CN114440404B - Load distribution method and device of air conditioning system and electronic equipment - Google Patents
Load distribution method and device of air conditioning system and electronic equipment Download PDFInfo
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- CN114440404B CN114440404B CN202210121460.4A CN202210121460A CN114440404B CN 114440404 B CN114440404 B CN 114440404B CN 202210121460 A CN202210121460 A CN 202210121460A CN 114440404 B CN114440404 B CN 114440404B
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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
- F24F11/30—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
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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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- F24F11/64—Electronic processing using pre-stored data
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Abstract
The invention provides a load distribution method and device of an air conditioning system and electronic equipment. Wherein the method comprises the following steps: determining a plurality of load distribution schemes corresponding to the total load of the air conditioning system, and calculating the adaptability corresponding to the plurality of distribution schemes; judging whether the air conditioning system meets preset constraint conditions or not based on the optimal adaptability; if not, adjusting the load of each equipment unit in the air conditioning system, and calculating the total energy consumption of the air conditioning system based on the adjusted load of each equipment unit; continuously executing the step of calculating the adaptability corresponding to the plurality of distribution schemes until the air conditioning system meets the constraint condition; and controlling the air conditioning system to execute operation based on the load distribution scheme corresponding to the total energy consumption meeting the constraint condition. The load of each equipment unit of the air conditioning system can be optimally distributed, so that the overall performance of the unit system is optimal, the energy consumption is minimum, the calculation speed of an optimization algorithm is high, the efficiency is high, and the method is applicable to sites with real-time requirements.
Description
Technical Field
The present invention relates to the technical field of air conditioning systems, and in particular, to a load distribution method, apparatus and electronic device for an air conditioning system.
Background
In general, in the total energy consumption of a building air conditioning system, the energy consumption of a water chiller is generally more than 40% of the total energy consumption of the air conditioning system, in most cases, the air conditioning system of the building is composed of multiple units, the type selection design of the air conditioning system is generally designed according to the maximum load, however, most cases are that the air conditioning load is smaller than the designed load, the partial load energy consumption is related to the characteristics and the load distribution of the air conditioning system, and the overall efficiency level of the air conditioning system is reduced when the air conditioning system has unreasonable load distribution of the multiple units under the partial load.
In order to achieve the effect of reducing energy consumption when the air conditioning system runs under partial load, after the type of the water chilling unit is determined, the control of the building air conditioning system usually adopts the optimization logic strategies such as equal proportion distribution, unit priority and the like under constant water supply temperature, but the control method of the building air conditioning system only realizes water outlet temperature control and simple optimization, and the running of the air conditioning system is not controlled and optimized globally, so that the overall performance of the air conditioning system is poor, the energy consumption is higher, the optimization speed is slower, and the method cannot be suitable for sites with real-time requirements. Therefore, how to reasonably distribute the cold load born by each water chiller, and reducing the total energy consumption of the system as much as possible have become the key of energy conservation and consumption reduction.
Disclosure of Invention
In view of the above, the present application aims to provide a load distribution method, a load distribution device and an electronic device for an air conditioning system, so as to improve the overall performance of the air conditioning system, reduce the energy consumption, increase the optimization speed, and be suitable for sites with real-time requirements.
In a first aspect, an embodiment of the present application provides a load distribution method of an air conditioning system, where the method includes: determining a plurality of load distribution schemes corresponding to the total load of the air conditioning system, and calculating the adaptability corresponding to the plurality of distribution schemes; judging whether the air conditioning system meets preset constraint conditions or not based on the optimal adaptability; wherein, the optimal fitness is the maximum value in fitness; if not, adjusting the load of each equipment unit in the air conditioning system, and calculating a plurality of total energy consumption of the air conditioning system based on the adjusted load of each equipment unit; continuously executing the step of calculating the adaptability corresponding to the plurality of distribution schemes until the air conditioning system meets the constraint condition; and controlling the air conditioning system to execute operation based on the allocation scheme corresponding to the total energy consumption meeting the constraint condition.
In a preferred embodiment of the present application, the step of determining a plurality of load distribution schemes corresponding to a total load of the air conditioning system and calculating fitness corresponding to the plurality of distribution schemes includes: acquiring a plurality of load distribution schemes corresponding to the total load of an air conditioning system; wherein each distribution scheme comprises the load of each equipment unit of the air conditioning system; the total energy consumption corresponding to each allocation scheme is determined based on the load of each equipment set of the air conditioning system.
In a preferred embodiment of the present application, the step of calculating the fitness corresponding to the plurality of allocation schemes includes: the fitness corresponding to the plurality of allocation schemes is calculated by the following formula:wherein f i Adaptation for the ith allocation schemeDegree, P max For maximum of multiple total energy consumption, P min Is the minimum value of a plurality of total energy consumption, P i For the ith total energy consumption, Δε is a preset first boundary processing coefficient and Δε' is a preset second boundary processing coefficient.
In a preferred embodiment of the present application, the step of determining whether the air conditioning system meets a preset constraint condition based on the optimal fitness includes: determining an optimal fitness in a specified number of iterations of the air conditioning system; if the difference values of the adjacent optimal fitness are smaller than a preset fitness threshold value, determining that the air conditioning system meets constraint conditions; if there is at least one adjacent difference in optimal fitness that is greater than or equal to the fitness threshold, it is determined that the air conditioning system does not satisfy the constraint.
In a preferred embodiment of the present application, the method further includes: determining the iteration times of an air conditioning system; judging whether the iteration times are larger than a preset time threshold value or not; if yes, determining that the air conditioning system meets constraint conditions; if not, determining that the air conditioning system does not meet the constraint condition.
In a preferred embodiment of the present application, the step of adjusting the load of each equipment set in the air conditioning system includes: if the load of the equipment unit in the air conditioning system is larger than a preset load threshold value, reducing the load of the equipment unit in the air conditioning system; and if the load of the equipment unit in the air conditioning system is smaller than the load threshold value, increasing the load of the equipment unit in the air conditioning system.
