CN114234662B - Indirect air cooling control system and method - Google Patents
Indirect air cooling control system and method Download PDFInfo
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- CN114234662B CN114234662B CN202111506204.9A CN202111506204A CN114234662B CN 114234662 B CN114234662 B CN 114234662B CN 202111506204 A CN202111506204 A CN 202111506204A CN 114234662 B CN114234662 B CN 114234662B
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F28—HEAT EXCHANGE IN GENERAL
- F28B—STEAM OR VAPOUR CONDENSERS
- F28B1/00—Condensers in which the steam or vapour is separate from the cooling medium by walls, e.g. surface condenser
- F28B1/02—Condensers in which the steam or vapour is separate from the cooling medium by walls, e.g. surface condenser using water or other liquid as the cooling medium
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F28—HEAT EXCHANGE IN GENERAL
- F28B—STEAM OR VAPOUR CONDENSERS
- F28B11/00—Controlling arrangements with features specially adapted for condensers
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F28—HEAT EXCHANGE IN GENERAL
- F28B—STEAM OR VAPOUR CONDENSERS
- F28B9/00—Auxiliary systems, arrangements, or devices
- F28B9/04—Auxiliary systems, arrangements, or devices for feeding, collecting, and storing cooling water or other cooling liquid
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B30/00—Energy efficient heating, ventilation or air conditioning [HVAC]
- Y02B30/70—Efficient control or regulation technologies, e.g. for control of refrigerant flow, motor or heating
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Abstract
The invention relates to an indirect air cooling control system which comprises a data acquisition module, a big data model calculation module, a mechanism model calculation module, a water temperature deviation processing module, a safety module, an execution processing module and an industrial controller, wherein the data acquisition module is simultaneously connected with the big data model calculation module, the mechanism model calculation module, the water temperature deviation processing module and the safety module, the execution processing module is connected with the big data model calculation module, the mechanism model calculation module and the water temperature deviation processing module, and the execution processing module and the safety module are connected with the industrial controller. The invention utilizes the combination of a big data model, a mechanism model and a water temperature deviation model, improves the stability of the indirect air cooling operation, utilizes the safety module to improve the safety of the indirect air cooling operation, and utilizes the system of each module to reduce the temperature of cold water at the outlet of the sector on the premise that the tube bundle is not frozen so as to achieve the purpose of reducing the back pressure of the steam turbine and further reducing the energy consumption.
Description
Technical Field
The invention relates to the technical field of simulation, system control, big data analysis and artificial intelligence of an indirect air cooling system of a thermal power plant, in particular to an indirect air cooling control system and method.
Background
In thermal power plants and nuclear power plants, the exhaust steam of a steam turbine needs to be cooled and condensed into water through a condenser and then returned to a boiler for recycling, and in northern water-deficient areas of China, the heat exchange of the condenser is usually completed through an indirect air cooling system. In the indirect air cooling system, circulating water cools the exhaust steam discharged by the steam turbine through the condenser, the temperature of the circulating water rises after the exhaust steam is cooled, the circulating water enters the indirect air cooling system and is cooled by air, and the cooled circulating water continuously cools the exhaust steam through the condenser. In order to ensure that the circulating water can cool the exhaust steam to a temperature range meeting the requirement, the heat exchange amount of air and the circulating water needs to be adjusted, and the current method is to change the opening degree of an indirect air cooling shutter. When the opening degree of the indirect air-cooling louver is changed, the air flow rate for exchanging heat with the circulating water is changed. According to the first law of thermodynamics and the Newton's cooling formula, the heat exchange amount between the air and the circulating water is changed. When the heat exchange quantity of the circulating water and the air is too small, the circulating water cannot be cooled to a proper temperature, the back pressure of a steam turbine is too high, the energy consumption is improved, when the heat exchange quantity of the circulating water and the air is too large, the temperature of the circulating water is too low, and when the temperature of the circulating water is reduced to be below 0 ℃ in winter, the phenomenon of pipe freezing can occur. It is important to control the temperature of the circulating water by controlling the opening of the louver.
