CN111442480A - Operation control method and system for air conditioning equipment, air conditioning equipment and storage medium - Google Patents

Operation control method and system for air conditioning equipment, air conditioning equipment and storage medium Download PDF

Info

Publication number
CN111442480A
CN111442480A CN202010269819.3A CN202010269819A CN111442480A CN 111442480 A CN111442480 A CN 111442480A CN 202010269819 A CN202010269819 A CN 202010269819A CN 111442480 A CN111442480 A CN 111442480A
Authority
CN
China
Prior art keywords
air conditioning
conditioning equipment
determining
water
energy efficiency
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
Application number
CN202010269819.3A
Other languages
Chinese (zh)
Inventor
方兴
李元阳
阎杰
梁锐
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
GD Midea Heating and Ventilating Equipment Co Ltd
Shanghai Meikong Smartt Building Co Ltd
Original Assignee
Midea Group Co Ltd
GD Midea Heating and Ventilating Equipment Co Ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Midea Group Co Ltd, GD Midea Heating and Ventilating Equipment Co Ltd filed Critical Midea Group Co Ltd
Priority to CN202010269819.3A priority Critical patent/CN111442480A/en
Publication of CN111442480A publication Critical patent/CN111442480A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F11/00—Control or safety arrangements
    • F24F11/30—Control or safety arrangements for purposes related to the operation of the system, e.g. for safety or monitoring
    • F24F11/46—Improving electric energy efficiency or saving
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F11/00—Control or safety arrangements
    • F24F11/62—Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
    • F24F11/63—Electronic processing
    • F24F11/64—Electronic processing using pre-stored data
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F11/00—Control or safety arrangements
    • F24F11/70—Control systems characterised by their outputs; Constructional details thereof
    • F24F11/80—Control systems characterised by their outputs; Constructional details thereof for controlling the temperature of the supplied air
    • F24F11/83—Control systems characterised by their outputs; Constructional details thereof for controlling the temperature of the supplied air by controlling the supply of heat-exchange fluids to heat-exchangers

Abstract

The invention provides an operation control method and system of air conditioning equipment, the air conditioning equipment and a storage medium, wherein the operation control method of the air conditioning equipment comprises the following steps: acquiring an operation data set of the air conditioning equipment; determining the total load of the air conditioning equipment according to the operation data set, and determining a starting and stopping scheme set of a water chilling unit corresponding to the total load; determining a first energy efficiency parameter of any water chilling unit corresponding to the start-stop scheme set according to the operation data set, and determining a second energy efficiency parameter corresponding to each start-stop scheme in the start-stop scheme set according to the first energy efficiency parameter; and determining a target start-stop scheme in the start-stop scheme set according to the second energy efficiency parameter, and controlling the air conditioning equipment to operate according to the target start-stop scheme. The invention can enable the final target start-stop scheme to correspond to the actual operation condition of the current air-conditioning equipment, and meet the optimal energy efficiency ratio corresponding to the current operation condition, thereby effectively improving the operation energy efficiency of the air-conditioning equipment.