In a preferred embodiment of the present application, after the step of calculating the total energy consumption of the air conditioning system based on the adjusted loads of the respective equipment units, the method further includes: and replacing the load of the equipment unit corresponding to the distribution scheme corresponding to the optimal fitness before adjustment with the load of the equipment unit corresponding to the distribution scheme corresponding to the minimum fitness after adjustment.
In a preferred embodiment of the present application, after the step of calculating the total energy consumption of the air conditioning system based on the adjusted loads of the respective equipment units, the method further includes: randomly selecting a first allocation scheme and a second total allocation scheme from the allocation schemes; and randomly replacing the load of the equipment unit corresponding to the first distribution scheme and the load of the equipment unit corresponding to the second total distribution scheme.
In a preferred embodiment of the present application, the step of randomly selecting the first allocation scheme and the second allocation scheme from the allocation schemes includes: calculating the probability of each allocation scheme based on the fitness; the first allocation scheme and the second allocation scheme are randomly selected based on the probabilities.
In a preferred embodiment of the present application, the step of calculating the probability of each total allocation scheme based on the fitness includes: the probability distribution of each allocation scheme is calculated based on the fitness by the following formula: p is p i ＝∑f i ′，Wherein, (p) i ,p i+1 ]For the selected probability interval of the ith fitness, m is the number of fitness, f i Is the i-th fitness.
In a preferred embodiment of the present application, after the step of calculating the total energy consumption of the air conditioning system based on the adjusted loads of the respective equipment units, the method further includes: and randomly selecting a target distribution scheme from the distribution scheme of the air conditioning system, and adjusting the load of the equipment unit corresponding to the target distribution scheme.
In a preferred embodiment of the present application, the step of adjusting the load of the equipment set corresponding to the target allocation scheme includes: determining a random number in a preset random number range; if the random number is smaller than the preset random number threshold value, the load of the equipment unit corresponding to the target allocation scheme is adjusted through the following formula:if the random number is greater than or equal to the random number threshold value, the load of the equipment unit corresponding to the target allocation scheme is adjusted through the following formula: /> Wherein f ij For the load of the ith corresponding jth equipment unit, C ij The refrigerating capacity of the jth equipment set corresponding to the ith allocation scheme is C ij_max Maximum refrigerating capacity of the jth equipment set corresponding to the ith allocation scheme, C ij_min And (3) for the minimum refrigerating capacity of the jth equipment unit corresponding to the ith allocation scheme, r is a random number, G is the current iteration number, and G is a preset number threshold.
In a second aspect, an embodiment of the present invention further provides a load distribution apparatus of an air conditioning system, where the apparatus includes: the fitness calculation module is used for determining a plurality of load distribution schemes corresponding to the total load of the air conditioning system and calculating fitness corresponding to the plurality of distribution schemes; the constraint condition judgment module is used for judging whether the air conditioning system meets preset constraint conditions or not based on the optimal adaptability; wherein, the optimal fitness is the maximum value in fitness; the load correction module is used for adjusting the load of each equipment unit in the air conditioning system if not, and calculating a plurality of total energy consumption of the air conditioning system based on the adjusted load of each equipment unit; the air conditioning unit iteration module is used for continuously executing the step of calculating the adaptability corresponding to the plurality of distribution schemes until the air conditioning system meets the constraint condition; and the air conditioning system operation module is used for controlling the air conditioning system to execute operation based on the allocation scheme corresponding to the total energy consumption meeting the constraint condition.
In a third aspect, an embodiment of the present invention further provides an electronic device, including a processor and a memory, where the memory stores computer executable instructions that can be executed by the processor, and the processor executes the computer executable instructions to implement the load distribution method of the air conditioning system.
In a fourth aspect, embodiments of the present invention also provide a computer-readable storage medium storing computer-executable instructions that, when invoked and executed by a processor, cause the processor to implement the load distribution method of an air conditioning system described above.
The embodiment of the invention has the following beneficial effects:
the load distribution method, the load distribution device and the electronic equipment of the air conditioning system provided by the embodiment of the invention can judge whether the air conditioning system meets the preset constraint condition based on the adaptability of a plurality of load distribution schemes of the air conditioning system; if not, the load of each equipment unit in the air conditioning system is adjusted until the adjusted air conditioning system meets the constraint condition, and the air conditioning system is controlled to execute operation based on a load distribution scheme corresponding to the total energy consumption meeting the constraint condition. In the mode, the load of each equipment unit of the air conditioning system can be optimally distributed, so that the overall performance of the unit system is optimal, the energy consumption is minimum, the calculation speed of an optimization algorithm is high, the efficiency is high, and the method is applicable to sites with real-time requirements.
Additional features and advantages of the disclosure will be set forth in the description which follows, or in part will be obvious from the description, or may be learned by practice of the techniques of the disclosure.
The foregoing objects, features and advantages of the disclosure will be more readily apparent from the following detailed description of the preferred embodiments taken in conjunction with the accompanying drawings.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of another load distribution method of an air conditioning system according to an embodiment of the present invention;
fig. 2 is a flowchart of a load distribution method of an air conditioning system according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a method for load distribution of an air conditioning system using a genetic algorithm according to an embodiment of the present invention;
Fig. 4 is a schematic structural diagram of a load distribution device of an air conditioning system according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of another load distribution device of an air conditioning system according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
At present, in general, in the total energy consumption of a building air conditioning system, the energy consumption of a water chiller is generally more than 40% of the total energy consumption of the air conditioning system, in most cases, the air conditioning system of the building is composed of multiple units, the air conditioning system is generally designed according to the maximum load, however, in most cases, the air conditioning load is smaller than the designed load, the partial load energy consumption is related to the characteristics and the load distribution of the air conditioning system, and in the partial load, the air conditioning system has the unreasonable load distribution of the multiple units, so that the overall efficiency level of the air conditioning system can be reduced.
