CN111609524A - Method and device for optimizing air quantity and water quantity combination of variable air quantity central air conditioner - Google Patents
Method and device for optimizing air quantity and water quantity combination of variable air quantity central air conditioner Download PDFInfo
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- CN111609524A CN111609524A CN201910136194.0A CN201910136194A CN111609524A CN 111609524 A CN111609524 A CN 111609524A CN 201910136194 A CN201910136194 A CN 201910136194A CN 111609524 A CN111609524 A CN 111609524A
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- 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
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- 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
- F24F11/72—Control systems characterised by their outputs; Constructional details thereof for controlling the supply of treated air, e.g. its pressure
- F24F11/74—Control systems characterised by their outputs; Constructional details thereof for controlling the supply of treated air, e.g. its pressure for controlling air flow rate or air velocity
- F24F11/77—Control systems characterised by their outputs; Constructional details thereof for controlling the supply of treated air, e.g. its pressure for controlling air flow rate or air velocity by controlling the speed of ventilators
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- 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
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B30/00—Energy efficient heating, ventilation or air conditioning [HVAC]
- Y02B30/70—Efficient control or regulation technologies, e.g. for control of refrigerant flow, motor or heating
Abstract
The invention discloses a method and a device for optimizing air quantity and water quantity combination of a variable air quantity central air conditioner, wherein the method comprises the following steps: constructing an objective function, wherein the objective function comprises a functional relation among fan frequency, chilled water flow and total energy consumption of the variable air volume central air conditioner; determining a fan frequency interval and a chilled water flow interval; and solving an optimal solution of the objective function based on a genetic algorithm according to the fan frequency interval and the chilled water flow interval, wherein the optimal solution comprises an optimal fan frequency and an optimal chilled water flow. According to the technical scheme, when the variable air volume central air-conditioning system is regulated and controlled according to the obtained optimal fan frequency and the optimal chilled water flow, the energy consumption of the variable air volume central air-conditioning system can be reduced.
Description
Technical Field
The invention relates to the technical field of central air conditioners, in particular to a method and a device for optimizing air volume and water volume combination of a variable air volume central air conditioner.
Background
The variable air volume central air-conditioning system is widely applied to daily production and life due to the advantages of relatively flexible control means, better adaptability to variable working conditions, higher system operation efficiency and the like.
At present, the variable air volume operation mode of the variable air volume central air-conditioning system is mainly determined through operation parameter simulation optimization.
The simulation optimization of the operation parameters does not consider the coupling of the air supply volume and the chilled water flow in the variable air volume central air-conditioning system, which may cause the energy consumption of the variable air volume central air-conditioning system to be higher.
Disclosure of Invention
The invention provides a method, a device, a readable medium and electronic equipment for optimizing air quantity and water quantity combination of a variable air quantity central air conditioner.
In a first aspect, the invention provides a method for optimizing the combination of air volume and water volume of a variable air volume central air conditioner, which comprises the following steps:
constructing an objective function, wherein the objective function comprises a functional relation among fan frequency, chilled water flow and total energy consumption of the variable air volume central air conditioner;
determining a fan frequency interval and a chilled water flow interval;
and solving an optimal solution of the objective function based on a genetic algorithm according to the fan frequency interval and the chilled water flow interval, wherein the optimal solution comprises an optimal fan frequency and an optimal chilled water flow.
Preferably, the first and second electrodes are formed of a metal,
solving the optimal solution of the objective function based on a genetic algorithm according to the fan frequency interval and the chilled water flow interval, wherein the optimal solution comprises the following steps:
a1, determining algorithm parameters, wherein the algorithm parameters comprise population size, crossing rate, variation rate and termination condition;
a2, forming a population consisting of at least two chromosomes according to the population scale, wherein the chromosomes comprise a fan frequency and a chilled water flow, the fan frequency is located in a fan frequency interval, the chilled water flow is located in a chilled water flow interval, and the cooling capacity generated when the variable air volume central air conditioner operates according to the fan frequency and the chilled water flow is greater than the preset cooling load demand;
a3, aiming at each chromosome in the population, carrying out coding treatment on the chromosome to form an individual;
a4, calculating the fitness value of each individual in the population according to the objective function, and determining a global optimal individual according to the fitness value of each individual;
a5, judging whether the termination condition is met, if so, executing A9, otherwise, executing A6;
a6, selecting at least two genetic individuals from the population according to the fitness value of each individual;
a7, sequentially carrying out cross treatment and variation treatment on the at least two selected genetic individuals according to the cross rate and the variation rate to obtain at least two cross individuals and at least one variation individual;
a8, forming the population using each of the genetic individuals, the at least two crossover individuals, and the at least one variant individual, and performing a 4;
and A9, decoding the globally optimal individual to obtain the optimal fan frequency and the optimal chilled water flow.
