Energy-saving control method for energy storage condensation and multi-stage adsorption VOCs system

Abstract

The application discloses an energy-saving control method for an energy storage condensation and multistage adsorption VOCs system, and relates to the technical field of energy saving and environmental protection. The method comprises the following steps: obtaining flow channel pressure data through a pressure transmitter installed at multiple points of a condenser tube bundle, calculating non-condensable gas partial pressure distribution, and adjusting a cold energy flow guide valve to realize spatial cold energy redistribution; combining variable frequency compressor shaft power to calculate heat exchange load change rate in real time, and performing nonlinear coupling adjustment on variable frequency frequency; online calibrating interface thermal resistance based on condensate precipitation rate and heat exchange temperature difference, and optimizing fluid dynamics characteristics through an air inlet adjusting valve. The system is linked to monitor adsorption bed layer pressure difference gradient and shell micro-vibration characteristics, dynamically corrects desorption flow rate, diagnoses working conditions by using motor current harmonics, and realizes global energy distribution of the system by combining a PLC multi-target optimization algorithm. The application solves problems of energy efficiency lag, heat exchange efficiency attenuation and low structural reliability of a traditional system, and realizes adaptive operation of a VOCs treatment system under complex dynamic working conditions.

Description

Technical Field

[0001] This invention relates to the field of energy-saving and environmental protection control technology, specifically to an energy-saving control method for an energy storage condensation and multi-stage adsorption VOCs system. Background Technology

[0002] Volatile organic compounds (VOCs) emitted during industrial production processes, such as petrochemicals, fine chemicals, coatings, and pharmaceuticals, not only cause severe ozone and particulate matter pollution in the atmosphere, but also often fail to effectively recover the high-value solvent resources they contain. Currently, the industry widely adopts a process combining energy storage condensation and multi-stage adsorption for treatment. This technology achieves preliminary recovery of high-concentration organic compounds through low-temperature condensation, and is supplemented by multi-stage adsorption for deep purification of residual components, offering significant advantages in terms of treatment efficiency and applicability.

[0003] However, existing treatment systems generally suffer from crude control methods and simplistic response mechanisms in practical industrial applications. Traditional processes often rely on simple PLC interlocking control based on time sequence or fixed pressure thresholds, making it difficult to respond in real time to complex dynamic fluctuations in the composition, flow rate, and concentration of exhaust gas. When handling highly variable operating conditions, the system is prone to overshoot or lag, leading not only to low compressor energy utilization but also to kinetic degradation of the condenser heat exchange surface due to the accumulation of non-condensable gases or severe liquid film insulation effects, resulting in a significant decrease in heat exchange efficiency.

[0004] Furthermore, the reliability of adsorption bed operation and the stability of system switching are also bottlenecks that urgently need to be overcome. Existing systems lack real-time monitoring of the physical states of the adsorption bed, such as saturation distribution and skeleton stress. Uneven flow fields can easily lead to premature adsorbent failure. Simultaneously, frequent valve switching is often accompanied by severe pipeline pressure shocks, which not only increase mechanical losses but also cause fluctuations in overall energy efficiency. Therefore, how to move away from coarse-grained control relying on simple logic thresholds and achieve energy optimization under multiple objectives through refined intervention and dynamic synergistic control of the physical mechanisms of the entire condensation and adsorption process has become a core technical challenge in the field of environmental protection and energy conservation control. Summary of the Invention

[0005] This invention aims to provide an energy-saving control method for a VOCs system with energy storage condensation and multi-stage adsorption. By constructing a closed-loop collaborative control system based on multi-point pressure sensing, dynamic compensation for phase change thermal resistance, valve nonlinear damping control, and multi-objective optimization, it solves the technical problems of energy efficiency lag, heat exchange efficiency decay, and insufficient equipment operation safety of existing VOCs treatment systems under complex operating conditions.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows: An energy-saving control method for a VOCs system involving energy storage condensation and multi-stage adsorption includes: Step S1: Obtain the total pressure distribution data of the flow channel by installing pressure transmitters at multiple points in the condenser tube bundle, and calculate the partial pressure distribution of non-condensable gases in each region based on the saturated steam pressure parameters under the current operating conditions. Step S2: Based on the partial pressure distribution of the non-condensable gas, adjust the action of the cooling capacity diversion valve to achieve precise redistribution of cooling capacity in the spatial dimension of the condenser; Step S3: Using the temperature sensor installed on the condenser tube wall, combined with the supply and return temperature of the refrigerant in the energy storage device, the refrigerant flow rate, liquid level and energy storage status data, the heat exchange load change rate is calculated and obtained in real time, and the refrigerant release amount, refrigerant circulation pump speed, cold energy diversion ratio and energy replenishment start and stop logic of the energy storage device are nonlinearly coupled and adjusted. Step S4: Monitor the condensate precipitation rate and heat exchange temperature difference in real time, deduce the characteristic value of interface thermal resistance, and change the fluid dynamic characteristics of the gas-liquid contact surface by adjusting the angle of the inlet regulating valve to achieve online calibration and closed-loop self-optimization of the heat transfer coefficient.

[0007] Preferably, in step S2, when the partial pressure of non-condensable gas in a specific flow channel region exceeds the upper limit of the threshold, a cooling medium flow rate compensation action based on fuzzy logic is performed, and the coolant distribution ratio is changed by PID adjustment according to the pressure gradient ratio between each flow channel.