The prior art uses manual operation to control the opening of the blind, or uses traditional control methods such as PID control. The manual control needs to consume the human cost, and because reasons such as people's mood, can't accurate control shutter aperture moreover. When the environmental temperature is lower than 0 ℃ in winter, the traditional control needs to increase the temperature of circulating water to prevent the circulating water from freezing, so that the back pressure of a steam turbine is increased to increase the energy consumption. Meanwhile, when the external conditions change, the traditional control means lags behind. With the development of artificial intelligence, artificial intelligence is used to control the opening degree of the blind in some places, but the artificial intelligence is based on a big data model, and the big data model has the limitation that a value with a large deviation is output sometimes, and even a mature model only reduces the probability of outputting the large deviation value. In addition, large data models cannot handle conditions that do not exist in their databases, which results in poor model applicability.
Disclosure of Invention
The invention aims to overcome the defects and provides an indirect air cooling control system and method, and the indirect air cooling louver can automatically increase or decrease the opening degree according to the situation under the condition of unmanned control, so that the aims of safe and stable operation and energy conservation are fulfilled.
The purpose of the invention is realized as follows:
the utility model provides an indirect air cooling control system, includes data acquisition module, big data model calculation module, mechanism model calculation module, temperature deviation processing module, safety module, carries out processing module and industrial controller, data acquisition module is connected with big data model calculation module, mechanism model calculation module, temperature deviation processing module, safety module simultaneously, carry out processing module and big data model calculation module, mechanism model calculation module, temperature deviation processing module and be connected, carry out processing module and safety module and be connected with industrial controller.
Preferably, the big data model calculation module is a model established based on a big data processing algorithm and an artificial intelligence algorithm, inputs data acquired by the data acquisition module, performs calculation by using the big data model, and outputs the big data opening of each sector louver in indirect air cooling.
Preferably, the mechanism model calculation module is a model established based on heat exchange characteristics and flow characteristics of water and air in indirect air cooling, inputs data acquired by the data acquisition module, and outputs the mechanism average opening degree of the shutters in each sector in indirect air cooling.
Preferably, the water temperature deviation processing module is a model established based on the temperature of the cold water at the outlet of the sector and the temperature of the cold water at the outlet set by the sector, and the model inputs the temperature of the cold water at the outlet of the sector and the temperature of the cold water at the outlet set by the sector, which are acquired by the data acquisition module, and outputs the supplementary average opening degree of the shutters of each sector in the indirect air cooling.
Preferably, the mechanism model calculation module takes one or more of the parameters of the temperature of a hot water main pipe of the unit, the temperature of a cold water main pipe of the sector, the flow of water entering the indirect air cooling for heat exchange, the external wind speed of the indirect air cooling and the ambient temperature as variables.
Preferably, the data collected by the data collection module comprises a temperature of a hot water main pipe of the unit, a temperature of a cold water main pipe of a sector, a flow rate of water entering the indirect air cooling for heat exchange, an external wind speed of the indirect air cooling, an external wind direction of the indirect air cooling, an environmental temperature, a backpressure of the unit, a generating load of the unit, a variable load instruction existence condition, an opening degree of each actuator of the louver, a current and a voltage of a circulating pump for increasing the pressure of the water entering the indirect air cooling for heat exchange, a set temperature of the cold water main pipe of the sector, a use condition of the calculation control system and a temperature field of each sector.
Preferably, the execution processing module analyzes and calculates output results of the mechanism model calculation module, the big data model calculation module and the water temperature deviation processing module, inputs the mechanism average opening degree, the big data opening degree and the supplementary average opening degree, and outputs the opening degree value of each actuator of each sector in the unit.