Preferably, the first and second electrodes are formed of a metal,
the termination condition comprises a maximum number of iterations;
then the process of the first step is carried out,
the A4, further comprising: recording the iterative updating times of the globally optimal individual;
the judging whether the termination condition is met includes:
and detecting whether the recorded iteration updating times reach the maximum iteration times.
Preferably, the first and second electrodes are formed of a metal,
the termination condition comprises an optimal fitness value;
then, the determining whether the termination condition is satisfied includes:
detecting whether the fitness value of the globally optimal individual reaches the optimal fitness value.
Preferably, the first and second electrodes are formed of a metal,
said selecting at least two genetic individuals from said population according to said fitness value of each of said individuals, comprising:
determining at least two candidate individuals according to the fitness value of each individual;
and decoding the candidate individuals to obtain current fan frequency and current chilled water flow for each candidate individual, detecting whether the cooling capacity generated by the variable air volume central air conditioner when the variable air volume central air conditioner operates according to the current fan frequency and the chilled water flow is not less than the preset cooling load demand, and if so, taking the candidate individuals as genetic individuals.
In a second aspect, the invention provides a device for optimizing the air quantity and water quantity combination of a variable air quantity central air conditioner, which comprises:
the construction function module is used for constructing an objective function, and the objective function comprises a functional relation among fan frequency, chilled water flow and total energy consumption of the variable air volume central air conditioner;
the interval determining module is used for determining a fan frequency interval and a chilled water flow interval;
and the optimal solution determining module is used for solving the optimal solution of the objective function based on a genetic algorithm according to the fan frequency interval and the chilled water flow interval, wherein the optimal solution comprises the optimal fan frequency and the optimal chilled water flow.
Preferably, the first and second electrodes are formed of a metal,
the optimal solution determination module comprises: the system comprises a parameter determining unit, a first group determining unit, an individual determining unit, an adaptability value determining unit, a judging unit, a selecting unit, a cross variation unit, a second group determining unit and an optimal solution determining unit; wherein the content of the first and second substances,
the parameter determining unit is used for determining algorithm parameters, and the algorithm parameters comprise population scale, crossing rate, variation rate and termination condition;
the first population determining unit is used for forming a population consisting of at least two chromosomes according to the population scale, wherein the chromosomes comprise a fan frequency and a chilled water flow, the fan frequency is located in a fan frequency interval, the chilled water flow is located in a chilled water flow interval, and the cooling capacity generated by the variable air volume central air conditioner when the variable air volume central air conditioner operates according to the fan frequency and the chilled water flow is greater than the preset cooling load demand;
the individual determination unit is used for encoding each chromosome in the population to form an individual;
the fitness value unit is used for calculating the fitness value of each individual in the population according to the objective function and determining a global optimal individual according to the fitness value of each individual;
the judging unit is used for judging whether the termination condition is met, if so, the optimal solution determining unit is triggered, and if not, the selecting unit is triggered;
the selection unit is used for selecting at least two genetic individuals from the population according to the fitness value of each individual;
the cross mutation unit is used for sequentially carrying out cross treatment and mutation treatment on the at least two selected genetic individuals according to the cross rate and the mutation rate to obtain at least two cross individuals and at least one mutation individual;
the second population determining unit is used for forming the population by utilizing each genetic individual, the at least two crossed individuals and the at least one variant individual and triggering the fitness value unit;
and the optimal solution determining unit is used for decoding the globally optimal individual to obtain the optimal fan frequency and the optimal chilled water flow.
Preferably, the first and second electrodes are formed of a metal,
the termination condition comprises a maximum number of iterations;
then the process of the first step is carried out,
the fitness value determining unit is further used for recording the iterative updating times of the globally optimal individual;
the judging unit is configured to detect whether the recorded iteration update times reaches the maximum iteration times.
Preferably, the first and second electrodes are formed of a metal,
the termination condition comprises an optimal fitness value;
then, the determining unit is configured to detect whether the minimum fitness value reaches the optimal fitness value.
Preferably, the first and second electrodes are formed of a metal,
the selection unit is used for determining at least two candidate individuals according to the fitness value of each individual; and decoding the candidate individuals to obtain current fan frequency and current chilled water flow for each candidate individual, detecting whether the cooling capacity generated by the variable air volume central air conditioner when the variable air volume central air conditioner operates according to the current fan frequency and the chilled water flow is not less than the preset cooling load demand, and if so, taking the candidate individuals as genetic individuals.
In a third aspect, the invention provides a readable medium comprising executable instructions, which when executed by a processor of an electronic device, perform the method according to any of the first aspect.