Description

Operation control method and system for air conditioning equipment, air conditioning equipment and storage medium
Technical Field
The present invention relates to the field of air conditioning equipment technology, and in particular, to an operation control method for air conditioning equipment, an operation control system for air conditioning equipment, and a computer-readable storage medium.
Background
In the related art, since the chiller operates under a partial load most of the time, in order to reduce the operating energy consumption of the air conditioning equipment and improve the efficiency, the operating load of the chiller needs to be optimally distributed according to the air conditioning load, so that the chiller always operates in a high-efficiency interval. However, in the current start-stop control, the water chilling unit is controlled by preset upper and lower limit values of load, and the actual working condition of the air conditioning equipment is not considered, so that the overall COP (Coefficient of performance) of the air conditioning equipment is not high.
Disclosure of Invention
The present invention is directed to solving at least one of the problems of the prior art or the related art.
To this end, a first aspect of the present invention proposes an operation control method of an air conditioning apparatus.
A second aspect of the present invention provides an operation control system of an air conditioning apparatus.
A third aspect of the invention proposes an air conditioning apparatus.
A fourth aspect of the present invention is directed to a computer-readable storage medium.
In view of the above, a first aspect of the present invention provides an operation control method for an air conditioning apparatus, the air conditioning apparatus including a plurality of chiller units, the operation control method including: acquiring an operation data set of the air conditioning equipment; determining the total load of the air conditioning equipment according to the operation data set, and determining a starting and stopping scheme set of a water chilling unit corresponding to the total load; determining a first energy efficiency parameter of any water chilling unit corresponding to the start-stop scheme set according to the operation data set, and determining a second energy efficiency parameter corresponding to each start-stop scheme in the start-stop scheme set according to the first energy efficiency parameter; and determining a target start-stop scheme in the start-stop scheme set according to the second energy efficiency parameter, and controlling the air conditioning equipment to operate according to the target start-stop scheme.
In the technical scheme, a real-time operation data set in the operation process of the air conditioner equipment is obtained, and the operation data set can reflect the actual operation condition of the air conditioner. The method comprises the steps of determining the total load of the air conditioning equipment through an operation data set, determining a preset set containing one or more start-stop schemes according to a load interval corresponding to the total load, and respectively determining a first energy efficiency parameter of each corresponding water chilling unit in the set.
And then, according to the first energy efficiency coefficient of the water chilling unit in each start-stop scheme, further determining second energy efficiency parameters of all alternative start-stop schemes in the start-stop scheme set to obtain a better COP of each alternative start-stop scheme in the start-stop scheme set, determining a start-stop scheme with the highest COP through comparison, determining the start-stop scheme with the optimal COP as a target start-stop scheme, and correspondingly controlling the air conditioning equipment to operate.
According to the technical scheme provided by the invention, the running data set is generated by acquiring real-time running data, the COP of each water chilling unit and the better COP corresponding to each starting and stopping scheme in all alternative starting and stopping schemes are further determined, so that the final target starting and stopping scheme is the scheme with the optimal energy efficiency ratio under the current air-conditioning equipment running working condition, and the running energy efficiency of the air-conditioning equipment is effectively improved.
In addition, the operation control method of the air conditioning equipment in the above technical solution provided by the present invention may further have the following additional technical features:
in the above technical solution, the operation data set includes: the air conditioning system comprises an air conditioning device, a cooling water outlet temperature, an air conditioning device cooling water inlet temperature, an air conditioning device cooling water flow, an air conditioning device cooling water outlet temperature, an air conditioning device cooling water return temperature and an air conditioning device cooling water flow.
In the technical scheme, the operation data set comprises the outlet water temperature, the inlet water temperature and the freezing water flow of the freezing water, and the outlet water temperature, the inlet water temperature and the cooling water flow of the cooling water, and the actual operation condition of the air conditioning equipment can be accurately reflected according to the parameters of the freezing water and the cooling water, so that the determined start-stop scheme is the scheme with the optimal energy efficiency ratio under the current actual operation condition, and the operation control effect of the air conditioning equipment is improved.
In any of the above technical solutions, the first energy efficiency parameter is determined by a first preset function, where the first preset function specifically is:
Figure BDA0002442735430000021
wherein COP is a first energy efficiency parameter,
Figure BDA0002442735430000031
the coefficient is corrected for the flow rate of the freezing water, and
Figure BDA0002442735430000032
the coefficient is corrected for the cooling water flow, and
Figure BDA0002442735430000033
b1、b2、b3、b4、b5、b6and b7As a fitting coefficient, the fitting coefficient is constant, Tcw,inFor the inlet water temperature of the cooling water, Tchw,outIs the temperature of the outlet water of the chilled water, Q is the total load, MchwFor chilled water flow, Mchw,desRated flow of chilled water, McwFor cooling water flow, Mcw,desThe rated flow rate of cooling water.
In the technical scheme, a COP regression function, namely a first preset function, is provided, so that the COP of the water chilling unit, namely a first energy efficiency parameter, can be accurately calculated, and further, each started water chilling unit can be ensured to operate in a higher COP interval in a finally determined start-stop scheme. Wherein，b1To b7The fitting coefficient is related to the actual cooling or heating capacity of the air conditioner.
In any of the above technical solutions, the second energy efficiency parameter is determined by a second preset function, where the second preset function specifically is:
Figure BDA0002442735430000034
wherein maxCop is a second energy efficiency parameter, Q is a total load, and Q isiThe load, COP, corresponding to the ith water chilling unitiAnd the energy efficiency parameter is a first energy efficiency parameter corresponding to the ith water chilling unit.
In the technical scheme, a COP optimization function is provided, and according to the COP optimization function, the energy efficiency ratio COP of each water chilling unit in the start-stop scheme obtained from the COP regression functioniAnd finally, the COP of each alternative start-stop scheme is obtained, the result is accurate, the calculated amount is small, and the accuracy and the operation efficiency of operation control can be effectively improved.
In any of the above technical solutions, the operation control method of the air conditioning equipment further includes: receiving a setting instruction corresponding to the fitting coefficient, and determining the fitting coefficient according to the setting instruction; and receiving an updating instruction corresponding to the fitting coefficient, and updating the fitting coefficient according to the updating instruction.
In the technical scheme, as the output capacity of the air conditioning equipment may change along with the increase of the service time, the setting instruction and the updating instruction corresponding to the fitting coefficient are received from the server every preset time interval, and the new fitting instruction is determined or the existing fitting instruction is updated, so that the accuracy of the COP regression function is ensured, and the reliability and the accuracy of the operation control of the air conditioning equipment are improved.
In any of the above technical solutions, the start-stop scheme set includes a plurality of start-stop schemes, and the step of determining the target start-stop scheme in the start-stop scheme set according to the second energy efficiency parameter specifically includes:
and calculating the fitness of the plurality of second energy efficiency parameters through a particle swarm optimization algorithm, and determining a target start-stop scheme corresponding to the second energy efficiency parameter with the highest fitness as the target start-stop scheme.
In the technical scheme, when a plurality of start-stop schemes in the start-stop scheme set are determined, the fitness of a plurality of second energy efficiency parameters is calculated through a particle swarm optimization algorithm, the second energy efficiency parameters with the highest fitness are finally obtained through comparison, the start-stop scheme corresponding to the second energy efficiency parameters with the highest fitness is selected and used as the target start-stop scheme, the control effect can be effectively improved, and the air conditioning equipment can operate with a high energy efficiency ratio.
The particle swarm optimization algorithm specifically comprises the following steps:
1. initializing the setting parameters of the particle swarm algorithm, mainly comprising the number of particles, the dimension of the particles, the inertial weight, the initial speed, the learning factor, the stopping condition and the like, and defining a fitness function.
2. The fitness of each particle was evaluated.
3. For each particle, comparing the adaptive value of the particle with the individual optimal value pbest of the particle, and taking the better party as the current pbest; and simultaneously comparing the adaptive value of the particle with the optimal value gbest of the group of the adaptive value of the particle, and taking the better part as the current gbest.
4. The particle velocity and particle position are updated separately according to:
vj(t+1)＝w×vj(t)+c1×R1(t)×(Pj(t)-xj(t))+c2×R2(t)×(Pg(t)-xj(t))；
xj(t+1)＝xj(t)+vj(t+1)；
wherein n is the total number of particles in the population, vjIs the velocity of the particle; w is the inertial weight, PjFor individual extrema, representing the optimum value, P, searched for by the particle itselfgFor a global extreme, representing the optimum value, R, in the current population of particles1(t) and R2(t) is a random number between (0, 1), xjIs the current position of the particle, c1And c2Is a learning factor.
In any of the above technical solutions, the operation control method of the air conditioning equipment further includes: acquiring operation data of air conditioning equipment; and performing data cleaning on the operation data to obtain an operation data set.
In the technical scheme, because the operation data set may include abnormal operation data, such as zero drift data generated by a sensor, data loss generated in a network transmission process, and the like, in order to improve the accuracy, the operation data is subjected to data cleaning in a big data cleaning mode to remove noise data in the data, so that a more accurate operation data set is obtained, the accuracy of control and calculation is further improved, and the operation energy efficiency of the air conditioning equipment is improved.
In any of the above counting method schemes, the step of performing data cleaning on the operation data to obtain an operation data set specifically includes: sequencing the operating data to obtain an operating data sequence; determining an operation data interval according to the operation data sequence, acquiring operation data in the operation data interval, and determining the operation data as a first data set; filling the first data set by a hot card filling method to obtain a second data set; and determining the working condition characteristics corresponding to each operating data in the second data set, acquiring the operating data corresponding to the working condition characteristics in the second data set, which accord with the preset working condition characteristics, and determining the operating data as the operating data set.