[0008] Preferably, the online calibration of interface thermal resistance in step S4 specifically includes: constructing a dynamic compensation equation for phase change liquid film thermal resistance based on the condensate precipitation rate and the temperature difference fluctuation characteristics of the heat exchange tube; and realizing secondary feedback correction of the refrigerant circulation pump speed by real-time correction of the liquid film thermal conductivity parameter in the compensation equation.

[0009] Preferably, the nonlinear coupling adjustment in step S3 specifically includes: establishing a dynamic correlation matrix between the refrigerant outlet temperature, refrigerant return temperature, stored energy, refrigerant circulation flow rate, condensing load and VOCs operating conditions of the energy storage device; predicting in advance the disturbance demand of the condenser on the intensity of cold energy release; and achieving real-time matching between the energy release power of the energy storage device and the VOCs treatment load by correcting the refrigerant circulation pump frequency, refrigerant release valve opening, cold energy diversion valve allocation ratio and energy replenishment equipment start / stop threshold.

[0010] Preferably, it also includes smooth control of the valve switching process. When switching multiple gas path valves, nonlinear damping control of multi-stage valve action is implemented according to a preset delay step and combined with gas path damping adjustment, so that the rate of change of pipeline airflow pressure is maintained below the peak value of the system shock wave.

[0011] Preferably, during the valve switching process, the rising edge slope and duration of the current change waveform are extracted by real-time detection of the drive current waveform characteristics of the actuator motor, and the motor torque output is dynamically adjusted by comparing it with the valve sealing pressure reference curve.

[0012] Preferably, it also includes linkage control for the adsorption unit, which establishes a bed saturation prediction logic by monitoring the micro pressure difference at the inlet and outlet of the adsorption bed, and automatically starts the adsorption tower desorption switching process when the pressure difference gradient reaches the preset regeneration trigger threshold.

[0013] Preferably, during the desorption switching process, the stress state of the adsorption bed skeleton is inferred by monitoring the external micro-vibration characteristics of the adsorption tower shell and the inlet and outlet pressure disturbance frequency, and the flow rate setting value for the desorption switching is corrected according to the stress state.

[0014] Preferably, the method also includes performing operating condition diagnosis on the variable frequency compressor, extracting specific harmonic components by performing a fast Fourier transform on the motor stator current signal, and correlating and comparing the harmonic ratio with the operating load torque to diagnose whether there is resonance or load mismatch in the condensing system.

[0015] Preferably, the VOCs system is monitored globally by a PLC, and the partial pressure of non-condensable gases, the characteristic value of interfacial thermal resistance, and the physical state parameters of the bed are compared with preset thresholds in a closed loop. Based on the ambient temperature and the frequency of VOCs intake load fluctuations, multi-objective optimization calculations are performed to dynamically adjust the energy distribution weights of the condensation cycle and the adsorption cycle.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention overcomes the limitations of traditional black-box operation of condensers, achieving microscopic and precise intervention in the heat exchange process. By deploying a high-density pressure sensor array to acquire the total pressure distribution in the flow channel, and utilizing fuzzy logic and a kinetic model to precisely adjust the cooling capacity guiding valve, the heat exchange dead zone caused by the retention of non-condensable gases is effectively eliminated, significantly improving the latent heat release efficiency of the condenser. Simultaneously, by constructing a dynamic compensation equation for the phase change liquid film thermal resistance and calibrating the heat transfer coefficient online, the thermal resistance effect caused by the thickening of the condensate film is actively offset, ensuring high efficiency and stability of heat exchange performance during long-term operation.

[0017] This invention significantly optimizes system energy efficiency and mechanical lifespan through nonlinear dynamic coupling and smooth control technology. By using the dynamic correlation matrix to predict condensing pressure disturbances, the variable frequency compressor achieves millisecond-level real-time power tracking of VOCs load, completely avoiding ineffective energy consumption fluctuations caused by lag response. Furthermore, for the valve switching process, nonlinear damping control based on motor current characteristics and torque closed-loop diagnostics are employed to suppress the pipeline airflow pressure fluctuation rate below the shock wave peak value. This not only reduces mechanical structural damage but also achieves smooth system-level switching, significantly extending the service life of critical components.

[0018] This invention represents a significant leap from individual control to global intelligent coordination. By introducing adsorption bed skeleton state monitoring and shell modal sensing, the system can proactively identify structural failure risks and adaptively adjust the desorption flow rate, achieving intelligent control in the safety dimension. Combining motor harmonic condition diagnosis and a Pareto-optimal multi-objective optimization algorithm, the system can dynamically allocate the energy consumption weights of the condensation cycle and adsorption cycle in real time according to ambient temperature changes and exhaust gas load, ensuring that the entire system always operates at the optimal energy efficiency point throughout the entire operating cycle. The overall energy efficiency ratio (EER) is significantly better than that of traditional timed interlocking control schemes. Attached Figure Description

[0019] Figure 1 A flowchart of an energy-saving control method for an energy storage condensation and multi-stage adsorption VOCs system; Figure 2 This is a graph showing the evolution of pressure drop gradient and saturation in the adsorption bed of this invention. Figure 3 This is a comparison chart of the energy efficiency ratios of the dynamic coupling control scheme of this invention and the traditional timed interlocking control scheme. Detailed Implementation

[0020] The following description is intended to disclose the invention and enable those skilled in the art to implement it. The preferred embodiments described below are merely examples, and other obvious variations will occur to those skilled in the art.