In a fourth aspect, the present invention provides an electronic device, comprising a processor and a memory storing execution instructions, wherein when the processor executes the execution instructions stored in the memory, the processor performs the method according to any one of the first aspect.
The invention provides a method, a device, a readable medium and electronic equipment for optimizing air quantity and water quantity combination of a variable air quantity central air conditioner, wherein the method comprises the steps of constructing an objective function, wherein the objective function comprises the functional relation among fan frequency, chilled water flow and total energy consumption of the variable air quantity central air conditioner, determining a fan frequency interval and a chilled water flow interval, solving an optimal solution of the objective function based on a genetic algorithm according to the fan frequency interval and the chilled water flow interval, the optimal solution comprises optimal fan frequency and optimal chilled water flow, and the direct functional relation exists between the fan frequency and the air supply quantity of the variable air quantity central air conditioner system And correspondingly, when the variable air volume central air-conditioning system is subsequently regulated and controlled according to the obtained optimal fan frequency and the optimal chilled water flow, the energy consumption of the variable air volume central air-conditioning system can be reduced.
Further effects of the above-mentioned unconventional preferred modes will be described below in conjunction with specific embodiments.
Drawings
In order to more clearly illustrate the embodiments or the prior art solutions of the present invention, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments described in the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive labor.
Fig. 1 is a schematic flow chart of a method for optimizing air volume and water volume combination of a variable air volume central air conditioner according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of an air quantity and water quantity combination optimizing device of a variable air quantity central air conditioner according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of another device for optimizing combination of air volume and water volume of a variable air volume central air conditioner according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be described in detail and completely with reference to the following embodiments and accompanying drawings. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, an embodiment of the present invention provides a method for optimizing air volume and water volume combination of a variable air volume central air conditioner, including the following steps:
101, constructing an objective function, wherein the objective function comprises a functional relation among fan frequency, chilled water flow and total energy consumption of the variable air volume central air conditioner;
103, solving an optimal solution of the objective function based on a genetic algorithm according to the fan frequency interval and the chilled water flow interval, wherein the optimal solution comprises an optimal fan frequency and an optimal chilled water flow.
The method comprises the steps of establishing an objective function, wherein the objective function comprises the functional relation among the fan frequency of the variable air volume central air conditioner, the chilled water flow and the total energy consumption, determining a fan frequency interval and a chilled water flow interval, and solving an optimal solution of the objective function based on a genetic algorithm according to the fan frequency interval and the chilled water flow interval, wherein the optimal solution comprises the optimal fan frequency and the optimal chilled water flow, and the fan frequency of the variable air volume central air conditioning system has a direct functional relation with the air supply volume, so that the obtained optimal fan frequency can directly indicate the optimal air supply volume of the variable air volume central air conditioner, namely the obtained optimal fan frequency and the optimal chilled water flow are the target function through the objective function, The constraints of the fan frequency interval and the chilled water flow interval comprehensively consider the coupling between the air supply volume and the chilled water flow of the variable air volume central air-conditioning system, and accordingly, when the variable air volume central air-conditioning system is subsequently regulated and controlled according to the obtained optimal fan frequency and the optimal chilled water flow, the energy consumption of the variable air volume central air-conditioning system can be reduced.
It should be noted that the objective function includes a functional relationship between the fan frequency and the chilled water flow of the variable air volume central air conditioner and the sum of the fan energy consumption and the chilled water pump energy consumption, where the total energy consumption refers to the sum of the fan energy consumption and the chilled water pump energy consumption when the variable air volume central air conditioner is in operation, the fan frequency corresponds to the fan energy consumption, and the chilled water flow corresponds to the chilled water pump energy consumption.
It should be further noted that two directly adjustable variables influencing the fan energy consumption and the chilled water pump energy consumption during the operation of the variable air volume central air conditioner are the air supply volume and the chilled water flow, the air supply volume corresponds to the fan energy consumption, the chilled water flow corresponds to the chilled water pump energy consumption, and for convenience of engineering implementation, the air supply volume can be indirectly expressed as the fan frequency, that is, the fan frequency corresponds to the fan energy consumption. When the indoor load demand is determined and other operation parameters are known, an optimal matching point of a certain determined air supply volume (fan frequency) and chilled water flow parameters exists, so that the total energy consumption of the cooling output when the variable air volume central air conditioner operates is the lowest when the indoor load demand is met, namely the fan frequency and the chilled water flow corresponding to the optimal matching point are the optimal fan frequency and the optimal chilled water flow.