In order to achieve the effect of reducing energy consumption when the air conditioning system runs under partial load, after the type of the water chilling unit is determined, the control of the building air conditioning system usually adopts the optimization logic strategies such as equal proportion distribution, unit priority and the like under constant water supply temperature, but the control method of the building air conditioning system only realizes water outlet temperature control and simple optimization, and the running of the air conditioning system is not controlled and optimized globally, so that the overall performance of the air conditioning system is poor, the energy consumption is higher, the optimization speed is slower, and the method cannot be suitable for sites with real-time requirements.
Therefore, how to reasonably distribute the cold load born by each water chiller, and reducing the total energy consumption of the system as much as possible have become the key of energy conservation and consumption reduction. Based on the above, the embodiment of the invention provides a load distribution method, a device and electronic equipment of an air conditioning system, in particular to a genetic algorithm-based multi-unit load distribution optimization method of a heating and ventilation system, which can optimize and distribute loads of all equipment units of the air conditioning system, so that the overall performance of the unit system is optimal, the energy consumption is minimum, and the optimization algorithm has high calculation speed and high efficiency and can be suitable for sites with real-time requirements.
For the convenience of understanding the present embodiment, a load distribution method of an air conditioning system disclosed in the embodiment of the present invention will be described in detail.
Embodiment one:
the embodiment of the invention provides a load distribution method of an air conditioning system, as shown in a flow chart of the load distribution method of the air conditioning system in fig. 1, the load distribution method of the air conditioning system comprises the following steps:
step S102, a plurality of load distribution schemes corresponding to the total load of the air conditioning system are determined, and the adaptability corresponding to the plurality of distribution schemes is calculated.
The air conditioning system in the embodiment of the invention may be provided with a plurality of air conditioning apparatuses, for example: compressors, water pumps, etc. A unit may include a compressor and a water pump, for example: the air conditioning system comprises 5 compressors and 5 water pumps, and then can comprise 5 units.
The load distribution scheme of the air conditioning system is a scheme for determining the opening degree of each air conditioning device in the air conditioning system, wherein the opening degree of the same device unit is generally the same, and therefore, the load distribution scheme of the air conditioning system can be understood as a scheme for determining the opening degree of different device units.
Specifically, the multiple distribution schemes in the embodiments of the present invention have the same total load, that is, the total load of the air conditioning system, which can be understood as the sum of the loads of all the equipment units in the air conditioning system of each distribution scheme. However, although the total load of each allocation scheme is the same, the total energy consumption of each allocation scheme is not necessarily the same, and the embodiment of the present invention may calculate the fitness corresponding to a plurality of total energy consumption by adopting the fitness function in the preset genetic algorithm.
In genetic algorithms, fitness is a major indicator describing the performance of an individual. And (5) according to the fitness, performing winner and winner elimination on the individual. Fitness is the motive force driving genetic algorithms. From a biological perspective, fitness corresponds to the viability of "competing for survival, surviving the fittest" organism, and is of great importance in genetic processes. And establishing a mapping relation between the objective function of the optimization problem and the fitness of the individual, and optimizing the objective function of the optimization problem in the group evolution process. The fitness function, also called the evaluation function, is a criterion for distinguishing between the quality of an individual in a population, determined from an objective function, which is always non-negative, the larger its value is in any case desired to be the better.
In the embodiment of the invention, the refrigerating capacity of the equipment unit can be used as a gene in a genetic algorithm, a plurality of genes form individuals in 1 genetic algorithm, namely, the total load of an air conditioning system is used as an individual, and the total load corresponding to a plurality of load distribution schemes is used as a population (also called a population) in the genetic algorithm.
Step S104, judging whether the air conditioning system meets preset constraint conditions or not based on the optimal adaptability; wherein, the optimal fitness is the maximum value in fitness.
After determining the fitness of each individual, it may be determined whether the air conditioning system satisfies a preset constraint, for example, based on the optimal fitness among the fitness: and judging whether the value of the optimal fitness in the continuous several times of iteration processes is close. Of course, it may also be determined in other manners whether the air conditioning system meets a preset constraint condition, for example: whether the number of iterations exceeds a preset threshold, etc.
Step S106, if not, the load of each equipment set in the air conditioning system is adjusted, and a plurality of total energy consumption of the air conditioning system is calculated based on the adjusted load of each equipment set.
If the air conditioning system does not meet the preset constraint condition, the individual value, namely the load of each equipment unit in the air conditioning system, needs to be adjusted, the distribution scheme is changed along with the load of each equipment unit, and the total energy consumption of the air conditioning system is also changed along with the load of each equipment unit.
Step S108, the step of calculating the adaptability degrees corresponding to the distribution schemes is continuously executed until the air conditioning system meets the constraint condition.
After the load of each equipment unit in the air conditioning system is adjusted, the adaptability corresponding to the adjusted allocation scheme can be continuously calculated, and whether the adjusted air conditioning unit meets the preset constraint condition or not is continuously determined; if still not, the adjustment is needed to be continued until the constraint condition is met.
Step S110, controlling the air conditioning system to execute the operation based on the allocation scheme corresponding to the total energy consumption satisfying the constraint condition.
If the air conditioning system meets the constraint condition, an allocation scheme corresponding to the total energy consumption meeting the constraint condition can be determined, and the air conditioning unit is controlled to execute the allocation scheme so as to optimize the load of each equipment unit for allocating the air conditioning system, so that the overall performance of the unit system is optimal and the energy consumption is lowest.
