CN113110356A - Intelligent optimization control equipment of low-temperature thermal system - Google Patents
Intelligent optimization control equipment of low-temperature thermal system Download PDFInfo
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Abstract
The invention provides intelligent optimization control equipment of a low-temperature thermal system, which comprises: the intelligent heat control system comprises a heat source unit, a heat trap unit and an intelligent heat control center, wherein the intelligent heat control center is used for heat transfer and heat balance between the heat source unit and the heat trap unit; the intelligent optimization control equipment comprises: the sensor units are respectively used for acquiring sensing parameters of the heat source unit, the heat sink unit and the heat intelligent control center; an edge calculation unit for performing the steps of: acquiring sensing parameters acquired by the plurality of sensor units, and quantitatively calculating heat balance and heat transfer parameters; a central optimization unit: inputting the acquired sensor parameters into a training prediction model, predicting heat exchange parameters based on the prediction model, and determining whether to adjust the control parameters of the intelligent heat regulation and control center based on the predicted heat exchange parameters and an optimization target of maximizing benefits.
Description
Technical Field
The invention relates to the field of oil refining and chemical engineering, in particular to intelligent optimization control equipment for a low-temperature thermal system.
Background
In recent years, petrochemical enterprises have conducted efficient exploration on low-temperature thermal systems based on whole plants under the framework of 'large system energy comprehensive utilization', a novel low-temperature thermal comprehensive utilization system covering multiple sets of production devices is designed and built, the energy consumption of the enterprises is effectively reduced, remarkable economic benefits are obtained, and the following problems generally exist in operation:
1) the system is huge and complex, a plurality of devices are involved, heat sources and heat traps are dispersed, part of key nodes lack measuring instruments, key operating parameters lack automatic control means, and unified management and timely control are difficult;
2) after the system runs, the system cannot adapt to extreme working condition changes, seasonal changes and changes of partial device startup and shutdown, and cannot be scheduled and adjusted in advance according to changes of working conditions, weather and the like;
3) the system operation management stays in an experience stage, a reasonable online mathematical model is lacked to provide decision support and optimization guidance for field technicians, the system operation is often deviated from an optimal point and the energy-saving effect cannot reach a design value under the limitation of a processing scheme, a processing load, a climate environment and the service level of managers;
4) in the operation process of the system, a closed loop of an optimization calculation result and a control device is lacked, the decision support and the optimization result provided by a mathematical model are difficult to ensure to be implemented, and manual adjustment not only increases the workload of field personnel, but also often causes the operation effect to be unexpected.
Therefore, how to optimally control the low-temperature thermal system is a technical problem to be solved urgently in the field.
Disclosure of Invention
It is an object of the present invention to provide an intelligent optimized control equipment of a cryogenic thermal system, thereby overcoming, at least to some extent, the above-mentioned technical problems due to the limitations and drawbacks of the related art.
According to a first aspect of the present invention, there is provided an intelligent optimization control arrangement for a cryogenic thermal system, the cryogenic thermal system comprising: the intelligent heat control system comprises a heat source unit, a heat trap unit and an intelligent heat control center, wherein the intelligent heat control center is used for heat transfer and heat balance between the heat source unit and the heat trap unit;
the intelligent optimization control equipment comprises:
the sensor units are respectively used for acquiring sensing parameters of the heat source unit, the heat sink unit and the heat intelligent control center;
an edge calculation unit for performing the steps of:
acquiring sensing parameters acquired by the plurality of sensor units;
carrying out quantitative calculation on heat balance and heat transfer parameters;
a central optimization unit for performing the steps of: inputting the acquired sensor parameters and training a prediction model;
predicting heat exchange parameters based on the prediction model;
and determining whether to adjust the control parameters of the intelligent heat regulation and control center or not based on the predicted heat exchange parameters and taking benefit maximization as an optimization target.
