A program-scheduled compressor energy recovery optimization system

Abstract

The present invention relates to the field of chemical distillation technology, and specifically discloses a program-scheduled compressor energy recovery optimization system, including distillation equipment, a state monitoring module, an energy consumption optimization module, and a control scheduling module. This solution collects the heat generated by the compressor compressing steam, the friction heat and motor heat generated during the operation of the compressor, and provides heat for the reboiler. The compressor outlet temperature and pressure are precisely controlled by the scheduling system to ensure that the energy recovery system operates in the optimal state; according to the operating requirements and conditions of the distillation process, the optimal parameters of the system operation under different states are predicted in real time, which is applicable to various complex nonlinear problems. The PLC controller dynamically adjusts the equipment parameters in the change to improve the efficiency of computing resources, and has strong robustness.

Description

Technical Field

[0001] The invention relates to the technical field of chemical distillation, and in particular to a program-scheduled compressor energy recovery optimization system. Background Art

[0002] Self-regenerative distillation is a process in which the components of a mixed liquid are separated in a distillation tower, the low-temperature steam at the top of the tower is compressed and heated by a compressor, and the obtained high-temperature steam is reused in the reboiler to heat the liquid in the bottom of the tower. The system operation only maintains the energy balance of the distillation process through the compressor. Generally, a large amount of heat energy is generated by the compressor during the process of compressing steam, and this heat energy is usually discharged as waste heat, resulting in unnecessary energy loss and power consumption; in the traditional distillation process, the equipment parameters are set based on experience. When the environment changes, the raw material composition fluctuates, and other uncontrollable process conditions change, the equipment parameters are difficult to adjust in time, resulting in the purity of the separation being affected. Summary of the invention

[0003] In view of the above situation and to overcome the defects of the prior art, the present invention provides a program-scheduled compressor energy recovery optimization system. In view of the problem that a large amount of heat energy is generated in the process of compressing steam in general compressors, and this heat energy is usually discharged as waste heat, resulting in unnecessary energy loss and power consumption, the present solution collects the heat generated by the compressor compressing steam, the friction heat and motor heat generated during the operation of the compressor, and supplies heat to the reboiler. The compressor outlet temperature and pressure are precisely controlled through the scheduling system to ensure that the energy recovery system operates in the optimal state. In view of the problem that the equipment parameters in the traditional distillation process are set based on experience, when the environment changes, the raw material composition fluctuates and other uncontrollable process conditions change, the equipment parameters are difficult to adjust in time, resulting in the purity of the separated product being affected, the present solution predicts the optimal parameters for the system operation under different states in real time according to the operating requirements and conditions of the distillation process, solves various complex nonlinear problems generated in the distillation process, and dynamically adjusts the equipment parameters through the PLC controller to improve the system operation efficiency and has strong stability.

[0004] The present invention provides a program-scheduled compressor energy recovery optimization system, comprising a distillation device, a state monitoring module, an energy consumption optimization module, and a control scheduling module;

[0005] The distillation equipment includes a compressor, a reboiler and a distillation tower;

[0006] The state monitoring module monitors the operating parameters of the distillation equipment and sends the operating parameters to the control scheduling module and the energy consumption optimization module;

[0007] The energy consumption optimization module establishes an energy consumption model of the compressor and a heat energy recovery model of the reboiler, uses a genetic algorithm to predict the optimal parameters when the heat energy recovery is maximum, and sends the optimal parameters to the control scheduling module;

[0008] The control and scheduling module is provided with a PLC controller, which dynamically adjusts the operation of the distillation equipment based on optimal parameters according to distillation requirements.

[0009] Furthermore, the method for constructing the energy consumption model includes the following steps:

[0010] Step S1: data collection, obtaining operating parameters, including the inlet and outlet pressures of the compressor, the temperature and flow rate of the steam;

[0011] Step S2: Establish an energy consumption model to calculate the actual power consumption of the compressor. The formula used is as follows:

[0012] ;

[0013] In the formula, Indicates the actual power consumption of the compressor. is the mass flow rate of steam, is the specific heat capacity of steam, represents the temperature after compression, Indicates the temperature before compression;

[0014] Step S3: isentropic efficiency calculation, comparing the difference between the actual compression process and the ideal isentropic compression process, the formula used is as follows:

[0015] ;

[0016] In the formula, represents the isentropic efficiency, represents ideal isentropic power consumption.

