CN113536525A - Global optimal energy-saving control method for central air conditioner - Google Patents
Global optimal energy-saving control method for central air conditioner Download PDFInfo
- Publication number
- CN113536525A CN113536525A CN202110409779.2A CN202110409779A CN113536525A CN 113536525 A CN113536525 A CN 113536525A CN 202110409779 A CN202110409779 A CN 202110409779A CN 113536525 A CN113536525 A CN 113536525A
- Authority
- CN
- China
- Prior art keywords
- water
- cooling
- temperature
- mathematical model
- cooling water
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2113/00—Details relating to the application field
- G06F2113/08—Fluids
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/08—Thermal analysis or thermal optimisation
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Air Conditioning Control Device (AREA)
Abstract
The invention discloses a global optimal energy-saving control method for a central air conditioner, which is characterized in that mathematical models of a water chilling unit, a cooling tower, a cooling water pump, a freezing water pump, a fresh air fan, an air conditioner and a return air exhauster are established based on a system, host energy efficiency COP under each operation condition can be calculated through the models, the optimized chilled water outlet temperature of the water chilling unit is dynamically set, reasonable machine addition and subtraction judgment is dynamically carried out, the optimal operation frequency and the optimal number of the freezing water pump and the cooling water pump are determined, the optimal operation frequency and the optimal operation frequency of the cooling tower and the cooling fan are determined, the operation frequency and the water valve state of each fan of the air conditioner are adjusted, the lowest overall energy consumption of the central air conditioning system is taken as a control target, and the control parameters and the states of each device are reasonably adjusted by a control system, so that the operation efficiency of the whole central air conditioning system is optimal.
Description
Technical Field
The invention relates to the technical field of central air conditioner control, in particular to a global optimal energy-saving control method for a central air conditioner.
Background
The general main control method of the central air-conditioning system is as follows: the cooling water pump runs according to the temperature of the outlet water, and the water chilling unit carries out load loading and unloading according to the water temperature; the cooling tower and the cooling pump run at a fixed frequency, the chilled water pump generally runs at a variable frequency, and partial systems run at a fixed frequency. The air conditioner and the fan generally run at a fixed frequency, and the two-way valve adjusts the opening degree according to the proportional integral of the return air temperature.
The existing control method has the main problems that: 1. when part of the load operates or the outdoor temperature and humidity are low, the energy-saving operation can not be realized due to the fact that the cooling pump and the cooling tower operate at a fixed frequency; 2. the water coolers and the tower pumps are operated in a one-to-one correspondence mode, and under the partial load working condition, an energy-saving operation mode of one machine with two towers cannot be adopted; 4. the two-way valve is adjusted according to the proportional integral of the return air temperature, the actual operation usually vibrates, and the stable operation is difficult; 5. the air conditioner and the fan operate at a fixed frequency, and the fan cannot start an energy-saving operation mode under partial load. However, the existing patent documents CN107883519A, CN103335363A, and CN101839528A are all single energy-saving control methods for single components or systems of the central air conditioner, and for global overall control of the central air conditioner, the energy-saving effect is far from sufficient, but the existing technology lacks an optimal energy-saving control method for global scheduling of the central air conditioner.
Disclosure of Invention
Aiming at the problems, the invention provides a global optimal energy-saving control method for a central air conditioner, which mainly solves the problems in the background technology.
The invention provides a global optimal energy-saving control method for a central air conditioner, which specifically comprises the following steps:
s1, establishing a mathematical model of the water chilling unit according to actual equipment, calculating the host energy efficiency COP under each operation condition through the mathematical model, dynamically setting the outlet water temperature of chilled water of the water chilling unit, and correspondingly and dynamically judging the operation of adding and subtracting;
s2, establishing a mathematical model of the chilled water pump according to actual equipment, calculating the energy consumption of the chilled water pump under each operation condition through the mathematical model, dynamically adjusting the operation frequency of the chilled water pump, ensuring the water supply and return pressure difference at the worst end of a chilled water path loop system, and further meeting the requirements of the chilled water flow at the tail end of a central air conditioner;
s3, establishing a mathematical model of the cooling tower according to actual equipment, calculating the energy consumption of the cooling water pump under each operation condition through the mathematical model, determining the optimal number of running fans and the running frequency of the fans under the current condition, and dynamically adjusting the number of running fans and the running frequency of the cooling fans;
s4, establishing a mathematical model of the cooling water pump according to actual equipment, calculating the energy consumption of the cooling tower under each operation condition through the mathematical model, dynamically adjusting the operation frequency of the cooling water pump, and determining the optimal operation frequency and the optimal operation number of the cooling water pump on the premise of ensuring the overall optimization of the energy consumption of the cooling tower, the energy consumption of the cooling water pump and the energy consumption of the water chilling unit;
s5, establishing mathematical models of the tail end air conditioner and the water regulating valve according to actual equipment, calculating the energy consumption of the air conditioner under each operation condition and the water valve opening corresponding to different chilled water flows through the mathematical models, and dynamically regulating the operation frequency of the air conditioner and the water valve opening;
s6, establishing a mathematical model of the tail-end exhaust fan according to the actual equipment, calculating the energy consumption of the exhaust fan under each operation condition through the mathematical model, and dynamically adjusting the operation frequency of the exhaust fan.
In a further improvement, the step S1 specifically includes:
s11, establishing a mathematical model of the water chilling unit according to the operation performance parameters or delivery performance parameters of actual equipment of the water chilling unit, and continuously correcting variable parameters of the mathematical model by combining operation data in actual operation;
s12, calculating different inlet water temperatures and outlet water temperatures of chilled water, different inlet water temperatures and outlet water temperatures of the chilled water and host energy efficiency COP values under different load factors in a reasonable range meeting the requirements of energy-saving operation of a system and the comfort level of the tail end of an air conditioner according to a mathematical model;
s13, setting the maximum opening value and the indoor humidity threshold value of the two-way valve;
s14, measuring indoor humidity in real time, and recording the opening degree of the two-way valve in real time;
s15, dynamically performing load and unload operations on the water chilling unit according to the temperature and humidity requirements of the air conditioning environment, the cold requirement of the air conditioning environment and the optimization principle of the optimal global energy efficiency of the air conditioning system, and dynamically searching for the optimal chilled water outlet temperature of the water chilling unit;
s16, the concrete operations of loading and unloading of the water chiller are as follows: when the drop rate of the outlet water temperature of the chilled water exceeds a system set value, subtracting the outlet water temperature set value from a real-time measured value of the outlet water temperature of the chilled water to be larger than a given range, and when the average current percentage of the running refrigerator is higher than the set value, simultaneously meeting the above conditions and continuing for a specified time, starting loading operation; and when the real-time measured value of the outlet water temperature minus the set value is smaller than the set value of the system, the rated refrigerating capacity of the system after a plurality of water coolers in the water chiller are closed can still meet the load requirement and is higher than the set value of the total load before the water chiller is closed according to the capacity and the current percentage of the water coolers in operation, and machine reduction operation is executed.
