CN114777325B - Boiler system regulation and control method, model building method, related equipment and medium - Google Patents
Boiler system regulation and control method, model building method, related equipment and medium Download PDFInfo
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- CN114777325B CN114777325B CN202210377404.7A CN202210377404A CN114777325B CN 114777325 B CN114777325 B CN 114777325B CN 202210377404 A CN202210377404 A CN 202210377404A CN 114777325 B CN114777325 B CN 114777325B
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- 238000000034 method Methods 0.000 title claims abstract description 61
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims abstract description 206
- 230000001105 regulatory effect Effects 0.000 claims abstract description 69
- 238000010438 heat treatment Methods 0.000 claims abstract description 67
- 230000001276 controlling effect Effects 0.000 claims abstract description 24
- 238000012549 training Methods 0.000 claims description 47
- 238000013499 data model Methods 0.000 claims description 46
- 238000012360 testing method Methods 0.000 claims description 25
- 238000003860 storage Methods 0.000 claims description 22
- 238000004422 calculation algorithm Methods 0.000 claims description 13
- 238000003066 decision tree Methods 0.000 claims description 11
- 238000011156 evaluation Methods 0.000 claims description 10
- 238000007781 pre-processing Methods 0.000 claims description 10
- 238000012706 support-vector machine Methods 0.000 claims description 8
- 230000007613 environmental effect Effects 0.000 claims description 7
- 238000007637 random forest analysis Methods 0.000 claims description 5
- 238000009795 derivation Methods 0.000 claims description 2
- 229910052799 carbon Inorganic materials 0.000 abstract description 7
- 239000000446 fuel Substances 0.000 abstract description 7
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 abstract description 6
- 238000005265 energy consumption Methods 0.000 abstract description 5
- 238000006386 neutralization reaction Methods 0.000 abstract description 3
- 230000002349 favourable effect Effects 0.000 abstract 1
- 238000004590 computer program Methods 0.000 description 42
- 238000010586 diagram Methods 0.000 description 17
- 230000006870 function Effects 0.000 description 16
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- 238000001816 cooling Methods 0.000 description 1
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- 239000005457 ice water Substances 0.000 description 1
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- 238000003303 reheating Methods 0.000 description 1
- 239000008400 supply water Substances 0.000 description 1
Classifications
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24H—FLUID HEATERS, e.g. WATER OR AIR HEATERS, HAVING HEAT-GENERATING MEANS, e.g. HEAT PUMPS, IN GENERAL
- F24H1/00—Water heaters, e.g. boilers, continuous-flow heaters or water-storage heaters
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24H—FLUID HEATERS, e.g. WATER OR AIR HEATERS, HAVING HEAT-GENERATING MEANS, e.g. HEAT PUMPS, IN GENERAL
- F24H9/00—Details
- F24H9/20—Arrangement or mounting of control or safety devices
- F24H9/2007—Arrangement or mounting of control or safety devices for water heaters
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- Control Of Steam Boilers And Waste-Gas Boilers (AREA)
Abstract
The application provides a boiler system regulation and control method, a model building method, related equipment and a medium, wherein the regulation and control method comprises the following steps: acquiring target heat supply parameters and real-time operation parameters of a boiler; based on the real-time operation parameters and the regulation model of the boiler, obtaining predicted heating parameters of the boiler; and regulating and controlling the boiler system according to the predicted heat supply parameter and the target heat supply parameter. This application automatically regulated boiler's operating parameter control boiler's water supply temperature avoids leading to increasing fuel quantity and extravagant water consumption because the temperature is too high, reduces energy consumption, improves the energy efficiency, is favorable to energy-concerving and environment-protective, accords with carbon neutralization, carbon and reaches peak theory, avoids simultaneously because the temperature is too low and can't satisfy the heat supply demand.
Description
Technical Field
The application relates to the technical field of boilers, in particular to a boiler system regulation and control method, a model building method, related equipment and a medium.
Background
The boiler is used as energy conversion equipment and is widely applied to industrial production and daily life. The boiler heats or humidifies the air in a hot water supply mode, if the water temperature supplied by the boiler is too high, the water temperature can meet the heating or humidifying requirement, but the temperature of the air is easily higher, ice water is required to be consumed for cooling, and meanwhile heat loss is increased. If the water temperature supplied by the boiler is too low, temperature rise or humidification may be affected. Therefore, means for controlling the water temperature of the boiler is lacking at present, the fuel consumption and the water consumption are easily increased due to the fact that the water temperature is too high, so that energy is wasted, or the heat supply requirement cannot be met due to the fact that the water temperature is too low.
Disclosure of Invention
In view of the foregoing, there is a need for a method for controlling a boiler system, a method for modeling a boiler system, a related apparatus and a medium for controlling a boiler water temperature, so as to solve the technical problems that fuel consumption and water consumption are increased and wasted due to too high water temperature or heat supply requirements cannot be satisfied due to too low water temperature.
The application provides a regulation and control method of a boiler system, which comprises the following steps:
acquiring target heat supply parameters and real-time operation parameters of a boiler;
based on the real-time operation parameters and the regulation model of the boiler, obtaining predicted heating parameters of the boiler;
and regulating and controlling the boiler system according to the predicted heat supply parameter and the target heat supply parameter.
The application also provides a regulation and control device of boiler system, include:
the first communicator is used for acquiring target heating parameters and real-time operation parameters of the boiler;
a first processor coupled to the first communicator; and
the first memory is used for storing instructions, and the instructions are loaded by the first processor and execute the regulation and control method of the boiler system.
The application also provides an electronic device comprising:
a second processor; and
And the second memory is used for storing instructions, and the instructions are loaded by the second processor and execute the regulation and control method of the boiler system.
The present application also provides a computer readable storage medium having stored thereon at least one computer instruction loaded by a second processor and performing the above-described method of regulating a boiler system.
The application also provides a method for establishing the regulation model of the boiler system, which comprises the following steps:
acquiring parameter data of the boiler system;
preprocessing the parameter data to obtain a training data set;
and obtaining a regulation model of the boiler system based on the training data set and the initial data model.
The application also provides a device for establishing a regulation model of a boiler system, wherein the device for establishing comprises:
the third communicator is used for acquiring data;
a third processor coupled to the third communicator; and
and the third memory is stored with instructions, and the instructions are loaded by the third processor and execute the method for establishing the regulation model of the boiler system.
The application also provides an electronic device, which comprises a fourth processor and a fourth memory, wherein the fourth memory is used for storing instructions, and the fourth processor is used for calling the instructions in the fourth memory, so that the electronic device executes the method for establishing the regulation model of the boiler system.
The application also provides a computer readable storage medium storing computer readable instructions which when executed by the fourth processor implement the method for building the regulation model of the boiler system.