The load distribution method of the air conditioning system provided by the embodiment of the invention can judge whether the air conditioning system meets the preset constraint condition or not based on the adaptability of a plurality of load distribution schemes of the air conditioning system; if not, the load of each equipment unit in the air conditioning system is adjusted until the adjusted air conditioning system meets the constraint condition, and the air conditioning system is controlled to execute operation based on a load distribution scheme corresponding to the total energy consumption meeting the constraint condition. In the mode, the load of each equipment unit of the air conditioning system can be optimally distributed, so that the overall performance of the unit system is optimal, the energy consumption is minimum, the calculation speed of an optimization algorithm is high, the efficiency is high, and the method is applicable to sites with real-time requirements.
Embodiment two:
The present embodiment provides another load distribution method of an air conditioning system, which is implemented on the basis of the above embodiment, as shown in a flowchart of another load distribution method of an air conditioning system in fig. 2, where the load distribution method of an air conditioning system in the present embodiment includes the following steps:
step S202, a plurality of load distribution schemes corresponding to the total load of the air conditioning system are determined, and the adaptability corresponding to the plurality of distribution schemes is calculated.
Specifically, a plurality of load distribution schemes corresponding to the total load of the air conditioning system can be determined by the following steps, and the fitness corresponding to the plurality of distribution schemes is calculated: acquiring a plurality of load distribution schemes corresponding to the total load of an air conditioning system; wherein each distribution scheme comprises the load of each equipment unit of the air conditioning system; the total energy consumption corresponding to each allocation scheme is determined based on the load of each equipment set of the air conditioning system.
The load of each equipment set of each air conditioning system can be respectively determined from each load distribution scheme of the air conditioning system, and the total energy consumption of the distribution scheme can be calculated based on the load of each equipment set of the distribution scheme.
The embodiment of the invention can adopt a genetic algorithm to distribute the load of the air conditioning system. The genetic algorithm is a search algorithm based on natural selection and population genetic mechanism, which simulates the phenomena of propagation, hybridization and mutation in natural selection and natural genetic process. When the problem is solved by using genetic algorithm, each possible solution of the problem is encoded as one "chromosome", i.e. individual, several individuals constituting a population (all possible solutions). At the beginning of the genetic algorithm, individuals (namely initial solutions) are randomly generated at all times, each individual is evaluated according to a preset objective function, an fitness value is given, based on the fitness value, some individuals are selected to generate the next generation, the selection operation shows the principle of ' survival of the right, good ' individuals are used for generating the next generation, bad ' individuals are eliminated, then the selected individuals are recombined through crossover and mutation operators to generate a new generation, and the individuals of the new generation are superior to the previous generation in performance because of inheriting some excellent characters of the previous generation, so that the individuals gradually evolve towards the optimal solution. Thus, the genetic algorithm can be seen as a process of initial evolution of a population consisting of viable solutions.
Referring to fig. 3, a schematic diagram of a manner of performing load distribution of an air conditioning system by using a genetic algorithm is shown, where coding and initializing a population (i.e. calculating fitness) are first required, where floating point number coding is adopted in the embodiment of the present invention, and total energy consumption (objective function) of the air conditioning system with multiple units is generally used as fitness. Specifically, the fitness corresponding to the plurality of allocation schemes may be calculated by the following expression:wherein f i For the corresponding adaptability of the ith allocation scheme, P max For maximum of multiple total energy consumption, P min Is the minimum value of a plurality of total energy consumption, P i For the ith total energy consumption, Δε is a preset first boundary processing coefficient and Δε' is a preset second boundary processing coefficient.
I.e. f i For the ith individual fitness under current load, P max P is the maximum total energy consumption in the population under current load min P is the minimum total energy consumption in the population under current load i Is the total energy consumption of the ith individual under the current load. From the above equation, P i Smaller f i The larger the overall energy consumption of the load distribution scheme is, the lower.
Step S204, judging whether the air conditioning system meets preset constraint conditions or not based on the optimal adaptability; wherein, the optimal fitness is the maximum value in fitness.
As shown in fig. 3, after initializing the population, it is necessary to determine whether constraints are satisfied, for example: the difference in consecutive m times of optimal fitness is smaller than sigma. Specifically, whether the air conditioning system satisfies a preset constraint condition may be determined based on the fitness by: determining an optimal fitness in a specified number of iterations of the air conditioning system; if the difference values of the adjacent optimal fitness are smaller than a preset fitness threshold value, determining that the air conditioning system meets constraint conditions; if there is at least one adjacent difference in optimal fitness that is greater than or equal to the fitness threshold, it is determined that the air conditioning system does not satisfy the constraint.
As shown in fig. 3, the optimal fitness in the course of a specified number of iterations (m times) of the air conditioning system may be determined, and if the difference between the consecutive m optimal fitness is less than the fitness threshold σ, the air conditioning system may be considered to satisfy the constraint condition. If there is at least one adjacent difference in optimal fitness greater than or equal to the fitness threshold σ, it is determined that the air conditioning system does not satisfy the constraint.
In addition, in addition to the above manner of judging whether the constraint condition is satisfied, the judgment may be further made by the number of iterations, for example: determining the iteration times of an air conditioning system; judging whether the iteration times are larger than a preset time threshold value or not; if yes, determining that the air conditioning system meets constraint conditions; if not, determining that the air conditioning system does not meet the constraint condition.
As shown in fig. 3, if the number of iterations N is greater than the number threshold N, then the constraint condition is considered satisfied; if the number of iterations N is less than or equal to the number threshold N, then the unconstrained condition is deemed satisfied.
Step S206, if not, the load of each equipment set in the air conditioning system is adjusted, and a plurality of total energy consumption of the air conditioning system is calculated based on the adjusted load of each equipment set.
As shown in fig. 3, individual corrections are required if the constraint is not satisfied, for example: if the load of the equipment unit in the air conditioning system is larger than a preset load threshold value, reducing the load of the equipment unit in the air conditioning system; and if the load of the equipment unit in the air conditioning system is smaller than the load threshold value, increasing the load of the equipment unit in the air conditioning system.