In some embodiments of the present application, the low temperature thermal system transfers heat through water circulation,
the sensing parameters include one or more of the following sensor parameters: the flow rate of the heating medium water, the inlet and outlet temperature of the heating medium water, the inlet and outlet pressure of the heating medium water, the process flow, the process inlet and outlet temperature, the conductivity of the heating medium water, dissolved oxygen, the pH value, the oil content and the turbidity;
the heat exchange parameters comprise one or more of the following parameters: the temperature of the heat source unit and the heat trap unit after process heat exchange and the temperature of the heat medium water after heat exchange;
the control parameters of the heat intelligent control center comprise one or more of the following control parameters: the flow rate of the heat medium water and the flow rate of the heat medium water pump entering each heat source unit and each heat sink unit.
In some embodiments of the present application, the determining whether to adjust the control parameter of the intelligent heat regulation and control center according to the predicted heat exchange parameter includes:
judging whether the predicted heat exchange parameters meet target heat exchange parameters or not;
if so, not adjusting the control parameters of the intelligent heat regulation and control center;
and if not, adjusting the control parameters of the intelligent heat regulation and control center according to the difference between the existing heat exchange parameters and the target heat exchange parameters.
In some embodiments of the present application, the prediction model is obtained based on historical sensing parameters and heat exchange parameter training, and iterative optimization training is performed based on sensing parameters acquired in real time and real-time heat exchange parameters.
In some embodiments of the present application, the predictive model is a feedforward neural network model whose hidden layer node transfer functions include hyperbolic tangent sigmoid functions and whose output layer node transfer functions include linear functions.
In some embodiments of the present application, the central optimization unit, in communication with the edge calculation unit,
the central optimization unit is used for executing:
training the prediction model;
optimizing control parameters of the heat intelligent control center;
and storing the sensing parameters, the heat exchange parameters and the control parameters.
In some embodiments of the present application, the central optimization unit is further configured to perform the following steps:
carrying out visual processing on the sensing parameters acquired by the plurality of sensor units and the control parameters of the intelligent heat regulation and control center;
and displaying the visually processed sensing parameters acquired by the plurality of sensor units and the control parameters of the intelligent heat regulation and control center in a control device page of an intelligent optimization control equipment client or a browser.
In some embodiments of the present application, the heat intelligent regulation center includes:
a heat source water inlet end and a heat source water outlet end which are connected to the heat source unit;
the hot trap water inlet end and the hot trap water outlet end are connected to the hot trap unit;
the water feeding and collecting unit is connected between the heat source water removing end and the heat sink water inlet end;
the backwater water collecting unit is connected between the hot trap water removing end and the heat source water inlet end;
and the water replenishing unit is connected between the backwater water collecting unit and the heat source water removing end.
In some embodiments of the present application, the edge calculation unit also inputs environmental parameters into the predictive model.
In some embodiments of the present application, the sensor unit comprises one or more wireless sensors.
The intelligent control device of the low-temperature thermal system provided by the invention has the following advantages:
the intelligent optimization and control equipment of the low-temperature thermal system is based on a wireless data acquisition system and communication transmission, a big data modeling algorithm and a heuristic optimization algorithm are used as cores, and edge computing equipment, a big data deep learning algorithm and an automatic control device are integrated, so that the functions of real-time data acquisition monitoring, on-line simulation of the low-temperature thermal system, optimization calculation of key operating parameters, automatic control of the operating parameters and the like are realized, and the closed-loop real-time optimization control of the low-temperature thermal system is ensured.
For a better understanding of the nature and technical content of the present application, reference should be made to the following detailed description and accompanying drawings, which are included to illustrate and not limit the scope of the present application.
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The above and other features and advantages of the present application will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings.
FIG. 1 is a schematic diagram of a cryogenic thermal system according to one embodiment of the present invention.
FIG. 2 is a schematic diagram of an intelligent optimization control apparatus according to an embodiment of the invention.
Fig. 3 is a schematic diagram of a low-temperature thermal system with an intelligent optimization control device in a thermal intelligent regulation center according to an embodiment of the invention.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The same reference numerals denote the same or similar structures in the drawings, and thus detailed descriptions thereof will be omitted.
Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to provide a thorough understanding of embodiments of the invention. One skilled in the relevant art will recognize, however, that the inventive aspects may be practiced without one or more of the specific details, or with other structures, components, steps, methods, and so forth. In other instances, well-known structures, components, or operations are not shown or described in detail to avoid obscuring aspects of the invention.
Additional features and advantages of the invention will be set forth in the detailed description which follows, or may be learned by practice of the invention.
The intelligent optimization control equipment of the low-temperature thermal system provided by the invention is explained by combining with the figures 1 to 3. FIG. 1 is a schematic diagram of a cryogenic thermal system according to one embodiment of the present invention. FIG. 2 is a schematic diagram of an intelligent optimization control apparatus according to an embodiment of the invention. Fig. 3 is a schematic diagram of a thermal intelligent regulation center of a low-temperature thermal system including intelligent optimization control equipment according to an embodiment of the invention.
The low-temperature heating system 10 comprises a heat source unit 11, a heat sink unit 12 and a heat intelligent control center 13. The heat intelligent control center 13 is used for heat transfer and heat balance between the heat source unit 11 and the heat sink unit 12.
In one embodiment of a cryogenic thermal system 10 as shown in fig. 1, the cryogenic thermal system 10 recovers heat from materials 1, 2, and 3 and delivers it to various locations to provide cryogenic heat to materials 4, 5, and 6, respectively. In the prior art, the original temperatures of the materials 1, 2 and 3 are different from 100 ℃ to 135 ℃, but the materials are cooled to a lower temperature (generally below 50 ℃) by an air cooler or a water cooler and then enter the downstream, and the heat of the materials 1, 2 and 3 is lost to the atmosphere by air cooling and water cooling (consuming electric energy). The original temperatures of the materials 4, 5 and 6 are different from 70 ℃ to 110 ℃, and the materials are heated to the required temperature through steam, and the steam can be purchased from the outside or can be produced by burning coal, natural gas and the like. Thus, in the prior art implementations, the heat lost by the materials 1, 2, 3 and the heat required by the materials 4, 5, 6 are not correlated, resulting in a waste of heat.
To this end, the low temperature thermal system 10 of fig. 1 may establish a hot water cycle. The heat medium water is pressurized by a pump in the heat intelligent control center 13 and then sent to the materials 1, 2 and 3 of the heat source unit 11 for heat exchange and temperature rise, the heat medium water returns to the heat intelligent control center 13 after temperature rise, and the materials 4, 5 and 6 sent to the heat trap unit 12 through water quantity control replace the steam at the original positions 4, 5 and 6 for heating. The temperature of the heat medium water is reduced and then returns to the heat intelligent control center 13, the water temperature is adjusted by an air cooler or a water cooler of the heat intelligent control center 13, then the water is pressurized by a pump, and the materials 1, 2 and 3 are sent by water quantity control to take heat to complete circulation. Through the application of the low-temperature heating system 10, the cooling consumption of the air cooler or the water cooler is reduced for the materials 1, 2 and 3, and the consumption of heating steam is reduced for the materials 4, 5 and 6, so that the utilization of heat is realized.
