimensional operational data for each photocatalytic reaction unit specifically includes:

[0088] S110 determines the optimal activity temperature range based on the characteristics of the catalyst material and configures an initial temperature setpoint for each photocatalytic reaction unit within the optimal activity temperature range.

[0089] Initial temperature setpoint (denoted as) This is a pre-set temperature reference value for each photocatalytic reaction unit, ranging from the optimal temperature range for catalyst activity. It serves as an initial reference for temperature control, ensuring the reaction starts at a temperature with high catalyst activity, providing a benchmark for subsequent dynamic adjustments, and guaranteeing a basic level of photocatalytic reaction efficiency.

[0090] Within the optimal activity temperature range of the catalyst Within this range, the value is selected based on the characteristics of each unit. For example, if the optimal activity range of a certain unit catalyst is 30-50℃, and the initial influent water temperature is stable at 35℃, then... =40℃ (balancing activity and stability); if the unit is susceptible to low temperature, set... =45℃ (close to) ).

[0091] S120 collects the inlet flow rate and inlet temperature of the inlet pipe, and simultaneously collects the internal temperature of the reactor in real time. The current light intensity of the ultraviolet lamp is collected by the power meter that is equipped with the ultraviolet lamp.

[0092] S130 packages the collected data on reactor internal temperature, current UV lamp intensity, influent flow rate, and influent temperature into multi-dimensional operational data.

[0093] The multi-dimensional operating data includes the reactor internal temperature, the current light intensity of the ultraviolet lamp, the influent flow rate, and the influent temperature.

[0094] like Figure 3 As shown, the generation of control commands for adjusting the temperature of the corresponding photocatalytic reaction unit includes:

[0095] S210 determines the negative deviation threshold based on the catalyst minimum activation temperature, determines the positive deviation threshold based on the catalyst tolerance limit, and sets a sliding time window for the reactor internal temperature.

[0096] in:

[0097] Negative deviation threshold ( ): Used to prevent the temperature inside the reactor from falling below the minimum activation temperature of the catalyst, thus avoiding the catalyst failing to activate due to insufficient temperature, which would lead to a sharp drop or even stagnation in the efficiency of the photocatalytic reaction.

[0098] The catalyst has a minimum activation temperature ( When the temperature is below this value, the activity is almost zero. Therefore, the negative deviation threshold is usually set to... ( (The initial temperature setpoint), when the reactor real-time temperature satisfy At this time, a temperature regulation is triggered to prevent the catalyst from deactivating due to the temperature falling below its activation point. This is because the catalyst needs to reach... Only at this temperature is the reaction active; below this temperature, the reaction efficiency drops sharply, therefore... Define the critical value at which the temperature must be increased.

[0099] Positive deviation threshold ( ): Used to prevent the internal temperature of the reactor from exceeding the catalyst's tolerance limit, thus avoiding catalyst deactivation, accelerated aging, or side reactions due to high temperature.

[0100] The catalyst has a tolerance limit temperature ( Exceeding this value will result in permanent damage. Therefore, the positive deviation threshold is set to... ,when When this occurs, a cooling regulation is triggered to prevent the catalyst from aging or becoming ineffective due to overheating. This is because the catalyst exceeds... It will be permanently damaged, therefore use Define the critical value at which cooling is necessary.

[0101] The sliding time window is a continuous time interval of a preset length (denoted as ). ),Include sampling points ( , (Sampling interval). The window slides over time: every [time period]... Remove the earliest data point and include the latest data point, always maintaining... One point.

[0102] The sliding time window is used to filter instantaneous fluctuations. The data within the window reflects the overall trend of temperature difference changes (continuously increasing / decreasing), avoiding accidental triggering of adjustment commands and improving control stability.

[0103] S220, calculate the real-time difference between the current internal temperature of the reactor and the initial temperature setpoint, and calculate the trend of the difference change according to the length of the sliding time window;

[0104] The trend of the difference (denoted as) The slope of the difference sequence within the window is calculated using the following formula:

[0105] ;

[0106] in:

[0107] : The trend of the difference, positive values ​​indicate The value increases with time, while a negative value indicates a decrease with time.

[0108] : Number of sampling points within the sliding window;

[0109] : No. The relative time of each sampling point within the window;

[0110] : No. The real-time temperature difference between each sampling point, i.e. ( For the first (Real-time temperature of the reactor).