According to the boiler system regulation and control method, the model building method, the related equipment and the medium, the operation parameters of the boiler can be automatically regulated to control the water supply temperature of the boiler, so that the water supply temperature of the boiler accords with the target water supply temperature, the increase of fuel consumption and waste of water consumption caused by overhigh water temperature are avoided, the energy consumption is reduced, the energy efficiency is improved, the energy conservation and environmental protection are facilitated, the carbon neutralization and carbon peak concept is met, and meanwhile, the heat supply requirement cannot be met due to overlow water temperature is avoided.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present application, and that other drawings may be obtained according to the provided drawings without inventive effort to a person skilled in the art.
Fig. 1 is a schematic structural view of a boiler according to an embodiment of the present application.
FIG. 2 is a flow chart of a method of regulating a boiler system according to an embodiment of the present application.
FIG. 3 is a flow chart of obtaining predicted heating parameters of a boiler based on real-time operating parameters and a regulatory model of the boiler according to an embodiment of the present application.
FIG. 4 is a flow chart of regulating an operating parameter of the boiler according to the predicted heating parameter and the target heating parameter provided in an embodiment of the present application.
FIG. 5 is a flow chart for adjusting and controlling the operating parameters of a boiler based on a parameter deviation value and a preset deviation value according to an embodiment of the present application.
Fig. 6 is a schematic structural view of a boiler according to another embodiment of the present application.
FIG. 7 is a flow chart for adjusting and controlling the operating parameters of a boiler based on a parameter deviation value and a preset deviation value according to an embodiment of the present application.
Fig. 8 is a schematic structural view of a boiler according to another embodiment of the present application.
FIG. 9 is a flow chart for adjusting and controlling the operating parameters of a boiler based on a parameter deviation value and a preset deviation value according to an embodiment of the present application.
Fig. 10 is a schematic structural view of a boiler according to another embodiment of the present application.
FIG. 11 is a flow chart for adjusting and controlling the operating parameters of a boiler based on a parameter deviation value and a preset deviation value according to an embodiment of the present application.
Fig. 12 is a schematic structural diagram of a regulating device according to an embodiment of the present application.
Fig. 13 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
FIG. 14 is a flow chart of a method of creating a regulatory model of a boiler system according to an embodiment of the present application.
Fig. 15 is a flowchart of preprocessing parameter data to obtain a training data set according to an embodiment of the present application.
FIG. 16 is a flow chart of preprocessing parameter data to obtain a training data set, according to an embodiment of the present application.
Fig. 17 is a schematic diagram of an evaluation index of a data model according to an embodiment of the present application.
Fig. 18 is a schematic structural diagram of an establishing device according to an embodiment of the present application.
Fig. 19 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Description of the main reference signs
Boiler system 1
Boiler 10
Temperature and humidity sensor 101
Water inlet 102
Water outlet 103
Water pump 11
Inlet pipe 12
Outlet pipe 13
First temperature sensor 131
Water supply pipe 14
Second temperature sensor 141
Return pipe 15
Third temperature sensor 151
First water circulation regulating pipeline 16
First bypass valve 161
Second water circulation regulating pipeline 17
Second bypass valve 171
Supply and demand target 18
Regulating device 2
First processor 201
First memory 202
First computer program 203
First communicator 204
Electronic devices 3, 5
Second processor 301
Second memory 302
Second computer program 303
The setting-up device 4
Third processor 401
Third memory 402
Third computer program 403
Third communicator 404
Fourth processor 501
Fourth memory 502
Fourth computer program 503
The following detailed description will further illustrate the application in conjunction with the above-described figures.
Detailed Description
In order that the above-recited objects, features and advantages of the present application will be more clearly understood, a more particular description of the application will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings. It should be noted that, in the case of no conflict, the embodiments of the present application and the features in the embodiments may be combined with each other.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application, and the described embodiments are merely some, rather than all, of the embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein in the description of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application.
Referring to fig. 1, a schematic structural diagram of a boiler system according to a first embodiment of the present application is shown. The boiler system 1 includes a boiler 10, a water pump 11 for water supply and return circulation, a water inlet pipe 12 connected to the water pump 11 and the water inlet 102, respectively, a water outlet pipe 13 connected to the water outlet 103, a water supply pipe 14 connected to the water outlet pipe 13, and a return pipe 15 connected to the water pump 11. In one embodiment, the boiler 10 is provided with a temperature and humidity sensor 101 for detecting the temperature and humidity of the outside air. The outlet pipe 13 is provided with a first temperature sensor 131, which is arranged adjacent to the boiler 10 for detecting the outlet water temperature T of the water heated from the boiler 10 Out of . The water supply pipe 14 is provided with a second temperature sensor 141 for detecting the real-time water supply temperature T Feed device Since heat loss and heat exchange with the outside air are generated when water from the boiler 10 flows to the water supply pipe 14 and the supply and demand target 18 through the water outlet pipe 13, the second temperature sensor 141 may be disposed adjacent to the supply and demand target 18 to more accurately measure the end actual water supply temperature T flowing into the supply and demand target 18 Feed device . The return pipe 15 is provided with a third temperature sensor 151 for detecting the return water temperature T Returning to 。
In one embodiment, the boiler 10 is used to supply hot water to a supply and demand target 18. The supply and demand target 18 may be a device, apparatus, system, or enclosed space, etc., the device, apparatus, or system may be a MAU (fresh Air Unit) device or system, an Air conditioner, or a heating device, etc., and the enclosed space may be an office, a machine shop, a clean room, etc. Thus, water circulation can be realized between the boiler 10 and the supply and demand target 18, hot water heated in the boiler 10 flows through the water outlet pipe 13 to the water supply pipe 14, and then the water supply pipe 14 finally supplies heat to the supply and demand target 18, and the water subjected to heat exchange and heat utilization by the supply and demand target 18 is circulated and returned to the boiler 10 through the water return pipe 15 and the water pump 11 again through the water inlet pipe 12 for reheating, recycling and reutilization.
Referring to fig. 2, a flowchart of a method for controlling a boiler system according to an embodiment of the present application is shown. The order of the steps in the flow chart may be changed and some steps may be omitted according to different needs. The regulation and control method of the boiler system comprises the following steps:
s101, acquiring target heating parameters and real-time operation parameters of the boiler 10.
In a heating scene of production or life, certain requirements are required on heating parameters, for example, certain temperature and humidity are required to be achieved, so that the target heating parameters meeting the requirements of supply and demand targets, such as 40 ℃ (environmental parameters or requirement parameters of heating targets), are obtained through the regulation and control method of the application. The parameters of the boiler system for supplying heat to the heat supply target in the running state are real-time running parameters.
In one embodiment, the target heating parameters of the boiler 10 are obtained to determine the heating target to be achieved by regulating the boiler system, and the real-time operation parameters of the boiler 10 are obtained to determine the parameters related to the predicted heating parameters, so that the accuracy of the predicted heating parameters obtained by the regulating method is improved. Wherein predicting the heating parameter comprises predicting a water supply temperature. The regulation and control method can predict the water supply temperature of the boiler based on the real-time operation parameters of the boiler, so that the boiler system can be regulated and controlled more timely and accurately.