Specifically, with continued reference to fig. 3, fig. 3 illustrates a specific configuration of the intelligent thermal system heat regulation center incorporating the intelligent optimization control equipment of the present invention. As shown in fig. 3, the heat intelligent control center includes a heat source water inlet end, a heat source water outlet end, a heat sink water inlet end, a heat sink water outlet end, a water feeding water collector, a water return water collector, a water supplementing end, a sewage discharging end and an intelligent optimization control device. The water inlet end of the heat source is connected to the heat source unit 11, so that the heating medium water flows into the intelligent heat regulation and control center 13 from the heat source unit 11. The heat source water removal end is connected to the heat source unit 11, so that the heating medium water flows into the heat source unit 11 from the heat intelligent control center 13. The water inlet end of the hot trap is connected to the hot trap unit 12, so that the heating medium water flows into the intelligent heat control center 13 from the hot trap unit 12. The hot trap water removing end is connected to the hot trap unit 12, so that the heating medium water flows into the hot trap unit 12 from the intelligent heat control center 13. The water feeding collector is connected between the heat source water removing end and the heat trap water inlet end so as to adjust the flow of the heat medium water of the heat source. The return water collector is connected between the hot trap water removal end and the heat source water supply end so as to adjust the flow of the heat medium water removed from the hot trap. The water replenishing end is arranged in the heat intelligent control center so as to supply water to the hot water circulation of the low-temperature heat system 10. The blowdown end is arranged at the heat intelligent control center and carries out blowdown according to the online analysis result of the quality of the hot medium water. The various reference numbers in fig. 3 illustrate: a hot water circulation pump 1; a hot water air cooler 2; adjusting valves 3- (1-6); a flow sensor 4; a pressure sensor 5; a temperature sensor 6; conductivity detection 7; detecting the oil content in water 8; detecting the pH value 9; detecting dissolved oxygen 10; a water supply collector 11A; the return water collector 12A. Wherein, all data such as all sensors, instrumentation, governing valve signal, pump air cooler running signal of heat intelligence allotment center all get into intelligent optimal control equipment.
The above is merely a schematic description of the present invention providing a low temperature thermal system 10 and the present invention is not so limited.
The intelligent optimization control apparatus 20 provided by the present invention is described below with reference to fig. 2. The intelligent optimization control equipment 20 comprises a plurality of sensor units 21 (only one sensor unit is shown in the figure for the sake of clarity, the invention is not limited to the number of sensor units), an edge calculation unit 22 and a central optimization unit 24.
The plurality of sensor units 21 are used for acquiring sensing parameters of the low-temperature thermal system of the intelligent heat control center. In the foregoing embodiment in which the low-temperature thermal system 10 performs heat transfer through water circulation, the sensing parameters of the thermal intelligent control center low-temperature thermal system may include, but are not limited to, the flow rate of the heat medium water, the inlet and outlet temperature of the heat medium water, and the inlet and outlet pressure of the heat medium water (which are collected by a plurality of temperature sensors, pressure sensors, and flow sensors disposed at different positions as shown in fig. 3). The sensor unit 21 may also be used to collect the process flow and the process inlet and outlet temperatures (i.e. the temperatures and flow rates of the materials 1-6 before and after the heat treatment) of the heat source unit and the heat sink unit. In some preferred embodiments, the sensor unit 21 comprises one or more wireless sensors, so that communication with the edge computing unit 22 may be achieved through the wireless gateway 22.
The edge calculation unit 22 may be configured to perform the following steps: acquiring sensing parameters acquired by the plurality of sensor units; heat transfer data for each heat exchanger is calculated. The central optimization unit 24 may be configured to perform the following steps: inputting the acquired sensor parameters and training a prediction model; predicting heat exchange parameters based on the prediction model; and determining whether to adjust the control parameters of the intelligent heat regulation and control center according to the predicted heat exchange parameters and taking benefit maximization as an optimization target. Specifically, the determination of whether to adjust the control parameter of the intelligent heat regulation and control center according to the predicted heat exchange parameter can be realized by the following steps: judging whether the predicted heat exchange parameters meet target heat exchange parameters or not; if so, not adjusting the control parameters of the intelligent heat regulation and control center; and if not, adjusting the control parameters of the intelligent heat regulation and control center according to the difference between the existing heat exchange parameters and the target heat exchange parameters. Wherein the heat exchange parameters include, but are not limited to: the temperature of the heat source unit and the heat trap unit after process heat exchange and the temperature of the heat medium water after heat exchange. The heat intelligent control center control parameters include but are not limited to: the flow rate of the heat medium water and the flow rate of the heat medium water pump entering each heat source unit and each heat sink unit.