As will be understood by those skilled in the art, in the actual operation of the variable air volume central air-conditioning system, the fan frequency and the chilled water flow have specific variation ranges, generally, the fan frequency interval may be 38 to 50Hz, and the chilled water flow interval may be 6 to 40m3/h。
In an embodiment of the present invention, the solving an optimal solution of the objective function based on a genetic algorithm according to the fan frequency interval and the chilled water flow interval includes:
a1, determining algorithm parameters, wherein the algorithm parameters comprise population size, crossing rate, variation rate and termination condition;
a2, forming a population consisting of at least two chromosomes according to the population scale, wherein each chromosome comprises a fan frequency and a chilled water flow, the fan frequency is located in a fan frequency interval, the chilled water flow is located in a chilled water flow interval, and the cooling capacity generated when the variable air volume central air conditioner operates according to the fan frequency and the chilled water flow is greater than the preset cooling load demand;
a3, aiming at each chromosome in the population, carrying out coding treatment on the chromosome to form an individual;
a4, calculating the fitness value of each individual in the population according to the objective function, and determining a global optimal individual according to the fitness value of each individual;
a5, judging whether the termination condition is met, if so, executing A9, otherwise, executing A6;
a6, selecting at least two genetic individuals from the population according to the fitness value of each individual;
a7, sequentially carrying out cross treatment and variation treatment on the at least two selected genetic individuals according to the cross rate and the variation rate to obtain at least two cross individuals and at least one variation individual;
a8, forming the population using each of the genetic individuals, the at least two crossover individuals, and the at least one variant individual, and performing a 4;
and A9, decoding the globally optimal individual to obtain the optimal fan frequency and the optimal chilled water flow.
In this embodiment, a population size, a crossover rate, a variation rate, and a termination condition may be set manually, and a combination of a plurality of fan frequencies and a plurality of freezing water flows may be determined from a fan frequency interval and a freezing water flow interval, where a total number of the combination of the fan frequencies and the freezing water flows is the same as the population size, for each combination of the fan frequencies and the freezing water flows, a cooling capacity of the variable air volume central air conditioner when operating at the fan frequencies and the freezing water flows may satisfy a preset cooling load demand, a combination of each fan frequency and the freezing water flows is determined as a chromosome, the chromosome may represent a hypothetical solution of an objective function, at this time, a mapping from a phenotype (chromosome) to a genotype (individual) needs to be established by coding, where the coding method may be a binary coding method, a floating point coding method, and a symbol coding method, and any one of the coding methods may be selected, encoding each chromosome to form each individual, wherein each individual is the minimum unit of evolution, then, the function value obtained by calculation according to the objective function can be determined as the fitness value of each individual in the population, namely, the smaller the fitness value, the closer the individual is to the optimal solution, at the moment, the individual with the minimum fitness value is determined as the global optimal individual, namely, the individual closest to the optimal solution in the population is determined, at the moment, whether the algorithm termination condition is met or not is judged, if so, the global optimal individual can be decoded to obtain the optimal solution, if not, at least two genetic individuals can be selected according to the fitness values, the main purpose of selection is to select the superior individual and eliminate the inferior individual, and particularly, the individual with each fitness value smaller than the preset fitness value can be determined as the genetic individual by setting the preset fitness value, and then, carrying out crossing and variation processing on the genetic individuals according to a preset crossing rate and a preset variation rate to obtain at least two crossing individuals and at least one variation individual, forming the at least two genetic individuals, the at least two crossing individuals and the at least one variation individual into a new population, replacing the original population with the new population, repeating the operation until an algorithm termination condition is met, and determining the optimal solution of the objective function, wherein the algorithm considers the coupling between the fan frequency and the chilled water flow of the variable air volume central air-conditioning system, and can determine the optimal fan frequency and the optimal chilled water flow during the operation of the variable air volume central air-conditioning system.
For example, the larger the population size, the more likely the optimal solution of the objective function is to be found, but the algorithm running time is also relatively longer, and for better calculation effect and calculation efficiency, the population size may be set to 20; the crossing rate determines the proportion of the number of individuals generated by crossing in the next generation population to the total number of the population, and in order to better improve each individual, the crossing probability can be set to be 0.4; the variation rate determines the proportion of the number of individuals generated by variation in the next generation population to the total number of the population, and in order to better improve each individual, the variation probability can be set to be 0.1; the chromosome includes fan frequency and chilled water flow, and the fan flow and the chilled water flow in the chromosome can be encoded and decoded by adopting a binary coding method, for example, the chromosome with the fan frequency of 13 and the chilled water flow of 7 is encoded to obtain an individual, the fan frequency 13 is binary-coded to obtain a binary coding string 1101, the chilled water flow is binary-coded to obtain another binary coding string 111, at this time, the coding string of an individual is 1101111, wherein the first four bits "1101" in the individual coding string represent the fan frequency, the 3 bits "111" after coding represent the chilled water flow, when the individual is decoded, the binary decoding method for "1101" can be performed to obtain the fan frequency of 13, and the binary decoding method for "111" can be performed to obtain the chilled water flow of 7.