In one embodiment, the target heating parameter comprises a target water supply temperature. The real-time operating parameters include at least one of a shutdown temperature, a start-up temperature, a discharge water temperature, a return water temperature, an outside air enthalpy value, an outside air temperature, an outside air humidity, and a real-time water supply temperature of the boiler 10.
S102, obtaining predicted heating parameters of the boiler based on real-time operation parameters and a regulation model of the boiler 10.
In one embodiment, the real-time operating parameters of the boiler 10 are used as input data for a regulation model, and the predicted heating parameters of the boiler are automatically output through the regulation model.
In an embodiment, the regulation model is a regression algorithm model, which is a support vector machine model, a random forest model, a gradient lifting decision tree algorithm model, or a ridge regression model.
Referring to FIG. 3, in one embodiment, obtaining predicted heating parameters for a boiler based on real-time operating parameters and a regulation model of the boiler 10 includes:
s1021, integrating the acquired real-time operation parameters to obtain input data.
In an embodiment, the acquired real-time operation parameters relate to temperature parameters, humidity parameters, enthalpy parameters and the like, the parameter types are relatively distributed, the parameter data formats are not uniform, and the regulation model cannot be directly input, so that the acquired operation parameters are integrated to obtain input data capable of being directly input into the regulation model.
In one embodiment, the integrating the acquired real-time operation parameters to obtain the input data includes: and performing row-column conversion and variable derivation on the real-time operation parameters to obtain input data.
In an embodiment, the real-time operation parameters are subjected to row-column conversion through SQL sentences of the database, different types of parameters are classified (such as temperature parameters are classified into one type and humidity parameters are classified into one type) according to presentation forms of the data, and derivative variables are performed on the real-time operation parameters based on a preset time interval, so that on one hand, the data quantity is enlarged, on the other hand, the accuracy of the data is optimized, and on the other hand, the data formats of the same type of parameters are unified while the derivative and conversion are performed, and optionally, the preset time interval is 6 minutes. For example, the real-time backwater temperature is derived, and the data including the data before 6 minutes, the data before 12 minutes and the backwater temperature data before 18 minutes are used as real-time operation parameters after error elimination, format calibration and the like.
S1022, obtaining the predicted heating parameters of the boiler based on the input data and the regulation model.
In one embodiment, the integrated input data is input into a regulation model to obtain the predicted heating parameters of the boiler without manual or other equipment for calculation.
S103, regulating and controlling the boiler system according to the predicted heat supply parameter and the target heat supply parameter.
According to the method, after the predicted heat supply parameters are obtained, the operation parameters of the heat supply system are controlled back through the regulation and control model and the target heat supply parameters, so that the predicted heat supply parameters output by the regulation and control model accord with the target heat supply parameters to meet heat supply requirements.
In one embodiment, regulating a boiler system in accordance with a predicted heating parameter and a target heating parameter includes: and regulating and controlling the operation parameters of the boiler according to the target water supply temperature and the predicted water supply temperature.
In one embodiment, after the predicted water supply temperature of the boiler is obtained through the regulation and control model, the predicted water supply temperature is compared with the target water supply temperature, and the operation parameters of the boiler system are automatically regulated and controlled based on the comparison result, so that the predicted water supply temperature accords with the target water supply temperature, and the intellectualization of regulation and control of the boiler system is realized.
In one embodiment, the operating parameters include, but are not limited to, a start-up temperature, a shut-down temperature, and a start-up and shut-down condition of the boiler.
Referring to fig. 4, in one embodiment, adjusting the operation parameters of the boiler according to the predicted heating parameters and the target heating parameters includes:
s1031, determining parameter deviation values according to the predicted heat supply parameters and the target heat supply parameters.
In an embodiment, the parameter deviation value between the predicted heating parameter and the target heating parameter is used as a comparison result of the predicted heating parameter and the target heating parameter, and is also a basis for regulating and controlling the operation parameter of the boiler.
In one embodiment, determining the parameter deviation value based on the predicted heating parameter and the target heating parameter comprises: and calculating a difference value obtained by subtracting the target water supply temperature from the predicted water supply temperature, and determining the difference value as a parameter deviation value. For example, if the predicted water supply temperature is 40 ℃, the target water supply temperature is 35 ℃, the parameter deviation value is +5 ℃, at this time, it is indicated that the boiler is operated with the existing real-time operation parameters, and the water supply temperature will be higher than the target water supply temperature by 5 ℃, thereby requiring readjustment of the operation of the boiler, and changing the operation parameters of the boiler so that the final water supply temperature is equal to 35 ℃.
In an embodiment, the parameter deviation value between the predicted heat supply parameter and the target heat supply parameter is used as a basis for measuring and controlling the operation parameter of the boiler system so as to accurately control the operation parameter of the boiler system.
S1032, regulating and controlling the operation parameters of the boiler based on the parameter deviation value and the preset deviation value.
In an embodiment, the magnitude relation between the predicted heating parameter and the target heating parameter may be determined by the positive and negative of the parameter deviation value, and the difference between the predicted heating parameter and the target heating parameter may be determined by the magnitude relation between the absolute value of the parameter deviation value and the preset deviation value.
Referring to fig. 5, in an embodiment, adjusting the operation parameters of the boiler based on the parameter deviation value and the preset deviation value includes:
s201, judging whether the parameter deviation value is larger than zero, judging whether the absolute value of the parameter deviation value is larger than a preset deviation value, and judging whether the boiler is shut down.
S202, based on the fact that the parameter deviation value is larger than zero and the absolute value of the parameter deviation value is larger than a preset deviation value, the boiler is not shut down, and the shutdown temperature is reduced.
In one embodiment, if the parameter deviation is greater than zero and the absolute value of the parameter deviation is greater than the preset deviation, the predicted water supply temperature T is indicated Feed device Exceeding the targetIf the boiler is not shut down, the boiler is shut down at a higher temperature and not shut down in time, so that the predicted water supply temperature T is caused Feed device Too high, so that the boiler is shut down in advance by reducing the shut down temperature, thereby timely reducing the predicted water supply temperature T Feed device So that the water supply temperature T is predicted Feed device The temperature of the water supply is reduced to the target water supply temperature in time, and meanwhile, the energy consumption is reduced.
In one embodiment, the heating time and the heating temperature of the boiler are controlled and regulated to reduce the shutdown temperature, so that the absolute value of the parameter deviation value is smaller than or equal to the preset deviation value, namely, the predicted water supply temperature T Feed device Meets the target water supply temperature.
S203, based on the fact that the parameter deviation value is smaller than zero and the absolute value of the parameter deviation value is larger than a preset deviation value, the boiler is shut down, and the starting temperature is improved.