In the technical scheme, the data cleaning of the operation data can be divided into the following steps:
first, outlier culling is performed. Specifically, the operation data of the same category are sorted according to the numerical value, so that an operation parameter sequence arranged according to the numerical value is obtained, a target parameter interval is determined according to the operation parameter sequence, wherein the upper quartile value and the lower quartile value of the operation parameter sequence can be calculated, the upper quartile value and the lower quartile value are used as boundary values to determine the upper boundary and the lower boundary of the target parameter interval, and when the operation parameter exceeds the upper boundary and the lower boundary of the target operation parameter, the data are judged to be abnormal. Due to the fact that conditions such as sensor drifting exist in the operation process, abnormal large values and abnormal small values of operation parameters can be caused, and therefore after the data are removed, a first data set of the operation parameters which can reflect normal operation conditions better can be obtained.
In a second step, missing value supplementation is performed on the first data set. Specifically, if the first data set has missing necessary data, a historical parameter closest to a working condition of a missing value is searched in a unit historical operation database through a hot card filling method, and the missing value is supplemented through the historical parameter, so that a second data set with better integrity is obtained.
And thirdly, screening the second data set under stable working conditions. Specifically, the working condition characteristic corresponding to each operating data in the second data set is determined, and whether the working condition characteristic meets the preset working condition or not is judged. In the operation process of the air conditioning equipment, extreme operation conditions such as start-stop process and the like can occur, and the corresponding working condition is unstable, so that only the operation data of the second data set under the stable working condition is obtained, and the operation data set is generated according to the operation parameters, so that the operation control effect of the air conditioning equipment can be ensured, and the energy efficiency of the air conditioning equipment is effectively improved.
In any of the above technical solutions, the target start-stop scheme includes a target chiller unit and a start-stop state and a target load rate corresponding to the target chiller unit; the method comprises the following steps of controlling the operation of the air conditioning equipment according to a target start-stop scheme, and specifically comprises the following steps: and controlling the target water chilling unit to work according to a certain starting and stopping state and a target load rate.
In the technical scheme, the start-stop scheme comprises a target water chilling unit which is started or closed, and a start-stop state and a target load rate which correspond to the target water chilling unit, so as to control the load rate of the target water chilling unit. When attention needs to be paid, in the start-stop scheme, the total load of all started water chilling units needs to be equal to the total load of the tail end of the air conditioner, and the load rate of each started water chilling unit needs to be between the maximum load rate and the minimum load rate of the water chilling unit. Wherein the maximum load rate is 1, and the minimum load rate is related to the performance of the water chilling unit.
In any of the above technical solutions, the operation control method of the air conditioning equipment further includes: determining a change value of the total load within a preset time length; and determining that the change value is greater than or equal to the change threshold, and executing a step of determining a start-stop scheme set of the water chilling unit corresponding to the total load.
In the technical scheme, the change value of the total load in the preset time length is determined. Specifically, the preset time duration may be set according to the actual operating environment of the system, and if the preset time duration is set to 15 minutes, after recording the total load of the system once, recording the total load of the system again after 15 minutes, and calculating a difference between the two recorded total loads. If the difference is smaller than the variation threshold, the working condition of the air conditioning equipment tends to be stable, no load change is generated, at the moment, a better energy efficiency ratio can be ensured only by depending on the load adjustment of each unit, and the start-stop scheme does not need to be adjusted.
If the difference is larger than or equal to the variation threshold, it indicates that the start-stop scheme needs to be adjusted, and at this time, a step of determining a set of start-stop schemes of the water chilling unit corresponding to the total load is executed. The variation threshold may be determined according to the rated load of the air conditioner, for example, set to 10% of the rated load.
A second aspect of the present invention provides an operation control system of an air conditioning apparatus, including: a memory configured to store a computer program; the processor is configured to execute the computer program to implement the operation control method of the air conditioning equipment provided in any one of the above technical solutions, and therefore, the operation control system of the air conditioning equipment includes all the beneficial effects of the operation control method of the air conditioning equipment provided in any one of the above technical solutions, which are not described herein again.
A third aspect of the present invention provides an air conditioner apparatus comprising: the water chilling units comprise compressors, cooling water pipes, freezing water pipes, heat exchangers and throttling devices; the detection device is configured to acquire the chilled water outlet temperature, the chilled water inlet temperature and the chilled water flow of the chilled water pipe, and the cooling water outlet temperature, the cooling water return temperature and the cooling water flow of the cooling water pipe; according to the operation control system of the air conditioning equipment provided by any one of the technical schemes, the operation control system of the air conditioning equipment is connected with the water chilling unit and the detection device.
In this technical solution, the air conditioning equipment includes the operation control system of the air conditioning equipment provided in any one of the above technical solutions, and therefore, the air conditioning equipment includes all the beneficial effects of the operation control system of the air conditioning equipment provided in any one of the above technical solutions, which are not described herein again.
A fourth aspect of the present invention provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the operation control method for an air conditioning device according to any one of the above technical solutions, and therefore, the computer-readable storage medium includes all the beneficial effects of the operation control method for an air conditioning device according to any one of the above technical solutions, and is not described herein again.
Drawings
The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
fig. 1 is a flowchart illustrating an operation control method of an air conditioner according to an embodiment of the present invention;
fig. 2 illustrates another flowchart of an operation control method of an air conditioner according to an embodiment of the present invention;
fig. 3 illustrates still another flowchart of an operation control method of an air conditioner according to an embodiment of the present invention;
fig. 4 is still another flowchart illustrating an operation control method of an air conditioner according to an embodiment of the present invention;
fig. 5 is still another flowchart illustrating an operation control method of an air conditioner according to an embodiment of the present invention;
fig. 6 is still another flowchart illustrating an operation control method of an air conditioner according to an embodiment of the present invention;
fig. 7 is still another flowchart illustrating an operation control method of an air conditioner according to an embodiment of the present invention;
fig. 8 is a diagram illustrating a COP performance curve of a chiller in an operation control method of an air conditioning apparatus according to an embodiment of the present invention;
fig. 9 is a graph showing a comparison of COP performance curves of a chiller in an operation control method of an air conditioning apparatus according to an embodiment of the present invention;
fig. 10 is a graph showing a comparison of COP performance curves of another chiller in an operation control method of an air conditioning apparatus according to an embodiment of the present invention;
fig. 11 is a block diagram illustrating an operation control system of an air conditioner according to an embodiment of the present invention.
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those specifically described herein, and therefore the scope of the present invention is not limited by the specific embodiments disclosed below.
An operation control method of an air conditioner, an operation control system of an air conditioner, and a computer-readable storage medium according to some embodiments of the present invention are described below with reference to fig. 1 to 11.
Example one
As shown in fig. 1, in an embodiment of the present invention, there is provided an operation control method of an air conditioning apparatus, the air conditioning apparatus including a plurality of water chilling units, the operation control method including:
step S102, acquiring an operation data set of the air conditioning equipment;
step S104, determining the total load of the air conditioning equipment according to the operation data set, and determining a starting and stopping scheme set of the water chilling unit corresponding to the total load;
step S106, determining a first energy efficiency parameter of any water chilling unit corresponding to the start-stop scheme set according to the operation data set, and determining a second energy efficiency parameter corresponding to each start-stop scheme in the start-stop scheme set according to the first energy efficiency parameter;
and S108, determining a target start-stop scheme in the start-stop scheme set according to the second energy efficiency parameter, and controlling the air conditioning equipment to operate according to the target start-stop scheme.
Wherein the operational data set comprises: the air conditioning system comprises an air conditioning device, a cooling water outlet temperature, an air conditioning device cooling water inlet temperature, an air conditioning device cooling water flow, an air conditioning device cooling water outlet temperature, an air conditioning device cooling water return temperature and an air conditioning device cooling water flow.
In step S106, a first energy efficiency parameter is determined by a first preset function, and a second energy efficiency parameter is determined by a second preset function.
The first preset function is specifically:
Figure BDA0002442735430000091
wherein COP is a first energy efficiency parameter, and
Figure BDA0002442735430000092
is a correction coefficient for the flow rate of the chilled water,
Figure BDA0002442735430000093
the coefficient is corrected for the cooling water flow, and
Figure BDA0002442735430000094
b1、b2、b3、b4、b5、b6and b7As a fitting coefficient, the fitting coefficient is constant, Tcw,inFor the inlet water temperature of the cooling water, Tchw,outIs the temperature of the outlet water of the chilled water, Q is the total load, MchwFor chilled water flow, Mchw,desRated flow of chilled water, McwFor cooling water flow, Mcw,desThe rated flow rate of cooling water.
The second preset function is specifically:
Figure BDA0002442735430000095
wherein maxCop is a second energy efficiency parameter, Q is a total load, and Q isiThe load, COP, corresponding to the ith water chilling unitiAnd the energy efficiency parameter is a first energy efficiency parameter corresponding to the ith water chilling unit.