For example, taking a population composed of 6 individuals 101010, 111101, 111001, 110100, 101101, 100000, the crossing rate is 0.4, the variation rate is 0.1 as an example, assuming that the fitness values corresponding to the 6 individuals 101010, 111101, 111001, 110100, 101101, 100000 are 1, 2, 3, 4, 5, 6, the smaller the fitness value is, the closer to the optimal solution, the individual 101010 with the fitness value of 1 is determined as the global optimal individual, if the determination result of whether the algorithm termination condition is satisfied is yes, the global optimal individual 101010 is decoded to obtain the optimal solution of the objective function, if the determination result of whether the algorithm termination condition is satisfied is no, the individual 100000 with the fitness value of 6 is eliminated according to the fitness value, the individual with the fitness value smaller than 6 is selected as the genetic individual, that is 101010, 111101, 111001, 110100, 101101 as the genetic individual, and the 5 genetic individuals are cross-processed according to the crossing rate, for example, the genetic individuals 110100 and 111001 are crossed to generate new individuals 111000 and 110101, 5 genetic individuals and 2 new individuals are subjected to mutation treatment according to the mutation rate, for example, the genetic individuals 110100 are subjected to mutation treatment to generate new individuals 110110, and the new individuals 111000 and 110101, 110110 and 5 genetic individuals 101010, 111101, 111001, 110100 and 101010 which are crossed are selected as new populations.
In one embodiment of the invention, the termination condition comprises a maximum number of iterations;
then the process of the first step is carried out,
the A4, further comprising: recording the iterative updating times of the globally optimal individual;
the judging whether the termination condition is met includes:
detecting whether the recorded iteration updating times reach the maximum iteration times;
in this embodiment, the maximum iteration number is the maximum iteration number of the process of determining the globally optimal individual, and the final purpose is to approach the required optimal solution, and the termination condition of the algorithm may be determined as the maximum iteration number, for example, the maximum iteration number is set to 100 generations, and the globally optimal individual when the population iterates 100 times can be determined.
In one embodiment of the invention, the termination condition comprises an optimal fitness value;
then, the determining whether the termination condition is satisfied includes:
detecting whether the fitness value of the globally optimal individual reaches the optimal fitness value.
In this embodiment, the optimal fitness value is the fitness value of the individual corresponding to the optimal solution of the objective function, the fitness value of the globally optimal individual may represent the individual closest to the optimal solution in the population, and the global optimal individual reaching the optimal fitness value may be determined by determining the algorithm termination condition as the optimal fitness value.
In one embodiment of the present invention, said selecting at least two genetic individuals from said population based on said fitness value of each of said individuals comprises:
determining at least two candidate individuals according to the fitness value of each individual;
and decoding the candidate individuals to obtain current fan frequency and current chilled water flow for each candidate individual, detecting whether the cooling capacity generated by the variable air volume central air conditioner when the variable air volume central air conditioner operates according to the current fan frequency and the chilled water flow is not less than the preset cooling load demand, and if so, taking the candidate individuals as genetic individuals.
In this embodiment, at least one individual greater than the preset fitness value may be specifically selected as the candidate individual, and at this time, it is determined whether each candidate individual satisfies the constraint condition (the cooling capacity is not less than the preset cooling load demand), and if so, at least one candidate individual may be determined as the genetic individual, and through this process, the genetic individual closer to the optimal solution may be selected.
It should be noted that the cold load requirement refers to the amount of heat that must be removed from the room by the air conditioning system in order to maintain the hot and humid environment of the building and the required indoor temperature; the cooling capacity specifically refers to the cooling capacity supplied to the room by the air conditioning system at a certain moment.
Based on the same concept as the method embodiment of the present invention, referring to fig. 3, the embodiment of the present invention further provides a device for air volume and water volume combination optimization of a variable air volume central air conditioner, comprising:
a construction function module 301, configured to construct an objective function, where the objective function includes a functional relationship between a fan frequency, a chilled water flow rate, and a total energy consumption of the variable air volume central air conditioner;
an interval determination module 302, configured to determine a fan frequency interval and a chilled water flow interval;
and an optimal solution determining module 303, configured to solve an optimal solution of the objective function based on a genetic algorithm according to the fan frequency interval and the chilled water flow interval, where the optimal solution includes an optimal fan frequency and an optimal chilled water flow.