In one embodiment, if the parameter deviation is less than zero and the absolute value of the parameter deviation is greater than the preset deviation, the predicted water supply temperature T is indicated Feed device If the water supply temperature is lower than the target water supply temperature, if the boiler is shut down, the boiler is stopped, the boiler is not started in time after the boiler is stopped, and the water in the pipeline cannot be continuously heated, so that the predicted water supply temperature T is caused Feed device Too low, in order to raise the predicted water supply temperature T Feed device The furnace starting temperature is increased, so that the boiler starts in advance, namely, the boiler is started to heat in time when the boiler is not completely cooled, and the predicted water supply temperature T is increased Feed device 。
In one embodiment, the heating time and the heating temperature of the boiler are controlled and regulated to improve the starting temperature of the boiler so that the absolute value of the parameter deviation value is smaller than or equal to the preset deviation value, namely, the predicted water supply temperature T Feed device Meets the target water supply temperature.
In the first embodiment, the outlet water temperature T sensed by the first temperature sensor 131 is acquired Out of Based on the outlet water temperature T Out of And (5) controlling the start-stop state of the boiler.
Specifically, if the water outlet temperature T Out of Is greater than the shutdown temperature, the boiler 10 is controlled to shutdown, if the outlet water temperature T Out of Is greater than the furnace starting temperatureThe temperature is lower than the shutdown temperature, and the operation of the boiler 10 is controlled. If the water outlet temperature T Out of Below the start-up temperature, the boiler 10 is controlled to operate, i.e. the boiler 10 continues to operate in a state where the boiler 10 is turned on. It should be noted that the water outlet temperature T can be determined by Out of Whether the temperature is higher than the shutdown temperature or not and judging the outlet water temperature T Out of Whether the furnace temperature is higher than the furnace starting temperature or not, so as to regulate and control the furnace stopping, furnace starting or continuous operation of the boiler 10.
If the outlet water temperature T Out of Is greater than the shutdown temperature, which indicates the water outlet temperature T Out of Too high, the boiler 10 is controlled to be shut down in order to ensure the stability of the boiler 10. During the shut down of the furnace, the boiler 10 gradually reduces the heat supply amount, stops supplying fuel, continues to supply heat by using the original fuel, and the water pump 11 continues to operate. If the water outlet temperature T Out of The temperature of the water is reduced to be higher than the starting temperature and lower than the stopping temperature due to the stopping of the furnace, which indicates the temperature T of the water Out of Having been reduced to a safe temperature, the boiler 10 is started. If the water outlet temperature T Out of Is smaller than the furnace starting temperature, which indicates the water outlet temperature T Out of The boiler 10 is operated at a low level.
Referring to fig. 6, a schematic structural diagram of a boiler system according to a second embodiment of the present application is shown. Further, a first water circulation regulating pipeline 16 is arranged between the water inlet pipe 12 and the water outlet pipe 13 of the boiler 10, and the first water circulation regulating pipeline 16 is connected with the boiler 10 in parallel. The first water circulation regulating line 16 is provided with a first bypass valve 161.
In an embodiment, the operating parameters of the boiler further include a switch state or an opening degree of the first bypass valve 161.
Referring to fig. 7, based on the parameter deviation value and the preset deviation value, the controlling the opening or closing state of the first bypass valve 161 includes:
s301, judging whether the parameter deviation value is larger than zero or not and judging whether the absolute value of the parameter deviation value is larger than a preset deviation value or not.
S302, controlling the first bypass valve 161 to open or increasing the opening of the first bypass valve 161 based on the parameter deviation value being greater than zero and the absolute value of the parameter deviation value being greater than the preset deviation value.
It should be noted that, if the parameter deviation value is greater than zero and the absolute value of the parameter deviation value is greater than the preset deviation value, the first bypass valve 161 is opened when the first bypass valve 161 is in the closed state, or the opening of the first bypass valve 161 is increased when the opening of the first bypass valve 161 is smaller, so that part of the backwater or more backwater enters the first water circulation regulating pipeline 16, and then is supplied to the supply and demand target 18 together with the water heated by the boiler 10 through the water supply pipe 14, and the backwater entering the first water circulation regulating pipeline 16 is not heated by the boiler 10, so that the predicted water supply temperature T can be reduced Feed device Avoiding the predicted water supply temperature T Feed device Too high to meet the heating demand, so that the predicted water supply temperature T Feed device Meets the target water supply temperature and simultaneously reduces the energy consumption in time.
S303, controlling the first bypass valve 161 to close or reducing the opening of the first bypass valve 161 based on the parameter deviation value being smaller than zero and the absolute value of the parameter deviation value being larger than the preset deviation value.
If the parameter deviation value is smaller than zero and the absolute value of the parameter deviation value is larger than the preset deviation value, the first bypass valve 161 is closed when the first bypass valve 161 is in the open state, or the opening of the first bypass valve 161 is reduced when the opening of the first bypass valve 161 is larger, so that the return water does not enter the first water circulation regulating pipeline 16 but enters the boiler 10, and the boiler 10 heats the return water, thereby increasing the predicted water supply temperature T Feed device Or reduce the return water entering the first water circulation regulating line 16 so that more return water enters the boiler 10, thereby increasing the predicted feed water temperature T Feed device So that the predicted water supply temperature T of the boiler Feed device Meets the target water supply temperature and avoids the predicted water supply temperature T Feed device Too low to meet the heating demand.
Fig. 8 is a schematic structural diagram of a boiler according to a third embodiment of the present application. Further, a second water circulation regulating line 17 is provided between the water supply pipe 14 and the water return pipe 15 of the boiler 10, and the second water circulation regulating line 17 is connected in parallel with the boiler 10. The second water circulation regulating line 17 is provided with a second bypass valve 171. In one embodiment, the boiler 10 is in the event that heating is just on or is not operating for a long period of timeThe water quantity of the return pipe 15 is less, the temperature is lower, the temperature difference of the system is larger, and the water supply temperature at the tail end is not stable enough. At this time, the second bypass valve 171 is opened so that part of the water supplied to the water supply pipe 14 is not supplied to the supply and demand target 18, but enters the water return pipe 15 through the second water circulation regulating pipeline 17, and further enters the boiler 10 in advance for heating, so that the water return temperature T is increased as soon as possible Returning to So that the boiler 10 safely and normally operates.
In the first embodiment, the operating parameters of the boiler further include the on-off state or opening degree of the second bypass valve 171.
Referring to fig. 9, the opening or closing state of the second bypass valve 171 is controlled based on the parameter deviation value and the preset deviation value.
S401, judging and predicting the water supply temperature T Feed device And backwater temperature T Returning to Whether the temperature difference between the two is larger than a preset temperature difference. Wherein the sensed backwater temperature T can be obtained from the third temperature sensor 151 Returning to And. Alternatively, the preset temperature difference may be set to 20 ℃ with reference to the safety performance of the boiler piping.
Based on the above-mentioned judgment result of step S401, if the boiler 10 is turned on immediately after the heat supply is started or is not operated for a long time, the water supply temperature T is predicted Feed device And backwater temperature T Returning to The temperature difference is greater than the preset temperature difference, then S402: controlling the opening of the second bypass valve 171 or increasing the opening of the second bypass valve 171 to increase the return water temperature T Returning to So that the boiler 10 operates normally.