In the embodiment, a real-time operation data set in the operation process of the air conditioner equipment is obtained, and the operation data set can reflect the actual operation condition of the air conditioner. The method comprises the steps of determining the total load of the air conditioning equipment through an operation data set, determining a preset start-stop scheme set containing one or more start-stop schemes according to a load interval corresponding to the total load, and respectively determining a first energy efficiency parameter of each water chilling unit corresponding to the set.
And then, according to the first energy efficiency parameter of the water chilling unit in each start-stop scheme, further determining second energy efficiency parameters of all alternative start-stop schemes in the start-stop scheme set to obtain a better COP of each alternative start-stop scheme in the start-stop scheme set, determining a start-stop scheme with the highest COP through comparison, determining the start-stop scheme with the optimal COP as a target start-stop scheme, and correspondingly controlling the operation of the air conditioning equipment.
The operation data set comprises the outlet water temperature, the inlet water temperature and the freezing water flow of the freezing water, the outlet water temperature, the inlet water temperature and the cooling water flow of the cooling water, and the actual operation working condition of the air conditioning equipment can be accurately reflected according to the parameters of the freezing water and the cooling water, so that the determined start-stop scheme is the scheme with the optimal energy efficiency ratio under the current actual operation working condition, and the operation control effect of the air conditioning equipment is improved.
By providing a COP regression function and a COP optimization function, namely a first preset function and a second preset function, the COP of the water chilling unit, namely a first energy efficiency parameter, can be accurately calculated through the first preset function, and therefore it can be guaranteed that in a finally determined start-stop scheme, each started water chilling unit operates in a higher COP interval. Wherein, b1To b7The fitting coefficient is related to the actual cooling or heating capacity of the air conditioner.
And by a second preset function, namely a COP optimization function, according to a function regressed by COPEnergy efficiency ratio COP of each water chilling unit in number-obtained starting and stopping schemeiAnd finally, the COP of each alternative start-stop scheme is obtained, the result is accurate, the calculated amount is small, and the accuracy and the operation efficiency of operation control can be effectively improved.
According to the embodiment provided by the invention, the running data set is generated by acquiring real-time running data, the COP of each corresponding water chilling unit and the better COP corresponding to each starting and stopping scheme in all alternative starting and stopping schemes are further determined, so that the final target starting and stopping scheme is the scheme with the optimal energy efficiency ratio under the current running working condition, and the running efficiency of the air conditioning equipment is effectively improved.
Example two
As shown in fig. 2, in an embodiment of the present invention, the operation control method of the air conditioner further includes:
step S202, receiving a setting instruction corresponding to the fitting coefficient, and determining the fitting coefficient according to the setting instruction;
and step S204, receiving an updating instruction corresponding to the fitting coefficient, and updating the fitting coefficient according to the updating instruction.
In this embodiment, since the output capacity of the air conditioning equipment may change as the service time increases, every interval of the preset duration, the server receives the setting instruction and the updating instruction corresponding to the fitting coefficient, and determines a new fitting instruction or updates the existing fitting instruction, so as to ensure the accuracy of the COP regression function and improve the reliability and accuracy of the operation control of the air conditioning equipment.
EXAMPLE III
In an embodiment of the present invention, the start-stop scheme set includes a plurality of start-stop schemes, and the step of determining the target start-stop scheme in the start-stop scheme set according to the second energy efficiency parameter specifically includes:
and calculating the fitness of the plurality of second energy efficiency parameters through a particle swarm optimization algorithm, and determining a target start-stop scheme corresponding to the second energy efficiency parameter with the highest fitness as the target start-stop scheme.
In this embodiment, when it is determined that the start-stop scheme set includes a plurality of start-stop schemes, the fitness of the plurality of second energy efficiency parameters is calculated through a particle swarm optimization algorithm, the second energy efficiency parameters with the highest fitness are finally obtained through comparison, and the start-stop scheme corresponding to the second energy efficiency parameter with the highest fitness is selected as the target start-stop scheme, so that the control effect can be effectively improved, and the operation energy efficiency of the air conditioning equipment is further improved.
The particle swarm optimization algorithm specifically comprises the following steps:
1. initializing the setting parameters of the particle swarm algorithm, mainly comprising the number of particles, the dimension of the particles, the inertial weight, the initial speed, the learning factor, the stopping condition and the like, and defining a fitness function.
2. The fitness of each particle was evaluated.
3. For each particle, comparing the adaptive value of the particle with the individual optimal value pbest of the particle, and taking the better party as the current pbest; and simultaneously comparing the adaptive value of the particle with the optimal value gbest of the group of the adaptive value of the particle, and taking the better part as the current gbest.
4. The particle velocity and particle position are updated separately according to:
vj(t+1)＝w×vj(t)+c1×R1(t)×(Pj(t)-xj(t))+c2×R2(t)×(Pg(t)-xj(t))；
xj(t+1)＝xj(t)+vj(t+1)；
wherein n is the total number of particles in the population, vjIs the velocity of the particle; w is the inertial weight, PjFor individual extrema, representing the optimum value, P, searched for by the particle itselfgFor a global extreme, representing the optimum value, R, in the current population of particles1(t) and R2(t) is a random number between (0, 1), xjIs the current position of the particle, c1And c2Is a learning factor.
Example four
As shown in fig. 3, in an embodiment of the present invention, the operation control method of the air conditioner further includes:
step S302, acquiring operation data of the air conditioning equipment;
and step S304, performing data cleaning on the operation data to obtain an operation data set.
In step S304, a step of performing data cleansing on the operation data to obtain an operation data set, as shown in fig. 4, specifically includes:
s402, sequencing the operation data to obtain an operation data sequence;
step S404, determining an operation data interval according to the operation data sequence, acquiring operation data in the operation data interval, and determining the operation data as a first data set;
step S406, filling the first data set by a hot card filling method to obtain a second data set;
step S408, determining the working condition characteristics corresponding to each operating data in the second data set, acquiring the operating data corresponding to the working condition characteristics in the second data set, which accord with the preset working condition characteristics, and determining the operating data as the operating data set.
In this embodiment, the data cleaning of the operation data can be divided into the following steps:
first, outlier culling is performed. Specifically, the operation data of the same category are sorted according to the numerical value, so that an operation parameter sequence arranged according to the numerical value is obtained, a target parameter interval is determined according to the operation parameter sequence, wherein the upper quartile value and the lower quartile value of the operation parameter sequence can be calculated, the upper quartile value and the lower quartile value are used as boundary values to determine the upper boundary and the lower boundary of the target parameter interval, and when the operation parameter exceeds the upper boundary and the lower boundary of the target operation parameter, the data are judged to be abnormal. Due to the fact that conditions such as sensor drifting exist in the operation process, abnormal large values and abnormal small values of operation parameters can be caused, and therefore after the data are removed, a first data set of the operation parameters which can reflect normal operation conditions better can be obtained.
In a second step, missing value supplementation is performed on the first data set. Specifically, if the first data set has missing necessary data, a historical parameter closest to a working condition of a missing value is searched in a unit historical operation database through a hot card filling method, and the missing value is supplemented through the historical parameter, so that a second data set with better integrity is obtained.
And thirdly, screening the second data set under stable working conditions. Specifically, the working condition characteristic corresponding to each operating data in the second data set is determined, and whether the working condition characteristic meets the preset working condition or not is judged. In the operation process of the air conditioning equipment, extreme operation conditions such as start-stop process and the like can occur, and the corresponding working condition is unstable, so that only the operation data of the second data set under the stable working condition is obtained, and the operation data set is generated according to the operation parameters, so that the operation control effect of the air conditioning equipment can be ensured, and the operation energy efficiency of the air conditioning equipment is effectively improved.
Because the operation data set may include abnormal operation data, such as zero drift data generated by a sensor, data loss generated in a network transmission process, and the like, in order to improve accuracy, the operation data is subjected to data cleaning in a big data cleaning mode to remove noise data in the data, so that a more accurate operation data set is obtained, further the accuracy of control and calculation is improved, and the operation energy efficiency of the air conditioning equipment is improved.
EXAMPLE five
In one embodiment of the invention, the target start-stop scheme comprises a target water chilling unit, a start-stop state and a target load rate corresponding to the target water chilling unit; the method comprises the following steps of controlling the operation of the air conditioning equipment according to a target start-stop scheme, and specifically comprises the following steps: and controlling the target water chilling unit to work according to the starting and stopping state and the target load rate.
As shown in fig. 5, the operation control method of the air conditioner further includes:
step S502, determining the change value of the total load within a preset time length;
and step S504, determining that the change value is greater than or equal to the change threshold, and executing the step of determining the start-stop scheme set of the water chilling unit corresponding to the total load.
In this embodiment, the start-stop scheme includes, on the one hand, a target chiller to be started or stopped, and also includes a start-stop state and a target load factor corresponding to the target chiller. When attention needs to be paid, in the start-stop scheme, the total load of all started water chilling units needs to be equal to the total load of the tail end of the air conditioner, and the load rate of each started water chilling unit needs to be between the maximum load rate and the minimum load rate of the water chilling unit. Wherein the maximum load rate is 1, and the minimum load rate is related to the performance of the water chilling unit.
And determining the change value of the total load within the preset time length. Specifically, the preset time duration may be set according to the actual operating environment of the system, and if the preset time duration is set to 15 minutes, after recording the total load of the system once, recording the total load of the system again after 15 minutes, and calculating a difference between the two recorded total loads. If the difference is smaller than the variation threshold, the working condition of the air conditioning equipment tends to be stable, no load change is generated, at the moment, a better energy efficiency ratio can be ensured only by depending on the load adjustment of each unit, and the start-stop scheme does not need to be adjusted.