Referring to fig. 4, in an embodiment of the present invention, the optimal solution determining module 303 includes: a parameter determining unit 3031, a first population determining unit 3032, an individual determining unit 3033, a fitness value determining unit 3034, a judging unit 3035, a selecting unit 3036, a cross variation unit 3037, a second population determining unit 3038 and an optimal solution determining unit 3039; wherein the content of the first and second substances,
the parameter determining unit 3031 is configured to determine algorithm parameters, where the algorithm parameters include a population scale, a crossover rate, a variation rate, and a termination condition;
the first population determining unit 3032 is configured to form a population composed of at least two chromosomes according to the population scale, where the chromosomes include a fan frequency and a chilled water flow rate, the fan frequency is located in the fan frequency interval, the chilled water flow rate is located in the chilled water flow rate interval, and a cooling capacity generated when the variable air volume central air conditioner operates according to the fan frequency and the chilled water flow rate is greater than a preset cooling load demand;
the individual determining unit 3033 is used for encoding each chromosome in the population to form an individual;
the fitness value unit 3034 is configured to calculate a fitness value of each individual in the population according to the objective function, and determine a global optimal individual according to the fitness value of each individual;
the determining unit 3035 is configured to determine whether the termination condition is met, if yes, trigger the optimal solution determining unit 3039, and otherwise, trigger the selecting unit 3036;
the selecting unit 3036 is configured to select at least two genetic individuals from the population according to the fitness value of each individual.
The crossover variation unit 3037 is configured to sequentially perform crossover processing and variation processing on the at least two selected genetic individuals according to the crossover rate and the variation rate to obtain at least two crossover individuals and at least one variation individual;
the second population determining unit 3038 is configured to form the population by using each of the genetic individuals, the at least two crossover individuals, and the at least one variant individual, and trigger the fitness value unit 3034;
the optimal solution determining unit 3039 is configured to decode the globally optimal individual to obtain an optimal fan frequency and an optimal chilled water flow rate.
In one embodiment of the invention, the termination condition comprises a maximum number of iterations;
then the process of the first step is carried out,
the fitness value determining unit 3034 is further configured to record iterative update times of the globally optimal individual;
the determining unit 3035 is configured to detect whether the recorded iteration update times reaches the maximum iteration times;
in one embodiment of the invention, the termination condition comprises an optimal fitness value;
then, the determining unit 3035 is configured to detect whether the minimum fitness value reaches the optimal fitness value.
In an embodiment of the present invention, the selecting unit 3036 is configured to determine at least two candidate individuals according to the fitness value of each of the individuals; and decoding the candidate individuals to obtain current fan frequency and current chilled water flow for each candidate individual, detecting whether the cooling capacity generated by the variable air volume central air conditioner when the variable air volume central air conditioner operates according to the current fan frequency and the chilled water flow is not less than the preset cooling load demand, and if so, taking the candidate individuals as genetic individuals.
For convenience of description, the above device embodiments are described with functions divided into various units or modules, and the functions of the units or modules may be implemented in one or more software and/or hardware when implementing the present invention.
Fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention. On the hardware level, the electronic device includes a processor 401 and a memory 402 storing execution instructions, and optionally an internal bus 403 and a network interface 404. The memory 402 may include a memory 4021, such as a Random-access memory (RAM), and may further include a non-volatile memory 4022 (e.g., at least 1 disk memory); the processor 401, the network interface 404, and the memory 402 may be connected to each other by an internal bus 403, and the internal bus 403 may be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, an EISA (extended Industry Standard Architecture) bus, or the like; the internal bus 403 may be divided into an address bus, a data bus, a control bus, etc., and only one bi-directional arrow is shown in fig. 4 for convenience of illustration, but does not indicate only one bus or one type of bus. Of course, the electronic device may also include hardware required for other services. When the processor 401 executes execution instructions stored by the memory 402, the processor 401 performs the method described in any of the embodiments of the present invention and at least is used to perform the method described in fig. 1.
In a possible implementation mode, the processor reads corresponding execution instructions from the nonvolatile memory to the memory and then runs the corresponding execution instructions, and corresponding execution instructions can also be obtained from other equipment, so that a method for optimizing the air quantity combination of the variable air quantity central air conditioner is formed on a logic level. The processor executes the execution instruction stored in the memory, so that the method for optimizing the combination of the air volume and the water volume of the variable air volume central air conditioner provided by any embodiment of the invention is realized through the executed execution instruction.
The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but also Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The embodiment of the invention also provides a computer readable medium, which comprises an execution instruction, and when a processor of the electronic device executes the execution instruction, the electronic device executes the method provided in any embodiment of the invention. The electronic device may specifically be the electronic device shown in fig. 4; the execution instruction is a computer program corresponding to a device for optimizing the air quantity and water quantity combination of the variable air quantity central air conditioner.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects.