When the boiler 10 is just started to supply heat, the water amount of the return pipe 15 is small, the temperature is low, the temperature difference of the system is large, and the temperature of the terminal water supply is not stable enough. At this time, the second bypass valve 171 is opened so that part of the water supply pipe 14 is not supplied to the supply and demand target 18, but enters the water return pipe 15 through the second water circulation regulating pipeline 17 under the action of the water pump 11, and further enters the boiler 10 for heating in advance, and the circulation is performed so as to increase the water return temperature T as soon as possible Returning to 。
Based on the determination result of the above step S401, if the water supply temperature T is predicted Feed device And backwater temperature T Returning to Temperature in betweenIf the difference is less than or equal to the preset temperature difference, S403: the second bypass valve 171 is controlled to close or reduce the opening degree of the second bypass valve 171.
If the temperature of the return pipe 15 is high, the temperature of the supply water at the end tends to be stable when the temperature difference of the system is small. At this time, the second bypass valve 171 is closed so that all the water of the water supply pipe 14 is supplied to the supply-demand target 18 without advancing into the return pipe 15 through the second water circulation regulating line 17.
Referring to fig. 10, a schematic structural diagram of a boiler according to a fourth embodiment of the present application is shown.
Further, a first water circulation regulating line 16 is arranged in parallel between the water inlet pipe 12 and the water outlet pipe 13 of the boiler 10, and the first water circulation regulating line 16 is provided with a first bypass valve 161. A second water circulation regulating line 17 is provided in parallel between the water supply pipe 14 and the water return pipe 15 of the boiler 10, and the second water circulation regulating line 17 is provided with a second bypass valve 171.
In the first embodiment, the operation parameters of the boiler include the on-off state, the shut-down temperature, the on-temperature, the number and frequency of water pump opening, the on-off state or opening of the first bypass valve 161, and the on-off state or opening of the second bypass valve 171.
Referring to fig. 11, the opening and closing states or the opening degrees of the first bypass valve 161 and the second bypass valve 171 are controlled back based on the parameter deviation value and the preset deviation value.
S501, judging and predicting the water supply temperature T Feed device And backwater temperature T Returning to Whether the temperature difference between the two is larger than a preset temperature difference. Alternatively, the preset temperature difference is 20 ℃.
Based on the determination result of step S501, if the water supply temperature T is predicted Feed device And backwater temperature T Returning to And if the temperature difference is greater than the preset temperature difference, performing S502: controlling the opening of the second bypass valve 171 or increasing the opening of the second bypass valve 171 to increase the return water temperature T Returning to So that the boiler 10 operates normally.
Based on the determination result of step S501, if the water supply temperature T is predicted Feed device And backwater temperature T Returning to And if the temperature difference is smaller than or equal to the preset temperature difference, performing S503: control of the firstThe two bypass valves 171 close or reduce the opening of the second bypass valve 171.
Based on the above step S502 or S503, S504: based on the parameter deviation value being greater than zero and the absolute value of the parameter deviation value being greater than a preset deviation value, the water supply at the tail end of the boiler is cooled by at least one of opening the first bypass valve 161 and increasing the opening of the first bypass valve 161 so as to reduce the predicted water supply temperature T Feed device So that the water supply temperature T is predicted Feed device Meets the target water supply temperature.
Or S505: based on the parameter deviation value being smaller than zero and the absolute value of the parameter deviation value being larger than a preset deviation value, the water supply at the tail end of the boiler is heated and warmed by at least one of closing the first bypass valve and reducing the opening of the first bypass valve so as to improve the predicted water supply temperature T Feed device So that the water supply temperature T is predicted Feed device Meets the target water supply temperature.
Fig. 12 is a schematic diagram of a control device of a boiler system according to an embodiment of the present application.
The regulating device 2 includes, but is not limited to, a first processor 201, a first memory 202, a first computer program 203 stored in the first memory 202 and executable on the first processor 201, and a first communicator 204. For example, the first computer program 203 is a regulatory program for a boiler system. The first processor 201 implements steps in the control method of the boiler system when executing the first computer program 203, for example, steps S101 to S103 shown in fig. 2, steps S1021 to S1022 shown in fig. 3, steps S1031 to S1032 shown in fig. 4, steps S201 to S203 shown in fig. 5, steps S301 to S303 shown in fig. 7, steps S401 to S403 shown in fig. 10, and steps S501 to S505 shown in fig. 11.
For example, the first computer program 203 may be divided into one or more modules/units, which are stored in the first memory 202 and executed by the first processor 201 to complete the present application. One or more of the modules/units may be a series of computer program instruction segments capable of performing a specific function, the instruction segments describing the execution of the first computer program 203 in the regulating device 2.
It will be appreciated by those skilled in the art that the schematic diagram is merely an example of the regulating device 2 and does not constitute a limitation of the regulating device 2, and may comprise more or less components than shown, or may combine certain components, or different components, e.g. the regulating device 2 may further comprise input-output devices, network access devices, buses, etc.
The first processor 201 may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSPs), application specific integrated circuits (Application Specific Integrated Circuit, ASICs), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. The general purpose processor may be a microprocessor or the first processor 201 may be any conventional processor or the like, and the first processor 201 is a control center of the regulating device 2, and connects various parts of the whole regulating device 2 by various interfaces and lines.
The first memory 202 may be used to store a first computer program 203 and/or modules/units, and the first processor 201 implements various functions of the regulating device 2 by running or executing the computer program and/or modules/units stored in the first memory 202 and invoking data stored in the first memory 202. The first memory 202 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function, and the like; the storage data area may store data created according to the use of the regulation device 2, and the like. In addition, the first memory 202 may include volatile and non-volatile memory, such as a hard disk, memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash Card (Flash Card), at least one disk storage device, a Flash memory device, or other storage device. The first communicator 204 is communicatively coupled to the communication module on the boiler 10 and to the first processor 201 and the first memory 202 for obtaining the target heating parameters and the real-time operating parameters of the boiler 10.
Fig. 13 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
The electronic device 3 may be a personal computer, a server, or the like. The electronic device 3 includes, but is not limited to, a second processor 301, a second memory 302, a second computer program 303 stored in the second memory 302 and executable on the second processor 301. For example, the second computer program 303 is a regulatory program of the boiler system. The second processor 301 executes the second computer program 303 to realize steps in the control method of the boiler system, for example, steps S101 to S103 shown in fig. 2, steps S1021 to S1022 shown in fig. 3, steps S1031 to S1032 shown in fig. 4, steps S201 to S203 shown in fig. 5, steps S301 to S303 shown in fig. 7, steps S401 to S403 shown in fig. 9, and steps S501 to S505 shown in fig. 11.
The second computer program 303 may be divided into one or more modules/units, which are stored in the second memory 302 and executed by the second processor 301, for example. One or more of the modules/units may be a series of computer program instruction segments capable of performing a specific function for describing the execution of the second computer program 303 in the electronic device 3.