If the difference is larger than or equal to the variation threshold, it indicates that the start-stop scheme needs to be adjusted, and at this time, a step of determining a set of start-stop schemes of the water chilling unit corresponding to the total load is executed. The variation threshold may be determined according to the rated load of the air conditioner, for example, set to 10% of the rated load.
EXAMPLE six
In an embodiment of the present invention, a specific chiller air conditioning unit is taken as an example to specifically describe the embodiment of the present invention:
the embodiment of the invention mainly comprises a load optimization distribution group control scheme of a water chilling unit, which comprises the following specific points:
firstly, applying a big data cleaning method to the pretreatment of BMS original data to obtain a data set of a stable operation working condition of a water chilling unit;
secondly, providing a self-adaptive online regression model Of the COP (Coefficient Of Performance) Of the water chilling unit, and performing self-adaptive regression on the COP Of the water chilling unit according to real-time operation data Of the water chilling unit;
thirdly, a load interval optimization algorithm is provided, and a start-stop combination scheme of the water chilling unit is determined according to the load of the central air-conditioning system;
fourthly, a COP optimization model of the water chilling unit is provided, a Particle swarm optimization algorithm (Particle swarm optimization) is adopted to solve the COP optimization model of the water chilling unit, and the overall optimal COP of the water chilling unit under different operation conditions is obtained;
and fifthly, outputting the final optimization result to the unit controller according to the COP optimization result of each start-stop combination of the unit, and performing online optimization control on the water chilling unit.
Wherein, the running parameter of the cooling water set that the BMS system adopted mainly includes: the outlet water temperature of the chilled water, the return water temperature of the chilled water, the outlet water temperature of the cooling water, the return water temperature of the cooling water and the flow rate of the chilled water. The data cleaning process adopted in the embodiment comprises outlier elimination, missing value supplement and stable working condition screening.
The step of removing the abnormal value comprises the following steps of firstly obtaining the upper quartile and the lower quartile of each parameter according to the historical normal operation data of the unit: including Q3 (upper quartile) and Q1 (lower quartile), and calculate the quartile distance: IQR ═ Q3-Q1, and the upper and lower bounds of the parameters were obtained:
Lup＝Q3+1.5×IQR，Llow＝Q1-1.5×IQR；
wherein, LupTo the upper boundary, LlowFor the lower boundary, Q3 is the upper quartile, Q1 is the lower quartile, and IQR is Q3-Q1.
Judging whether each operation parameter obtained from the BMS database is located in the upper and lower boundary ranges, if so, retaining the data; if not, the abnormal value is eliminated.
And a step of supplementing the missing value, which can adopt a Hot card filling method (Hot deck), find a data corresponding to the working condition closest to the current missing data in the unit historical operation database, and then supplement the missing data by using the corresponding data of the similar working condition.
The purpose of stable condition screening is in order to get rid of the unstable data that cooling water set produced at the start-stop in-process, avoids causing the precision decline of COP regression model, and stable condition judgement condition is: the inlet temperature of the chilled water-the outlet temperature of the chilled water is more than or equal to 2 ℃.
The COP regression equation of the chiller adopts the following functions:
Figure BDA0002442735430000141
Figure BDA0002442735430000151
wherein COP is a first energy efficiency parameter,
Figure BDA0002442735430000152
the coefficient is corrected for the flow rate of the freezing water, and
Figure BDA0002442735430000153
the coefficient is corrected for the cooling water flow, and
Figure BDA0002442735430000154
b1、b2、b3、b4、b5、b6and b7As a fitting coefficient, the fitting coefficient is constant, Tcw,inFor the inlet water temperature of the cooling water, Tchw,outIs the temperature of the outlet water of the chilled water, Q is the total load, MchwFor chilled water flow, Mchw,desRated flow of chilled water, McwFor cooling water flow, Mcw,desThe rated flow rate of cooling water.
Wherein the content of the first and second substances,
Figure BDA0002442735430000155
the equation is fitted to chilled water.
Figure BDA0002442735430000156
The equation is fitted to the cooling water.
The total load of the central air-conditioning system is obtained by calculation according to the supply and return water temperature difference of chilled water and the flow rate of the chilled water, and the calculation formula is as follows:
Q＝c×Mchw×(Tchw,in-Tchw,out)；
wherein Q is total load, c is specific heat capacity at constant pressure, and MchwFor freezingWater flow rate, Tchw,inThe temperature of the inlet water of the chilled water, Tchw,outIs the temperature of the outlet water of the chilled water.
Setting the load detection time interval of the water chilling unit to be 15min, setting the load change rate to be 10% of the rated load, namely judging whether the total load of the current central air-conditioning system exceeds the last 10% of the rated load every 15min, if not, adjusting the running state of the current unit, and if so, entering a load optimization process.
For different water chilling unit start-stop schemes, a unit COP optimization objective function is respectively established as follows:
Figure BDA0002442735430000157
wherein maxCop is a second energy efficiency parameter, Q is a total load, and Q isiThe load, COP, corresponding to the ith water chilling unitiAnd the energy efficiency parameter is a first energy efficiency parameter corresponding to the ith water chilling unit.
The equality constraints are:
Figure BDA0002442735430000158
wherein Q is the total load, QiLoad of i-th water chiller plant, P L RiIs the load factor of the ith water chilling unit, c is the specific heat capacity at constant pressure, Mchw,iThe flow of chilled water of the ith water chilling unit, Tchw,in,iThe inlet water temperature T of the chilled water of the ith water chilling unitchw,out,iThe temperature of the outlet water of the chilled water of the ith water chilling unit.
The equality constraint indicates that the sum of the loads of each water chiller unit in the start-stop scheme is equal to the total load of the air conditioning equipment.
The inequality constraint conditions are as follows:
PLRmin≤PLRi≤PLRmax,i＝1,2,...,n；
wherein, P L RiLoad factor of the i-th water chiller plant, P L RminFor the ith chiller, the minimum load rate can be set, for example0.2，PLRmaxThe maximum load rate of the ith water chilling unit is 1.0.
The inequality constraint condition indicates that the load rate of each water chilling unit is between the maximum load rate and the minimum load rate.
The COP optimizing process of the water chilling unit by adopting the particle swarm optimization algorithm comprises the following steps:
1. initializing the setting parameters of the particle swarm algorithm, mainly comprising the number of particles, the dimension of the particles, the inertial weight, the initial speed, the learning factor, the stopping condition and the like, and defining a fitness function.
2. The fitness of each particle was evaluated.
3. For each particle, comparing the adaptive value of the particle with the individual optimal value pbest of the particle, and taking the better party as the current pbest; and simultaneously comparing the adaptive value of the particle with the optimal value gbest of the group of the adaptive value of the particle, and taking the better part as the current gbest.
4. The particle velocity and particle position are updated separately according to:
vj(t+1)＝w×vj(t)+c1×R1(t)×(Pj(t)-xj(t))+c2×R2(t)×(Pg(t)-xj(t))；
xj(t+1)＝xj(t)+vj(t+1)；
wherein n is the total number of particles in the population, vjIs the velocity of the particle; w is the inertial weight, PjFor individual extrema, representing the optimum value, P, searched for by the particle itselfgFor a global extreme, representing the optimum value, R, in the current population of particles1(t) and R2(t) is a random number between (0, 1), xjIs the current position of the particle, c1And c2Is a learning factor.
And repeating the steps until an optimal adaptive value is found, otherwise, finishing the optimization according to an iteration termination condition. And comparing the COP optimization results under each unit start-stop combination scheme, selecting the maximum COP start-stop scheme as the final optimization result, and outputting the optimization parameters of each unit to the unit controller so as to control the rotating speed and the air suction quantity of the compressor of the unit and maximize the integral COP of the unit under the current working condition.
The following is a specific embodiment of the present invention:
the self-adaptive COP regression process of the water chilling unit is shown in fig. 6:
step S602, establishing a water chilling unit COP self-adaptive regression model;
step S604, determining a unit COP self-adaptive regression period;
step S606, reading inlet and outlet water temperatures of chilled water, chilled water flow and chilled water flow of a water cooling unit in a BMS database;
step S608, data cleaning is carried out on the operation parameters;
step S610, updating a COP data set of the water chilling unit;
and step S612, performing self-adaptive regression on the COP of the water chilling unit, and outputting a regression coefficient.
In step S602, a COP adaptive regression model is established on the upper computer or a server networked with the upper computer, and is used for performing adaptive online regression on the COP of the chiller.
In step S604, the unit COP adaptive regression period τ is determined, that is, the COP adaptive regression model sends a data call request to the BMS database at regular intervals.
In step S606, the COP adaptive regression module sends a data call request to the BMS database, and reads the operation data of the chiller in two adjacent cycle intervals, including: the temperature of the outlet water of the chilled water, the temperature of the return water of the chilled water, the temperature of the outlet water of the cooling water, the temperature of the return water of the cooling water, the flow rate of the chilled water and the flow rate of the cooling water.
In step S608, the COP adaptive regression module performs data cleaning on the read parameters, and the cleaning method includes outlier rejection, missing value supplement, and stable condition screening.
Wherein, the step of removing abnormal values comprises the following steps of firstly obtaining the upper quartile and the lower quartile of each parameter according to the historical normal operation data of the unit: including Q3 (upper quartile) and Q1 (lower quartile), and calculate the quartile distance: IQR ═ Q3-Q1, and the upper and lower bounds of the parameters were obtained:
Lup＝Q3+1.5×IQR，Llow＝Q1-1.5×IQR；
wherein, LupTo the upper boundary, LlowFor the lower boundary, Q3 is the upper quartile, Q1 is the lower quartile, and IQR is Q3-Q1.
Judging whether each operation parameter obtained from the BMS database is located in the upper and lower boundary ranges, if so, retaining the data; if not, the abnormal value is eliminated.
And a step of supplementing the missing value, which can adopt a Hot card filling method (Hot deck), find a data corresponding to the working condition closest to the current missing data in the unit historical operation database, and then supplement the missing data by using the corresponding data of the similar working condition.
The purpose of stable condition screening is in order to get rid of the unstable data that cooling water set produced at the start-stop in-process, avoids causing the precision decline of COP regression model, and stable condition judgement condition is: the inlet temperature of the chilled water-the outlet temperature of the chilled water is more than or equal to 2 ℃.
In step S610, the BMS data after the data washing is stored in the COP data set, and the update of the data set is completed.