In a further improvement, the step S2 specifically includes:
s21, establishing a mathematical model of the chilled water pump according to the operation performance parameters or delivery performance parameters of the actual equipment of the chilled water pump, and continuously correcting variable parameters of the mathematical model by combining operation data in actual operation;
s22, calculating the running efficiency and running power of the chilled water pump under running conditions of different flow, different lift and different frequency within a reasonable range meeting the requirements of energy-saving running and the comfort level of the tail end of the air conditioner according to a mathematical model, and setting the lowest running frequency of the chilled water pump;
s23, measuring the inlet water temperature and the outlet water temperature of the chilled water pump and the pressure difference of the supply water and the return water of the most unfavorable end equipment in real time;
s24, according to the principle of meeting the total cooling capacity requirement of the system and the global optimization of the central air conditioning system, under the condition of considering the requirement of meeting the supply and return water temperature difference of chilled water and the supply and return water pressure difference of the most unfavorable end equipment with the maximum pipeline resistance, determining the optimal operating frequency and the optimal number of chilled water pumps;
s25, calculating a chilled water temperature difference value between the chilled water inlet water temperature and the chilled water outlet water temperature, wherein the temperature difference value is equal to a value obtained by subtracting the chilled water outlet water temperature from the chilled water inlet water temperature;
and S26, when the difference value of the chilled water temperature is reduced, reducing the operating frequency of the chilled water pump, when the difference value of the chilled water temperature is increased, increasing the operating frequency of the chilled water pump, and when the difference value is not changed, returning to the step S25.
In a further improvement, the step S3 specifically includes:
s31, establishing a mathematical model of the cooling tower according to the operation performance parameters or delivery performance parameters of the actual equipment of the cooling tower, and continuously correcting the variable parameters of the mathematical model by combining operation data in the actual operation;
s32, setting the temperature difference temperature and the operation frequency of the cooling tower within the upper and lower limit ranges, wherein the operation frequency of a fan of the cooling tower needs to meet the requirement that the temperature of cooling water discharged from the cooling tower is ensured within the upper and lower limit ranges, the frequency of a cooling pump needs to meet the requirement that the temperature difference of cooling water for supplying and returning water is ensured within the upper and lower limit ranges, and if the temperature difference and the operation frequency exceed the upper and lower limit ranges, triggering a protection mechanism to readjust the operation frequency of the fan of the cooling tower until the operation frequency is within a regression protection range;
s33, measuring the outdoor wet bulb temperature, the cooling water inlet water temperature and the cooling water outlet water temperature of the cooling tower in real time, and calculating the cooling water temperature difference between the cooling water outlet water temperature and the cooling water inlet water temperature, wherein the cooling water temperature difference is equal to the value obtained by subtracting the cooling water inlet water temperature from the cooling water outlet water temperature, and the approximation degree is equal to the value obtained by subtracting the outdoor air wet bulb temperature from the cooling water outlet water temperature;
and S34, determining the optimal number of fans and the optimal fan operating frequency under the current working condition according to the principle of meeting the heat discharge requirement of the system and the global optimization of the air conditioning system, and dynamically adjusting the number of the cooling fans and the operating frequency.
The set point combination (cooling water temperature difference, number and frequency of water pumps running, number and frequency of cooling towers running) can ensure that the sum of the power of the cold machine, the cooling pump and the cooling tower under the current load is minimum, and the step S33 is returned.
In a further improvement, the step S4 specifically includes:
s41, establishing a mathematical model of the cooling water pump according to the operation performance parameters or delivery performance parameters of the actual equipment of the cooling water pump, and continuously correcting variable parameters of the mathematical model in the actual operation by combining operation data;
s42, calculating the operation efficiency and the operation power of the cooling water pump under the operation conditions of different flow rates, different lifts and different frequencies within a reasonable range meeting the requirements of energy-saving operation of the system and the comfort level of the tail end of the air conditioner according to a mathematical model, and setting the lowest operation frequency of the cooling water pump;
s43, measuring the inlet water temperature and the outlet water temperature of the cooling water pump in real time; calculating a cooling water temperature difference between the cooling water outlet temperature and the cooling water inlet temperature, the cooling water temperature difference being equal to a value obtained by subtracting the cooling water inlet temperature from the cooling water outlet temperature;
and S44, determining the optimal cooling water temperature difference temperature, the optimal cooling water pump running frequency and the optimal number of the cooling water pumps according to the global optimization principle of the central air-conditioning system and under the condition that the requirement of the water supply flow of the cooling tower is met and the overall optimal energy consumption of the cooling tower, the cooling water pump and the water chilling unit is ensured.
S45, when the actual operation frequency of the cooling water pump is lower than the optimal operation frequency, reducing the operation frequency of the cooling water pump; when the cooling water temperature difference increases, the operating frequency of the cooling water pump is increased, and when the cooling water temperature difference does not change, the process returns to step S43.
In a further improvement, the step S5 specifically includes:
s51, establishing mathematical models of the air conditioner and the water regulating valve according to the operation performance parameters or delivery performance parameters of actual equipment of the air conditioner and the water regulating valve, and continuously correcting variable parameters of the mathematical models by combining operation data in actual operation;
s52, calculating different air inlet dry bulb temperatures and wet bulb temperatures, different chilled water flow rates, different chilled water supply temperatures and operating power, air outlet dry bulb temperatures and wet bulb temperatures under operating conditions of different air conditioner fan frequencies within a reasonable range meeting the requirements of system energy-saving operation and air conditioner terminal comfort level according to a mathematical model;
s53, calculating the valve opening corresponding to different chilled water flows within a reasonable range according to the mathematical model;
s54, setting the lowest running frequency of the air feeder, setting the indoor dry bulb temperature and relative humidity threshold value, and setting the opening threshold value of the water valve;
s55, measuring the dry bulb temperature and the wet bulb temperature of the air inlet, the dry bulb temperature and the wet bulb temperature of the air outlet, the opening degree of a water valve and the water supply flow of the chilled water in real time;
and S56, dynamically adjusting the operation frequency of the air conditioner and the opening of a water valve according to the principle of meeting the total cooling capacity requirement of the system and the global optimization of the air conditioning system.
In a further improvement, the step S6 specifically includes:
s61, establishing a mathematical model of the exhaust fan according to the operation performance parameters or the delivery performance parameters of the actual equipment of the exhaust fan, and continuously correcting the variable parameters of the mathematical model by combining operation data in the actual operation;
s62, calculating the operation power of the exhaust fan under the operation conditions of different air volumes, different lifts and different frequencies within a reasonable range meeting the requirements of system energy-saving operation and air conditioner terminal comfort level according to a mathematical model;
s63, setting the lowest operation frequency of the return exhaust fan;
s64, recording the fresh air volume of the fresh air fan and the air volume of the blower in real time;
s65, calculating the air volume difference value between the fresh air volume and the air volume, wherein the air volume difference value is equal to the difference value obtained by subtracting the fresh air volume from the air volume;
and S66, when the air volume difference is reduced, reducing the running frequency of the air returning machine, when the air volume difference is increased, improving the running frequency of the air returning machine, and when the air volume difference is not changed, returning to the step S64.
The further improvement lies in that the control method of the fresh air machine is also included, and the control method specifically comprises the following steps:
s71, setting a low value and a high value of the carbon dioxide concentration, wherein the low value is lower than the high value by more than 200 ppm;
s72, measuring the indoor carbon dioxide concentration in real time;
s73, when the carbon dioxide concentration value is higher than the high value of the carbon dioxide concentration threshold value, starting a new fan to operate; when the carbon dioxide concentration value is lower than the low value of the carbon dioxide concentration threshold value, closing the fresh air fan; when the carbon dioxide concentration value is equal to the carbon dioxide concentration threshold value, return is made to step S72.