[0017] Furthermore, the method for constructing the heat recovery model comprises the following steps:

[0018] Step A1: define the heat source. The sources of heat energy of the compressor include waste heat of compressed steam, friction heat, and motor heat. The heat energy is recovered and used to heat the reboiler.

[0019] Step A2: Establish a basic model for heat recovery and calculate the heat recovery of the reboiler according to the heat balance equation. The formula used is as follows:

[0020] ;

[0021] In the formula, Indicates the amount of heat recovery, represents the mass flow rate of steam received by the reboiler, represents the steam temperature received by the reboiler, Indicates the temperature of the compressed steam waste heat;

[0022] Step A3: Calculate the heat recovery efficiency using the following formula:

[0023] ;

[0024] In the formula, represents the heat recovery efficiency, Indicates the friction heat and motor heat generated by the operation of the compressor;

[0025] Step A4: Establishing a heat recovery optimization model, including the following steps:

[0026] Step A41: Objective function definition, variables include compressed steam waste heat temperature, steam mass flow rate and other operating requirements, the optimization goal is to maximize the heat recovery efficiency, the formula used is as follows:

[0027] ;

[0028] In the formula, represents the fitness function, represents the objective function, Indicates other operational requirements;

[0029] Step A42: setting variable constraints;

[0030] Step A43: Optimize variable values ​​and use genetic algorithms to predict optimal parameters. The variables when the objective function reaches the optimal value are the optimal parameters.

[0031] Furthermore, the control scheduling module uses a PLC controller to dynamically adjust the operation of the distillation equipment, specifically including the following steps:

[0032] Step T1: Initialization, use industrial standard wired connections to connect the PLC controller to the compressor, reboiler, and distillation tower respectively, and set the adjustment priority and threshold of the distillation equipment, with the compressor having the highest priority and the distillation tower having the lowest priority;

[0033] Step T2: Set the Modbus communication protocol in the PLC controller, configure the Modbus communication parameters, periodically receive the operating parameters transmitted by the status monitoring module, store the operating parameters in the buffer area of ​​the PLC controller, add delay processing logic to perform delay processing operations, add data verification logic to retransmit the lost operating parameters, and set the maximum number of retransmissions;

[0034] Step T3: Set up a fault handling procedure to determine the operating status of the distillation equipment through a preset threshold. When the operating parameters of the compressor exceed the threshold, perform fault diagnosis, and the PLC controller automatically switches to the standby compressor to maintain system operation. If the operating parameters of the reboiler are abnormal, automatically adjust the heating power to keep the operating parameters within the threshold.

[0035] Step T4: Fault handling, storing the fault type, time and handling measures in the log;

[0036] Step T5: Log management, analyze log data, identify potential problems in the operation of distillation equipment, and improve and optimize distillation equipment that often fails through data analysis.

[0037] The beneficial effects achieved by the present invention using the above scheme are as follows:

[0038] (1) In view of the problem that a large amount of heat energy is generated in the process of compressing steam in general compressors, which is usually discharged as waste heat, resulting in unnecessary energy loss and power consumption, this solution collects the heat generated by the compressor when compressing steam, the friction heat and motor heat generated during the operation of the compressor, and provides heat for the reboiler. The dispatching system accurately controls the compressor outlet temperature and pressure to ensure that the energy recovery system operates in the optimal state.

[0039] (2) In the traditional distillation process, equipment parameters are set based on experience. When the environment changes, the raw material composition fluctuates, and other uncontrollable process conditions change, the equipment parameters are difficult to adjust in time, resulting in the purity of the separated products being affected. This solution predicts the optimal parameters for system operation under different conditions in real time based on the operating requirements and conditions of the distillation process, solves various complex nonlinear problems arising in the distillation process, and dynamically adjusts the equipment parameters through the PLC controller to improve the system operation efficiency and has strong stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 A schematic diagram of a program-scheduled compressor energy recovery optimization system proposed by the present invention;

[0041] Figure 2 This is a schematic diagram of the operation of the distillation equipment.

[0042] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention. DETAILED DESCRIPTION

[0043] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments; based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0044] In the description of the present invention, it should be understood that terms such as “upper”, “lower”, “front”, “back”, “left”, “right”, “top”, “bottom”, “inside” and “outside” indicating directions or positional relationships are based on the directions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore should not be understood as limiting the present invention.