[0111] S230, when the real-time difference exceeds the negative deviation threshold and the corresponding trend of the difference change is negative, the increase in the light intensity of the ultraviolet lamp is calculated based on the real-time difference, and a corresponding light intensity increase control command is generated, wherein the increase is proportional to the real-time difference;

[0112] The increase in light intensity (denoted as) It is proportional to the negative real-time difference, as shown in the formula:

[0113] ;

[0114] in:

[0115] The increase in light intensity of the ultraviolet lamp tube, i.e., the light intensity after adjustment. Original light intensity;

[0116] Light intensity enhancement ratio;

[0117] Negative real-time difference, i.e. (at this time (and is a positive value).

[0118] S240, when the real-time difference exceeds the positive deviation threshold and the corresponding trend of the difference change is positive, the reduction rate of the ultraviolet lamp light intensity and the increase rate of the cooling system valve opening are calculated based on the real-time difference, and corresponding joint adjustment control commands are generated.

[0119] Light intensity reduction ( ):

[0120] ;

[0121] Increase the valve opening percentage of the cooling system ( ):

[0122] ;

[0123] in:

[0124] The degree of light intensity reduction, i.e., the adjusted light intensity. ;

[0125] The percentage increase in valve opening, i.e., the adjusted opening degree. ( (original opening);

[0126] Light intensity reduction coefficient;

[0127] Valve adjustment proportional coefficient;

[0128] Positive real-time difference, i.e. (at this time (and is a positive value).

[0129] like Figure 4 As shown, the operating status data of each photocatalytic reaction unit after the synchronous acquisition control command is executed includes:

[0130] S310, issue the control command to drive the light intensity adjustment module of the ultraviolet lamp and the valve adjustment of the cooling system;

[0131] S320, after executing the control command, continuously collects the real-time reaction temperature and real-time inlet water temperature inside the reactor;

[0132] S330, calculate the instantaneous heat load based on the inlet water flow rate, real-time reaction temperature, and the difference between the real-time inlet water temperature and the inlet water temperature in the multi-dimensional operating data.

[0133] Instantaneous heat load (denoted as) The formula reflects the change in heat in a reaction unit per unit time:

[0134] ;

[0135] in:

[0136] Instantaneous heat load: positive values ​​indicate heat absorption by the unit, and negative values ​​indicate heat release;

[0137] : Inlet water flow rate;

[0138] The density of water;

[0139] Specific heat capacity of water;

[0140] : Real-time temperature of the reactor after the control command is executed;

[0141] : Real-time inlet water temperature after the control command is executed.

[0142] like Figure 5 As shown, the generation of the global optimization strategy includes:

[0143] S410 periodically receives the operating status data uploaded by all photocatalytic reaction units and analyzes it to obtain the real-time reaction temperature and instantaneous heat load of each photocatalytic reaction unit.

[0144] S420, based on the instantaneous heat load data of all photocatalytic reaction units, predicts the total cooling energy consumption in the next 15 minutes, calculates the dynamic temperature setpoint with the goal of mitigating the total cooling energy consumption, and uses it as the updated dynamic temperature setpoint command.

[0145] Specifically:

[0146] 1. Data Collection: Set the data reception period. That is, the time interval at which the system periodically receives operating status data from all photocatalytic reaction units, every Receive all Instantaneous heat load of each unit ( (At the current moment).

[0147] 2. Predicting heat load for the next 15 minutes: using the ARIMA model based on historical data. Predict the heat load of each unit for the next 15 minutes. ( =1,2,...,15 minutes, a total of 15 time steps).

[0148] 3. Calculate and predict total cooling energy consumption: Total cooling energy consumption is proportional to heat load, as shown in the formula:

[0149] ;

[0150] in:

[0151] Predicts total cooling energy consumption for the next 15 minutes;

[0152] Total number of photocatalytic reaction units;

[0153] : No. The unit in the future Predicted heat load for minutes;

[0154] Time step =60s.

[0155] 4. Determine the target energy consumption: Set the target total energy consumption. ,in:

[0156] Average total cooling energy consumption over the past 24 hours;

[0157] It is a smoothing coefficient (taken as 0.9-1.1 to control the range of energy consumption fluctuations).

[0158] 5. Calculate the dynamic temperature setpoint: Adjust the setpoints of each unit to bring the predicted energy consumption close to the target. The formula is:

[0159] ;

[0160] in:

[0161] : No. The updated dynamic temperature setpoint for each unit;

[0162] : No. Each unit's original setpoint;

[0163] Setpoint adjustment coefficient (negative coefficient, to ensure) Reduce when exceeding the target To reduce cooling requirements);

[0164] The remaining parameters are the same as in steps 3-4.