It will be appreciated by those skilled in the art that the schematic diagram is merely an example of the electronic apparatus 3 and does not constitute a limitation of the electronic apparatus 3, and may include more or fewer components than shown, or may combine certain components, or different components, e.g. the electronic apparatus 3 may further include input-output devices, network access devices, buses, etc.
The second processor 301 may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. The general purpose processor may be a microprocessor or the second processor 301 may be any conventional processor or the like, the second processor 301 being a control center of the electronic device 3, the various interfaces and lines being used to connect the various parts of the entire electronic device 3.
The second memory 302 may be used to store a second computer program 303 and/or a module/unit, and the second processor 301 implements various functions of the electronic device 3 by running or executing the computer program and/or module/unit stored in the second memory 302 and invoking data stored in the second memory 302. The second memory 302 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program (such as a sound playing function, an image playing function, etc.) required for at least one function, and the like; the storage data area may store data created according to the use of the electronic device 3, or the like. In addition, the second memory 302 may include volatile and non-volatile memory, such as a hard disk, memory, plug-in hard disk, smart Media Card (SMC), secure Digital (SD) Card, flash Card (Flash Card), at least one disk storage device, flash memory device, or other storage device.
Referring to fig. 14, a flowchart of a method for establishing a control model of a boiler system according to an embodiment of the present application is shown. The order of the steps in the flow chart may be changed and some steps may be omitted according to different needs.
S601, acquiring parameter data of a boiler system.
In one embodiment, the parameter data includes historical operating data and historical environmental data for the boiler 10. Historical operating data includes, but is not limited to, boiler load, fan frequency, target water supply temperature, furnace start-up temperature, furnace shut-down temperature, water outlet temperature, boiler return water temperature, main pipe water supply temperature. Historical environmental data includes, but is not limited to, outside air temperature, outside air humidity, and outside air enthalpy.
S602, preprocessing parameter data to obtain a training data set.
Referring to fig. 15, in one embodiment, preprocessing parameter data to obtain a training data set includes:
and S6021, classifying the parameter data to obtain at least one group of class data.
In an embodiment, the parameter data may be historical data of the boiler or data collected by the boiler over a period of time. The name of each parameter data is a group of category data. For example, the temperatures in the history data or the collected data are classified as target water supply temperature, furnace start temperature, furnace stop temperature, water outlet temperature, boiler return water temperature, main water return temperature, main water supply temperature, outside air temperature, humidity in the history data or the collected data is classified as outside air humidity, enthalpy in the history data or the collected data is classified as outside air enthalpy, percentage in the history data or the collected data is classified as boiler load, and frequency in the history data or the collected data is classified as fan frequency, respectively.
S6022, determining a variance value of each group of category data.
In one embodiment, determining the variance value for each set of category data includes: an average value of each group of the class data is calculated, and a variance value of each group of the class data is calculated based on the average value.
S6023, forming a training data set based on the category data with variance values meeting a preset threshold.
In one embodiment, forming the training data set based on the category data whose variance value satisfies the preset threshold includes: and determining the category data with the variance value larger than a preset threshold value as training data or test data in the training data set.
Referring to fig. 16, in another embodiment, preprocessing parameter data to obtain a training data set includes:
s6024, acquiring target heat supply parameters of the boiler.
In one embodiment, the target heating parameter is a target water supply temperature.
And S6025, determining a correlation coefficient between the parameter data and the target heating parameter of the boiler.
In an embodiment, determining the correlation coefficient between the parameter data and the target heating parameter of the boiler comprises: calculating a pearson correlation coefficient r between each category of parameter data and the target heating parameter, wherein the calculation formula is as follows:
in the above calculation formula, X is parameter data, and Y is target heating parameter.
In an embodiment, determining the correlation coefficient between the parameter data and the target heating parameter of the boiler further comprises: the significance P value of the pearson correlation coefficient r between the parameter data of each category and the target heating parameter is calculated.
S6026, forming a training data set based on parameter data of which the correlation coefficient with the target heating parameter of the boiler meets the preset requirement.
In one embodiment, forming the training data set based on parameter data satisfying a preset requirement with respect to a correlation coefficient with a target heating parameter of the boiler includes: and determining parameter data with the significance P value smaller than or equal to a threshold value, selecting parameter data of a preset number of categories from the parameter data with the significance P value smaller than or equal to the threshold value, and determining the parameter data of the preset number of categories as training data in a training data set. Alternatively, the threshold is 0.05 and the preset number is 5.
S603, obtaining a regulation model of the boiler system based on the training data set and the initial data model.
In an embodiment, the training data set comprises training data and test data. For example, each set of input data and output data is a set of training data or a set of test data, 80% of the data in the training data set may be used as training data, and 20% of the data may be used as test data.
In one embodiment, obtaining a regulatory model of the boiler system based on the training data set and the initial data model includes: training the initial data model by using training data, and testing the trained initial data model by using test data to obtain a regulation and control model of the boiler system. Optionally, the initial data model includes at least one of a support vector machine model, a random forest model, a gradient lifting decision tree algorithm model, and a ridge regression model.
In one embodiment, testing the trained initial data model with test data to obtain a regulatory model of the boiler system includes: inputting the test data into the trained initial data model to obtain a predicted value; calculating an error of the predicted value based on the predicted value and a true value in the test data; and determining the trained initial model as a regulation model of the boiler system based on the error of the predicted value obtained by the trained initial data model being smaller than or equal to a preset value.
In one embodiment, each set of test data includes input data that is parameter data other than the actual water supply temperature and output data that is the actual water supply temperature, i.e., the actual value in the test data. The input data of each set of test data is input into an initial data model to obtain a predicted value (predicted water supply temperature), and a prediction error is calculated based on the predicted value and the true value of each set of test data. Wherein the error k= |predictor-true value|/|true value|. Alternatively, the preset value is 3%. And if the error is smaller than or equal to the preset value, determining the trained initial model as a regulation model of the boiler system.
In the above embodiment, the training data and the test data are input into any one of a support vector machine model, a random forest model, a gradient lifting decision tree algorithm model, and a ridge regression model to establish a regulation model of the boiler system. In another embodiment, the training data and the test data may be input into a plurality of support vector machine models, random forest models, gradient lifting decision tree algorithm models, and ridge regression models to build a plurality of regulation models of the boiler system, and then an optimal regulation model is determined from the plurality of regulation models.
In another embodiment, after establishing the plurality of regulatory models of the boiler system, deriving the regulatory model of the boiler system based on the training data set and the initial data model further comprises: calculating an evaluation index of the trained initial data model, wherein the evaluation index comprises at least one of a decision coefficient, a mean square error and an average absolute error, and determining an optimal data model in the trained initial data model based on the evaluation index to obtain a regulation model of the boiler system.
In another embodiment, the predicted values of the initial data model after training are assumedTrue value y= { y 1 ,y 2 ,…,y n }. The predicted and actual values of the initial data model are generated from the test data in the training dataset input initial data model and/or from the new test data input initial data model.