[0045] Example 1, see Figure 1 and Figure 2 , a program-scheduled compressor energy recovery optimization system provided by the present invention includes a distillation device, a state monitoring module, an energy consumption optimization module, and a control scheduling module;

[0046] The distillation equipment includes a compressor, a reboiler and a distillation tower;

[0047] The state monitoring module monitors the operating parameters of the distillation equipment, uses a temperature sensor to monitor the inlet and outlet temperatures of the compressor, a pressure sensor to monitor the inlet and outlet pressures of the compressor, a flow meter to monitor the mass flow of compressed steam, and a calorimeter to monitor the recovered thermal energy, and sends the operating parameters to the control scheduling module and the energy consumption optimization module;

[0048] The energy consumption optimization module establishes an energy consumption model of the compressor and a heat energy recovery model of the reboiler, uses a genetic algorithm to predict the optimal parameters when the heat energy recovery is maximum, and sends the optimal parameters to the control scheduling module;

[0049] The control and scheduling module is provided with a PLC controller, which dynamically adjusts the operation of the distillation equipment based on optimal parameters according to distillation requirements.

[0050] Example 2, see Figure 1 and Figure 2This embodiment is based on the above embodiment. In this embodiment, a two-component mixed liquid is separated. A plate-type distillation tower is used as a distillation tower, which contains a plate with small holes inside. The mixed liquid enters the middle of the distillation tower after preheating. The steam generated after preheating rises to the top of the distillation tower through the small holes in the plate. The mixed liquid flows to the bottom of the distillation tower by gravity. The mixed liquid collected at the bottom of the distillation tower is heated by a reboiler to generate a certain flow of steam. The steam enters the distillation tower, a part of which rises to the top of the distillation tower through the small holes on the plate and is discharged, and the other part generates pressure to make the bottom of the distillation tower The mixed liquid flows into the reboiler, and steam reflux is formed at the bottom of the distillation tower and the reboiler; after the steam at the top of the distillation tower is discharged, part of it is condensed into liquid, refluxes into the distillation tower, and flows along the tower plate to the bottom of the distillation tower again, and the other part enters the compressor, which compresses the steam to high temperature to provide a heat source for the reboiler; the upward-flowing steam and the downward-flowing liquid in the distillation tower contact on the tower plate, part of the steam condenses, and part of the liquid vaporizes, realizing heat and mass transfer between the gas and liquid phases, and finally obtaining high-purity volatile components at the top of the distillation tower and less volatile components at the bottom.

[0051] Example 3, see Figure 1 This embodiment is based on the above embodiment, and the method for constructing the energy consumption model includes the following steps:

[0052] Step S1: data collection, obtaining operating parameters, including the inlet and outlet pressures of the compressor, the temperature and flow rate of the steam;

[0053] Step S2: Establish an energy consumption model to calculate the actual power consumption of the compressor. The formula used is as follows:

[0054] ;

[0055] In the formula, Indicates the actual power consumption of the compressor. is the mass flow rate of steam, is the specific heat capacity of steam, represents the temperature after compression, Indicates the temperature before compression;

[0056] Step S3: isentropic efficiency calculation, comparing the difference between the actual compression process and the ideal isentropic compression process, the formula used is as follows:

[0057] ;

[0058] In the formula, represents the isentropic efficiency, represents ideal isentropic power consumption.

[0059] Example 4, see Figure 1This embodiment is based on the above embodiment, and the method for constructing the heat recovery model includes the following steps:

[0060] Step A1: define the heat source. The sources of heat energy of the compressor include waste heat of compressed steam, friction heat, and motor heat. The heat energy is recovered and used to heat the reboiler.