The principle of the individual correction method is that the unit load is increased in a high-load interval as much as possible, the high-load equipment unit increases the load, and the low-load equipment unit reduces the load, for example, when the total cold of an individual is larger than the distributed load, the load is reduced from the low-load equipment unit; or when the total cold of the individual is smaller than the distributed load, if the residual capacity of the running unit is larger than the unassigned load, distributing the residual capacity of the running unit to the running units in proportion; otherwise, the residual capacity ratio is proportionally distributed to each unit.
Step S208, the load of the equipment unit corresponding to the distribution scheme corresponding to the optimal fitness before adjustment is replaced by the load of the equipment unit corresponding to the distribution scheme corresponding to the smallest fitness after adjustment.
As shown in fig. 3, after the individual correction is performed, the worst individual of the current population may be replaced by the last best individual, that is, the load of the equipment set corresponding to the allocation scheme of the best fitness in the last iteration replaces the load of the equipment set corresponding to the allocation scheme of the smallest fitness in the current iteration.
As shown in fig. 3, the individual substitutions may be completed followed by selection and crossover operations, such as: randomly selecting a first allocation scheme and a second total allocation scheme from the allocation schemes; and randomly replacing the load of the equipment unit corresponding to the first distribution scheme and the load of the equipment unit corresponding to the second total distribution scheme.
The selection operation refers to an operation of selecting a good individual from a population and eliminating a bad individual. It is based on fitness evaluation. The greater the fitness of the individual, the greater the likelihood of being selected, the greater the number of his "offspring" in the next generation, and the selected individual is placed in the pairing library. The selection methods commonly used at present are a roulette method, an optimal individual reservation method, a desired value method, a sorting selection method, a competition method, a linear standardization method and the like.
The embodiment of the invention can adopt a roulette plate method to execute the selection operation, so that the fitness probability distribution calculation is carried out. For example: calculating the probability of each allocation scheme based on the fitness; the first allocation scheme and the second allocation scheme are randomly selected based on the probabilities.
Specifically, the probability distribution of each allocation scheme can be calculated based on the fitness by the following expression: p is p i ＝∑f i ′，Wherein, (p) i ,p i+1 ]For the selected probability interval of the ith fitness, m is the number of fitness, f i Is the i-th fitness.
The crossover operation is an operation of replacing and recombining part of structures of two parent individuals to generate new individuals, and the crossover purpose is to generate new individuals in the next generation, and the searching capability of a genetic algorithm is dramatically improved through the crossover operation. Crossover is an important means for genetic algorithms to obtain good individuals. The crossover operation is carried out by randomly selecting two individuals from a matching library according to a certain crossover probability, and the crossover position is also random.
For example, two individuals are randomly selected under the condition that a certain probability is met, and then the starting points of the intersections are randomly generated for interval intersection. I.e. two individuals are selected: the first distribution scheme and the second distribution scheme are used for randomly replacing genes of two individuals, namely, the load of the equipment unit corresponding to the first distribution scheme and the load of the equipment unit corresponding to the second total distribution scheme are randomly replaced.
As shown in fig. 3, in addition to selection and crossover, mutation operations may be performed that randomly alter the values of certain genes of individuals in a population with a small probability of mutation. For example, a certain gene of a certain individual is randomly selected and mutation operation is performed when a certain probability is satisfied. Specifically, a target distribution scheme may be randomly selected from distribution schemes of the air conditioning system, and a load of the equipment unit corresponding to the target distribution scheme may be adjusted.
For example, the random number may be determined within a preset random number range; if the random number is smaller than the preset random number threshold value, the load of the equipment unit corresponding to the target allocation scheme is adjusted through the following formula:if the random number is greater than or equal to the random number threshold value, the load of the equipment unit corresponding to the target allocation scheme is adjusted through the following formula: />
Wherein f ij For the ith corresponding jth deviceLoad of unit, C ij The refrigerating capacity of the jth equipment set corresponding to the ith allocation scheme is C ij_max Maximum refrigerating capacity of the jth equipment set corresponding to the ith allocation scheme, C ij_min For the minimum refrigerating capacity of the jth equipment unit corresponding to the ith allocation scheme, r is a random number, G is the current iteration number, and G is a preset number threshold; by the variation mode, the variation function becomes smaller along with the increase of the iteration times, so that the convergence speed of the genetic algorithm can be increased, and the calculation speed and efficiency can be improved.
Step S210, the step of calculating the fitness corresponding to the plurality of allocation schemes is continuously executed until the air conditioning system meets the constraint condition.
The process of each adjustment of the air conditioning system may be referred to as an iteration, where the number of iterations is increased by 1, i.e., n=n+1 in fig. 3, and after a plurality of iterations, it may be determined that the air conditioning system satisfies the constraint condition.
In step S212, the air conditioning system is controlled to execute the operation based on the allocation scheme corresponding to the total energy consumption satisfying the constraint condition.
According to the method provided by the embodiment of the invention, the global search can be distributed to the load of the unit by adopting the genetic algorithm, so that the minimum energy consumption of the whole unit under partial load can be solved.
Compared with other adopted genetic optimization algorithms, the embodiment of the invention improves the fitness function calculation, the crossover method and the mutation method and the function under the combination practical condition. The embodiment of the invention reserves the optimal chromosome in population iteration. According to the embodiment of the invention, the individuals which do not meet the constraint conditions can be corrected and put back into the population again, so that the individual difference of the population is enlarged, and the situation that the population falls into local optimum too quickly is prevented.
Therefore, the embodiment of the invention can quickly converge the genetic algorithm to obtain the optimized result. A point can be optimized within 50ms on average in a common computer, and real-time requirements can be met, namely, a basis is rapidly provided in a product control system or an energy-saving scheme.
In addition, compared with the existing priority-to-proportion load distribution method, the energy consumption of the load distribution method is obviously lower after optimization. The average energy saving of 2 different sets of optimization is reduced by about 4%, the average energy saving of 3 different sets of optimization is reduced by about 9%, the average energy saving of 4 different sets of optimization is reduced by about 13%, namely the more various sets are, the better the optimization effect of the load distribution method is.