In step S612, adaptive regression is performed on the chiller COP in the updated data set by using the least square method, and a COP prediction model is output.
Through the steps, the running performance of the water chilling unit can be subjected to regression prediction periodically, the COP change condition of the water chilling unit can be accurately reflected, and an optimization target is provided for load optimization distribution group control of the water chilling unit.
Next, chiller load optimization allocation is performed.
On the basis of establishing a water chilling unit COP self-adaptive regression model, a load optimization distribution method is further adopted to find out the working condition point with the optimal integral COP of the water chilling unit under different operating conditions. The load optimization distribution process of the water chilling unit is shown in fig. 7:
step S702, inputting unit configuration;
step S704, collecting system operation data;
step S706, detecting the load change rate;
step S708, judging whether the load rate is greater than a set value; if yes, go to step S710, otherwise return to step S704;
step S710, optimizing a load interval;
step 712, determining the start-stop state and the number of the hosts;
for start-stop combination 1:
step S714, determining the partial load rate of each host;
step S716, determining an optimization model of the water chilling unit;
step S718, determining whether the COP is maximum; if yes, go to step S720, otherwise, execute the PSO optimization algorithm and return to step S714;
step S720, determining the optimal COP of the current combination1；
For start-stop combination 2:
step S722, determining the partial load rate of each host;
step S724, determining a water chilling unit optimization model;
step S726, judge whether it is the maximum COP; if yes, the step S728 is executed, otherwise, the PSO optimization algorithm is executed and the step S722 is returned;
step S728, determining the current combination optimal COP2；
For start-stop combination n:
step S730, determining the partial load rate of each host;
step S732, determining an optimization model of the water chilling unit;
step S734, determining whether the COP is maximum; if yes, the step S736 is carried out, otherwise, the PSO optimization algorithm is executed and the step S730 is returned to;
step S736, determining the optimal COP of the current combinationn；
Step S738, output optimal COPmaxAnd optimizing the parameters.
The load distribution optimization process of the water chilling unit comprises the following steps:
step 1: and inputting configuration information of the water chilling units, wherein the configuration information comprises the number of the units and rated working condition parameters of each unit.
Step 2: the operation parameters of the air conditioning system are collected through the BMS, and the real-time load of the air conditioning system is calculated according to the supply and return water temperature difference of the chilled water and the chilled water flow.
And step 3: setting a load detection time interval of a water chilling unit to be 15min, wherein the time interval can be adjusted according to requirements, the load change rate threshold is 10% of the rated load, namely, judging whether the change rate of the total load of the current central air conditioning system compared with the last time exceeds 10% of the rated load every 15min, if not, adjusting the running state of the current unit, and if so, entering a load interval optimizing process.
And 4, step 4: the load interval optimization is to find different load intervals by arranging and combining all possible running conditions of the water chilling units, judge which load interval the current air conditioning system load belongs to, and intelligently select the number of the water chilling units needing to be started and stopped so as to meet the total load of the current central air conditioning system.
It should be noted that the optimization result may be one or a combination of start and stop of various units. For example, if the project uses 2 500RT and 2 250RT chiller units, and the current air conditioning system load is calculated to be 400RT, the load optimization result may be to turn on 1 500RT or turn on 2 250 RT.
And 5: for different water chilling unit start-stop schemes, a unit COP optimization objective function is respectively established as follows:
Figure BDA0002442735430000191
wherein maxCop is a second energy efficiency parameter, Q is a total load, and Q isiThe load, COP, corresponding to the ith water chilling unitiAnd the energy efficiency parameter is a first energy efficiency parameter corresponding to the ith water chilling unit.
The equality constraints are:
Figure BDA0002442735430000201
wherein Q is the total load, QiLoad of i-th water chiller plant, P L RiIs the load factor of the ith water-cooling unit, c is the specific heat capacity at constant pressure, Mchw,iThe flow of chilled water of the ith water chilling unit, Tchw,in,iThe inlet water temperature T of the chilled water of the ith water chilling unitchw,out,iThe temperature of the outlet water of the chilled water of the ith water chilling unit.
The equality constraint indicates that the sum of the loads of each water chiller unit in the start-stop scheme is equal to the total load of the air conditioning equipment.
The inequality constraint conditions are as follows:
PLRmin≤PLRi≤PLRmax,i＝1,2,...,n；
wherein, P L RiLoad factor of the i-th water chiller plant, P L RminFor the ith chiller, the minimum load rate can be set to 0.2, P L RmaxThe maximum load rate of the ith water chilling unit is 1.0.
The inequality constraint condition indicates that the load rate of each water chilling unit is between the maximum load rate and the minimum load rate.
The Optimization problem is optimized by using Particle Swarm Optimization (PSO). The particle swarm optimization algorithm flow is as follows:
1. initializing the setting parameters of the particle swarm algorithm, mainly comprising the number of particles, the dimension of the particles, the inertial weight, the initial speed, the learning factor, the stopping condition and the like, and defining a fitness function.
2. The fitness of each particle was evaluated.
3. For each particle, comparing the adaptive value of the particle with the individual optimal value pbest of the particle, and taking the better party as the current pbest; and simultaneously comparing the adaptive value of the particle with the optimal value gbest of the group of the adaptive value of the particle, and taking the better part as the current gbest.
4. The particle velocity and particle position are updated separately according to:
vj(t+1)＝w×vj(t)+c1×R1(t)×(Pj(t)-xj(t))+c2×R2(t)×(Pg(t)-xj(t))；
xj(t+1)＝xj(t)+vj(t+1)；
wherein n is the total number of particles in the population, vjIs the velocity of the particle; w is the inertial weight, PjFor individual extrema, representing the optimum value, P, searched for by the particle itselfgFor a global extreme, representing the optimum value, R, in the current population of particles1(t) and R2(t) is a random number between (0, 1), xjIs the current position of the particle, c1And c2Is a learning factor.
And (5) circulating the steps 2 to 4 until an optimal adaptive value is found, and otherwise, finishing the optimization according to an iteration termination condition.
By solving the optimization problem, the optimal COP under each unit start-stop combination scheme is obtained, the scheme of the maximum COP start-stop is selected as the final optimization result to be output, and simultaneously the optimization load of each unit is obtained and output to the unit controller, so that the rotating speed and the air suction volume of the compressor of the unit are controlled.
The following is a specific data analysis:
suppose that 4 centrifugal chiller units are configured in a certain project, wherein 2 rated refrigerating capacities are 1000kW, 2 rated refrigerating capacities are 500kW, and COP performance curves of the chiller units with 500kW rated loads and the chiller units with 1000kW rated loads are shown in FIG. 8.
Because 4 cooling water set total cold volume are 3000kW, get air conditioning system cold load variation range and do: 0 to 3000kW, unit operating condition parameter is: the water inlet temperature of the cooling water is 31 ℃, and the water outlet temperature of the chilled water is 7 ℃.
FIG. 9 is a comparison of the load rates of the units in the conventional group control method (left in FIG. 9) and the load optimized distribution group control method (right in FIG. 9), where P L R01, P L R02 are the partial load rates of two units with a rated cooling capacity of 500kW, P L R03, and P L R04 are the partial load rates of two units with a rated cooling capacity of 1000 kW.
Fig. 10 is a comparison of the unit energy consumption and COP in the conventional group control method (fig. 10 left) and the load optimization distribution group control method (fig. 10 right).
It can be seen that the overall energy consumption of the unit is reduced, the COP is obviously improved, the average energy consumption is reduced by 6.4%, and the average COP is improved by 7.2% by adopting the load optimization distribution group control method under different air conditioner loads. The method for controlling the water chilling unit group based on load optimization distribution can effectively improve the operation efficiency of the unit, thereby reducing the energy consumption of the building.
EXAMPLE seven
As shown in fig. 11, in an embodiment of the present invention, there is provided an operation control system 1100 of an air conditioner including: a memory 1102 configured to store a computer program; the processor 1104 is configured to execute a computer program to implement the operation control method of the air conditioning equipment provided in any of the above embodiments, and therefore, the operation control system 1100 of the air conditioning equipment includes all the beneficial effects of the operation control method of the air conditioning equipment provided in any of the above embodiments, which are not described herein again.
Example eight
In one embodiment of the present invention, there is provided an air conditioner apparatus including: the water chilling units comprise compressors, cooling water pipes, freezing water pipes, heat exchangers and throttling devices; the detection device is configured to acquire the chilled water outlet temperature and the chilled water inlet temperature of the chilled water pipe, the chilled water inlet flow rate of the chilled water pipe, and the cooling water outlet temperature, the cooling water return temperature and the cooling water flow rate of the cooling water pipe; in the operation control system of the air conditioning equipment provided in any one of the above embodiments, the operation control system of the air conditioning equipment is connected with the water chilling unit and the detection device.
In this embodiment, the air conditioner includes the operation control system of the air conditioner provided in any one of the above embodiments, and therefore, the overall beneficial effects of the operation control system of the air conditioner provided in any one of the above embodiments are not described herein again.
Example nine
In an embodiment of the present invention, a computer-readable storage medium is provided, on which a computer program is stored, and the computer program, when executed by a processor, implements the operation control method of the air conditioning equipment provided in any one of the above embodiments, and therefore, the computer-readable storage medium includes all the beneficial effects of the operation control method of the air conditioning equipment provided in any one of the above embodiments, and details are not repeated herein.
In the description of the present invention, the terms "plurality" or "a plurality" refer to two or more, and unless otherwise specifically defined, the terms "upper", "lower", and the like indicate orientations or positional relationships based on the orientations or positional relationships illustrated in the drawings, and are only for convenience in describing the present invention and simplifying the description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and thus, should not be construed as limiting the present invention; the terms "connected," "mounted," "secured," and the like are to be construed broadly and include, for example, fixed connections, removable connections, or integral connections; may be directly connected or indirectly connected through an intermediate. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
In the description of the present invention, the description of the terms "one embodiment," "some embodiments," "specific embodiments," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In the present invention, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (13)