[0021] Reference Figure 1 As shown, an energy-saving control method for a VOCs system using energy storage condensation and multi-stage adsorption includes: Step S1: Obtain the total pressure distribution data of the flow channel by installing pressure transmitters at multiple points in the condenser tube bundle, and calculate the partial pressure distribution of non-condensable gases in each region based on the saturated steam pressure parameters under the current operating conditions. Step S2: Based on the partial pressure distribution of the non-condensable gas, adjust the action of the cooling capacity diversion valve to achieve precise redistribution of cooling capacity in the spatial dimension of the condenser; Step S3: Using the temperature sensor installed on the condenser tube wall, combined with the supply and return temperature of the refrigerant in the energy storage device, the refrigerant flow rate, liquid level and energy storage status data, the heat exchange load change rate is calculated and obtained in real time, and the refrigerant release amount, refrigerant circulation pump speed, cold energy diversion ratio and energy replenishment start and stop logic of the energy storage device are nonlinearly coupled and adjusted. Step S4: Monitor the condensate precipitation rate and heat exchange temperature difference in real time, deduce the characteristic value of interface thermal resistance, and change the fluid dynamic characteristics of the gas-liquid contact surface by adjusting the angle of the inlet regulating valve to achieve online calibration and closed-loop self-optimization of the heat transfer coefficient.

[0022] It should be noted that the control method of this invention is based on a specific spatial three-dimensional matrix hardware design. Each functional unit is physically presented as a closed-loop array of condensation, adsorption, power, and monitoring, as follows: A high-density sensor matrix is ​​arranged within the main cavity of the condenser, and its tube bundle structure adopts a shunt design, dividing the tube bundle space into several logical regions. A pressure transmitter is installed at the boundary between the windward and leeward sides of each logical region, connected to a PLC controller via a high-frequency signal bus. The temperature sensors are symmetrically distributed radially and axially along the heat exchange tube bundle, embedded inside the condenser tube wall. This array-like spatial distribution allows the system to map the phase change temperature field distribution within the entire condensation space in real time using temperature data from discrete sampling points through Lagrange interpolation calculations.

[0023] Both the cooling capacity diversion valve and the intake regulating valve employ electro-pneumatic proportional servo control technology. The diversion valve actuator integrates a high-precision rotary encoder for real-time recording of the valve disc's angular displacement. An electromagnetic proportional throttle valve is connected in series in the pneumatic control circuit, and this throttle valve is directly connected to the PLC's nonlinear damping control algorithm. In terms of piping connections, the valve actuator is installed close to the condenser inlet flange and equipped with a vibration-damping support to reduce the impact of structural resonance caused by pressure waves during switching on the actuator's sealing performance.

[0024] The adsorption unit consists of multiple sets of adsorption towers connected in parallel, each filled with granular adsorbent material. Micro-differential pressure sensors, accurate to below 10 Pa, are installed at the bed inlet and outlet to capture extremely subtle changes in flow resistance. Piezoelectric vibration sensors are evenly distributed on the middle of the outer wall of the adsorption tower and on the supporting base. These piezoelectric sensors are connected to a data acquisition card via shielded cables, with a sampling frequency of at least 10 kHz to ensure accurate capture of the high-frequency micro-vibration characteristics of the bed structure under high-speed airflow penetration.

[0025] As the core energy supply and control component of the condensing unit, the energy storage device internally includes at least a refrigerant storage unit, a heat transfer medium storage unit, a refrigerant circulation pump, a heat transfer medium circulation pump, a supplementary cooling / heat transfer interface, and corresponding temperature, pressure, liquid level, and flow rate detection elements. Before system startup, the energy storage device pre-stores enough refrigerant and heat transfer medium to meet the condensing and defrosting requirements. During system operation, it automatically adjusts the refrigerant release intensity, refrigerant circulation volume, and refrigerant / heat transfer medium switching state based on the condenser heat exchange load, refrigerant supply and return temperature difference, and refrigerant tank level changes, thereby continuously and stably providing cooling or heating to the condensing unit.

[0026] It should be noted that the refrigeration unit, ice machine, or compressor serves only as supplementary energy equipment for the energy storage device. It is used to supplement cooling or energy when the refrigerant temperature or stored energy in the energy storage device falls below a set range. Its start-up and shutdown are interlocked and controlled by the temperature, liquid level, and energy storage status of the energy storage device, and it is not the primary control object directly following VOCs load fluctuations during the condensation process. Therefore, the dynamic adjustment of the condensing unit is achieved primarily through the energy release capacity, refrigerant circulation capacity, and cold / heat refrigerant switching capacity of the energy storage device.

[0027] The PLC global monitoring unit, serving as the core computing platform of the system, exchanges data in real time with all the aforementioned sensor arrays, actuators, and frequency converter control interfaces. The global monitoring unit embeds a multi-tasking real-time operating system (RTOS), supporting the concurrent operation of condensation logic, adsorption logic, and global optimization logic. Before entering the calculation module, all sensor data undergoes noise reduction processing using a pre-processing filter to ensure that the multi-objective optimization algorithm dynamically outputs energy distribution control quantities for the condensation and adsorption cycles based on highly accurate input parameters. The main output target of the condensation logic is the energy storage device, including the refrigerant circulation pump frequency, refrigerant release valve opening, cold air diversion valve opening, hot air defrost branch switching status, and the start / stop status of the supplemental cooling / heating equipment. The compressor or refrigeration unit only intermittently supplements energy based on the energy storage status of the energy storage device and does not participate in the direct control of the condensation load.

[0028] The input and output relationships of each core control logic in this system are defined in the table below: Table 1 Inputs and Outputs of Each Control Logic Logic

[0029] In step S2, when the partial pressure of non-condensable gas in a specific flow channel region exceeds the upper limit of the threshold, a cooling medium flow rate compensation action based on fuzzy logic is performed. According to the pressure gradient ratio between each flow channel, the coolant distribution ratio is changed by PID adjustment.