Embodiment III:
in accordance with the above-described method embodiment, the present invention provides a load distribution apparatus for an air conditioning system, referring to a schematic structural diagram of a load distribution apparatus for an air conditioning system shown in fig. 4, the load distribution apparatus for an air conditioning system includes:
the fitness calculating module 41 is configured to determine a plurality of load distribution schemes corresponding to a total load of the air conditioning system, and calculate fitness corresponding to the plurality of distribution schemes;
a constraint condition judgment module 42 for judging whether the air conditioning system satisfies a preset constraint condition based on the optimal fitness; wherein, the optimal fitness is the maximum value in fitness;
a load correction module 43 for adjusting the load of each equipment set in the air conditioning system if not, and calculating a plurality of total energy consumption of the air conditioning system based on the adjusted load of each equipment set;
The air conditioning unit iteration module 44 is configured to continue to perform the step of calculating the fitness corresponding to the plurality of allocation schemes until the air conditioning system meets the constraint condition;
the air conditioning system operation module 45 is configured to control the air conditioning system to perform an operation based on an allocation scheme corresponding to the total energy consumption satisfying the constraint condition.
The load distribution device of the air conditioning system provided by the embodiment of the invention can judge whether the air conditioning system meets the preset constraint condition or not based on the adaptability corresponding to a plurality of load distribution schemes of the air conditioning system; if not, the load of each equipment unit in the air conditioning system is adjusted until the adjusted air conditioning system meets the constraint condition, and the air conditioning system is controlled to execute operation based on a load distribution scheme corresponding to the total energy consumption meeting the constraint condition. In the mode, the load of each equipment unit of the air conditioning system can be optimally distributed, so that the overall performance of the unit system is optimal, the energy consumption is minimum, the calculation speed of an optimization algorithm is high, the efficiency is high, and the method is applicable to sites with real-time requirements.
The fitness computing module is used for obtaining a plurality of load distribution schemes corresponding to the total load of the air conditioning system; wherein each distribution scheme comprises the load of each equipment unit of the air conditioning system; the total energy consumption corresponding to each allocation scheme is determined based on the load of each equipment set of the air conditioning system.
The fitness calculating module is configured to calculate fitness corresponding to the multiple allocation schemes according to the following formula:wherein f i For the corresponding adaptability of the ith allocation scheme, P max For maximum of multiple total energy consumption, P min Is the minimum value of a plurality of total energy consumption, P i For the ith total energy consumption, Δε is a preset first boundary processing coefficient and Δε' is a preset second boundary processing coefficient.
The constraint condition judging module is used for determining the optimal fitness in the iterative process of the designated times of the air conditioning system; if the difference values of the adjacent optimal fitness are smaller than a preset fitness threshold value, determining that the air conditioning system meets constraint conditions; if there is at least one adjacent difference in optimal fitness that is greater than or equal to the fitness threshold, it is determined that the air conditioning system does not satisfy the constraint.
The device further comprises: the second constraint condition judgment module is used for determining the iteration times of the air conditioning system; judging whether the iteration times are larger than a preset time threshold value or not; if yes, determining that the air conditioning system meets constraint conditions; if not, determining that the air conditioning system does not meet the constraint condition.
The load correction module is used for reducing the load of the equipment unit in the air conditioning system if the load of the equipment unit in the air conditioning system is greater than a preset load threshold; and if the load of the equipment unit in the air conditioning system is smaller than the load threshold value, increasing the load of the equipment unit in the air conditioning system.
Referring to a schematic structural view of a load distribution apparatus of another air conditioning system shown in fig. 5, the load distribution apparatus of an air conditioning system further includes: the selection and crossing module 46 is connected to the load correction module 43, and the selection and crossing module 46 is used for replacing the load of the equipment unit corresponding to the distribution scheme corresponding to the minimum adaptability after adjustment with the load of the equipment unit corresponding to the distribution scheme corresponding to the optimal adaptability before adjustment.
The selection crossing module is used for randomly selecting a first allocation scheme and a second total allocation scheme from the allocation schemes; and randomly replacing the load of the equipment unit corresponding to the first distribution scheme and the load of the equipment unit corresponding to the second total distribution scheme.
The selection crossing module is used for calculating the probability of each allocation scheme based on the fitness; the first allocation scheme and the second allocation scheme are randomly selected based on the probabilities.
The selection crossing module is configured to calculate a probability distribution of each allocation scheme based on the fitness by the following formula: p is p i ＝∑f i ′，Wherein, (p) i ,p i+1 ]For the selected probability interval of the ith fitness, m is the number of fitness, f i Is the i-th fitness.
As shown in fig. 5, the load distribution apparatus of the air conditioning system further includes: the mutation module 47, the selection crossing module 46, the mutation module 47 and the air conditioning unit iteration module 44 are sequentially connected, and the mutation module 47 is used for randomly selecting a target distribution scheme from distribution schemes of an air conditioning system and adjusting the load of a device unit corresponding to the target distribution scheme.
The mutation module is used for determining random numbers in a preset random number range; if the random number is smaller than the preset random number threshold value, the load of the equipment unit corresponding to the target allocation scheme is adjusted through the following formula:if the random number is greater than or equal to the random number threshold value, the load of the equipment unit corresponding to the target allocation scheme is adjusted through the following formula:wherein f ij For the load of the ith corresponding jth equipment unit, C ij The refrigerating capacity of the jth equipment set corresponding to the ith allocation scheme is C ij_max Maximum refrigerating capacity of the jth equipment set corresponding to the ith allocation scheme, C ij_min And (3) for the minimum refrigerating capacity of the jth equipment unit corresponding to the ith allocation scheme, r is a random number, G is the current iteration number, and G is a preset number threshold.