Specifically, the prediction model can be obtained based on historical sensing parameters and heat exchange parameter training, and iterative optimization training can be performed based on real-time acquired sensing parameters and real-time heat exchange parameters. In a specific implementation of the above embodiment, the prediction model may be modeled by using an open source program (e.g., matlab) and is built by using a feedforward neural network algorithm with a strong nonlinear mapping capability. The hidden layer node transfer functions of the neural network model include, but are not limited to, hyperbolic tangent sigmoid functions, and the output layer node transfer functions include, but are not limited to, linear functions. When modeling is carried out, real-time data can be collected every 10-30 minutes, the data of 15-1 month of system operation is used as input and output parameters to train the model, and the output under different control parameters is predicted based on the training model. Furthermore, an open source program (such as matlab) can be utilized to perform optimization calculation through a heuristic algorithm, so as to obtain the target control parameters under the benefit optimization condition.
The input parameters of the prediction model include, but are not limited to: the process stream pre-heat exchange temperature and flow of the heat source, heat sink, the hot carrier water pre-heat exchange temperature and flow, and environmental parameters such as actual air temperature data. Output parameters of the predictive model include, but are not limited to: the temperature of the process material flow of the heat source and the heat trap after heat exchange and the temperature of the heat medium water after heat exchange.
The central optimization unit 24 may also be configured to perform the following steps: carrying out visual processing on the sensing parameters acquired by the plurality of sensor units and the control parameters of the intelligent heat regulation and control center; and displaying the sensing parameters acquired by the plurality of visual sensor units and the control parameters of the intelligent heat regulation and control center in a control device page 25 of an intelligent optimization control equipment client or a browser. Further, the central optimization unit 24 may also communicate with the automatic control unit 26 to send the optimization calculation result to the automatic control unit 26 for execution, so as to realize automatic adjustment of the flow rate, temperature, and the like of the medium water in the low-temperature thermal system, and ensure stable and optimized operation of the low-temperature thermal system under the change of the production working condition.
In one specific implementation, the model input parameters include 4 streams of process stream pre-heat exchange flow (instantaneous values are 116t/h, 165t/h, 82t/h and 60t/h respectively), 4 streams of process stream pre-heat exchange temperature (instantaneous values are 104 ℃, 158 ℃, 152 ℃ and 179 ℃), heat medium water pre-heat exchange flow and temperature (instantaneous values are 1210t/h and 78 ℃ respectively), and the model output parameters include heat medium water post-heat exchange temperature (instantaneous values are 90 ℃). Model training and optimization calculation are carried out through an algorithm preset by a central optimization unit, the temperature of the target heat medium water after heat exchange is 94 ℃, and the flow control value of the heat medium water is 820 t/h. And then, the central optimization unit sends the control value to the automatic control unit, and the flow of the circulating water pump is adjusted through an actuating mechanism. The intelligent optimization control equipment for the low-temperature thermal system provided by the invention has the following advantages:
the intelligent optimization and control equipment of the low-temperature thermal system is based on a wireless data acquisition system and communication transmission, a big data modeling algorithm and a heuristic optimization algorithm are used as cores, and edge computing equipment, a big data deep learning algorithm and an automatic control device are integrated, so that the functions of real-time data acquisition monitoring, on-line simulation of the low-temperature thermal system, optimization calculation of key operating parameters, automatic control of the operating parameters and the like are realized, and the closed-loop real-time optimization control of the low-temperature thermal system is ensured.
The present invention has been described in relation to the above embodiments, which are only exemplary of the implementation of the present invention. It should be noted that the disclosed embodiments do not limit the scope of the invention. Rather, it is intended that all such modifications and variations be included within the spirit and scope of this invention.
Claims (10)
1. An intelligent optimization control arrangement for a cryogenic thermal system, the cryogenic thermal system comprising: the intelligent heat control system comprises a heat source unit, a heat trap unit and an intelligent heat control center, wherein the intelligent heat control center is used for heat transfer and heat balance between the heat source unit and the heat trap unit;
the intelligent optimization control equipment comprises:
the sensor units are respectively used for acquiring sensing parameters of the heat source unit, the heat sink unit and the heat intelligent control center;
an edge calculation unit for performing the steps of:
acquiring sensing parameters acquired by the plurality of sensor units;
carrying out quantitative calculation on heat balance and heat transfer parameters;
a central optimization unit for performing the steps of:
inputting the acquired sensor parameters and training a prediction model;
predicting heat exchange parameters based on the prediction model;
and confirming whether to adjust the control parameters of the heat intelligent control center or not based on the predicted heat exchange parameters.