[0030] The online calibration of interface thermal resistance in step S4 specifically includes: constructing a dynamic compensation equation for phase change liquid film thermal resistance based on the condensate precipitation rate and the temperature difference fluctuation characteristics of the heat exchange tube; and realizing secondary feedback correction of the refrigerant circulation pump speed by real-time correction of the liquid film thermal conductivity parameter in the compensation equation.

[0031] The nonlinear coupling adjustment in step S3 specifically includes: establishing a dynamic correlation matrix between the refrigerant outlet temperature, refrigerant return temperature, stored energy, refrigerant circulation flow rate, condensing load and VOCs operating conditions of the energy storage device; predicting in advance the disturbance demand of the condenser on the intensity of cold energy release; and achieving real-time matching between the energy release power of the energy storage device and the VOCs treatment load by correcting the refrigerant circulation pump frequency, refrigerant release valve opening, cold energy diversion valve allocation ratio and energy replenishment equipment start / stop threshold.

[0032] It should be noted that the condensation dead zone flow compensation control addresses the problem of heat transfer blind zones caused by the localized accumulation of non-condensable gases (such as N2 and O2) in the condenser. When the partial pressure of non-condensable gases in a specific flow channel region exceeds a threshold, this invention employs a fuzzy logic controller (FLC) to compensate for the cooling medium flow rate. The input is the local non-condensable gas partial pressure offset within the flow channel. and the rate of change of the mean pressure in this region. By setting fuzzy control rules that compensate for large deviations with large flow rates and smooth corrections for small deviations, a Gaussian distributed membership function is used to map the input values ​​to five levels: negative large (NB), negative small (NS), zero (ZO), positive small (PS), and positive large (PB). After defuzzification, the weighting coefficients of the PID controller are generated, thereby changing the coolant distribution ratio. This regulation not only corrects localized heat transfer but also avoids backflow interference caused by multiple parallel flow channels.

[0033] To address the increased thermal resistance resulting from the thickening of the condensate film over time, this invention implements an active compensation logic that constructs a nonlinear dynamic compensation equation based on thermodynamic evolution: In the formula, For total thermal resistance, Due to the inherent thermal resistance of the pipe wall, For real-time monitoring of condensate precipitation rate, For runtime, Where A is the liquid film thickness, and B, C are calibration coefficients. is the thermal conductivity of the liquid film.

[0034] The heat transfer coefficient was obtained online using the least squares method. The system can accurately identify the thickness of the liquid film. The growth trend. When the actual temperature difference of the heat exchanger tube wall deviates from the calculated value, the output of this model is used as the refrigerant pump speed. Input weights: This secondary feedback enables real-time optimization of the refrigerant forced circulation intensity, preventing the liquid film from crossing the critical thermal resistance point.

[0035] To achieve instantaneous linkage between the cooling capacity release of an accumulator or energy storage device and the processing load under instantaneous load fluctuations in VOCs exhaust gas, this invention constructs a coupling mapping matrix between the refrigerant supply and return temperature difference, refrigerant flow rate, stored energy, condensation load, and refrigerant driving signal of the energy storage device. In the formula, The system dynamic gain matrix characterizing the thermophysical properties of the working fluid. This is a dynamic advance compensation operator based on a predictive operator. The matrix model decouples the condensing load shock caused by sudden changes in VOCs concentration or flow rate into refrigerant release valve opening adjustment signals, refrigerant circulation pump frequency adjustment signals, and cold energy diversion valve distribution signals by calculating the derivative term of the VOCs intake load change rate. This enables the energy storage device to respond proactively to condensing load disturbances. Therefore, when there are significant fluctuations in VOCs load, the system prioritizes rapid compensation by releasing stored cold energy from the energy storage device, rather than relying directly on real-time adjustments based on compressor frequency changes, thus ensuring a stable temperature field and cold energy distribution from the condenser inlet to the outlet.

[0036] Table 2 Comparison of Key System Performance Improvements

[0037] It also includes smooth control of the valve switching process. When switching multiple gas path valves, nonlinear damping control of multi-stage valve action is implemented according to the preset delay step and combined with gas path damping adjustment, so that the rate of change of pipeline airflow pressure is kept below the peak value of the system shock wave.

[0038] During the valve switching process, the rising edge slope and duration of the current change waveform are extracted by real-time detection of the drive current waveform characteristics of the actuator motor, and the motor torque output is dynamically adjusted by comparing it with the valve sealing pressure reference curve.

[0039] It should be noted that the multi-stage valve nonlinear damping control strategy is as follows: To eliminate the water hammer effect caused by the pressure pulse generated during valve opening, this invention introduces a switching scheme based on time-series damping. A delay ladder model is established, and the valve action sequence delay time sequence is defined. The sequence is non-linearly increasing and satisfies: In the formula, The base delay time is given by i, where i is the valve number, k is the air path damping coefficient, and C is the system response compensation term.

[0040] The airflow buffering mechanism adjusts the exhaust throttling cross-sectional area of ​​the pneumatic circuit via an electromagnetic proportional valve, thereby reducing the rate of fluid pressure fluctuation within the pipe. Keep the system pressure change rate within the target range to ensure it meets the following requirements: In the formula, It is the shock wave reduction factor, which aims to suppress the rate of change of airflow pressure to below the system's shock wave allowable threshold.