The embodiments of the present invention are described in a progressive manner, and the same and similar parts among the embodiments can be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above description is only an example of the present invention, and is not intended to limit the present invention. Various modifications and alterations to this invention will become apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of the claims of the present invention.
Claims (10)
1. A method for optimizing the combination of air volume and water volume of a variable air volume central air conditioner is characterized by comprising the following steps:
constructing an objective function, wherein the objective function comprises a functional relation among fan frequency, chilled water flow and total energy consumption of the variable air volume central air conditioner;
determining a fan frequency interval and a chilled water flow interval;
and solving an optimal solution of the objective function based on a genetic algorithm according to the fan frequency interval and the chilled water flow interval, wherein the optimal solution comprises an optimal fan frequency and an optimal chilled water flow.
2. The method of claim 1,
solving the optimal solution of the objective function based on a genetic algorithm according to the fan frequency interval and the chilled water flow interval, wherein the optimal solution comprises the following steps:
a1, determining algorithm parameters, wherein the algorithm parameters comprise population size, crossing rate, variation rate and termination condition;
a2, forming a population consisting of at least two chromosomes according to the population scale, wherein the chromosomes comprise a fan frequency and a chilled water flow, the fan frequency is located in a fan frequency interval, the chilled water flow is located in a chilled water flow interval, and the cooling capacity generated when the variable air volume central air conditioner operates according to the fan frequency and the chilled water flow is greater than the preset cooling load demand;
a3, aiming at each chromosome in the population, carrying out coding treatment on the chromosome to form an individual;
a4, calculating the fitness value of each individual in the population according to the objective function, and determining a global optimal individual according to the fitness value of each individual;
a5, judging whether the termination condition is met, if so, executing A9, otherwise, executing A6;
a6, selecting at least two genetic individuals from the population according to the fitness value of each individual;
a7, sequentially carrying out cross treatment and variation treatment on the at least two selected genetic individuals according to the cross rate and the variation rate to obtain at least two cross individuals and at least one variation individual;
a8, forming the population using each of the genetic individuals, the at least two crossover individuals, and the at least one variant individual, and performing a 4;
and A9, decoding the globally optimal individual to obtain the optimal fan frequency and the optimal chilled water flow.
3. The method of claim 2,
the termination condition comprises a maximum number of iterations;
then the process of the first step is carried out,
the A4, further comprising: recording the iterative updating times of the globally optimal individual;
the judging whether the termination condition is met includes:
detecting whether the recorded iteration updating times reach the maximum iteration times;
or the like, or, alternatively,
the termination condition comprises an optimal fitness value;
then, the determining whether the termination condition is satisfied includes:
detecting whether the fitness value of the globally optimal individual reaches the optimal fitness value.
4. The method of claim 2,
the A6, comprising:
determining at least two candidate individuals according to the fitness value of each individual;
and decoding the candidate individuals to obtain current fan frequency and current chilled water flow for each candidate individual, detecting whether the cooling capacity generated by the variable air volume central air conditioner when the variable air volume central air conditioner operates according to the current fan frequency and the chilled water flow is not less than the preset cooling load demand, and if so, taking the candidate individuals as genetic individuals.
5. The utility model provides a device that variable blast volume central air conditioning air flow volume combination was optimized which characterized in that includes:
the construction function module is used for constructing an objective function, and the objective function comprises a functional relation among fan frequency, chilled water flow and total energy consumption of the variable air volume central air conditioner;
the interval determining module is used for determining a fan frequency interval and a chilled water flow interval;
and the optimal solution determining module is used for solving the optimal solution of the objective function based on a genetic algorithm according to the fan frequency interval and the chilled water flow interval, wherein the optimal solution comprises the optimal fan frequency and the optimal chilled water flow.