1. An operation control method of an air conditioning apparatus, characterized in that the air conditioning apparatus includes a plurality of chiller units, the operation control method comprising:
acquiring an operation data set of the air conditioning equipment;
determining the total load of the air conditioning equipment according to the operation data set, and determining a starting and stopping scheme set of the water chilling unit corresponding to the total load;
determining a first energy efficiency parameter of any water chilling unit corresponding to the start-stop scheme set according to the operation data set, and determining a second energy efficiency parameter corresponding to each start-stop scheme in the start-stop scheme set according to the first energy efficiency parameter;
and determining a target start-stop scheme in the start-stop scheme set according to the second energy efficiency parameter, and controlling the air conditioning equipment to operate according to the target start-stop scheme.
2. The operation control method of an air conditioning apparatus according to claim 1, characterized in that the operation data set includes:
the air conditioning equipment's refrigerated water leaving water temperature, air conditioning equipment's refrigerated water temperature of intaking, air conditioning equipment's refrigerated water flow, air conditioning equipment's cooling water leaving water temperature, air conditioning equipment's cooling water return water temperature with air conditioning equipment cooling water flow.
3. The operation control method of an air conditioning apparatus according to claim 2, wherein the first energy efficiency parameter is determined by a first preset function, and the first preset function is specifically:
Figure FDA0002442735420000011
wherein COP is the first energy efficiency parameter,
Figure FDA0002442735420000012
the coefficient is corrected for the flow rate of the freezing water, and
Figure FDA0002442735420000013
Figure FDA0002442735420000014
the coefficient is corrected for the cooling water flow, and
Figure FDA0002442735420000015
b1、b2、b3、b4、b5、b6and b7Is a fitting coefficient, said fitting coefficient being a constant, Tcw,inIs the inlet water temperature, T, of the cooling waterchw,outIs the chilled water outlet temperature, Q is the total load, MchwFor the flow rate of the freezing water, Mchw,desRated flow of chilled water, McwFor said cooling water flow rate, Mcw,desThe rated flow rate of cooling water.
4. The operation control method of an air conditioning apparatus according to claim 3, wherein the second energy efficiency parameter is determined by a second preset function, and the second preset function is specifically:
Figure FDA0002442735420000021
wherein maxCop is the second energy efficiency parameter, Q is the total load, Q isiThe load, COP, corresponding to the ith water chilling unitiAnd the first energy efficiency parameter is the first energy efficiency parameter corresponding to the ith water chilling unit.
5. The operation control method of an air conditioning apparatus according to claim 3, characterized by further comprising:
receiving a setting instruction corresponding to the fitting coefficient, and determining the fitting coefficient according to the setting instruction;
and receiving an updating instruction corresponding to the fitting coefficient, and updating the fitting coefficient according to the updating instruction.
6. The operation control method of the air conditioning equipment according to any one of claims 1 to 5, wherein the start-stop scheme set includes a plurality of start-stop schemes, and the step of determining the target start-stop scheme in the start-stop scheme set according to the second energy efficiency parameter specifically includes:
calculating the fitness of the plurality of second energy efficiency parameters through a particle swarm optimization algorithm, and determining the target start-stop scheme corresponding to the second energy efficiency parameter with the highest fitness as the target start-stop scheme.
7. The operation control method of an air conditioning apparatus according to any one of claims 1 to 5, characterized by further comprising:
acquiring operation data of the air conditioning equipment;
and performing data cleaning on the operation data to obtain the operation data set.
8. The operation control method of an air conditioning apparatus according to claim 7, wherein the step of performing data cleansing on the operation data to obtain the operation data set specifically includes:
sequencing the operating data to obtain an operating data sequence;
determining an operation data interval according to the operation data sequence, acquiring the operation data in the operation data interval, and determining the operation data as a first data set;
filling the first data set by a hot card filling method to obtain a second data set;
and determining the working condition characteristics corresponding to each operating data in the second data set, acquiring the operating data corresponding to the working condition characteristics in the second data set, which accord with preset working condition characteristics, and determining the operating data as the operating data set.
9. The operation control method of the air conditioning equipment according to any one of claims 1 to 5, wherein the target start-stop scheme comprises a target chiller set start-stop state and a target load factor corresponding to the target chiller set;
controlling the air conditioning equipment to operate according to the target start-stop scheme, which specifically comprises the following steps:
and controlling the target water chilling unit to work according to the starting and stopping state and the target load factor.
10. The operation control method of an air conditioning apparatus according to any one of claims 1 to 5, characterized by further comprising:
determining a change value of the total load within a preset time length;
and determining that the change value is greater than or equal to a change threshold value, and executing the step of determining the start-stop scheme set of the water chilling unit corresponding to the total load.
11. An operation control system of an air conditioning apparatus, characterized by comprising:
a memory configured to store a computer program;
a processor configured to execute the computer program to implement the operation control method of the air conditioning apparatus according to any one of claims 1 to 9.
12. An air conditioning apparatus, characterized by comprising:
the system comprises a plurality of water chilling units, a control unit and a control unit, wherein each water chilling unit comprises a compressor, a cooling water pipe, a freezing water pipe, a heat exchanger and a throttling device;
the detection device is configured to acquire the chilled water outlet temperature, the chilled water inlet temperature and the chilled water flow of the chilled water pipe, and the cooling water outlet temperature, the cooling water return temperature and the cooling water flow of the cooling water pipe;
the operation control system of an air conditioner according to claim 11, being connected with the chiller and the detection device.
13. A computer-readable storage medium on which a computer program is stored, characterized in that the computer program, when executed by a processor, implements a control method of an air conditioning apparatus according to any one of claims 1 to 10.
CN202010269819.3A 2020-04-08 2020-04-08 Operation control method and system for air conditioning equipment, air conditioning equipment and storage medium Pending CN111442480A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202010269819.3A CN111442480A (en) 2020-04-08 2020-04-08 Operation control method and system for air conditioning equipment, air conditioning equipment and storage medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202010269819.3A CN111442480A (en) 2020-04-08 2020-04-08 Operation control method and system for air conditioning equipment, air conditioning equipment and storage medium