[0041] Dynamic sensing of the sealing state based on motor current characteristics, corresponding to current waveform detection, and closed-loop health assessment of the mechanical state of the sealing pair are achieved by analyzing the current characteristics of the valve actuator motor; feature parameter extraction involves detecting the motor current signal I(t) and extracting the rising edge slope of the current abrupt change waveform at the end of the drive stroke. With duration Construct a mapping equation between valve torque M and current characteristic value: In the formula, For standard sealing torque, and This serves as a reference value for sudden current changes in the valve under standard conditions. This is the feedback gain coefficient.

[0042] By monitoring By measuring the deviation, the system can identify whether the valve has worn sealing surfaces, stuck foreign objects, or an overly tight packing gland, and automatically correct the driving torque, thus avoiding uneven mechanical force or seal failure caused by traditional timed switching.

[0043] Table 3. Key Indicators for Valve Switching

[0044] It also includes linkage control for the adsorption unit. By monitoring the micro-pressure difference at the inlet and outlet of the adsorption bed, a logic for calculating the bed saturation is established. When the pressure difference gradient reaches the preset regeneration trigger threshold, the adsorption tower desorption switching process is automatically started.

[0045] During the desorption switching process, the stress state of the adsorption bed skeleton is inferred by monitoring the external micro-vibration characteristics of the adsorption tower shell and the frequency of pressure disturbance at the inlet and outlet, and the flow rate setting value for the desorption switching is corrected according to the stress state.

[0046] It should be noted that traditional adsorption switching is mostly based on fixed-time triggering. This invention achieves dynamic triggering based on the actual saturation of the adsorption bed by establishing a physical model online. The saturation deduction logic uses an inlet and outlet micro-pressure difference sensor array to obtain the airflow resistance coefficient inside the adsorption bed. Adsorption saturation was established based on a variant of the Ergun equation. With bed pressure drop Functional relationship: In the formula, L is the bed thickness. The diameter of the adsorbent particles is [missing information]. For airflow viscosity, Let be the gas density, and v be the flow velocity. Porosity increases with adsorbate filling. Dynamic reduction leads to a decrease in drag coefficient A characteristic slope change occurs. The system monitors the derivative of the pressure drop gradient in real time. When the gradient value deviates from the quasi-steady-state value When the concentration exceeds 15%, an adsorption saturation warning is triggered.

[0047] Combination Figure 2 As shown in the figure, this figure further reveals the dynamic early warning mechanism of the evolution of the pressure drop gradient and saturation of the adsorption bed. Figure 2 The horizontal axis represents the continuous operating time of the system, and the vertical axis represents the pressure drop gradient. The specific physical evolution of this early warning mechanism includes the following three stages: During the normal adsorption phase (Stage 1) of the system operation, the adsorbent has sufficient pores, and the actual pressure drop gradient curve (solid line in the figure) basically coincides with the quasi-steady-state baseline, showing a stable linear increase. This indicates that the system's airflow penetration resistance is in a normal state and the system is operating stably. As the operating time progresses and the system enters the nonlinear deviation stage (Stage 2), a large amount of VOCs molecules in the exhaust gas accumulate and fill the bed, resulting in a decrease in the effective porosity of the bed. As the pressure decreases dynamically, the airflow drag coefficient increases sharply. The actual pressure drop gradient curve begins to rise rapidly, exhibiting a significant nonlinear deviation from the quasi-steady-state baseline, indicating that the bed is about to reach saturation. When the actual pressure drop gradient curve continues to rise and touches the set warning trigger threshold, i.e., when it deviates from the quasi-steady-state value by more than 15% (the horizontal dotted line), the system enters the ecological restoration warning stage (Stage 3). At this time, the global monitoring unit accurately captures the saturation critical point and automatically triggers and starts the desorption-regeneration switching process of the adsorption tower. This invention introduces this dynamic triggering mechanism based on state evolution, replacing the traditional rigid switching with fixed time settings. While maximizing the utilization rate of effective adsorption capacity, it effectively eliminates the risk of VOCs penetration emissions due to oversaturation.

[0048] Based on micro-vibration frequency spectrum analysis, the stress state of the bed frame is perceived, and corresponding desorption correction is implemented: During desorption, high-temperature gas flow and vacuum negative pressure may cause instability of the bed structure. This invention introduces shell modal analysis to implement active safety intervention; structural state criterion: the power spectral density (PSD) of the shell micro-vibration is obtained through a piezoelectric sensor installed outside the adsorption tower shell. The natural frequencies of the bed frame are extracted. offset : like Exceeding the safety threshold This indicates a decrease in the support capacity of the skeleton or a slight collapse, and the system is judged to be in a structural risk state. Therefore, a desorption velocity correction factor is introduced. Perform closed-loop flow rate correction: When the structural vibration is detected to be intensified, the correction factor automatically reduces the desorption flow velocity to prevent airflow-induced vibration caused by high flow velocity and protect the integrity of the bed support skeleton.

[0049] Table 4 Key Indicators for Adsorption Tower Operation Safety and Efficiency

[0050] It also includes operating condition diagnosis of energy storage devices and refrigerant circulation drive units. By performing fast Fourier transform on the stator current signals of refrigerant circulation pump motor, refrigerant release valve actuator motor or energy replenishment equipment motor, the subharmonic components are extracted, and the harmonic ratio is correlated and compared with the operating load torque to diagnose whether there is pump and valve resonance, flow blockage, load mismatch or abnormal operating condition of energy replenishment equipment in the refrigerant circulation system.