An indirect air cooling control method comprises the following steps:
step one, data acquisition;
inputting the acquired data into a big data model calculation module, a mechanism model calculation module and a water temperature deviation processing module to obtain big data opening, mechanism average opening and supplementary average opening;
inputting the opening degree of the big data, the mechanism average opening degree and the supplement average opening degree into an execution processing module, and calculating to obtain an opening degree value;
feeding the opening value back to an industrial controller, and controlling the opening of each shutter actuator by the industrial controller;
and step two, inputting the acquired data into the safety module, outputting an instruction whether to inhibit the opening of a certain actuator or not and an instruction for reducing the opening of the actuator by the safety module, directly controlling the opening of the shutter actuator according to the instruction of the safety module when the safety module is triggered, and performing the step three when the safety module is not triggered.
Preferably, the execution processing module is calculated as follows:
1. when the big data opening degree is within a certain range of the rational average opening degree, carrying out weighted average on the big data opening degree and the supplementary average opening degree, and multiplying the calculation result by the number of the cooling triangles in the sector to obtain a total opening degree value;
when the big data opening degree is not in a certain range of the mechanism average opening degree, the difference between the big data opening degree and the mechanism average opening degree is weighted and averaged, then the difference is added to the big data opening degree, the calculation result and the supplementary average opening degree are weighted and averaged, and the calculation result is multiplied by the number of the cooling triangles in the sector to obtain a total opening degree value;
2. and sequencing the cooling triangles according to the corresponding average temperatures of the cooling triangles according to the temperature field data, and then distributing the total opening value to the cooling triangles according to a certain strategy.
The invention has the beneficial effects that:
1. the invention limits the large data opening by using the mechanism average opening, avoids the problem of large error and improves the stability of indirect air cooling operation.
2. According to the invention, the calculation result is corrected by using the water temperature deviation processing module, so that the problem that the opening of an actuator is not changed when the water temperature fluctuates due to unknown parameters by a big data model calculation module is solved, and the stability of indirect air cooling operation is improved.
3. According to the invention, the calculation result is processed by the execution processing module and then is sent to each actuator, so that the uniformity of the temperature field is improved, the risk of freezing the tube bundle is reduced, and the safety of indirect air cooling operation is improved.
4. The invention utilizes the safety module to monitor the indirect air cooling, and restrains or reduces the opening of a certain actuator when the freezing is expected to occur, thereby improving the safety of the operation of the indirect air cooling.
5. The invention utilizes the synergistic effect of each module, can reduce the temperature of cold water at the outlet of the sector on the premise of not freezing the tube bundle, and achieves the purpose of reducing the back pressure of the steam turbine so as to reduce the energy consumption.
Drawings
FIG. 1 is a block diagram of the present invention.
Detailed Description
Referring to fig. 1, the invention relates to an indirect air cooling control system, which comprises a data acquisition module, a big data model calculation module, a mechanism model calculation module, a water temperature deviation processing module, a safety module, an execution processing module and an industrial controller, wherein the data acquisition module is simultaneously connected with the big data model calculation module, the mechanism model calculation module, the water temperature deviation processing module and the safety module, the execution processing module is connected with the big data model calculation module, the mechanism model calculation module and the water temperature deviation processing module, and the execution processing module and the safety module are connected with the industrial controller.
The data collected by the data collection module comprise the temperature of a hot water main pipe of the unit, the temperature of a cold water main pipe of a sector, the flow of water entering the indirect air cooling for heat exchange, the external wind speed of the indirect air cooling, the external wind direction of the indirect air cooling, the environmental temperature, the backpressure of the unit, the generating load of the unit, the existence condition of a variable load instruction, the opening degree of each actuator of the shutter, the current and the voltage of a circulating pump for improving the pressure of the water entering the indirect air cooling for heat exchange, the set temperature of the cold water main pipe of the sector, the use condition of the calculation control system and the temperature field of each sector.
The data acquisition module is used for preprocessing the acquired data.
The big data model calculation module is a model established based on a big data processing algorithm and an artificial intelligence algorithm, inputs data acquired by the data acquisition module, performs calculation by using the big data model, and outputs big data openness of each sector louver in indirect air cooling, and the big data openness is marked as a.