[0165] S430, based on the real-time reaction temperature, light intensity adjustment, and cooling system status of each photocatalytic reaction unit, directs low-temperature inlet water that needs to be heated to the photocatalytic reaction unit in the heating state, and directs high-temperature inlet water that needs to be cooled to the photocatalytic reaction unit in the cooling state, generating intelligent hydraulic routing instructions.

[0166] like Figure 6 As shown, adjusting the water inlet distribution of each photocatalytic reaction unit includes:

[0167] S510, the updated dynamic temperature setpoint command is sent to the corresponding photocatalytic reaction unit to cover the original initial temperature setpoint and serve as the temperature control reference for the next control cycle.

[0168] S520, the intelligent hydraulic routing command is sent to the water inlet distribution valve group to adjust the opening of the cooling system valves of each branch, thereby realizing the dynamic adjustment of the water inlet distribution of each photocatalytic reaction unit.

[0169] Figure 7 A structural block diagram of a distributed controlled photocatalytic system for large-scale industrial water treatment provided in an embodiment of the present invention is shown below. Figure 7 As shown, the system includes:

[0170] The data acquisition module 100 is used to configure an initial temperature setpoint for each photocatalytic reaction unit and to collect multi-dimensional operating data for each photocatalytic reaction unit. The multi-dimensional operating data includes the internal temperature of the reactor, the current light intensity of the ultraviolet lamp, the influent flow rate, and the influent temperature.

[0171] The temperature control command generation module 200 is used to generate control commands for adjusting the temperature of the corresponding photocatalytic reaction unit based on the multi-dimensional operating data and the initial temperature setpoint, according to the difference between the current internal temperature of the reactor and the initial temperature setpoint and the trend of the difference.

[0172] The operation status data synchronous acquisition module 300 is used to synchronously acquire the operation status data of each photocatalytic reaction unit after the control command is executed during the execution of the control command. The operation status data includes real-time reaction temperature and instantaneous heat load.

[0173] The global optimization strategy generation module 400 is used to generate a global optimization strategy based on the operating status data of all photocatalytic reaction units. The global optimization strategy includes updated dynamic temperature setpoint instructions and intelligent hydraulic routing instructions.

[0174] The instruction issuing module 500 is used to update the updated dynamic temperature setpoint instruction to the initial temperature setpoint and send the intelligent hydraulic routing instruction to the water inlet distribution valve group to adjust the water inlet distribution of each photocatalytic reaction unit.

[0175] like Figure 8 As shown, the temperature control command generation module 200 includes:

[0176] The deviation threshold setting unit 210 is used to determine a negative deviation threshold based on the minimum catalyst activation temperature, determine a positive deviation threshold based on the catalyst tolerance limit, and set a sliding time window for the internal temperature of the reactor.

[0177] The trend analysis unit 220 is used to calculate the real-time difference between the current internal temperature of the reactor and the initial temperature setpoint, and to calculate the trend of the difference change according to the length of the sliding time window.

[0178] The light intensity control command generation unit 230 is used to calculate the increase in light intensity of the ultraviolet lamp tube based on the real-time difference when the real-time difference exceeds the negative deviation threshold and the corresponding change trend of the difference is negative, and generate a corresponding light intensity increase control command, wherein the increase is proportional to the real-time difference.

[0179] The joint control command generation unit 240 is used to calculate the reduction rate of the ultraviolet lamp light intensity and the increase rate of the cooling system valve opening based on the real-time difference when the real-time difference exceeds the positive deviation threshold and the corresponding difference change trend is positive, and generate corresponding joint adjustment control commands.

[0180] like Figure 9 As shown, the operating status data synchronization acquisition module 300 includes:

[0181] The control command issuing unit 310 is used to issue the control command to drive the light intensity adjustment unit of the ultraviolet lamp tube, which is used to adjust the valve of the cooling system.

[0182] The real-time temperature data acquisition unit 320 is used to continuously acquire the real-time reaction temperature and real-time inlet water temperature inside the reactor after executing the control command.

[0183] The instantaneous heat load calculation unit 330 is used to calculate the instantaneous heat load based on the inlet water flow rate, real-time reaction temperature, and the difference between the real-time inlet water temperature and the inlet water temperature in the multi-dimensional operation data.

[0184] like Figure 10 As shown, the global optimization strategy generation module 400 includes:

[0185] The operation status data parsing unit 410 is used to periodically receive the operation status data uploaded by all photocatalytic reaction units and parse it to obtain the real-time reaction temperature and instantaneous heat load of each photocatalytic reaction unit.

[0186] The dynamic temperature setpoint calculation unit 420 is used to predict the total cooling energy consumption in the next 15 minutes based on the instantaneous heat load data of all photocatalytic reaction units, and calculate the dynamic temperature setpoint as the updated dynamic temperature setpoint command with the goal of balancing the total cooling energy consumption.