6. The apparatus of claim 5,
the optimal solution determination module comprises: the system comprises a parameter determining unit, a first group determining unit, an individual determining unit, an adaptability value determining unit, a judging unit, a selecting unit, a cross variation unit, a second group determining unit and an optimal solution determining unit; wherein the content of the first and second substances,
the parameter determining unit is used for determining algorithm parameters, and the algorithm parameters comprise population scale, crossing rate, variation rate and termination condition;
the first population determining unit is used for forming a population consisting of at least two chromosomes according to the population scale, wherein the chromosomes comprise a fan frequency and a chilled water flow, the fan frequency is located in a fan frequency interval, the chilled water flow is located in a chilled water flow interval, and the cooling capacity generated by the variable air volume central air conditioner when the variable air volume central air conditioner operates according to the fan frequency and the chilled water flow is greater than the preset cooling load demand;
the individual determination unit is used for encoding each chromosome in the population to form an individual;
the fitness value unit is used for calculating the fitness value of each individual in the population according to the objective function and determining a global optimal individual according to the fitness value of each individual;
the judging unit is used for judging whether the termination condition is met, if so, the optimal solution determining unit is triggered, and if not, the selecting unit is triggered;
the selection unit is used for selecting at least two genetic individuals from the population according to the fitness value of each individual;
the cross mutation unit is used for sequentially carrying out cross treatment and mutation treatment on the at least two selected genetic individuals according to the cross rate and the mutation rate to obtain at least two cross individuals and at least one mutation individual;
the second population determining unit is used for forming the population by utilizing each genetic individual, the at least two crossed individuals and the at least one variant individual and triggering the fitness value unit;
and the optimal solution determining unit is used for decoding the globally optimal individual to obtain the optimal fan frequency and the optimal chilled water flow.
7. The apparatus of claim 6,
the termination condition comprises a maximum number of iterations;
then the process of the first step is carried out,
the fitness value determining unit is further used for recording the iterative updating times of the globally optimal individual;
the judging unit is used for detecting whether the recorded iteration updating times reach the maximum iteration times;
or the like, or, alternatively,
the termination condition comprises an optimal fitness value;
then, the determining unit is configured to detect whether the minimum fitness value reaches the optimal fitness value.
8. The apparatus of any one of claim 6,
the selection unit is used for determining at least two candidate individuals according to the fitness value of each individual; and decoding the candidate individuals to obtain current fan frequency and current chilled water flow for each candidate individual, detecting whether the cooling capacity generated by the variable air volume central air conditioner when the variable air volume central air conditioner operates according to the current fan frequency and the chilled water flow is not less than the preset cooling load demand, and if so, taking the candidate individuals as genetic individuals.
9. A readable medium comprising executable instructions which, when executed by a processor of an electronic device, cause the electronic device to perform the method of any of claims 1 to 4.
10. An electronic device comprising a processor and a memory storing execution instructions, the processor performing the method of any of claims 1-4 when the processor executes the execution instructions stored by the memory.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113761807A (en) * | 2021-09-28 | 2021-12-07 | 科瑞特空调集团有限公司 | Hybrid optimization-based quick air-conditioning air-water system optimization method |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102734890A (en) * | 2011-04-13 | 2012-10-17 | 上海信业智能科技股份有限公司 | Fuzzy control method and device for chilled water of central air-conditioning and central air-conditioning system |
| CN104566868A (en) * | 2015-01-27 | 2015-04-29 | 徐建成 | Central air-conditioning control system and control method thereof |
| CN104713205A (en) * | 2013-12-12 | 2015-06-17 | 广州市地下铁道总公司 | Ventilation air conditioning energy saving system for subway |
| CN106940068A (en) * | 2017-03-15 | 2017-07-11 | 山东大学 | A kind of determination method of the water cool-storage technology energy saving of system Optimal Control Strategy based on GACA algorithm |
| CN107017640A (en) * | 2017-06-12 | 2017-08-04 | 广东工业大学 | A kind of optimal load flow computational methods of power system, apparatus and system |
-
2019
- 2019-02-25 CN CN201910136194.0A patent/CN111609524A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102734890A (en) * | 2011-04-13 | 2012-10-17 | 上海信业智能科技股份有限公司 | Fuzzy control method and device for chilled water of central air-conditioning and central air-conditioning system |
| CN104713205A (en) * | 2013-12-12 | 2015-06-17 | 广州市地下铁道总公司 | Ventilation air conditioning energy saving system for subway |
| CN104566868A (en) * | 2015-01-27 | 2015-04-29 | 徐建成 | Central air-conditioning control system and control method thereof |
| CN106940068A (en) * | 2017-03-15 | 2017-07-11 | 山东大学 | A kind of determination method of the water cool-storage technology energy saving of system Optimal Control Strategy based on GACA algorithm |
| CN107017640A (en) * | 2017-06-12 | 2017-08-04 | 广东工业大学 | A kind of optimal load flow computational methods of power system, apparatus and system |
Non-Patent Citations (1)
| Title |
|---|
| 周璇: "基于遗传算法的空调机组风量水量最优组合优化研究", 《建筑科学》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113761807A (en) * | 2021-09-28 | 2021-12-07 | 科瑞特空调集团有限公司 | Hybrid optimization-based quick air-conditioning air-water system optimization method |
| CN113761807B (en) * | 2021-09-28 | 2022-11-15 | 科瑞特空调集团有限公司 | Hybrid optimization-based quick air-conditioning air-water system optimization method |
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