[0051] The VOCs system is monitored globally by a PLC. The partial pressure of non-condensable gases, the characteristic value of interfacial thermal resistance, and the physical state parameters of the bed are compared with preset thresholds in a closed loop. Based on the ambient temperature and the frequency of VOCs intake load fluctuations, multi-objective optimization calculations are performed to dynamically adjust the energy distribution weights of the condensation cycle and the adsorption cycle.

[0052] It should be noted that, in order to achieve high-precision operational condition diagnosis of the energy storage device and the refrigerant circulation system, this invention uses the refrigerant circulation pump motor, the refrigerant release valve actuator motor, and the energy replenishment equipment motor as sensing sources of vibration and load changes, and reveals hidden faults in the condensing energy supply system through signal processing.

[0053] Perform a Discrete Fourier Transform (DFT) on the stator current I(t) of the aforementioned drive motor to obtain the current spectrum sequence. Extract the subharmonic components (typically the 5th and 7th harmonics) related to the characteristic frequency of the load torque, and construct the harmonic distortion rate. With operating load Association Model : In the formula, Let J be the fundamental current and J be the moment of inertia of the condensation system. ω is the angular frequency.

[0054] Diagnostic logic: When Exceeding the set resonance criterion threshold When the refrigerant circulation pump or refrigerant pipeline resonance warning is triggered, and when a characteristic deviation occurs and is accompanied by abnormal supply and return temperature difference, abnormal refrigerant flow or abnormal energy storage decrease, it is determined that there is a mismatch between the energy storage device's energy release capacity and the condensing load. The system automatically adjusts the refrigerant circulation pump frequency, refrigerant release valve opening degree and energy replenishment equipment start and stop threshold to avoid the resonance point and restore a stable energy supply state.

[0055] This invention uses a PLC to perform global optimization calculations to dynamically offset the energy efficiency ratio (EER) of the condensation cycle and the adsorption cycle (low energy consumption, purification guarantee) centered on the accumulator or energy storage device.

[0056] A multi-objective optimization model is defined, with the global energy consumption objective function J defined as follows: Constraints: Emission concentration And cyclic energy distribution ; In the formula, For ambient temperature, This refers to the frequency of VOCs intake load fluctuation.

[0057] Optimization mechanism: The PLC adopts a Pareto optimal strategy, automatically increasing the power supply when the ambient temperature rises, causing a decrease in condensing energy efficiency. (Adsorption cycle weight) Based on the real-time energy storage of the energy storage device, the temperature difference between refrigerant supply and return, and the liquid level of the refrigerant tank, the refrigerant release intensity, the frequency of the refrigerant circulation pump, and the start-stop interval of the energy replenishment equipment are dynamically adjusted to ensure that the energy storage device always participates in the global energy distribution as the main control object on the condenser side, and to ensure the optimal global energy efficiency of the system under environmental temperature changes and exhaust gas fluctuations.

[0058] Table 5 Comparison of Fault Diagnosis and Global Optimization Logic

[0059] This invention is not only applicable to steady-state operating conditions, but also enables automatic protection and adaptive adjustment when facing extreme fluctuations common in industrial settings, through preset robust control logic. When the ambient temperature is below a set threshold, such as -10°C, the system automatically identifies the potential risk of excess cooling capacity in the condenser tube bundle. The PLC limits the refrigerant flow by locking the cooling capacity diversion valve logic and dynamically adjusts the refrigerant release ratio, refrigerant recirculation mixing ratio, and refrigerant circulation pump frequency of the energy storage device based on the tube wall temperature feedback from the temperature sensor. If necessary, it reduces or suspends the supply of cooling equipment to the energy storage device to maintain the exhaust temperature above the dew point and prevent localized icing or freezing cracking of the condenser.

[0060] When the VOCs intake concentration instantly exceeds the standard due to a sudden solvent leak, the system enters overload treatment mode. The PLC immediately increases the opening of the refrigerant release valve of the energy storage device and the operating frequency of the refrigerant circulation pump to the preset safety limit, and prioritizes the use of the low-temperature refrigerant stored in the energy storage device to release cooling capacity to the condenser. At the same time, it automatically switches the adsorption tower to parallel adsorption mode to increase the overall processing capacity of the system. If the refrigerant temperature or stored energy of the energy storage device is close to the lower limit, the system interlocks and starts the ice machine or other supplementary cooling equipment to supplement the energy storage device. If the pressure sensor detects an abnormal increase in the total intake pressure, the system activates the bypass pressure relief logic to divert some of the high-concentration waste gas to the auxiliary buffer tank, which is then released smoothly after the treatment load decreases, preventing the system from triggering interlock shutdown due to overload.

[0061] When an unexpected power failure is detected, the preset automatic pressure relief valve opens mechanically via the energy storage device, quickly emptying the residual high-pressure refrigerant in the pipeline. This prevents damage to the energy storage device, refrigerant circulation pump, and refrigerant pipeline due to abnormal pressure accumulation during shutdown. After power is restored, the RTOS embedded in the monitoring platform automatically enters a tiered restart logic: first, it performs a self-check on the liquid level, temperature, pressure of the energy storage device, and the status of the refrigerant circulation pump. After confirming that the signals from each sensor have returned to normal, it starts the condensation cycle and adsorption cycle in stages. Nonlinear damping control is used to smooth the pressure pulse at the moment of restart, preventing secondary shocks caused by hard starts under load.

[0062] When a pressure sensor experiences signal drift or physical damage, the PLC performs spatial interpolation based on the data correlation of the neighboring sensor matrix to reconstruct the pressure distribution map of the missing node online, thereby maintaining the normal operation of the system even with sensor damage. Simultaneously, the faulty node is marked in real time and an alarm is sent to the maintenance terminal, ensuring online maintenance is completed without affecting governance efficiency.