Compared with the prior art, the invention has the beneficial effects that:
the invention discloses a global optimal energy-saving control method for a central air conditioner, which is an energy-saving control method for multidimensional and active optimization of the whole central air conditioner system based on global optimal control of the whole operation of the system and a performance model. The control method is based on the overall performance characteristics of each device and the air system of the refrigerating machine room, and the optimal operation states (including valve opening, device frequency, opening number and the like) of the whole refrigerating machine room and the air system under the condition of meeting the process design and the cold quantity requirement are searched by a multi-dimensional optimization method, so that the optimal energy-saving goal is realized.
Detailed Description
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted" and "connected" are to be interpreted broadly, e.g., as being either fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, so to speak, as communicating between the two elements. The specific meaning of the above terms in the present invention can be understood in specific cases to those skilled in the art. The technical solution of the present invention is further described below with reference to examples.
The invention relates to a global optimal energy-saving control method for a central air conditioner, which is characterized in that mathematical models of a water chilling unit, a cooling tower, a cooling water pump, a freezing water pump, a fresh air fan, an air conditioner and a return air exhauster are established based on a system, host energy efficiency COP under each operation condition can be calculated through the models, the optimized chilled water outlet temperature of the water chilling unit is dynamically set, reasonable machine addition and subtraction judgment is dynamically carried out, the optimal operation frequency and the optimal number of the freezing water pumps and the optimal operation frequency of the cooling water pumps are determined, the optimal operation frequency and the optimal operation frequency of the cooling fan of the cooling tower are determined, the operation frequency of each fan of the air conditioner and the state of a water valve are adjusted, and the lowest overall energy consumption of the central air conditioning system is taken as a control target. The control system reasonably adjusts the control parameters and states of all the devices, so that the operation efficiency of the whole central air-conditioning system is optimal.
A global optimal energy-saving control method for a central air conditioner specifically comprises the following steps:
s1, establishing a mathematical model of the water chilling unit according to actual equipment, calculating the host energy efficiency COP under each operation condition through the mathematical model, dynamically setting the outlet water temperature of chilled water of the water chilling unit, and correspondingly and dynamically judging the operation of adding and subtracting;
s2, establishing a mathematical model of the chilled water pump according to actual equipment, calculating the energy consumption of the chilled water pump under each operation condition through the mathematical model, dynamically adjusting the operation frequency of the chilled water pump, ensuring the water supply and return pressure difference at the worst end of a chilled water path loop system, and further meeting the requirements of the chilled water flow at the tail end of a central air conditioner;
s3, establishing a mathematical model of the cooling tower according to actual equipment, calculating the energy consumption of the cooling water pump under each operation condition through the mathematical model, determining the optimal number of running fans and the running frequency of the fans under the current condition, and dynamically adjusting the number of running fans and the running frequency of the cooling fans;
s4, establishing a mathematical model of the cooling water pump according to actual equipment, calculating the energy consumption of the cooling tower under each operation condition through the mathematical model, dynamically adjusting the operation frequency of the cooling water pump, and determining the optimal operation frequency and the optimal operation number of the cooling water pump on the premise of ensuring the overall optimization of the energy consumption of the cooling tower, the energy consumption of the cooling water pump and the energy consumption of the water chilling unit;
s5, establishing mathematical models of the tail end air conditioner and the water regulating valve according to actual equipment, calculating the energy consumption of the air conditioner under each operation condition and the water valve opening corresponding to different chilled water flows through the mathematical models, and dynamically regulating the operation frequency of the air conditioner and the water valve opening;
s6, establishing a mathematical model of the tail-end exhaust fan according to the actual equipment, calculating the energy consumption of the exhaust fan under each operation condition through the mathematical model, and dynamically adjusting the operation frequency of the exhaust fan.
As a preferred embodiment of the present invention, the step S1 specifically includes:
s11, establishing a mathematical model of the water chilling unit according to the operation performance parameters or delivery performance parameters of actual equipment of the water chilling unit, and continuously correcting variable parameters of the mathematical model by combining operation data in actual operation;
s12, calculating different inlet water temperatures and outlet water temperatures of chilled water, different inlet water temperatures and outlet water temperatures of the chilled water and host energy efficiency COP values under different load factors in a reasonable range meeting the requirements of energy-saving operation of a system and the comfort level of the tail end of an air conditioner according to a mathematical model;
s13, setting the maximum opening value and the indoor humidity threshold value of the two-way valve;
s14, measuring indoor humidity in real time, and recording the opening degree of the two-way valve in real time;
s15, dynamically performing load and unload operations on the water chilling unit according to the temperature and humidity requirements of the air conditioning environment, the cold requirement of the air conditioning environment and the optimization principle of the optimal global energy efficiency of the air conditioning system, and dynamically searching for the optimal chilled water outlet temperature of the water chilling unit;
s16, the concrete operations of loading and unloading of the water chiller are as follows: when the drop rate of the outlet water temperature of the chilled water exceeds a system set value, subtracting the outlet water temperature set value from a real-time measured value of the outlet water temperature of the chilled water to be larger than a given range, and when the average current percentage of the running refrigerator is higher than the set value, simultaneously meeting the above conditions and continuing for a specified time, starting loading operation; and when the real-time measured value of the outlet water temperature minus the set value is smaller than the set value of the system, the rated refrigerating capacity of the system after a plurality of water coolers in the water chiller are closed can still meet the load requirement and is higher than the set value of the total load before the water chiller is closed according to the capacity and the current percentage of the water coolers in operation, and machine reduction operation is executed.
More specifically, a mathematical model of the chiller is established based on the actual equipment. The accurate and reasonable water chilling unit performance model reflects the basic operation characteristics of actual equipment, accords with the unique operation curve of the water chilling unit, and can calculate the host energy efficiency COP under each operation condition through the model. According to the principle of meeting the process design, the cold quantity requirement and the global optimization of the air conditioning system, the optimized chilled water outlet temperature of the water chilling unit is dynamically set, reasonable machine adding and subtracting judgment is dynamically carried out, and the power consumption is reduced.
As a preferred embodiment of the present invention, the step S2 specifically includes:
s21, establishing a mathematical model of the chilled water pump according to the operation performance parameters or delivery performance parameters of the actual equipment of the chilled water pump, and continuously correcting variable parameters of the mathematical model by combining operation data in actual operation;
s22, calculating the running efficiency and running power of the chilled water pump under running conditions of different flow, different lift and different frequency within a reasonable range meeting the requirements of energy-saving running and the comfort level of the tail end of the air conditioner according to a mathematical model, and setting the lowest running frequency of the chilled water pump;
s23, measuring the inlet water temperature and the outlet water temperature of the chilled water pump and the pressure difference of the supply water and the return water of the most unfavorable end equipment in real time;
s24, according to the principle of meeting the total cooling capacity requirement of the system and the global optimization of the central air conditioning system, under the condition of considering the requirement of meeting the supply and return water temperature difference of chilled water and the worst supply and return water pressure difference of the terminal equipment, determining the optimal operating frequency and the optimal number of chilled water pumps;
s25, calculating a chilled water temperature difference value between the chilled water inlet water temperature and the chilled water outlet water temperature, wherein the temperature difference value is equal to a value obtained by subtracting the chilled water outlet water temperature from the chilled water inlet water temperature;
and S26, when the difference value of the chilled water temperature is reduced, reducing the operating frequency of the chilled water pump, when the difference value of the chilled water temperature is increased, increasing the operating frequency of the chilled water pump, and when the difference value is not changed, returning to the step S25.