It will be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working process of the load distribution apparatus of the air conditioning system described above may refer to the corresponding process in the embodiment of the load distribution method of the air conditioning system described above, and will not be repeated herein.
Embodiment four:
the embodiment of the invention also provides electronic equipment, which is used for running the load distribution method of the air conditioning system; referring to a schematic structural diagram of an electronic device shown in fig. 6, the electronic device includes a memory 100 and a processor 101, where the memory 100 is configured to store one or more computer instructions, and the one or more computer instructions are executed by the processor 101 to implement the load distribution method of the air conditioning system.
Further, the electronic device shown in fig. 6 further includes a bus 102 and a communication interface 103, and the processor 101, the communication interface 103, and the memory 100 are connected through the bus 102.
The memory 100 may include a high-speed random access memory (RAM, random Access Memory), and may further include a non-volatile memory (non-volatile memory), such as at least one magnetic disk memory. The communication connection between the system network element and at least one other network element is implemented via at least one communication interface 103 (which may be wired or wireless), and may use the internet, a wide area network, a local network, a metropolitan area network, etc. Bus 102 may be an ISA bus, a PCI bus, an EISA bus, or the like. The buses may be divided into address buses, data buses, control buses, etc. For ease of illustration, only one bi-directional arrow is shown in FIG. 6, but not only one bus or type of bus.
The processor 101 may be an integrated circuit chip with signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in the processor 101 or instructions in the form of software. The processor 101 may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU for short), a network processor (Network Processor, NP for short), etc.; but also digital signal processors (Digital Signal Processor, DSP for short), application specific integrated circuits (Application Specific Integrated Circuit, ASIC for short), field-programmable gate arrays (Field-Programmable Gate Array, FPGA for short) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The disclosed methods, steps, and logic blocks 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 steps of the method disclosed in connection with the embodiments of the present invention may be embodied directly in the execution of a hardware decoding processor, or in the execution of a combination of hardware and software modules in a decoding processor. The software modules may be located in a random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The storage medium is located in the memory 100 and the processor 101 reads information in the memory 100 and in combination with its hardware performs the steps of the method of the previous embodiments.
The embodiment of the invention also provides a computer readable storage medium, which stores computer executable instructions that, when being called and executed by a processor, cause the processor to implement the load distribution method of the air conditioning system, and the specific implementation can be referred to the method embodiment and will not be described herein.
The load distribution method and apparatus for an air conditioning system and the computer program product of the electronic device provided in the embodiments of the present invention include a computer readable storage medium storing program codes, and instructions included in the program codes may be used to execute the method in the foregoing method embodiment, and specific implementation may refer to the method embodiment and will not be described herein.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described system and/or apparatus may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein.
In addition, in the description of embodiments of the present invention, unless explicitly stated and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention will be understood in specific cases by those of ordinary skill in the art.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
In the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. are based on the directions or positional relationships shown in the drawings, are merely for convenience of describing the present invention and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
Finally, it should be noted that: the above examples are only specific embodiments of the present invention, and are not intended to limit the scope of the present invention, but it should be understood by those skilled in the art that the present invention is not limited thereto, and that the present invention is described in detail with reference to the foregoing examples: any person skilled in the art may modify or easily conceive of the technical solution described in the foregoing embodiments, or perform equivalent substitution of some of the technical features, while remaining within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention, and are intended to be included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (13)
1. A load distribution method of an air conditioning system, the method comprising:
determining a plurality of load distribution schemes corresponding to the total load of the air conditioning system, and calculating the adaptability corresponding to the plurality of distribution schemes;
judging whether the air conditioning system meets preset constraint conditions or not based on the optimal fitness; wherein the optimal fitness is the maximum of the fitness;
If not, adjusting the load of each equipment unit in the air conditioning system, and calculating a plurality of total energy consumption of the air conditioning system based on the adjusted load of each equipment unit;
continuing to execute the step of calculating the adaptability degrees corresponding to the plurality of distribution schemes until the air conditioning system meets the constraint condition;
controlling the air conditioning system to execute operation based on the distribution scheme corresponding to the total energy consumption meeting the constraint condition;
after the step of calculating a plurality of total energy consumption of the air conditioning system based on the adjusted loads of the respective equipment units, the method further includes: randomly selecting a target distribution scheme from the distribution scheme of the air conditioning system, and adjusting the load of the equipment unit corresponding to the target distribution scheme;
the step of adjusting the load of the equipment unit corresponding to the target allocation scheme comprises the following steps: determining a random number in a preset random number range; if the random number is smaller than a preset random number threshold, the load of the equipment unit corresponding to the target allocation scheme is adjusted through the following formula:if the random number is greater than or equal to the random number threshold, the load of the equipment unit corresponding to the target allocation scheme is adjusted through the following formula: / >Wherein f ij For the load of the j-th equipment unit corresponding to the i-th allocation scheme, C ij The refrigeration capacity of the jth equipment set corresponding to the ith allocation scheme is C ij_max For the maximum refrigerating capacity of the j-th equipment set corresponding to the i-th allocation scheme, C ij_min And (3) for the minimum refrigerating capacity of the jth equipment unit corresponding to the ith allocation scheme, r is the random number, G is the current iteration number, and G is a preset number threshold.
2. The method of claim 1, wherein the step of determining a plurality of load distribution schemes corresponding to a total load of the air conditioning system and calculating fitness corresponding to the plurality of distribution schemes comprises:
acquiring a plurality of load distribution schemes corresponding to the total load of an air conditioning system; wherein each of the distribution schemes includes a load of a respective one of the equipment units of the air conditioning system;
and determining the total energy consumption corresponding to each distribution scheme based on the load of each equipment unit of the air conditioning system.