[0187] The intelligent hydraulic routing instruction generation unit 430 is used to generate intelligent hydraulic routing instructions based on the real-time reaction temperature, light intensity adjustment, and cooling system status of each photocatalytic reaction unit, directing low-temperature inlet water that needs to be heated to the photocatalytic reaction unit in the heating state, and directing high-temperature inlet water that needs to be cooled to the photocatalytic reaction unit in the cooling state.

[0188] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0189] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

[0190] 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, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A distributed controlled photocatalytic method for large-scale industrial water treatment, characterized in that, The method includes: An initial temperature setpoint was configured for each photocatalytic reaction unit, and multi-dimensional operational data for each photocatalytic reaction unit was collected. Based on the multi-dimensional operating data and the initial temperature setpoint, control commands for adjusting the temperature of the corresponding photocatalytic reaction unit are generated according to the difference between the current internal temperature of the reactor and the initial temperature setpoint and the trend of the difference. During the execution of the control command, the operating status data of each photocatalytic reaction unit is collected synchronously after the control command is executed; Based on the operating status data of all photocatalytic reaction units, a global optimization strategy is generated, which includes updated dynamic temperature setpoint instructions and intelligent hydraulic routing instructions. The updated dynamic temperature setpoint instruction is updated to the initial temperature setpoint, and the intelligent hydraulic routing instruction is sent to the water inlet distribution valve group to adjust the water inlet distribution of each photocatalytic reaction unit. The generation of control commands for adjusting the temperature of the corresponding photocatalytic reaction unit includes: The negative deviation threshold is determined based on the catalyst minimum activation temperature, the positive deviation threshold is determined based on the catalyst tolerance limit, and a sliding time window is set for the internal temperature of the reactor. Calculate the real-time difference between the current internal temperature of the reactor and the initial temperature setpoint, and calculate the trend of the difference change according to the length of the sliding time window; When the real-time difference exceeds the negative deviation threshold and the corresponding trend of the difference change is negative, the increase in the light intensity of the ultraviolet lamp is calculated based on the real-time difference, and a corresponding light intensity increase control command is generated. The increase is proportional to the real-time difference. When the real-time difference exceeds the positive deviation threshold and the corresponding trend of the difference change is positive, the reduction of the light intensity of the ultraviolet lamp and the increase of the opening of the cooling system valve are calculated based on the real-time difference, and corresponding joint adjustment control commands are generated. The generation of the global optimization strategy includes: The system periodically receives the operating status data uploaded by all photocatalytic reaction units and analyzes it to obtain the real-time reaction temperature and instantaneous heat load of each photocatalytic reaction unit. Based on the instantaneous heat load data of all photocatalytic reaction units, the total cooling energy consumption in the next 15 minutes is predicted. With the goal of mitigating the total cooling energy consumption, the dynamic temperature setpoint is calculated and used as the updated dynamic temperature setpoint command. Based on the real-time reaction temperature, light intensity regulation, and cooling system status of each photocatalytic reaction unit, low-temperature inlet water that needs to be heated is directed to the photocatalytic reaction unit in the heating state, and high-temperature inlet water that needs to be cooled is directed to the photocatalytic reaction unit in the cooling state, generating intelligent hydraulic routing instructions.

2. The method according to claim 1, characterized in that, The process involves configuring an initial temperature setpoint for each photocatalytic reaction unit and collecting multi-dimensional operational data for each unit, specifically including: The optimal activity temperature range is determined based on the characteristics of the catalyst material, and an initial temperature setpoint is configured for each photocatalytic reaction unit within the optimal activity temperature range. The system collects the inlet flow rate and temperature of the inlet pipe, and simultaneously collects the internal temperature of the reactor in real time. The system also collects the current light intensity of the ultraviolet lamp through the power meter that is equipped with the ultraviolet lamp. The collected data, including reactor internal temperature, current UV lamp intensity, influent flow rate, and influent temperature, are packaged into multi-dimensional operational data. The multi-dimensional operating data includes the reactor internal temperature, the current light intensity of the ultraviolet lamp, the influent flow rate, and the influent temperature.

3. The method according to claim 2, characterized in that, The synchronous acquisition control command is used to collect the operating status data of each photocatalytic reaction unit after execution, including: The control command is issued to drive the light intensity adjustment module of the ultraviolet lamp and the valve adjustment of the cooling system; After executing the control command, the real-time reaction temperature and real-time inlet water temperature inside the reactor are continuously collected; The instantaneous heat load is calculated based on the inlet flow rate, real-time reaction temperature, and the difference between the real-time inlet temperature and the inlet temperature in the multi-dimensional operating data.