More specifically, a mathematical model of the chilled water pump is established based on the actual equipment. And the energy consumption of the water pump under each operation condition can be calculated by the model. And determining the optimal running frequency and the optimal number of the chilled water pumps according to the principle of meeting the total cooling capacity requirement of the system and the global optimization of the central air-conditioning system and considering the changes of chilled water supply/return water temperature and differential pressure. The running frequency of the water pump is matched, the return water supply pressure difference of the worst end of the chilled water loop system is ensured, the flow demand of chilled water at the tail end of the air conditioner is met, and the chilled water frequency is dynamically adjusted.
As a preferred embodiment of the present invention, the step S3 specifically includes:
s31, establishing a mathematical model of the cooling tower according to the operation performance parameters or delivery performance parameters of the actual equipment of the cooling tower, and continuously correcting the variable parameters of the mathematical model by combining operation data in the actual operation;
s32, setting the temperature difference temperature and the operation frequency of the cooling tower within the upper and lower limit ranges, (the upper limit of the operation frequency refers to the highest frequency of 50Hz, the lower limit is manually set, generally 25Hz or 30Hz, and the temperature difference temperature is generally 4-6 ℃), ensuring the temperature of the cooling water discharged from the cooling tower within the upper and lower limit ranges, ensuring the temperature difference of the cooling water supplied and returned within the upper and lower limit ranges by the frequency of a cooling pump, and triggering a protection mechanism to readjust the operation frequency of the cooling tower fan until the operation frequency is within the regression protection range if the temperature difference temperature and the operation frequency are beyond the ranges;
s33, measuring the outdoor wet bulb temperature, the cooling water inlet water temperature and the cooling water outlet water temperature of the cooling tower in real time, and calculating the cooling water temperature difference between the cooling water outlet water temperature and the cooling water inlet water temperature, wherein the cooling water temperature difference is equal to the value obtained by subtracting the cooling water inlet water temperature from the cooling water outlet water temperature, and the approximation degree is equal to the value obtained by subtracting the outdoor air wet bulb temperature from the cooling water outlet water temperature;
and S34, determining the optimal number of fans and the optimal fan operating frequency under the current working condition according to the principle of meeting the heat discharge requirement of the system and the global optimization of the air conditioning system, and dynamically adjusting the number of the cooling fans and the operating frequency.
The set point combination (cooling water temperature difference, number and frequency of water pumps running, number and frequency of cooling towers running) can ensure that the sum of the power of the cold machine, the cooling pump and the cooling tower under the current load is minimum, and the step S33 is returned.
More specifically, a mathematical model of the cooling tower is established based on the actual plant. And the energy consumption of the cooling tower under each operation condition can be calculated by the model. According to the principle of meeting the heat discharge requirement of the system and the global optimization of the air conditioning system, the optimal tower outlet water temperature under the current working condition is determined, the optimal fan operation number is automatically selected according to the temperature, and the cooling fan operation frequency is dynamically adjusted.
As a preferred embodiment of the present invention, the step S4 specifically includes:
s41, establishing a mathematical model of the cooling water pump according to the operation performance parameters or delivery performance parameters of the actual equipment of the cooling water pump, and continuously correcting variable parameters of the mathematical model in the actual operation by combining operation data;
s42, calculating the operation efficiency and the operation power of the cooling water pump under the operation conditions of different flow rates, different lifts and different frequencies within a reasonable range meeting the requirements of energy-saving operation of the system and the comfort level of the tail end of the air conditioner according to a mathematical model, and setting the lowest operation frequency of the cooling water pump;
s43, measuring the inlet water temperature and the outlet water temperature of the cooling water pump in real time; calculating a cooling water temperature difference between the cooling water outlet temperature and the cooling water inlet temperature, the cooling water temperature difference being equal to a value obtained by subtracting the cooling water inlet temperature from the cooling water outlet temperature;
and S44, determining the optimal cooling water temperature difference temperature, the optimal cooling water pump running frequency and the optimal number of the cooling water pumps according to the global optimization principle of the central air-conditioning system and under the condition that the requirement of the water supply flow of the cooling tower is met and the overall optimal energy consumption of the cooling tower, the cooling water pump and the water chilling unit is ensured.
S45, when the actual operation frequency of the cooling water pump is lower than the optimal operation frequency, reducing the operation frequency of the cooling water pump; when the cooling water temperature difference increases, the operating frequency of the cooling water pump is increased, and when the cooling water temperature difference does not change, the process returns to step S43.
More specifically, a mathematical model of the cooling water pump is established based on the actual equipment. And the energy consumption of the water pump under each operation condition can be calculated by the model. According to the global optimization principle of the central air-conditioning system, under the condition that the requirement of the water supply flow of the cooling tower is met and the overall optimization of the energy consumption of the cooling tower, the energy consumption of the cooling water pumps and the energy consumption of the water chilling unit is guaranteed, the optimal operating frequency and the number of the cooling water pumps are determined, and the chilled water frequency is dynamically adjusted.
As a preferred embodiment of the present invention, the step S5 specifically includes:
s51, establishing mathematical models of the air conditioner and the water regulating valve according to the operation performance parameters or delivery performance parameters of actual equipment of the air conditioner and the water regulating valve, and continuously correcting variable parameters of the mathematical models by combining operation data in actual operation;
s52, calculating different air inlet dry bulb temperatures and wet bulb temperatures, different chilled water flow rates, different chilled water supply temperatures and operating power, air outlet dry bulb temperatures and wet bulb temperatures under operating conditions of different air conditioner fan frequencies within a reasonable range meeting the requirements of system energy-saving operation and air conditioner terminal comfort level according to a mathematical model;
s53, calculating the valve opening corresponding to different chilled water flows within a reasonable range according to the mathematical model;
s54, setting the lowest running frequency of the air feeder, setting the indoor dry bulb temperature and relative humidity threshold value, and setting the opening threshold value of the water valve;
s55, measuring the dry bulb temperature and the wet bulb temperature of the air inlet, the dry bulb temperature and the wet bulb temperature of the air outlet, the opening degree of a water valve and the water supply flow of the chilled water in real time;
and S56, dynamically adjusting the operation frequency of the air conditioner and the opening of a water valve according to the principle of meeting the total cooling capacity requirement of the system and the global optimization of the air conditioning system.
More specifically, a mathematical model of the terminal air conditioning system is established based on the actual equipment. And the energy consumption of the air conditioning box under each operation condition can be calculated by the model. And dynamically adjusting the running frequency of each fan of the air conditioner and the states of an air valve and a water valve according to the principle of meeting the total cooling capacity requirement of the system and the global optimization of the air conditioning system.
As a preferred embodiment of the present invention, the step S6 specifically includes:
s61, establishing a mathematical model of the exhaust fan according to the operation performance parameters or the delivery performance parameters of the actual equipment of the exhaust fan, and continuously correcting the variable parameters of the mathematical model by combining operation data in the actual operation;
s62, calculating the operation power of the exhaust fan under the operation conditions of different air volumes, different lifts and different frequencies within a reasonable range meeting the requirements of system energy-saving operation and air conditioner terminal comfort level according to a mathematical model;
s63, setting the lowest operation frequency of the return exhaust fan;
s64, recording the fresh air volume of the fresh air fan and the air volume of the blower in real time;
s65, calculating the air volume difference value between the fresh air volume and the air volume, wherein the air volume difference value is equal to the difference value obtained by subtracting the fresh air volume from the air volume;
and S66, when the air volume difference is reduced, reducing the running frequency of the air returning machine, when the air volume difference is increased, improving the running frequency of the air returning machine, and when the air volume difference is not changed, returning to the step S64.