The big data model calculation module calculates the opening of the blind window based on the big data model, the average error of the calculation result of the big data model is smaller than that of the mechanism model, but the maximum error is larger than that of the mechanism model, and the average error of the whole calculation can be reduced by using the big data model.
The mechanism model calculation module is a model established based on the heat exchange characteristics and the flow characteristics of water and air in indirect air cooling, data collected by the data collection module is input, parameters such as the temperature of a hot water main pipe of a unit, the temperature of a cold water main pipe of a sector, the flow of water entering the indirect air cooling for heat exchange, the external wind speed of the indirect air cooling and the ambient temperature are taken as variables, and the mechanism average opening degree of shutters in each sector in the indirect air cooling is output and is marked as b.
The mechanism is modeled as follows:
according to the first law of thermodynamics:
Qw＝cpwqw(Twin-Twout)＝cpaqa(Taout-Tain) (1)
in the above formula cpRepresents specific heat capacity, q represents flow rate, T represents temperature, w in subscript represents water, a represents airIn represents entering the cooling triangle and out represents exiting the cooling triangle. Wherein the specific heat capacities of water and air are 4175J/(kg. K) and 1004J/(kg. K) respectively at constant values. The flow rate of water is the value collected if it can be collected, otherwise it is equal to the design value. The temperatures of the water entering and leaving the cooling triangle are collected values (respectively corresponding to the temperature of a hot water main pipe of the unit and the temperature of a cold water main pipe of the sector), the temperature of the air entering the cooling triangle is collected values (corresponding to the ambient temperature), and therefore the unknowns of the formula comprise the temperature of the air leaving the cooling triangle, the flow rate of the air and Qw。
Because the heat given off by the water is transferred to the air through the fins, the following results are obtained:
Qw＝hAΔTm (2)
in the above formula, h is the heat transfer coefficient and is equal to the design value, A is the heat transfer area and is equal to the design value, and delta TmIs the logarithmic mean temperature difference. The calculation is as follows:
ΔTm＝[(Twin-Taout)-(Twout-Tain)]/ln[(Twin-Taout)/(Twout-Tain)]
the unknown number of the formula (2) is QwAnd the temperature of the air exiting the cooling delta. The flow rate of the air can be calculated by the joint type (1) and the formula (2).
The flow rate of air was calculated using the following formula.
u＝qa/Aa
In the above formula, u is the air flow rate, qaIs the flow rate of air, AaThe air flow area is equal to the design value.
The design values are values in designing the intercooling tower and come from the design data of the intercooling tower.
The method of calculating the average opening degree from the air flow rate is as follows:
when the ambient temperature is less than or equal to 5 ℃ and the air flow rate is less than 0.6 m/s:
mechanism average opening degree-60.05526405 u2+89.47111658u-10.3685
When the ambient temperature is less than or equal to 5 ℃ and the air flow rate is more than or equal to 0.6m/s and less than 1 m/s:
mechanism average opening degree-10.69878226 u2+40.04772118u +1.69225938
When the ambient temperature is less than or equal to 5 ℃ and the air flow rate is more than or equal to 1 m/s:
mechanism average opening degree of 6.5116254u2+17.45436323u +8.77491237
When the ambient temperature is greater than 5 ℃:
mechanism average opening degree of 8.68695204u22+14.2449067u +12.45736583
In the above formula, u is the air flow rate.
The mechanism model calculation module calculates the opening of the blind window based on the mechanism model, the average error of the calculation result of the mechanism model is larger than that of the big data model, but the maximum error of the calculation result of the mechanism model is smaller than that of the big data model, and the large error calculation result of the whole calculation system can be avoided by utilizing the mechanism model.
The water temperature deviation processing module is a model established based on the outlet cold water temperature of the sector and the set outlet cold water temperature of the sector, inputs the outlet cold water temperature of the sector and the set outlet cold water temperature of the sector which are acquired by the data acquisition module, and outputs the supplement average opening degree of each sector shutter in indirect air cooling, which is recorded as c.