[0061] Step A2: Establish a basic model for heat recovery and calculate the heat recovery of the reboiler according to the heat balance equation. The formula used is as follows:

[0062] ;

[0063] In the formula, Indicates the amount of heat recovery, represents the mass flow rate of steam received by the reboiler, represents the steam temperature received by the reboiler, Indicates the temperature of the compressed steam waste heat;

[0064] Step A3: Calculate the heat recovery efficiency using the following formula:

[0065] ;

[0066] In the formula, represents the heat recovery efficiency, Indicates the friction heat and motor heat generated by the operation of the compressor;

[0067] Step A4: Establishing a heat recovery optimization model, including the following steps:

[0068] Step A41: Objective function definition, variables include compressed steam waste heat temperature, steam mass flow rate and other operating requirements, the optimization goal is to maximize the heat recovery efficiency, the formula used is as follows:

[0069] ;

[0070] In the formula, represents the fitness function, represents the objective function, Indicates other operational requirements;

[0071] Step A42: setting variable constraints;

[0072] Step A43: Optimize variable values ​​and use genetic algorithms to predict optimal parameters. The variables when the objective function reaches the optimal value are the optimal parameters, including the following steps:

[0073] Step A431: variable initialization, randomly generate n groups of initial values ​​of variables within the constraints as the initial population, and calculate the fitness value of each group of variables;

[0074] Step A432: Select t groups of variables with the highest fitness values ​​to enter the next generation population, select 2 groups of variables for crossover operation, and generate new offspring individuals;

[0075] Step A433: Select some offspring individuals to perform mutation operation, and randomly change the value of a variable in each group of offspring individuals within the constraints;

[0076] Step A434: The offspring individuals obtained through the selection, crossover and mutation operations are combined into a new generation population, and the fitness value of each group of variables in the new generation population is calculated;

[0077] Step A435: repeat steps A432 to A434 until the fitness value no longer increases significantly, then stop iterating and obtain the final population;

[0078] Step A436: Select the individual with the highest fitness from the final population, and its variable value is the optimal parameter.

[0079] By performing the operations described above, in view of the problem that a large amount of heat energy is generated in the process of compressing steam in general compressors, and usually this heat energy is discharged as waste heat, resulting in unnecessary energy loss and power consumption, this solution collects the heat generated by the compressor compressing steam, the friction heat and motor heat generated during the operation of the compressor, and provides heat for the reboiler. The compressor outlet temperature and pressure are precisely controlled through the scheduling system to ensure that the energy recovery system operates in the optimal state.

[0080] Example 5, see Figure 1 This embodiment is based on the above embodiment. The compressor selects a Roots steam compressor. In step A42, the temperature range of the compressed steam waste heat is 70~120℃, the mass flow rate range of the steam is 0.3kg / s~0.7kg / s, and other operating requirements include the compression ratio of the compressor, the internal pressure of the distillation tower, and the operating environment temperature.

[0081] Example 6, see Figure 1 and Figure 2 This embodiment is based on the above embodiment, and the control scheduling module uses a PLC controller to dynamically adjust the operation of the distillation equipment, specifically including the following steps:

[0082] Step T1: Initialization, use industrial standard wired connections to connect the PLC controller to the compressor, reboiler, and distillation tower respectively, and set the adjustment priority and threshold of the distillation equipment, with the compressor having the highest priority and the distillation tower having the lowest priority;

[0083] Step T2: Set the Modbus communication protocol in the PLC controller, configure the Modbus communication parameters, periodically receive the operating parameters transmitted by the status monitoring module, store the operating parameters in the buffer area of ​​the PLC controller, add delay processing logic to perform delay processing operations, add data verification logic to retransmit the lost operating parameters, and set the maximum number of retransmissions;

[0084] Step T3: Set up a fault handling procedure to determine the operating status of the distillation equipment through a preset threshold. When the operating parameters of the compressor exceed the threshold, perform fault diagnosis, and the PLC controller automatically switches to the standby compressor to maintain system operation. If the operating parameters of the reboiler are abnormal, automatically adjust the heating power to keep the operating parameters within the threshold.

[0085] Step T4: Fault handling, storing the fault type, time and handling measures in the log;

[0086] Step T5: Log management, analyze log data, identify potential problems in the operation of distillation equipment, and improve and optimize distillation equipment that often fails through data analysis.

[0087] By executing the operations, in view of the problem that the equipment parameters in the traditional distillation process are set based on experience, when the environment changes, the raw material composition fluctuates and other uncontrollable process conditions change, the equipment parameters are difficult to adjust in time, resulting in the purity of the separated product being affected, this solution predicts the optimal parameters for the system operation under different states in real time according to the operating requirements and conditions of the distillation process, solves various complex nonlinear problems generated in the distillation process, dynamically adjusts the equipment parameters through the PLC controller, improves the system operation efficiency, and has strong stability.