More specifically, basic characteristics of each main device and each air system of a machine room are taken as the basis, a mathematical model is established for the refrigerating machine room and the air system by combining an intelligent optimization algorithm based on the cold load of the system, the joint operation of each device and each air system in the refrigerating machine room is coordinated through various control and optimization measures, a matched device performance model is established for each device and each air system of a cold station, and the lowest overall energy consumption of a central air-conditioning system is taken as a control target. The control system reasonably adjusts the control parameters and states of all the devices, so that the operation efficiency of the whole central air-conditioning system is optimal.
As a preferred embodiment of the present invention, the present invention further includes a control method of a fresh air machine, specifically including:
s71, setting a low value and a high value of the carbon dioxide concentration, wherein the low value is lower than the high value by more than 200 ppm;
s72, measuring the indoor carbon dioxide concentration in real time;
s73, when the carbon dioxide concentration value is higher than the high value of the carbon dioxide concentration threshold value, starting a new fan to operate; when the carbon dioxide concentration value is lower than the low value of the carbon dioxide concentration threshold value, closing the fresh air fan; when the carbon dioxide concentration value is equal to the carbon dioxide concentration threshold value, return is made to step S72.
The above examples of the present invention are merely examples for clearly illustrating the present invention and are not intended to limit the embodiments of the present invention. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the claims of the present invention.
Claims (8)
1. A global optimal energy-saving control method for a central air conditioner is characterized by comprising the following steps:
s1, establishing a mathematical model of the water chilling unit according to actual equipment, calculating the host energy efficiency COP under each operation condition through the mathematical model, dynamically setting the outlet water temperature of chilled water of the water chilling unit, and correspondingly and dynamically judging the operation of adding and subtracting;
s2, establishing a mathematical model of the chilled water pump according to actual equipment, calculating the energy consumption of the chilled water pump under each operation condition through the mathematical model, dynamically adjusting the operation frequency of the chilled water pump, ensuring the water supply and return pressure difference at the worst end of a chilled water path loop system, and further meeting the requirements of the chilled water flow at the tail end of a central air conditioner;
s3, establishing a mathematical model of the cooling tower according to actual equipment, calculating the energy consumption of the cooling water pump under each operation condition through the mathematical model, determining the optimal number of running fans and the running frequency of the fans under the current condition, and dynamically adjusting the number of running fans and the running frequency of the cooling fans;
s4, establishing a mathematical model of the cooling water pump according to actual equipment, calculating the energy consumption of the cooling tower under each operation condition through the mathematical model, dynamically adjusting the operation frequency of the cooling water pump, and determining the optimal operation frequency and the optimal operation number of the cooling water pump on the premise of ensuring the overall optimization of the energy consumption of the cooling tower, the energy consumption of the cooling water pump and the energy consumption of the water chilling unit;
s5, establishing mathematical models of the tail end air conditioner and the water regulating valve according to actual equipment, calculating the energy consumption of the air conditioner under each operation condition and the water valve opening corresponding to different chilled water flows through the mathematical models, and dynamically regulating the operation frequency of the air conditioner and the water valve opening;
s6, establishing a mathematical model of the tail-end exhaust fan according to the actual equipment, calculating the energy consumption of the exhaust fan under each operation condition through the mathematical model, and dynamically adjusting the operation frequency of the exhaust fan.
2. The global optimal energy-saving control method for the central air conditioner according to claim 1, wherein the step S1 specifically comprises:
s11, establishing a mathematical model of the water chilling unit according to the operation performance parameters or delivery performance parameters of actual equipment of the water chilling unit, and continuously correcting variable parameters of the mathematical model by combining operation data in actual operation;
s12, calculating different inlet water temperatures and outlet water temperatures of chilled water, different inlet water temperatures and outlet water temperatures of the chilled water and host energy efficiency COP values under different load factors in a reasonable temperature range meeting the requirements of energy-saving operation of a system and the comfort level of the tail end of an air conditioner according to a mathematical model;
s13, setting the maximum opening value and the indoor humidity threshold value of the two-way valve;
s14, measuring indoor humidity in real time, and recording the opening degree of the two-way valve in real time;
s15, dynamically performing load and unload operations on the water chilling unit according to the temperature and humidity requirements of the air conditioning environment, the cold requirement of the air conditioning environment and the optimization principle of the optimal global energy efficiency of the air conditioning system, and dynamically searching for the optimal chilled water outlet temperature of the water chilling unit;
s16, the concrete operations of loading and unloading of the water chiller are as follows: when the drop rate of the outlet water temperature of the chilled water exceeds a system set value, subtracting the outlet water temperature from a real-time measured value of the outlet water temperature of the chilled water, wherein the system set value is larger than a given range, and when the average current percentage of the running refrigerator is higher than the set value, the above conditions are met and the loading operation is started when the specified time is continued; and when the real-time measured value of the outlet water temperature minus the set value is smaller than the set value of the system, the rated refrigerating capacity of the system after a plurality of water coolers in the water chiller are closed can still meet the load requirement and is higher than the set value of the total load before the water chiller is closed according to the capacity and the current percentage of the water coolers in operation, and machine reduction operation is executed.
3. The global optimal energy-saving control method for the central air conditioner according to claim 1, wherein the step S2 specifically comprises:
s21, establishing a mathematical model of the chilled water pump according to the operation performance parameters or delivery performance parameters of the actual equipment of the chilled water pump, and continuously correcting variable parameters of the mathematical model by combining operation data in actual operation;
s22, calculating the running efficiency and running power of the chilled water pump under running conditions of different flow, different lift and different frequency within a reasonable range meeting the requirements of energy-saving running and the comfort level of the tail end of the air conditioner according to a mathematical model, and setting the lowest running frequency of the chilled water pump;
s23, measuring the inlet water temperature and the outlet water temperature of the chilled water pump and the pressure difference of the supply water and the return water of the most unfavorable end equipment in real time;
s24, according to the principle of meeting the total cooling capacity requirement of the system and the global optimization of the central air conditioning system, under the condition of considering the requirement of meeting the supply and return water temperature difference of chilled water and the supply and return water pressure difference of the most unfavorable end equipment with the maximum pipeline resistance, determining the optimal operating frequency and the optimal number of chilled water pumps;
s25, calculating a chilled water temperature difference value between the chilled water inlet water temperature and the chilled water outlet water temperature, wherein the temperature difference value is equal to a value obtained by subtracting the chilled water outlet water temperature from the chilled water inlet water temperature;
and S26, when the difference value of the chilled water temperature is reduced, reducing the operating frequency of the chilled water pump, when the difference value of the chilled water temperature is increased, increasing the operating frequency of the chilled water pump, and when the difference value is not changed, returning to the step S25.