The water temperature deviation processing module has two functions, namely, under the condition that the big data model calculation module and the mechanism model calculation module are invalid, the water temperature deviation processing module calculates according to the deviation between the set water temperature of the sector and the actual outlet cold water temperature of the sector, and prevents the water temperature from being overridden due to the fact that the shutter does not act. And the second function is to perform supplementary calculation on the big data opening a and the mechanism average opening b under the unit variable load working condition, so as to achieve the purpose of more accurately controlling the water temperature.
The execution processing module is used for analyzing and calculating output results of the mechanism model calculating module, the big data model calculating module and the water temperature deviation processing module. The module inputs a big data opening a, a mechanism average opening b and a supplement average opening c and outputs opening values of actuators of all sectors in the unit.
The execution processing module has the following calculation mode:
1. when the big data opening a is within a certain range of the rational average opening b, carrying out weighted average on the big data opening a and the supplementary average opening c, and multiplying the calculation result by the number of the cooling triangles in the sector to obtain a total opening value which is recorded as d;
and when the big data opening a is not in a certain range of the mechanism average opening b, the difference between the big data opening a and the mechanism average opening b is weighted and averaged, then the weighted average is added to the big data opening a, the calculation result and the supplement average opening c are weighted and averaged, and the calculation result is multiplied by the number of the cooling triangles in the sector, so that a total opening value d is obtained and recorded as d.
2. And sequencing the cooling triangles according to the corresponding average temperatures according to the temperature field data, and then distributing the total opening value according to a certain strategy.
The strategy is as follows: when the temperature of the cold water main pipe at the outlet of the sector is higher than the set value, the total opening value is multiplied by 2/3 (the result is rounded down) and then divided by 1/2 of the number of the cooling triangles (the result is rounded up), the cooling triangles with the corresponding number of large average temperatures are allocated, and the cooling triangles which are not allocated are averagely allocated after the total opening minus the already allocated opening. When the temperature of the cold water main pipe at the outlet of the sector is lower than the set value, the total opening value is multiplied by 2/3 (the result is rounded downwards) and then divided by 1/2 of the number of the cooling triangles (the result is rounded upwards), the cooling triangles with the corresponding small average temperature are distributed, and the cooling triangles which are not distributed are evenly distributed after the total opening minus the already distributed opening.
For ease of understanding, the assignment of the total opening value is exemplified:
if the number of the cooling triangles is 5, the total opening value d is 50, the temperature of the cold water main pipe at the outlet of the sector is higher than a set value, and the triangles A1, A2, A3, A4 and A5 are arranged according to the temperature average from large to small. The total opening value d is multiplied by 2/3 (rounded down) to be 33, divided by 1/2 (rounded up) of the total number of sectors to be 33/3 to 11, and allocated to a corresponding number of cooling triangles with large average temperature, then a1, a2 and A3 are respectively allocated to 11, after subtracting the already allocated opening from the total opening, the total opening is averagely allocated to the cooling triangles which are not allocated, namely 50-33 to 17, and 17/2 to 8.5, then a4 and a5 are allocated to 8.5.
And the execution processing module feeds back the final opening value to the industrial controller, and the industrial controller sends an instruction to the shutter actuator according to the opening value, so that the opening of the shutter actuator is realized.
The safety module is used for preventing a tube bundle in the unit from being frozen, the module inputs temperature field data, outputs an instruction whether to inhibit the opening of a certain actuator and an instruction for closing the opening of the actuator to be small, and feeds the instruction back to the industrial controller, and the opening of the shutter actuator is controlled through the industrial controller. The safety module monitors the temperature field and suppresses or reduces the opening of a certain actuator when it is deemed necessary.
The safety module is used for calculating whether the tube bundle freezing is generated in the next period or a plurality of periods, when the freezing is not generated in the calculation, the safety module does not act, and when the freezing is generated in the calculation, the opening degree of the actuator is interfered according to the severity of the freezing. The security module has the highest priority among all modules.