[0088] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0089] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

[0090] The present invention and its embodiments are described above, and such description is not restrictive. The drawings show only one embodiment of the present invention, and the actual structure is not limited thereto. In short, if ordinary technicians in the field are inspired by it, without departing from the purpose of the invention, they can design a structure and embodiment similar to the technical solution without creativity, which should belong to the protection scope of the present invention.

Claims

1. A program-scheduled compressor energy recovery optimization system, characterized in that: Including distillation equipment, status monitoring module, energy consumption optimization module, control scheduling module; The distillation equipment includes a compressor, a reboiler and a distillation tower; The state monitoring module monitors the operating parameters of the distillation equipment and sends the operating parameters to the control scheduling module and the energy consumption optimization module; The energy consumption optimization module establishes an energy consumption model of the compressor and a heat energy recovery model of the reboiler, uses a genetic algorithm to predict the optimal parameters when the heat energy recovery is maximum, and sends the optimal parameters to the control scheduling module; The control and scheduling module is provided with a PLC controller, which dynamically adjusts the operation of the distillation equipment based on the optimal parameters according to the distillation demand; The method for constructing the energy consumption model comprises the following steps: Step S1: data collection, obtaining operating parameters, including the inlet and outlet pressures of the compressor, the temperature and flow rate of the steam; Step S2: Establish an energy consumption model to calculate the actual power consumption of the compressor. The formula used is as follows: ； In the formula, Indicates the actual power consumption of the compressor. is the mass flow rate of steam, is the specific heat capacity of steam, represents the temperature after compression, Indicates the temperature before compression; Step S3: isentropic efficiency calculation, comparing the difference between the actual compression process and the ideal isentropic compression process, the formula used is as follows: ； In the formula, represents the isentropic efficiency, represents the ideal isentropic power consumption; The method for constructing the heat energy recovery model comprises the following steps: Step A1: define the heat source. The sources of heat energy of the compressor include waste heat of compressed steam, friction heat, and motor heat. The heat energy is recovered and used to heat the reboiler. Step A2: Establish a basic model for heat recovery and calculate the heat recovery of the reboiler according to the heat balance equation. The formula used is as follows: ； In the formula, Indicates the amount of heat recovery, represents the mass flow rate of steam received by the reboiler, represents the steam temperature received by the reboiler, Indicates the temperature of the compressed steam waste heat; Step A3: Calculate the heat recovery efficiency using the following formula: ； In the formula, represents the heat recovery efficiency, Indicates the friction heat and motor heat generated by the operation of the compressor; Step A4: Establishing a heat recovery optimization model, including the following steps: Step A41: Objective function definition, variables include compressed steam waste heat temperature, steam mass flow rate and other operating requirements, the optimization goal is to maximize the heat recovery efficiency, the formula used is as follows: ； In the formula, represents the fitness function, represents the objective function, Indicates other operational requirements; Step A42: setting variable constraints; Step A43: Optimize variable values ​​and use genetic algorithms to predict optimal parameters. The variables when the objective function reaches the optimal value are the optimal parameters.

2. A program-scheduled compressor energy recovery optimization system according to claim 1, characterized in that: The control scheduling module uses a PLC controller to dynamically adjust the operation of the distillation equipment, specifically including the following steps: Step T1: Initialization, use industrial standard wired connections to connect the PLC controller to the compressor, reboiler, and distillation tower respectively, and set the adjustment priority and threshold of the distillation equipment, with the compressor having the highest priority and the distillation tower having the lowest priority; Step T2: Set the Modbus communication protocol in the PLC controller, configure the Modbus communication parameters, periodically receive the operating parameters transmitted by the status monitoring module, store the operating parameters in the buffer area of ​​the PLC controller, add delay processing logic to perform delay processing operations, add data verification logic to retransmit the lost operating parameters, and set the maximum number of retransmissions; Step T3: Set up a fault handling procedure to determine the operating status of the distillation equipment through a preset threshold. When the operating parameters of the compressor exceed the threshold, perform fault diagnosis, and the PLC controller automatically switches to the standby compressor to maintain system operation. If the operating parameters of the reboiler are abnormal, automatically adjust the heating power to keep the operating parameters within the threshold. Step T4: Fault handling, storing the fault type, time and handling measures in the log; Step T5: Log management, analyze log data, identify potential problems in the operation of distillation equipment, and improve and optimize distillation equipment that often fails through data analysis.

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