4. The global optimal energy-saving control method for the central air conditioner according to claim 1, wherein the step S3 specifically comprises:
s31, establishing a mathematical model of the cooling tower according to the operation performance parameters or delivery performance parameters of the actual equipment of the cooling tower, and continuously correcting the variable parameters of the mathematical model by combining operation data in the actual operation;
s32, setting the temperature difference temperature and the operation frequency of the cooling tower within the upper and lower limit ranges, wherein the operation frequency of a fan of the cooling tower needs to meet the requirement that the temperature of cooling water discharged from the cooling tower is ensured within the upper and lower limit ranges, the frequency of a cooling pump needs to meet the requirement that the temperature difference of cooling water for supplying and returning water is ensured within the upper and lower limit ranges, and if the temperature difference and the operation frequency exceed the upper and lower limit ranges, triggering a protection mechanism to readjust the operation frequency of the fan of the cooling tower until the operation frequency is within a regression protection range;
s33, measuring the outdoor wet bulb temperature, the cooling water inlet water temperature and the cooling water outlet water temperature of the cooling tower in real time, and calculating the cooling water temperature difference between the cooling water outlet water temperature and the cooling water inlet water temperature, wherein the cooling water temperature difference is equal to the value obtained by subtracting the cooling water inlet water temperature from the cooling water outlet water temperature, and the approximation degree is equal to the value obtained by subtracting the outdoor air wet bulb temperature from the cooling water outlet water temperature;
and S34, determining the optimal number of fans and the optimal fan operating frequency under the current working condition according to the principle of meeting the heat discharge requirement of the system and the global optimization of the air conditioning system, and dynamically adjusting the number of the cooling fans and the operating frequency.
5. The global optimal energy-saving control method for the central air conditioner according to claim 1, wherein the step S4 specifically comprises:
s41, establishing a mathematical model of the cooling water pump according to the operation performance parameters or delivery performance parameters of the actual equipment of the cooling water pump, and continuously correcting variable parameters of the mathematical model in the actual operation by combining operation data;
s42, calculating the operation efficiency and the operation power of the cooling water pump under the operation conditions of different flow rates, different lifts and different frequencies within a reasonable range meeting the requirements of energy-saving operation of the system and the comfort level of the tail end of the air conditioner according to a mathematical model, and setting the lowest operation frequency of the cooling water pump;
s43, measuring the inlet water temperature and the outlet water temperature of the cooling water pump in real time; calculating a cooling water temperature difference between the cooling water outlet temperature and the cooling water inlet temperature, the cooling water temperature difference being equal to a value obtained by subtracting the cooling water inlet temperature from the cooling water outlet temperature;
and S44, determining the optimal cooling water temperature difference temperature, the optimal cooling water pump running frequency and the optimal number of the cooling water pumps according to the global optimization principle of the central air-conditioning system and under the condition that the requirement of the water supply flow of the cooling tower is met and the overall optimal energy consumption of the cooling tower, the cooling water pump and the water chilling unit is ensured.
S45, when the actual operation frequency of the cooling water pump is lower than the optimal operation frequency, reducing the operation frequency of the cooling water pump; when the cooling water temperature difference increases, the operating frequency of the cooling water pump is increased, and when the cooling water temperature difference does not change, the process returns to step S43.
6. The global optimal energy-saving control method for the central air conditioner according to claim 1, wherein the step S5 specifically comprises:
s51, establishing mathematical models of the air conditioner and the water regulating valve according to the operation performance parameters or delivery performance parameters of actual equipment of the air conditioner and the water regulating valve, and continuously correcting variable parameters of the mathematical models by combining operation data in actual operation;
s52, calculating different air inlet dry bulb temperatures and wet bulb temperatures, different chilled water flow rates, different chilled water supply temperatures and operating power, air outlet dry bulb temperatures and wet bulb temperatures under operating conditions of different air conditioner fan frequencies within a reasonable range meeting the requirements of system energy-saving operation and air conditioner terminal comfort level according to a mathematical model;
s53, calculating the valve opening corresponding to different chilled water flows within a reasonable range according to the mathematical model;
s54, setting the lowest running frequency of the air feeder, setting the indoor dry bulb temperature and relative humidity threshold value, and setting the opening threshold value of the water valve;
s55, measuring the dry bulb temperature and the wet bulb temperature of the air inlet, the dry bulb temperature and the wet bulb temperature of the air outlet, the opening degree of a water valve and the water supply flow of the chilled water in real time;
and S56, dynamically adjusting the operation frequency of the air conditioner and the opening of a water valve according to the principle of meeting the total cooling capacity requirement of the system and the global optimization of the air conditioning system.
7. The global optimal energy-saving control method for the central air conditioner according to claim 1, wherein the step S6 specifically comprises:
s61, establishing a mathematical model of the exhaust fan according to the operation performance parameters or the delivery performance parameters of the actual equipment of the exhaust fan, and continuously correcting the variable parameters of the mathematical model by combining operation data in the actual operation;
s62, calculating the operation power of the exhaust fan under the operation conditions of different air volumes, different lifts and different frequencies within a reasonable range meeting the requirements of system energy-saving operation and air conditioner terminal comfort level according to a mathematical model;
s63, setting the lowest operation frequency of the return exhaust fan;
s64, recording the fresh air volume of the fresh air fan and the air volume of the blower in real time;
s65, calculating the air volume difference value between the fresh air volume and the air volume, wherein the air volume difference value is equal to the difference value obtained by subtracting the fresh air volume from the air volume;
and S66, when the air volume difference is reduced, reducing the running frequency of the air returning machine, when the air volume difference is increased, improving the running frequency of the air returning machine, and when the air volume difference is not changed, returning to the step S64.