An indirect air cooling control method comprises the following steps:
step one, data acquisition;
inputting the acquired data into a big data model calculation module, a mechanism model calculation module and a water temperature deviation processing module to obtain big data opening, mechanism average opening and supplementary average opening;
inputting the big data opening degree, the mechanism average opening degree and the supplement average opening degree into an execution processing module, and calculating to obtain a total opening degree value;
and step four, feeding back the total opening value to an industrial controller, and controlling the opening of each shutter actuator by the industrial controller.
And step two, inputting the acquired data into the safety module, outputting an instruction whether to inhibit the opening of a certain actuator or not and an instruction for reducing the opening of the actuator by the safety module, directly controlling the opening of the shutter actuator according to the instruction of the safety module when the safety module is triggered, and performing the step three when the safety module is not triggered.
In addition to the above embodiments, the present invention also includes other embodiments, and any technical solutions formed by equivalent transformation or equivalent replacement should fall within the scope of the claims of the present invention.
Claims (8)
1. An indirect air cooling control method is characterized in that: the method comprises the following steps:
step one, data acquisition;
inputting the acquired data into a big data model calculation module, a mechanism model calculation module and a water temperature deviation processing module to obtain big data opening, mechanism average opening and supplementary average opening;
inputting the big data opening degree, the mechanism average opening degree and the supplement average opening degree into an execution processing module, and calculating to obtain a total opening degree value;
feeding back the total opening value to an industrial controller, and controlling the opening of each shutter actuator by the industrial controller;
inputting the collected data into a safety module, outputting an instruction whether to inhibit the opening of a certain actuator or not and an instruction for reducing the opening of the actuator by the safety module, directly controlling the opening of the shutter actuator according to the instruction of the safety module when the safety module is triggered, and performing the step three when the safety module is not triggered;
the execution processing module has the following calculation mode:
1) when the big data opening degree is within a certain range of the mechanism average opening degree, carrying out weighted average on the big data opening degree and the supplement average opening degree, and multiplying the calculation result by the number of the cooling triangles in the sector to obtain a total opening degree value;
when the big data opening degree is not in a certain range of the mechanism average opening degree, the difference between the big data opening degree and the mechanism average opening degree is weighted and averaged, then the difference is added to the big data opening degree, the calculation result and the supplementary average opening degree are weighted and averaged, and the calculation result is multiplied by the number of the cooling triangles in the sector to obtain a total opening degree value;
2) and sequencing the cooling triangles according to the corresponding average temperatures of the cooling triangles according to the temperature field data, and then distributing the total opening value according to a certain strategy.
2. An indirect air-cooling control system for realizing an indirect air-cooling control method according to claim 1, characterized in that: the water temperature deviation monitoring system comprises a data acquisition module, a big data model calculation module, a mechanism model calculation module, a water temperature deviation processing module, a safety module, an execution processing module and an industrial controller, wherein the data acquisition module is simultaneously connected with the big data model calculation module, the mechanism model calculation module, the water temperature deviation processing module and the safety module, the execution processing module is connected with the big data model calculation module, the mechanism model calculation module and the water temperature deviation processing module, and the execution processing module and the safety module are connected with the industrial controller.
3. An indirect air-cooling control system according to claim 2, wherein: the big data model calculation module is a model established based on a big data processing algorithm and an artificial intelligence algorithm, inputs data collected by the data collection module, performs calculation by using the big data model, and outputs the big data opening degree of each sector shutter in indirect air cooling.
4. An indirect air-cooling control system according to claim 3, wherein: the mechanism model calculation module is a model established based on the heat exchange characteristics and the flow characteristics of water and air in indirect air cooling, inputs data acquired by the data acquisition module, and outputs the mechanism average opening degree of the shutters in each sector in the indirect air cooling.
5. An indirect air-cooling control system according to claim 4, wherein: the water temperature deviation processing module is a model established based on the outlet cold water temperature of the sector and the set outlet cold water temperature of the sector, inputs the outlet cold water temperature of the sector and the set outlet cold water temperature of the sector which are acquired by the data acquisition module, and outputs the supplement average opening degree of shutters of each sector in indirect air cooling.