[0063] This embodiment takes a system for treating VOCs waste gas (containing toluene and dichloromethane) from a petrochemical fine chemical workshop as an example. The specific implementation steps are as follows: Step 1: Flow field sensing and refined redistribution of cooling capacity in the condensing unit After system startup, the pressure transmitter matrix installed at the inlet, middle section, and outlet of the condenser tube bundle begins to collect total pressure data of the flow path. Based on the physical properties of the exhaust gas under the current operating conditions, the PLC calculates the partial pressure of non-condensable gases (such as nitrogen) in each tube bundle region in real time. When the partial pressure in the middle tube bundle region exceeds a preset threshold (e.g., 15 kPa), the PLC activates the fuzzy logic controller, which automatically increases the opening of the corresponding cooling capacity guide valve in that region through PID instructions, changing the flow rate ratio of the cooling medium between tube bundles, thereby eliminating local heat exchange dead zones and ensuring that the internal cooling capacity distribution of the condenser matches the VOCs concentration distribution.

[0064] Step 2: Online calibration of interface thermal resistance and correction of refrigerant circulation The system monitors the condensate precipitation rate (via a flow meter) and the temperature difference between the heat exchange tube walls in real time. The PLC utilizes a constructed dynamic compensation equation for the thermal resistance of the phase change liquid film to iteratively calculate the current heat transfer coefficient. If an increase in liquid film thickness leads to a decrease in heat transfer performance of more than 10%, the system automatically triggers the refrigerant circulation pump to increase its speed, using high-velocity turbulence to flush the heat exchange surface. This secondary feedback calibration mechanism ensures that the heat exchange efficiency remains above 95% of the design value during long-term operation, avoiding the periodic decline in heat exchange capacity caused by liquid film accumulation in traditional solutions.

[0065] Step 3: Nonlinear frequency conversion regulation of the compressor based on the dynamic matrix To address sudden changes in VOCs intake load (flow rate / concentration), the PLC utilizes the dynamic correlation matrix of the energy storage device to couple and calculate the refrigerant outlet temperature, refrigerant return temperature, stored energy, refrigerant circulation flow rate, condensation load, and VOCs operating conditions. When the VOCs intake load increases instantaneously by 25%, the system does not need to wait for the pressure fluctuation transmission lag. It directly predicts the cooling demand based on the load change rate and pre-corrects the refrigerant release valve opening, refrigerant circulation pump frequency, and cooling capacity diversion valve allocation ratio. This achieves real-time coupling between the energy storage device's energy release power and the processing load, smoothing out exhaust pressure fluctuations within ±0.03 MPa.

[0066] Step 4: Status monitoring and coordinated desorption of the adsorption unit After the adsorption unit enters operation, the micro-differential pressure sensor array continuously collects the micro-differential pressure gradient at the inlet and outlet of the bed. When the gradient reaches the regeneration threshold, the system initiates the desorption process. During desorption, piezoelectric sensors monitor the micro-vibration power spectral density (PSD) of the adsorption tower shell in real time. If the detected natural frequency deviation exceeds the safety benchmark value, the system determines that the bed skeleton is under high stress and immediately corrects the setpoint of the desorption gas flow, reducing the scouring intensity of the desorption gas flow and effectively preventing the risk of bed collapse.

[0067] Step 5: Smooth switching of air circuit valves and power feedback diagnosis When switching between multiple adsorption tower gas paths, the PLC employs a delayed step strategy to open multiple gas path valves. At the moment of switching, the system monitors the current waveform of the actuator motor in real time and analyzes its rising edge slope (S). If S is greater than a reference value (indicating increased sealing resistance), the system dynamically increases the motor output torque to ensure the valve seals smoothly within a very short time. Furthermore, through nonlinear damping control, the rate of change in gas pressure within the pipeline is kept below the peak value of the system shock wave.

[0068] Step Six: System Operating Condition Diagnosis and Global Energy Efficiency Closed-Loop Optimization During operation, the PLC extracts the 5th and 7th harmonic components of the current from the refrigerant circulation pump motor, the refrigerant release valve actuator motor, and the energy replenishment equipment motor using Fourier transform. It compares the harmonic distortion rate with the operating load torque to diagnose any abnormalities in refrigerant circulation, pump and valve mechanical resonance, obstructed energy release from the energy storage device, or abnormal load on the energy replenishment equipment. Finally, based on multi-objective Pareto optimization calculations, the PLC dynamically adjusts the energy allocation weights of the condensation cycle and adsorption cycle in real time according to the current ambient temperature (e.g., high summer temperatures) and the frequency of VOCs load fluctuations. The main control parameters on the condensing circulation side are the refrigerant release intensity of the energy storage device, the refrigerant circulation pump frequency, the cold / hot refrigerant switching status, and the energy replenishment start / stop threshold. Under the operating conditions of this embodiment, compared with traditional timed switching control, the overall energy efficiency ratio (EER) of this system is improved by approximately 18.5%, and the system's operational stability is significantly enhanced.

[0069] Figure 3 The figure visually demonstrates the energy efficiency ratio (EER) comparison between the dynamic coupling control scheme of this invention and the traditional timed interlocking control scheme under different VOCs load fluctuation frequencies. As shown in the figure, the system energy efficiency ratio (EER) of this invention (Pareto optimization scheme) is significantly higher than that of the benchmark scheme at low, medium, and high fluctuation frequencies. Moreover, the advantage is more obvious when the load fluctuation is more severe, which fully verifies the energy-saving effect of this invention under complex operating conditions.