8. The global optimal energy-saving control method for the central air conditioner according to claim 1, further comprising a control method for a fresh air machine, and specifically comprising:
s71, setting a low value and a high value of the carbon dioxide concentration, wherein the low value is lower than the high value by more than 200 ppm;
s72, measuring the indoor carbon dioxide concentration in real time;
s73, when the carbon dioxide concentration value is higher than the high value of the carbon dioxide concentration threshold value, starting a new fan to operate; when the carbon dioxide concentration value is lower than the low value of the carbon dioxide concentration threshold value, closing the fresh air fan; when the carbon dioxide concentration value is equal to the carbon dioxide concentration threshold value, return is made to step S72.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110409779.2A CN113536525A (en) | 2021-04-16 | 2021-04-16 | Global optimal energy-saving control method for central air conditioner |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110409779.2A CN113536525A (en) | 2021-04-16 | 2021-04-16 | Global optimal energy-saving control method for central air conditioner |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113536525A true CN113536525A (en) | 2021-10-22 |
Family
ID=78124322
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110409779.2A Pending CN113536525A (en) | 2021-04-16 | 2021-04-16 | Global optimal energy-saving control method for central air conditioner |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113536525A (en) |
Cited By (24)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114396714A (en) * | 2021-12-14 | 2022-04-26 | 广州智业节能科技有限公司 | System and method for automatically controlling and operating system starting number |
| CN114440410A (en) * | 2022-02-14 | 2022-05-06 | 深圳嘉力达节能科技有限公司 | Method for carrying out variable flow control on freezing and cooling water pumps based on heat exchange efficiency |
| CN114459133A (en) * | 2022-01-10 | 2022-05-10 | 广东建设职业技术学院 | Energy-saving control method and energy-saving control system for central air-conditioning system |
| CN114459136A (en) * | 2021-12-31 | 2022-05-10 | 佛山市联讯控制设备有限公司 | High-energy-efficiency optimization control method for terminal equipment of central air-conditioning system |
| CN114909791A (en) * | 2022-06-17 | 2022-08-16 | 杭州医学院 | Management and control system of central air-conditioning cooling water system of medical building |
| CN114963447A (en) * | 2022-05-23 | 2022-08-30 | 北京新兴合众科技有限公司 | Intelligent control system and method for water chilling unit |
| CN115115143A (en) * | 2022-08-25 | 2022-09-27 | 南京群顶科技有限公司 | Method for calculating optimal number of opened cooling tower and minimum operation energy consumption based on AI algorithm |
| CN115307377A (en) * | 2022-07-08 | 2022-11-08 | 万国数据服务有限公司 | Temperature regulating system control method and device, electronic equipment and readable storage medium |
| CN115373368A (en) * | 2022-08-19 | 2022-11-22 | 广州地铁设计研究院股份有限公司 | Online real-time energy efficiency monitoring and evaluating system for central air-conditioning refrigeration system |
| CN115493256A (en) * | 2022-11-21 | 2022-12-20 | 南京群顶科技股份有限公司 | Intelligent optimizing method for energy-saving operation of central refrigeration system |
| CN115682357A (en) * | 2022-10-31 | 2023-02-03 | 广州施杰节能科技有限公司 | Approximation degree-centered cooling water optimization method and independent control system |
| CN115682324A (en) * | 2022-11-08 | 2023-02-03 | 上海瑞森纳智能科技有限公司 | Central air-conditioning system energy-saving optimization control method, device, equipment and storage medium |
| CN115796055A (en) * | 2023-01-10 | 2023-03-14 | 北京云庐科技有限公司 | An Optimal Operation Adjustment Method Based on Simulation Model of Complete Air Conditioning System |
| CN115823928A (en) * | 2022-12-05 | 2023-03-21 | 西安交通大学 | An intelligent control system and control method for a cooling tower |
| CN115860445A (en) * | 2022-11-15 | 2023-03-28 | 中核陕西铀浓缩有限公司 | Multi-level cooperative scheduling method for uranium enrichment refrigerating unit and closed cooling tower |
| CN116029011A (en) * | 2021-10-26 | 2023-04-28 | 重庆美的通用制冷设备有限公司 | A HVAC water system energy consumption simulation calculation method and device |
| CN116068886A (en) * | 2022-12-09 | 2023-05-05 | 上海碳索能源服务股份有限公司 | Optimal control device of cooling water system of efficient refrigeration machine room |
| CN116258022A (en) * | 2023-05-11 | 2023-06-13 | 上海能誉科技股份有限公司 | Annual energy consumption analog simulation calculation method and system for high-efficiency refrigeration station house |
| CN116447726A (en) * | 2023-06-20 | 2023-07-18 | 上海能誉科技股份有限公司 | Control system and control method for chilled water circulation system of central air conditioner |
| CN116481150A (en) * | 2023-06-25 | 2023-07-25 | 烟台东方智能技术有限公司 | Efficient air conditioner room system energy efficiency optimization control method based on end cloud cooperation |
| CN116624969A (en) * | 2023-07-21 | 2023-08-22 | 蘑菇物联技术（深圳）有限公司 | Method, device and medium for determining temperature difference between supply and return cooling water |
| CN116734404A (en) * | 2023-06-06 | 2023-09-12 | 中国电子系统工程第三建设有限公司 | Energy-saving optimization control system and optimization method for central air conditioning system |
| CN117029238A (en) * | 2023-08-28 | 2023-11-10 | 中国建筑西南设计研究院有限公司 | Chilled water control system and control method |
| CN118446030A (en) * | 2024-07-01 | 2024-08-06 | 深圳市前海能源科技发展有限公司 | Air conditioning cooling water system parameter optimization method and device, equipment and storage medium |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102147146A (en) * | 2011-04-22 | 2011-08-10 | 黄真银 | Digital integrated intelligent control system of central air conditioner and adjusting method thereof |
| CN105020845A (en) * | 2015-03-09 | 2015-11-04 | 厦门立思科技股份有限公司 | Linkage energy-saving control system and method for air conditioning system |
| CN108151253A (en) * | 2017-12-21 | 2018-06-12 | 中国舰船研究设计中心 | A kind of air quantity variable air conditioner wind pushing temperature automatic compensating method |
| CN108489012A (en) * | 2018-01-30 | 2018-09-04 | 深圳市新环能科技有限公司 | Cold source of air conditioning energy efficiency model control method based on load prediction and constraint |
| CN109612030A (en) * | 2018-11-08 | 2019-04-12 | 广州地铁设计研究院股份有限公司 | A kind of full frequency conversion energy-saving control method of central air-conditioning |
| CN109631282A (en) * | 2018-12-21 | 2019-04-16 | 深圳市紫衡技术有限公司 | A kind of central air conditioner system control method and its system, equipment, storage medium |
| CN112346351A (en) * | 2020-11-19 | 2021-02-09 | 四川九门科技股份有限公司 | Thing networking device integration intelligence centralized control system based on BIM |
-
2021
- 2021-04-16 CN CN202110409779.2A patent/CN113536525A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102147146A (en) * | 2011-04-22 | 2011-08-10 | 黄真银 | Digital integrated intelligent control system of central air conditioner and adjusting method thereof |
| CN105020845A (en) * | 2015-03-09 | 2015-11-04 | 厦门立思科技股份有限公司 | Linkage energy-saving control system and method for air conditioning system |
| CN108151253A (en) * | 2017-12-21 | 2018-06-12 | 中国舰船研究设计中心 | A kind of air quantity variable air conditioner wind pushing temperature automatic compensating method |
| CN108489012A (en) * | 2018-01-30 | 2018-09-04 | 深圳市新环能科技有限公司 | Cold source of air conditioning energy efficiency model control method based on load prediction and constraint |
| CN109612030A (en) * | 2018-11-08 | 2019-04-12 | 广州地铁设计研究院股份有限公司 | A kind of full frequency conversion energy-saving control method of central air-conditioning |
| CN109631282A (en) * | 2018-12-21 | 2019-04-16 | 深圳市紫衡技术有限公司 | A kind of central air conditioner system control method and its system, equipment, storage medium |
| CN112346351A (en) * | 2020-11-19 | 2021-02-09 | 四川九门科技股份有限公司 | Thing networking device integration intelligence centralized control system based on BIM |
Cited By (33)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116029011A (en) * | 2021-10-26 | 2023-04-28 | 重庆美的通用制冷设备有限公司 | A HVAC water system energy consumption simulation calculation method and device |