6. An indirect air-cooling control system according to claim 4, wherein: the mechanism model calculation module takes one or more of the parameters of the temperature of a hot water main pipe of the unit, the temperature of a cold water main pipe of the sector, the flow of water entering indirect air cooling for heat exchange, the external wind speed of the indirect air cooling and the ambient temperature as variables.
7. An indirect air-cooling control system according to claim 2, wherein: the data that the data acquisition module gathered include the female pipe temperature of unit hot water, the female pipe temperature of unit cold water, the female pipe temperature of sector cold water, get into the flow that indirect air cooling was used for the water of heat transfer, the external wind speed of indirect air cooling, the external wind direction of indirect air cooling, ambient temperature, unit backpressure, unit power generation load, it has the situation to become the load instruction, the aperture of each executor of shutter, promote the electric current and the voltage of the circulating pump that gets into the pressure that indirect air cooling was used for the water of heat transfer, the setting temperature of the female pipe of sector cold water, the situation of using of computational control system, the temperature field of each sector.
8. An indirect air-cooling control system according to claim 5, wherein: the execution processing module analyzes and calculates output results of the mechanism model calculation module, the big data model calculation module and the water temperature deviation processing module, inputs mechanism average opening, big data opening and supplementary average opening and outputs opening values of actuators of all sectors in the unit.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20100024549A (en) * | 2008-08-26 | 2010-03-08 | 안상준 | Volume type damper louver for cooling tower |
| CN108469185A (en) * | 2018-01-25 | 2018-08-31 | 济南蓝辰能源技术有限公司 | A kind of antifreeze return water temperature control method of indirect air cooling system |
| CN110285687A (en) * | 2019-06-26 | 2019-09-27 | 双良节能系统股份有限公司 | A kind of air-cooled control system and its control method based on artificial intelligence technology |
| CN111735319A (en) * | 2020-06-29 | 2020-10-02 | 中国电力工程顾问集团西北电力设计院有限公司 | Control method, system and equipment for air cooling system of thermal power generating unit and readable storage medium |
| CN113031544A (en) * | 2021-03-01 | 2021-06-25 | 首航高科能源技术股份有限公司 | Indirect air cooling intelligent control system and method |
| CN113154930A (en) * | 2021-04-28 | 2021-07-23 | 国能龙源电力技术工程有限责任公司 | Steel structure indirect cooling tower temperature field monitoring system under 5G mode |
| CN113503749A (en) * | 2021-07-14 | 2021-10-15 | 无锡混沌能源技术有限公司 | Intelligent water temperature control method for indirect air cooling system |
-
2021
- 2021-12-10 CN CN202111506204.9A patent/CN114234662B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20100024549A (en) * | 2008-08-26 | 2010-03-08 | 안상준 | Volume type damper louver for cooling tower |
| CN108469185A (en) * | 2018-01-25 | 2018-08-31 | 济南蓝辰能源技术有限公司 | A kind of antifreeze return water temperature control method of indirect air cooling system |
| CN110285687A (en) * | 2019-06-26 | 2019-09-27 | 双良节能系统股份有限公司 | A kind of air-cooled control system and its control method based on artificial intelligence technology |
| CN111735319A (en) * | 2020-06-29 | 2020-10-02 | 中国电力工程顾问集团西北电力设计院有限公司 | Control method, system and equipment for air cooling system of thermal power generating unit and readable storage medium |
| CN113031544A (en) * | 2021-03-01 | 2021-06-25 | 首航高科能源技术股份有限公司 | Indirect air cooling intelligent control system and method |
| CN113154930A (en) * | 2021-04-28 | 2021-07-23 | 国能龙源电力技术工程有限责任公司 | Steel structure indirect cooling tower temperature field monitoring system under 5G mode |
| CN113503749A (en) * | 2021-07-14 | 2021-10-15 | 无锡混沌能源技术有限公司 | Intelligent water temperature control method for indirect air cooling system |
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