4. The method according to claim 3, characterized in that, The adjustment of the water inlet distribution for each photocatalytic reaction unit includes: The updated dynamic temperature setpoint command is sent to the corresponding photocatalytic reaction unit, overwriting the original initial temperature setpoint, and used as the temperature control reference for the next control cycle. The intelligent hydraulic routing command is sent to the water inlet distribution valve group to adjust the opening of the cooling system valves of each branch, thereby realizing the dynamic adjustment of the water inlet distribution of each photocatalytic reaction unit.

5. A distributed controlled photocatalytic system for large-scale industrial water treatment, characterized in that: The system includes: The data acquisition module is used to configure an initial temperature setpoint for each photocatalytic reaction unit and to collect multi-dimensional operating data for each photocatalytic reaction unit. The multi-dimensional operating data includes the internal temperature of the reactor, the current light intensity of the ultraviolet lamp, the influent flow rate, and the influent temperature. The temperature control command generation module is used to generate control commands for adjusting the temperature of the corresponding photocatalytic reaction unit based on the multi-dimensional operating data and the initial temperature setpoint, according to the difference between the current internal temperature of the reactor and the initial temperature setpoint and the trend of the difference. The operation status data synchronous acquisition module is used to synchronously acquire the operation status data of each photocatalytic reaction unit after the control command is executed during the execution of the control command. The operation status data includes real-time reaction temperature and instantaneous heat load. The global optimization strategy generation module is used to generate a global optimization strategy based on the operating status data of all photocatalytic reaction units. The global optimization strategy includes updated dynamic temperature setpoint instructions and intelligent hydraulic routing instructions. The instruction issuing module is used to update the updated dynamic temperature setpoint instruction to the initial temperature setpoint and send the intelligent hydraulic routing instruction to the water inlet distribution valve group to adjust the water inlet distribution of each photocatalytic reaction unit. The temperature control command generation module includes: The deviation threshold setting unit is used to determine the negative deviation threshold based on the minimum catalyst activation temperature, determine the positive deviation threshold based on the catalyst tolerance limit, and set a sliding time window for the internal temperature of the reactor. The trend analysis unit is used to calculate the real-time difference between the current internal temperature of the reactor and the initial temperature setpoint, and to calculate the trend of the difference change according to the length of the sliding time window. A light intensity control command generation unit is used to calculate the increase in light intensity of the ultraviolet lamp tube based on the real-time difference when the real-time difference exceeds the negative deviation threshold and the corresponding change trend of the difference is negative, and generate a corresponding light intensity increase control command, wherein the increase is proportional to the real-time difference. The joint control command generation unit is used to calculate the reduction rate of the ultraviolet lamp light intensity and the increase rate of the cooling system valve opening based on the real-time difference when the real-time difference exceeds the positive deviation threshold and the corresponding difference change trend is positive, and generate corresponding joint adjustment control commands. The global optimization strategy generation module includes: The operation status data analysis unit is used to periodically receive the operation status data uploaded by all photocatalytic reaction units and analyze it to obtain the real-time reaction temperature and instantaneous heat load of each photocatalytic reaction unit. The dynamic temperature setpoint calculation unit is used to predict the total cooling energy consumption in the next 15 minutes based on the instantaneous heat load data of all photocatalytic reaction units. With the goal of balancing the total cooling energy consumption, it calculates the dynamic temperature setpoint as the updated dynamic temperature setpoint instruction. The intelligent hydraulic routing instruction generation unit is used to generate intelligent hydraulic routing instructions based on the real-time reaction temperature, light intensity adjustment, and cooling system status of each photocatalytic reaction unit. It directs low-temperature inlet water that needs to be heated to photocatalytic reaction units that are in a heated state, and directs high-temperature inlet water that needs to be cooled to photocatalytic reaction units that are in a cooled state.

6. The system according to claim 5, characterized in that, The operation status data synchronization acquisition module includes: A control command issuing unit is used to issue the control command to drive the light intensity adjustment unit of the ultraviolet lamp tube, which is used to adjust the valve of the cooling system. The real-time temperature data acquisition unit is used to continuously acquire the real-time reaction temperature and real-time inlet water temperature inside the reactor after executing the control command. The instantaneous heat load calculation unit is used to calculate the instantaneous heat load based on the inlet water flow rate, real-time reaction temperature, and the difference between the real-time inlet water temperature and the inlet water temperature in the multi-dimensional operating data.

Images