2. Intelligent optimized control equipment for a cryogenic thermal system according to claim 1, characterized in that the cryogenic thermal system carries out heat transfer by means of water circulation,
the sensing parameters include one or more of the following sensor parameters: the flow rate of the heating medium water, the inlet and outlet temperature of the heating medium water, the inlet and outlet pressure of the heating medium water, the process flow, the process inlet and outlet temperature, the conductivity of the heating medium water, dissolved oxygen, the pH value, the oil content and the turbidity;
the heat exchange parameters comprise one or more of the following parameters: the temperature of the heat source unit and the heat trap unit after process heat exchange and the temperature of the heat medium water after heat exchange;
the control parameters of the heat intelligent control center comprise one or more of the following control parameters: the flow rate of the heat medium water and the flow rate of the heat medium water pump entering each heat source unit and each heat sink unit.
3. The intelligent optimization control equipment of a low temperature thermal system according to claim 2, wherein the determining whether to adjust the control parameters of the intelligent heat regulation center according to the predicted heat exchange parameters comprises:
judging whether the predicted heat exchange parameters meet target heat exchange parameters or not;
if so, not adjusting the control parameters of the intelligent heat regulation and control center;
and if not, adjusting the control parameters of the intelligent heat regulation and control center according to the difference between the existing heat exchange parameters and the target heat exchange parameters.
4. The intelligent optimization control equipment of a cryogenic thermal system of claim 1, wherein the predictive model is obtained based on historical sensing parameters and heat exchange parameter training and is iteratively optimized and trained based on real-time acquired sensing parameters and real-time heat exchange parameters.
5. The intelligent optimization control equipment of a cryogenic thermal system of claim 4, wherein the predictive model is a feed-forward neural network model whose hidden layer node transfer function comprises a hyperbolic tangent sigmoid function and whose output layer node transfer function comprises a linear function.
6. The intelligent optimization control arrangement for a cryogenic thermal system of claim 1, wherein the central optimization unit is in communication with the edge calculation unit,
the central optimization unit is further configured to perform:
training the prediction model;
optimizing control parameters of the heat intelligent control center;
and storing the sensing parameters, the heat exchange parameters and the control parameters.
7. The intelligent optimized control equipment for a cryogenic thermal system of claim 6, wherein the central optimization unit is further configured to perform the steps of:
carrying out visual processing on the sensing parameters acquired by the plurality of sensor units and the control parameters of the intelligent heat regulation and control center;
and displaying the visually processed sensing parameters acquired by the plurality of sensor units and the control parameters of the intelligent heat regulation and control center in a control device page of an intelligent optimization control equipment client or a browser.
8. The intelligent optimal control equipment of a cryogenic thermal system of claim 2, wherein the thermal intelligent regulation center comprises:
a heat source water inlet end and a heat source water outlet end which are connected to the heat source unit;
the hot trap water inlet end and the hot trap water outlet end are connected to the hot trap unit;
the water feeding and collecting unit is connected between the heat source water removing end and the heat sink water inlet end;
the backwater water collecting unit is connected between the hot trap water removing end and the heat source water inlet end;
and the water replenishing unit is connected between the backwater water collecting unit and the heat source water removing end.
9. The intelligent optimization control arrangement for a cryogenic thermal system of claim 1, wherein the edge calculation unit further inputs environmental parameters into the predictive model.
10. The intelligent optimized control equipment for a cryogenic thermal system of any one of claims 1 to 9, wherein the sensor unit comprises one or more wireless sensors.
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| CN202110492287.4A CN113110356A (en) | 2021-05-06 | 2021-05-06 | Intelligent optimization control equipment of low-temperature thermal system |
| PCT/CN2021/112963 WO2022233101A1 (en) | 2021-05-06 | 2021-08-17 | Intelligent optimization control device for low-temperature thermal system |
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