Determining the coefficient R 2 The calculation formula of (2) is as follows:
determining an optimal data model in the trained initial data model based on the evaluation index, wherein obtaining the regulation model of the boiler system comprises the following steps: and determining the data model with the largest decision coefficient as the optimal data model. Referring to fig. 17, the decision coefficient (0.988585) of the gradient-lifting decision tree algorithm model XGBoost is the largest, so that the trained gradient-lifting decision tree algorithm model is determined to be the optimal data model, that is, the regulation model of the boiler system is the trained gradient-lifting decision tree algorithm model.
The mean square error MSE is calculated as:
determining an optimal data model in the trained initial data model based on the evaluation index, wherein obtaining the regulation model of the boiler system comprises the following steps: and determining the data model with the minimum mean square error as an optimal data model. As shown in fig. 17, the mean square error (0.198888) of the gradient boost decision tree algorithm model XGBoost is minimal, and thus, the trained gradient boost decision tree algorithm model is determined to be the optimal data model, that is, the regulation model of the boiler system is the trained gradient boost decision tree algorithm model.
The calculation formula of the average absolute error MAE is:
Determining an optimal data model in the trained initial data model based on the evaluation index, wherein obtaining the regulation model of the boiler system comprises the following steps: the data model with the smallest average absolute error is determined as the optimal data model. As shown in fig. 18, the mean absolute error (0.274123) of the support vector machine model SVR is the smallest, and therefore, the trained support vector machine model is determined to be the optimal data model, i.e., the regulatory model of the boiler system is the trained support vector machine model.
Fig. 18 is a schematic diagram of a device for establishing a control model of a boiler system according to an embodiment of the present application.
The establishing means 4 includes, but is not limited to, a third processor 401, a third memory 402, a third computer program 403 stored in the third memory 402 and executable on the third processor 401, and a third communicator 404. For example, the third computer program 403 is a build program of a regulatory model. The third processor 401 executes the third computer program 403 to realize steps in the method for creating the control model of the boiler system, for example, steps S601 to S603 shown in fig. 14, and S6021 to S6026 shown in fig. 15 to 16.
By way of example, the third computer program 403 may be divided into one or more modules/units, which are stored in the third memory 402 and executed by the third processor 401 to complete the present application. One or more of the modules/units may be a series of computer program instruction segments capable of performing the specific functions for describing the execution of the third computer program 403 in the establishing means 4.
It will be appreciated by a person skilled in the art that the schematic diagram is only an example of the establishing means 4 and does not constitute a limitation of the establishing means 4, and may comprise more or less components than shown, or may be combined with certain components, or different components, e.g. the establishing means 4 may also comprise input and output devices, network access devices, buses, etc.
The third processor 401 may be a central processing unit, but may also be other general purpose processors, digital signal processors, application specific integrated circuits, off-the-shelf programmable gate arrays or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general purpose processor may be a microprocessor or the third processor 401 may also be any conventional processor or the like, the third processor 401 being a control center of the setting-up device 4, the various interfaces and lines being used to connect the various parts of the entire setting-up device 4.
The third memory 402 may be used to store a third computer program 403 and/or modules/units, and the third processor 401 may implement various functions of the setting-up device 4 by running or executing the computer program and/or modules/units stored in the third memory 402 and invoking data stored in the third memory 402. The third memory 402 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function, and the like; the storage data area may store data created according to the use of the creation means 4, etc. In addition, the third memory 402 may include volatile and non-volatile memory, such as a hard disk, memory, a plug-in hard disk, a smart memory card, a secure digital card, a flash memory card, at least one magnetic disk storage device, a flash memory device, or other storage device. The third communicator 404 is communicatively coupled to the communication module on the boiler 10 and to the third processor 401 and the third memory 402 for obtaining operational data and environmental data of the boiler 10.
Fig. 19 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
The electronic device 5 may be a personal computer, a server, or the like. The electronic device 5 includes, but is not limited to, a fourth processor 501, a fourth memory 502, a fourth computer program 503 stored in the fourth memory 502 and executable on the fourth processor 501. For example, the fourth computer program 503 is a build program for a regulatory model. The fourth processor 501 performs steps in the method for creating the control model of the boiler system, for example, steps S601 to S603 shown in fig. 14, and steps S6021 to S6026 shown in fig. 15 to 16, when executing the fourth computer program 503.
Illustratively, the fourth computer program 503 may be split into one or more modules/units, which are stored in the fourth memory 502 and executed by the fourth processor 501 to complete the present application. One or more of the modules/units may be a series of computer program instruction segments capable of performing the specified functions, which instruction segments are used for describing the execution of the fourth computer program 503 in the electronic device 5.
It will be appreciated by those skilled in the art that the schematic diagram is merely an example of the electronic apparatus 5 and does not constitute a limitation of the electronic apparatus 5, and may include more or fewer components than shown, or may combine certain components, or different components, e.g., the electronic apparatus 5 may further include input-output devices, network access devices, buses, etc.
The fourth processor 501 may be a central processing unit, but may also be other general purpose processors, digital signal processors, application specific integrated circuits, off-the-shelf programmable gate arrays or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general purpose processor may be a microprocessor or the fourth processor 501 may be any conventional processor or the like, the fourth processor 501 being a control center of the electronic device 5, the various interfaces and lines being utilized to connect various parts of the overall electronic device 5.
The fourth memory 502 may be used to store a fourth computer program 503 and/or modules/units, and the fourth processor 501 may implement various functions of the electronic device 5 by executing or executing the computer program and/or modules/units stored in the fourth memory 502 and invoking data stored in the fourth memory 502. The fourth memory 502 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program (such as a sound playing function, an image playing function, etc.) required for at least one function, and the like; the storage data area may store data created according to the use of the electronic device 5, or the like. In addition, fourth memory 502 may include volatile and non-volatile memory, such as a hard disk, memory, plug-in hard disk, smart memory card, secure digital card, flash memory card, at least one magnetic disk storage device, flash memory device, or other storage device.
The integrated modules/units of the electronic devices 3, 5 may be stored in a computer readable storage medium if implemented in the form of software functional units and sold or used as separate products. Based on such understanding, the present application may implement all or part of the flow of the method of the above embodiment, or may be implemented by implementing relevant hardware by using a computer program to instruct relevant hardware, where the computer program may be stored in a computer readable storage medium, and where the computer program, when executed by a processor, may implement the steps of each method embodiment described above. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, executable files or in some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying computer program code, a recording medium, a USB flash disk, a removable hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory, a random access memory.
According to the boiler system regulation and control method, the model building method, the related equipment and the medium, the operation parameters of the boiler can be automatically regulated to control the water supply temperature of the boiler, so that the predicted water supply temperature of the boiler accords with the target water supply temperature, the increase of fuel consumption and waste of water consumption caused by overhigh water temperature is avoided, the energy consumption is reduced, the energy efficiency is improved, the energy conservation and environmental protection are facilitated, the carbon neutralization and carbon peak idea is met, and meanwhile, the heat supply requirement cannot be met due to overlow water temperature is avoided.