[0070] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention. The scope of protection claimed by the appended claims and their equivalents is defined.

Claims

1. An energy-saving control method for a VOCs system using energy storage condensation and multi-stage adsorption, characterized in that, include: Step S1: Obtain the total pressure distribution data of the flow channel by installing pressure transmitters at multiple points in the condenser tube bundle, and calculate the partial pressure distribution of non-condensable gases in each region based on the saturated steam pressure parameters under the current operating conditions. Step S2: Based on the partial pressure distribution of the non-condensable gas, adjust the action of the cooling capacity diversion valve to achieve precise redistribution of cooling capacity in the spatial dimension of the condenser; Step S3: Using the temperature sensor installed on the condenser tube wall, combined with the supply and return temperature of the refrigerant in the energy storage device, the refrigerant flow rate, liquid level and energy storage status data, the heat exchange load change rate is calculated and obtained in real time, and the refrigerant release amount, refrigerant circulation pump speed, cold energy diversion ratio and energy replenishment start and stop logic of the energy storage device are nonlinearly coupled and adjusted. Step S4: Monitor the condensate precipitation rate and heat exchange temperature difference in real time, deduce the characteristic value of interface thermal resistance, and change the fluid dynamic characteristics of the gas-liquid contact surface by adjusting the angle of the inlet regulating valve to achieve online calibration and closed-loop self-optimization of the heat transfer coefficient.

2. The energy-saving control method for a VOCs system based on energy storage condensation and multi-stage adsorption according to claim 1, characterized in that: In step S2, when the partial pressure of non-condensable gas in a certain flow channel region exceeds the upper limit of the threshold, a cooling medium flow rate compensation action based on fuzzy logic is performed. According to the pressure gradient ratio between each flow channel, the coolant distribution ratio is changed by PID adjustment.

3. The energy-saving control method for a VOCs system based on energy storage condensation and multi-stage adsorption according to claim 1, characterized in that: The online calibration of interface thermal resistance in step S4 specifically includes: constructing a dynamic compensation equation for phase change liquid film thermal resistance based on the condensate precipitation rate and the temperature difference fluctuation characteristics of the heat exchange tube; and realizing secondary feedback correction of the refrigerant circulation pump speed by real-time correction of the liquid film thermal conductivity parameter in the compensation equation.

4. The energy-saving control method for a VOCs system with energy storage condensation and multi-stage adsorption according to claim 1, characterized in that: The nonlinear coupling adjustment in step S3 specifically includes: establishing a dynamic correlation matrix between the refrigerant outlet temperature, refrigerant return temperature, stored energy, refrigerant circulation flow rate, condensing load and VOCs operating conditions of the energy storage device; predicting in advance the disturbance demand of the condenser on the intensity of cold energy release; and achieving real-time matching between the energy release power of the energy storage device and the VOCs treatment load by correcting the refrigerant circulation pump frequency, refrigerant release valve opening, cold energy diversion valve allocation ratio and energy replenishment equipment start / stop threshold.

5. The energy-saving control method for a VOCs system with energy storage condensation and multi-stage adsorption according to claim 1, characterized in that: It also includes linkage control for the adsorption unit. By monitoring the micro-pressure difference at the inlet and outlet of the adsorption bed, a logic for calculating the bed saturation is established. When the pressure difference gradient reaches the preset regeneration trigger threshold, the adsorption tower desorption switching process is automatically started.

6. The energy-saving control method for a VOCs system with energy storage condensation and multi-stage adsorption according to claim 5, characterized in that: During the desorption switching process, the stress state of the adsorption bed skeleton is inferred by monitoring the external micro-vibration characteristics of the adsorption tower shell and the frequency of inlet and outlet pressure disturbances, and the flow rate setting value of the desorption switching is corrected according to the stress state.

7. The energy-saving control method for a VOCs system with energy storage condensation and multi-stage adsorption according to claim 1, characterized in that: It also includes smooth control of the valve switching process. When switching multiple gas path valves, nonlinear damping control of multi-stage valve action is implemented according to the preset delay step and combined with gas path damping adjustment, so that the rate of change of pipeline airflow pressure is kept below the peak value of the system shock wave.

8. The energy-saving control method for a VOCs system with energy storage condensation and multi-stage adsorption according to claim 7, characterized in that: During the valve switching process, the rising edge slope and duration of the current change waveform are extracted by real-time detection of the drive current waveform characteristics of the actuator motor, and the motor torque output is dynamically adjusted by comparing it with the valve sealing pressure reference curve.

9. The energy-saving control method for a VOCs system with energy storage condensation and multi-stage adsorption according to claim 1, characterized in that: It also includes operating condition diagnosis of variable frequency compressors. By performing a fast Fourier transform on the motor stator current signal, the subharmonic components are extracted, and the proportion of harmonics is correlated and compared with the operating load torque to diagnose whether there is resonance or load mismatch in the condensing system.

10. The energy-saving control method for a VOCs system with energy storage condensation and multi-stage adsorption according to claim 1, characterized in that: The VOCs system is monitored globally by a PLC. The partial pressure of non-condensable gases, the characteristic value of interfacial thermal resistance, and the physical state parameters of the bed are compared with preset thresholds in a closed loop. Based on the ambient temperature and the frequency of VOCs intake load fluctuations, multi-objective optimization calculations are performed to dynamically adjust the energy distribution weights of the condensation cycle and the adsorption cycle.

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