Publications (1)

Publication Number Publication Date
CN111442480A true CN111442480A (en) 2020-07-24

Family

ID=71651141

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202010269819.3A Pending CN111442480A (en) 2020-04-08 2020-04-08 Operation control method and system for air conditioning equipment, air conditioning equipment and storage medium

Country Status (1)

Country Link
CN (1) CN111442480A (en)

Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111895582A (en) * 2020-08-06 2020-11-06 广东Tcl智能暖通设备有限公司 Compressor control method and device and air conditioning system
CN112283834A (en) * 2020-11-04 2021-01-29 新奥数能科技有限公司 Chilled water outlet temperature control method and device for water chilling unit
CN113834185A (en) * 2021-08-18 2021-12-24 青岛海尔空调器有限总公司 Control method and device for air conditioner and server
CN114739066A (en) * 2022-04-20 2022-07-12 江苏一万节能科技股份有限公司 Dynamic control method and system for modular magnetic suspension refrigerating unit
CN114893879A (en) * 2022-04-26 2022-08-12 重庆美的通用制冷设备有限公司 Refrigerant switching method and switching device, readable storage medium and refrigeration device
WO2023020078A1 (en) * 2021-08-18 2023-02-23 青岛海尔空调器有限总公司 Control method and device for air conditioner, and server
WO2024046434A1 (en) * 2022-08-31 2024-03-07 青岛海信日立空调系统有限公司 Water-chilling unit air-conditioning system and control method therefor

Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103912966A (en) * 2014-03-31 2014-07-09 武汉科技大学 Optimal control method for ground source heat pump refrigerating system
CN106225184A (en) * 2016-09-18 2016-12-14 珠海格力电器股份有限公司 Central air conditioner system and control system thereof and control method
JP2017101881A (en) * 2015-12-02 2017-06-08 東芝キヤリア株式会社 Refrigerating air conditioner, controlling device and computer program
CN108168030A (en) * 2017-12-14 2018-06-15 南京师范大学 A kind of intelligent control method based on refrigeration performance curve
CN108626923A (en) * 2017-03-15 2018-10-09 约克广州空调冷冻设备有限公司 A kind of control structure and control method of air-conditioning system
CN108731190A (en) * 2018-06-15 2018-11-02 广东美的暖通设备有限公司 Detection method, detection device and the detecting system of air-conditioner host parameter
CN108917103A (en) * 2018-05-03 2018-11-30 广东美的暖通设备有限公司 The cold water main unit control method of central air conditioner system, apparatus and system
CN109583008A (en) * 2018-10-18 2019-04-05 天津大学 Water cooler energy efficiency model universal modeling method based on successive Regression
KR101993627B1 (en) * 2018-06-18 2019-06-27 노승엽 Geothermal heating and cooling system for optimization of heat pump And That control method

Patent Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103912966A (en) * 2014-03-31 2014-07-09 武汉科技大学 Optimal control method for ground source heat pump refrigerating system
JP2017101881A (en) * 2015-12-02 2017-06-08 東芝キヤリア株式会社 Refrigerating air conditioner, controlling device and computer program
CN106225184A (en) * 2016-09-18 2016-12-14 珠海格力电器股份有限公司 Central air conditioner system and control system thereof and control method
CN108626923A (en) * 2017-03-15 2018-10-09 约克广州空调冷冻设备有限公司 A kind of control structure and control method of air-conditioning system
CN108168030A (en) * 2017-12-14 2018-06-15 南京师范大学 A kind of intelligent control method based on refrigeration performance curve
CN108917103A (en) * 2018-05-03 2018-11-30 广东美的暖通设备有限公司 The cold water main unit control method of central air conditioner system, apparatus and system
CN108731190A (en) * 2018-06-15 2018-11-02 广东美的暖通设备有限公司 Detection method, detection device and the detecting system of air-conditioner host parameter
KR101993627B1 (en) * 2018-06-18 2019-06-27 노승엽 Geothermal heating and cooling system for optimization of heat pump And That control method
CN109583008A (en) * 2018-10-18 2019-04-05 天津大学 Water cooler energy efficiency model universal modeling method based on successive Regression

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
李楠: "《中国资源产出率测算分析》", 31 December 2016, 河北科学技术出版社 *

Cited By (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111895582A (en) * 2020-08-06 2020-11-06 广东Tcl智能暖通设备有限公司 Compressor control method and device and air conditioning system
CN112283834A (en) * 2020-11-04 2021-01-29 新奥数能科技有限公司 Chilled water outlet temperature control method and device for water chilling unit
CN113834185A (en) * 2021-08-18 2021-12-24 青岛海尔空调器有限总公司 Control method and device for air conditioner and server
CN113834185B (en) * 2021-08-18 2022-12-23 青岛海尔空调器有限总公司 Control method and device for air conditioner and server
WO2023020078A1 (en) * 2021-08-18 2023-02-23 青岛海尔空调器有限总公司 Control method and device for air conditioner, and server
CN114739066A (en) * 2022-04-20 2022-07-12 江苏一万节能科技股份有限公司 Dynamic control method and system for modular magnetic suspension refrigerating unit
CN114739066B (en) * 2022-04-20 2023-08-11 江苏一万节能科技股份有限公司 Dynamic control method and system for modularized magnetic suspension refrigerating unit
CN114893879A (en) * 2022-04-26 2022-08-12 重庆美的通用制冷设备有限公司 Refrigerant switching method and switching device, readable storage medium and refrigeration device
CN114893879B (en) * 2022-04-26 2023-08-29 重庆美的通用制冷设备有限公司 Refrigerant switching method and switching device, readable storage medium, and refrigeration device
WO2024046434A1 (en) * 2022-08-31 2024-03-07 青岛海信日立空调系统有限公司 Water-chilling unit air-conditioning system and control method therefor

Similar Documents

Publication Publication Date Title
CN111442480A (en) Operation control method and system for air conditioning equipment, air conditioning equipment and storage medium
CN111442489B (en) Control method and system of air conditioner, air conditioner and readable storage medium
CN111076376B (en) Method and system for predicting cold load demand and distributing ice storage air conditioner load
WO2020119038A1 (en) Method and device for controlling air conditioner and air conditioner
CN110410942B (en) Energy-saving optimization control method and system for cold and heat source machine room
CN107940679B (en) Group control method based on performance curve of water chilling unit of data center
CN108168030B (en) Intelligent control method based on refrigeration performance curve
CN115493256B (en) Intelligent optimizing method for energy-saving operation of central refrigerating system
CN110325805B (en) System and method for determining the efficiency of a chiller
CN111678247A (en) Operation control method of air conditioning equipment, air conditioning equipment and computer storage medium
CN109974231A (en) Ice-storage air-conditioning ice gauge draws method, apparatus, equipment and medium
CN115115143B (en) Method for calculating optimal number of opened cooling tower and minimum operation energy consumption based on AI algorithm
CN115776795A (en) Data center air conditioning system diagnosis method and device
CN110940061A (en) Central air conditioner control method and system
JP2002364901A (en) Control system of regenerative air conditioning installation, controlled planning apparatus, controlled planning method, and recording medium and program for executing the controlled planning
CN113701321A (en) Energy-saving frequency conversion control method for central air-conditioning water pump
CN111102691A (en) Module combined air conditioning system
CN110470000B (en) Control method and device for defrosting of air conditioner and air conditioner
CN110848889A (en) Method for evaluating operation energy efficiency of main unit of central air-conditioning system
CN111787764B (en) Energy consumption optimization method and device for multi-split refrigerating unit, electronic equipment and storage medium
CN114206071A (en) Data center cooling system based on hyperbolic cooling tower
CN113899055B (en) Control system of water chilling unit
CN115309056A (en) Control method of multiple water chilling units
CN112364999B (en) Training method and device for water chiller adjustment model and electronic equipment
CN113757856A (en) Control method and device for air conditioner cooling water system

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
TA01 Transfer of patent application right

Effective date of registration: 20210205

Address after: Room C, 14th floor, 309 Tanggu Road, Hongkou District, Shanghai 200080

Applicant after: Shanghai Meikong Intelligent Building Co.,Ltd.

Applicant after: GD MIDEA HEATING & VENTILATING EQUIPMENT Co.,Ltd.

Address before: 528311 Industrial Road, Penglai Road, Beijiao Town, Shunde District, Guangdong, Foshan

Applicant before: GD MIDEA HEATING & VENTILATING EQUIPMENT Co.,Ltd.

Applicant before: MIDEA GROUP Co.,Ltd.

TA01 Transfer of patent application right
RJ01 Rejection of invention patent application after publication

Application publication date: 20200724

RJ01 Rejection of invention patent application after publication