It will be evident to those skilled in the art that the present application is not limited to the details of the foregoing illustrative embodiments, and that the present application may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned. Furthermore, it is evident that the word "comprising" does not exclude other elements or steps, and that the singular does not exclude a plurality. Several of the units or means recited in the apparatus claims may also be embodied by one and the same unit or means, either in software or hardware. The terms first, second, etc. are used to denote a name, but not any particular order.
The above embodiments are only for illustrating the technical solution of the present application and not for limiting, and although the present application has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present application may be modified or substituted equally without departing from the spirit and scope of the technical solution of the present application.
Claims (20)
1. A method of regulating a boiler system, the method comprising:
acquiring a target heat supply parameter and a real-time operation parameter of a boiler, wherein the real-time operation parameter comprises the outlet water temperature of the boiler;
based on the real-time operation parameters and the regulation model of the boiler, obtaining predicted heating parameters of the boiler;
regulating the operation parameters of the boiler according to the predicted heat supply parameters and the target heat supply parameters, wherein regulating the operation parameters of the boiler according to the predicted heat supply parameters and the target heat supply parameters comprises the following steps:
determining a parameter deviation value according to the predicted heating parameter and the target heating parameter;
based on the parameter deviation value being greater than zero and the absolute value of the parameter deviation value being greater than a preset deviation value, and the boiler not being shut down, reducing a shut down temperature in the operating parameter; or based on the parameter deviation value being smaller than zero and the absolute value of the parameter deviation value being larger than the preset deviation value, and the boiler being shut down, increasing the furnace starting temperature in the operation parameters;
controlling the boiler to stop based on the outlet water temperature being greater than the stop temperature; controlling the boiler to work based on the fact that the outlet water temperature is higher than the furnace starting temperature and lower than the furnace stopping temperature; or controlling the boiler to work based on the fact that the outlet water temperature is smaller than the starting temperature.
2. The method of regulation and control of claim 1, wherein: the real-time operation parameters comprise at least one of the furnace stopping temperature, the furnace starting temperature, the backwater temperature, the external air enthalpy value, the external air temperature, the external air humidity and the real-time water supply temperature of the boiler.
3. The method of regulation and control of claim 1, wherein: the target heating parameter includes a target water supply temperature and the predicted heating parameter includes a predicted water supply temperature.
4. The regulation method of claim 1, wherein the obtaining the predicted heating parameters of the boiler based on the real-time operating parameters of the boiler and a regulation model comprises:
integrating the acquired real-time operation parameters to obtain input data;
and obtaining the predicted heating parameters of the boiler based on the input data and the regulation model.
5. The method of regulation and control of claim 1, wherein: the regulation model is a regression algorithm model.
6. A regulation device of a boiler system, the regulation device comprising:
the first communicator is used for acquiring target heating parameters and real-time operation parameters of the boiler;
a first processor coupled to the first communicator; and
A first memory having instructions stored therein, the instructions being loaded by the first processor and executing the method of regulating the boiler system according to any one of claims 1 to 5.
7. An electronic device, the electronic device comprising:
a second processor; and
a second memory having instructions stored therein, the instructions being loaded by the second processor and executing the method of regulating the boiler system according to any one of claims 1 to 5.
8. A computer-readable storage medium, on which at least one computer instruction is stored, characterized in that the instructions are loaded by a second processor and execute the regulation method of the boiler system according to any one of claims 1 to 5.
9. A method of building a regulation model of a boiler system for implementing a regulation method according to any one of claims 1 to 5, the method comprising:
acquiring parameter data of the boiler system, wherein the parameter data comprises historical operation data and historical environment data of the boiler, the historical operation data at least comprises target water supply temperature, furnace starting temperature, furnace stopping temperature, water outlet temperature and backwater temperature, and the historical environment data at least comprises outside air temperature, outside air humidity and outside air enthalpy value;
Preprocessing the parameter data to obtain a training data set;
and obtaining a regulation model of the boiler system based on the training data set and the initial data model.
10. The method of establishing of claim 9, wherein: the training data set comprises training data and test data, the obtaining a regulation model of the boiler system based on the training data set and an initial data model comprises the following steps:
training the initial data model by adopting the training data;
and testing the trained initial data model by adopting the test data to obtain a regulation and control model of the boiler system.
11. The method of establishing of claim 10, wherein: the initial data model comprises at least one of a support vector machine model, a random forest model, a gradient lifting decision tree algorithm model and a ridge regression model.
12. The method of building of claim 11, wherein said testing the trained initial data model with the test data to obtain a regulatory model of the boiler system comprises:
inputting the test data into the trained initial data model to obtain a predicted value;
Calculating an error of the predicted value based on the predicted value and a true value in the test data;
and determining the initial data model after training as a regulation model of the boiler system based on the fact that the error of the predicted value obtained by the initial data model after training is smaller than or equal to a preset value.
13. The method of building of claim 12, wherein the deriving a regulatory model of the boiler system based on the training data set and an initial data model further comprises:
calculating an evaluation index of the initial data model after training, wherein the evaluation index comprises at least one of a decision coefficient, a mean square error and an average absolute error;
and determining the initial data model after training based on the evaluation index to obtain a regulation and control model of the boiler system.
14. The method of establishing of claim 9, wherein: the parameter data includes operational data and environmental data of the boiler.
15. The method of establishing of claim 9, wherein the preprocessing the parameter data to obtain a training data set comprises:
classifying the parameter data to obtain at least one group of class data;
Determining a variance value of each set of the category data;
and forming the training data set based on the category data of which the variance value meets a preset threshold value.
16. The method of establishing of claim 9, wherein the preprocessing the parameter data to obtain a training data set comprises:
acquiring target heat supply parameters of the boiler;
determining a correlation coefficient between the parameter data and a target heating parameter of the boiler;
and forming the training data set based on the parameter data meeting preset requirements of the correlation coefficient with the target heating parameter of the boiler.
17. The method of building as claimed in claim 15 or 16, wherein said preprocessing said parameter data to obtain a training data set, further comprising:
establishing a time reference value, and performing data derivation on the training data set based on the time reference value.
18. A device for building a regulation model of a boiler system, the device comprising:
the third communicator is used for acquiring data;
a third processor coupled to the third communicator; and
a third memory having instructions stored therein, the instructions being loaded by the third processor and executing the method of building a regulatory model of a boiler system according to any one of claims 9 to 17.
19. An electronic device comprising a fourth processor and a fourth memory, the fourth memory for storing instructions, the fourth processor for invoking the instructions in the fourth memory to cause the electronic device to perform the method of building a regulatory model of a boiler system according to any of claims 9-17.
20. A computer readable storage medium storing computer readable instructions, which when executed by a fourth processor, implement a method of building a regulatory model of a boiler system according to any of claims 9 to 17.
Priority Applications (1)
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