| CN114396714B (en) * | 2021-12-14 | 2023-03-24 | 广州智业节能科技有限公司 | System and method for automatically controlling and operating system starting number |
| CN114396714A (en) * | 2021-12-14 | 2022-04-26 | 广州智业节能科技有限公司 | System and method for automatically controlling and operating system starting number |
| CN114459136A (en) * | 2021-12-31 | 2022-05-10 | 佛山市联讯控制设备有限公司 | High-energy-efficiency optimization control method for terminal equipment of central air-conditioning system |
| CN114459136B (en) * | 2021-12-31 | 2024-05-24 | 佛山市联讯控制设备有限公司 | High-energy-efficiency optimal control method for terminal equipment of central air conditioning system |
| CN114459133A (en) * | 2022-01-10 | 2022-05-10 | 广东建设职业技术学院 | Energy-saving control method and energy-saving control system for central air-conditioning system |
| CN114459133B (en) * | 2022-01-10 | 2024-07-05 | 广东建设职业技术学院 | Energy-saving control method and energy-saving control system for central air conditioning system |
| CN114440410A (en) * | 2022-02-14 | 2022-05-06 | 深圳嘉力达节能科技有限公司 | Method for carrying out variable flow control on freezing and cooling water pumps based on heat exchange efficiency |
| CN114440410B (en) * | 2022-02-14 | 2023-09-08 | 深圳嘉力达节能科技有限公司 | Variable flow control method for freezing and cooling water pump based on heat exchange efficiency |
| CN114963447A (en) * | 2022-05-23 | 2022-08-30 | 北京新兴合众科技有限公司 | Intelligent control system and method for water chilling unit |
| CN114909791A (en) * | 2022-06-17 | 2022-08-16 | 杭州医学院 | Management and control system of central air-conditioning cooling water system of medical building |
| CN115307377A (en) * | 2022-07-08 | 2022-11-08 | 万国数据服务有限公司 | Temperature regulating system control method and device, electronic equipment and readable storage medium |
| CN115373368A (en) * | 2022-08-19 | 2022-11-22 | 广州地铁设计研究院股份有限公司 | Online real-time energy efficiency monitoring and evaluating system for central air-conditioning refrigeration system |
| CN115115143A (en) * | 2022-08-25 | 2022-09-27 | 南京群顶科技有限公司 | Method for calculating optimal number of opened cooling tower and minimum operation energy consumption based on AI algorithm |
| CN115682357A (en) * | 2022-10-31 | 2023-02-03 | 广州施杰节能科技有限公司 | Approximation degree-centered cooling water optimization method and independent control system |
| CN115682324A (en) * | 2022-11-08 | 2023-02-03 | 上海瑞森纳智能科技有限公司 | Central air-conditioning system energy-saving optimization control method, device, equipment and storage medium |
| CN115860445A (en) * | 2022-11-15 | 2023-03-28 | 中核陕西铀浓缩有限公司 | Multi-level cooperative scheduling method for uranium enrichment refrigerating unit and closed cooling tower |
| CN115860445B (en) * | 2022-11-15 | 2024-02-09 | 中核陕西铀浓缩有限公司 | Multi-level collaborative scheduling method for uranium enrichment refrigerating unit and closed cooling tower |
| CN115493256A (en) * | 2022-11-21 | 2022-12-20 | 南京群顶科技股份有限公司 | Intelligent optimizing method for energy-saving operation of central refrigeration system |
| CN115823928B (en) * | 2022-12-05 | 2025-07-25 | 西安交通大学 | Intelligent control system and control method for cooling tower |
| CN115823928A (en) * | 2022-12-05 | 2023-03-21 | 西安交通大学 | An intelligent control system and control method for a cooling tower |
| CN116068886A (en) * | 2022-12-09 | 2023-05-05 | 上海碳索能源服务股份有限公司 | Optimal control device of cooling water system of efficient refrigeration machine room |
| CN115796055B (en) * | 2023-01-10 | 2023-04-07 | 北京云庐科技有限公司 | Optimized operation adjusting method based on complete air conditioning system simulation model |
| CN115796055A (en) * | 2023-01-10 | 2023-03-14 | 北京云庐科技有限公司 | An Optimal Operation Adjustment Method Based on Simulation Model of Complete Air Conditioning System |
| CN116258022A (en) * | 2023-05-11 | 2023-06-13 | 上海能誉科技股份有限公司 | Annual energy consumption analog simulation calculation method and system for high-efficiency refrigeration station house |
| CN116734404A (en) * | 2023-06-06 | 2023-09-12 | 中国电子系统工程第三建设有限公司 | Energy-saving optimization control system and optimization method for central air conditioning system |
| CN116447726A (en) * | 2023-06-20 | 2023-07-18 | 上海能誉科技股份有限公司 | Control system and control method for chilled water circulation system of central air conditioner |
| CN116481150B (en) * | 2023-06-25 | 2023-08-29 | 烟台东方智能技术有限公司 | Efficient air conditioner room system energy efficiency optimization control method based on end cloud cooperation |
| CN116481150A (en) * | 2023-06-25 | 2023-07-25 | 烟台东方智能技术有限公司 | Efficient air conditioner room system energy efficiency optimization control method based on end cloud cooperation |
| CN116624969A (en) * | 2023-07-21 | 2023-08-22 | 蘑菇物联技术（深圳）有限公司 | Method, device and medium for determining temperature difference between supply and return cooling water |
| CN116624969B (en) * | 2023-07-21 | 2023-10-10 | 蘑菇物联技术（深圳）有限公司 | Methods, equipment and media for determining the temperature difference between cooling water supply and return water |
| CN117029238A (en) * | 2023-08-28 | 2023-11-10 | 中国建筑西南设计研究院有限公司 | Chilled water control system and control method |
| CN118446030A (en) * | 2024-07-01 | 2024-08-06 | 深圳市前海能源科技发展有限公司 | Air conditioning cooling water system parameter optimization method and device, equipment and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113536525A (en) | Global optimal energy-saving control method for central air conditioner | |
| CN109631282B (en) | Central air-conditioning system control method and system, equipment and storage medium thereof | |
| CN110579046B (en) | Control method and device for electronic expansion valve in multi-split refrigeration operation | |
| CN104134100B (en) | A cloud-based energy-saving management system | |
| CN115325682B (en) | Optimal control method and device for monitoring performance of efficient intelligent refrigeration machine room | |
| CN106225362B (en) | A kind of control method and system of Double-head centrifugal refrigerating machines | |
| CN111678247B (en) | Operation control method of air conditioning equipment, air conditioning equipment and computer storage medium | |
| CN113739371B (en) | Central air conditioning system based on cloud cooperation and control method thereof | |
| CN113446705B (en) | Energy-saving control system and control method for subway efficient machine room | |
| CN102635926A (en) | Air conditioning system and pressure adjusting method for same | |
| CN107401806A (en) | Main frame and refrigerating water pump comprehensive energy efficiency lifting control method in central air conditioning freezing station | |
| CN110388706B (en) | Refrigerating pump operation optimization configuration method of central air-conditioning chilled water secondary pump system | |
| CN114459133A (en) | Energy-saving control method and energy-saving control system for central air-conditioning system | |
| CN115823706A (en) | Primary pump self-adaptive variable pressure difference energy-saving control system and method | |
| CN114611288A (en) | Intelligent efficient computer room energy-saving algorithm model of central air-conditioning system | |
| CN211903215U (en) | Energy-saving control system for subway efficient machine room | |
| CN108168170A (en) | A kind of cold storage refrigerating system intelligent control method based on on-line identification | |
| CN115507559A (en) | Control method of chiller and chiller | |
| CN115235052B (en) | Automatic adjusting control system of water chiller | |
| CN114508808B (en) | Magnetic suspension variable frequency water chilling unit | |
| CN114165898A (en) | Central air conditioner | |
| CN120274468A (en) | Double-compressor control system | |
| CN118376029B (en) | Refrigerating system energy saving method adopting AI algorithm | |
| CN116697530B (en) | Efficient machine room self-adaptive energy-saving control system and method based on working condition prediction | |
| CN118780019A (en) | A control system and method for a dual refrigeration circuit series reverse flow large temperature difference cold and hot air unit |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20211022 |
|
| RJ01 | Rejection of invention patent application after publication |