3. The method of claim 1, wherein the step of calculating the fitness corresponding to a plurality of the allocation schemes comprises:
calculating the adaptability of a plurality of distribution schemes according to the following formulas: Wherein f i For the corresponding adaptability of the ith allocation scheme, P max For a plurality of maximum values of the total energy consumption, P min Being the minimum of a plurality of said total energy consumption, P i For the ith energy consumption, Δε is a preset first boundary processing coefficient, and Δε' is a preset second boundary processing coefficient.
4. The method of claim 1, wherein the step of determining whether the air conditioning system satisfies a preset constraint based on the optimal fitness comprises:
determining an optimal fitness in a specified number of iterations of the air conditioning system;
if the difference values of the adjacent optimal fitness are smaller than a preset fitness threshold value, determining that the air conditioning system meets constraint conditions;
and if at least one adjacent difference value of the optimal fitness is greater than or equal to the fitness threshold value, determining that the air conditioning system does not meet the constraint condition.
5. The method according to claim 1, wherein the method further comprises:
determining the iteration times of the air conditioning system;
judging whether the iteration times are larger than a preset time threshold value or not;
if yes, determining that the air conditioning system meets constraint conditions;
If not, determining that the air conditioning system does not meet the constraint condition.
6. The method of claim 1, wherein the step of adjusting the load of each equipment unit in the air conditioning system comprises:
if the load of the equipment unit in the air conditioning system is larger than a preset load threshold, reducing the load of the equipment unit in the air conditioning system;
and if the load of the equipment unit in the air conditioning system is smaller than the load threshold value, increasing the load of the equipment unit in the air conditioning system.
7. The method of claim 1, wherein after the step of calculating a plurality of total energy consumption of the air conditioning system based on the adjusted loads of the respective equipment units, the method further comprises:
and replacing the load of the equipment unit corresponding to the distribution scheme corresponding to the optimal fitness before adjustment with the load of the equipment unit corresponding to the distribution scheme corresponding to the smallest fitness after adjustment.
8. The method of claim 7, wherein after the step of calculating a plurality of total energy consumption of the air conditioning system based on the adjusted loads of the respective equipment units, the method further comprises:
Randomly selecting a first allocation scheme and a second total allocation scheme from the allocation schemes;
and randomly replacing the load of the equipment unit corresponding to the first distribution scheme and the load of the equipment unit corresponding to the second total distribution scheme.
9. The method of claim 8, wherein the step of randomly selecting the first allocation scheme and the second allocation scheme from the allocation schemes comprises:
calculating the probability of each allocation scheme based on the fitness;
the first allocation scheme and the second allocation scheme are randomly selected based on the probabilities.
10. The method of claim 9, wherein the step of calculating a probability for each of the total allocation schemes based on the fitness comprises:
calculating a probability distribution of each of the allocation schemes based on the fitness by the following formula: p is p i ＝∑f i ′，Wherein, (p) i ，p i+1 ]For the i-th selected probability interval of the fitness, m is the number of the fitness, f i And (5) the i-th fitness.
11. A load distribution apparatus of an air conditioning system, the apparatus comprising:
the fitness calculation module is used for determining a plurality of load distribution schemes corresponding to the total load of the air conditioning system and calculating fitness corresponding to the distribution schemes;
The constraint condition judgment module is used for judging whether the air conditioning system meets preset constraint conditions or not based on the optimal adaptability; wherein the optimal fitness is the maximum of the fitness;
the load correction module is used for adjusting the load of each equipment unit in the air conditioning system and calculating a plurality of total energy consumption of the air conditioning system based on the adjusted load of each equipment unit if not;
the air conditioning unit iteration module is used for continuously executing the step of calculating the adaptability degrees corresponding to the plurality of distribution schemes until the air conditioning system meets the constraint conditions;
the air conditioning system operation module is used for controlling the air conditioning system to execute operation based on the allocation scheme corresponding to the total energy consumption meeting the constraint condition;
the apparatus further comprises: the mutation module is used for randomly selecting a target distribution scheme from the distribution scheme of the air conditioning system and adjusting the load of the equipment unit corresponding to the target distribution scheme;
the mutation module is used for determining random numbers in a preset random number range; if the random number is smaller than a preset random number threshold, the load of the equipment unit corresponding to the target allocation scheme is adjusted through the following formula: If the random number is greater than or equal to the random number threshold, the load of the equipment unit corresponding to the target allocation scheme is adjusted through the following formula: wherein f ij For the load of the j-th equipment unit corresponding to the i-th allocation scheme, C ij The refrigeration capacity of the jth equipment set corresponding to the ith allocation scheme is C ij_max For the maximum refrigerating capacity of the j-th equipment set corresponding to the i-th allocation scheme, C ij_min And (3) for the minimum refrigerating capacity of the jth equipment unit corresponding to the ith allocation scheme, r is the random number, G is the current iteration number, and G is a preset number threshold.
12. An electronic device comprising a processor and a memory, the memory storing computer executable instructions executable by the processor, the processor executing the computer executable instructions to implement the load distribution method of the air conditioning system of any of claims 1 to 10.
13. A computer readable storage medium storing computer executable instructions which, when invoked and executed by a processor, cause the processor to implement the load distribution method of an air conditioning system according to any one of claims 1 to 10.
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| WO2020198971A1 (en) * | 2019-03-29 | 2020-10-08 | 亿可能源科技（上海）有限公司 | Management method and system, and control method and system for air conditioning system, and storage medium |
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| WO2020198971A1 (en) * | 2019-03-29 | 2020-10-08 | 亿可能源科技（上海）有限公司 | Management method and system, and control method and system for air conditioning system, and storage medium |
| CN111811111A (en) * | 2020-06-17 | 2020-10-23 | 上海电力大学 | Central air conditioner energy consumption control method based on improved particle swarm algorithm |
| CN112906966A (en) * | 2021-02-22 | 2021-06-04 | 西安建筑科技大学 | Load optimization method, system, medium and equipment for central air-conditioning water chilling unit |
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