CN116009622A - System control method, device, equipment and storage medium - Google Patents

System control method, device, equipment and storage medium Download PDF

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CN116009622A
CN116009622A CN202211666172.3A CN202211666172A CN116009622A CN 116009622 A CN116009622 A CN 116009622A CN 202211666172 A CN202211666172 A CN 202211666172A CN 116009622 A CN116009622 A CN 116009622A
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energy
parameter
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CN116009622B (en
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阮前
郭志斌
胡建村
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China Mobile Communications Group Co Ltd
China Mobile Information Technology Co Ltd
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China Mobile Information Technology Co Ltd
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Abstract

The application discloses a control method, a device, equipment and a storage medium of a system. The method comprises the following steps: respectively acquiring target data; according to the preset multiple frequency ranges and multiple temperature ranges, randomly sampling working frequencies of working frequencies in the preset multiple frequency ranges in target data and randomly sampling temperatures in the preset multiple temperature ranges in the target data to obtain a sampling data set; calculating the power consumption of the equipment according to the working frequency and the temperature; calculating a first fitness function value according to the relation between the power consumption and the fitness function value; determining the working frequency and the temperature corresponding to the minimum first fitness function value in the first fitness function values as initial energy-saving parameters, and determining the working frequency and the temperature corresponding to a preset number of smaller fitness function values except the initial energy-saving parameters as candidate energy-saving parameters; determining a target energy-saving parameter according to the initial energy-saving parameter and the candidate energy-saving parameter; and controlling the system according to the target energy-saving parameter.

Description

System control method, device, equipment and storage medium
Technical Field
The application belongs to the technical field of energy conservation, and particularly relates to a control method, a device, equipment and a storage medium of a system.
Background
Along with the progress of industrial automation and informatization, in order to ensure the constant temperature of the production environment, the temperature of the environment is often required to be regulated by a temperature control system, and a great amount of energy consumption is generated, and in order to ensure the stability of the production environment and reduce the energy consumption, the control parameters of related energy consumption equipment are required to be optimized, and the optimal control parameters are searched to control the temperature control system. In the related art, a heuristic algorithm is generally used to search for an optimal control parameter, and the search is often performed in a full safe value range of the control parameter of the device.
However, for the data center, because the data center has a large amount of related energy consumption equipment, when searching is performed by adopting the existing heuristic algorithm, the data center needs a long time for test calculation, the calculation cost is high, and because the data center is usually required to be in a production running state, a large amount of test calculation easily brings potential safety hazards.
Disclosure of Invention
The embodiment of the application provides a control method, a device, equipment and a storage medium of a system, which can reduce search calculation time for obtaining optimal energy-saving parameters.
In a first aspect, an embodiment of the present application provides a method for controlling a system, including:
acquiring target data, wherein the target data comprises a freezing pump frequency, a cooling pump frequency and a cooling tower water outlet temperature;
according to a plurality of preset frequency ranges and a plurality of temperature ranges, randomly sampling the working frequency of the working frequency in the target data in the preset frequency ranges respectively and randomly sampling the temperature of the target data in the preset temperature ranges respectively to obtain a plurality of sampling data sets;
calculating the power consumption of the device according to the working frequency and the temperature in the sampling data set;
calculating a first fitness function value according to the relation between the power consumption and the fitness function value;
determining the working frequency and the temperature in the data set corresponding to the minimum first fitness function value in the first fitness function values as initial energy-saving parameters, and determining the working frequency and the temperature in the data set corresponding to a preset number of smaller fitness function values except the initial energy-saving parameters as candidate energy-saving parameters;
determining a target energy-saving parameter according to the initial energy-saving parameter and the candidate energy-saving parameter;
and controlling the system according to the target energy-saving parameter.
In one possible implementation manner of the embodiment of the present application, before randomly sampling the operating frequency of the target data of each device in the preset multiple frequency ranges and randomly sampling the temperature of the target data of each device in the preset multiple temperature ranges according to the preset multiple frequency ranges and the multiple temperature ranges, to obtain the sampled data set of the multiple devices, the method further includes:
Dividing the frequency of the target data into a plurality of first frequency range ranges with different preset lengths according to the frequency in the target data of each device;
according to the temperature in the target data of each device, the temperature in the target data is divided into a plurality of first temperature ranges with different preset lengths.
Dividing the temperature in the target data into a plurality of first temperature ranges with different preset lengths according to the temperature in the target data, randomly sampling the working frequencies of the working frequencies in the preset frequency ranges in the target data according to the preset frequency ranges and the temperature ranges, and randomly sampling the temperatures in the target data in the preset temperature ranges to obtain a plurality of sampling data sets, wherein the method further comprises the steps of:
dividing each first frequency range into a plurality of second frequency ranges uniformly to obtain a plurality of preset frequency ranges;
and uniformly dividing each first temperature range into a plurality of second temperature ranges to obtain a plurality of preset temperature ranges.
In one possible implementation manner of the embodiment of the present application, determining the target energy saving parameter according to the initial energy saving parameter and the candidate energy saving parameter includes:
According to the deviation between each candidate energy-saving parameter and the initial energy-saving parameter in the candidate energy-saving parameters, respectively calculating a target first parameter corresponding to each candidate energy-saving parameter;
respectively calculating the equipment power consumption corresponding to the target first parameter, and determining a second fitness function value corresponding to each power consumption according to the relation between the equipment power consumption and the fitness function;
determining a target working frequency and a target temperature corresponding to the smallest second fitness function value in the second fitness function values as target initial energy-saving parameters, and determining working frequencies and temperatures corresponding to a preset number of smaller second fitness function values except the target working frequency and the target temperature as candidate target energy-saving parameters;
according to the frequency deviation and the temperature deviation of each candidate target energy-saving parameter in the candidate target energy-saving parameters and the target initial energy-saving parameters, respectively calculating a target second parameter corresponding to each candidate target energy-saving parameter;
respectively calculating the equipment power consumption corresponding to the target second parameter, and determining a third fitness function value corresponding to each power consumption according to the relation between the equipment power consumption and the fitness function;
when the times of calculating the third fitness function value reach the preset iteration updating times, determining the working frequency and the temperature corresponding to the smallest third fitness function value in the third fitness function value as target energy-saving parameters.
In one possible implementation manner of the embodiment of the present application, according to a frequency deviation and a temperature deviation of each candidate target energy saving parameter from a target initial energy saving parameter, respectively calculating a target second parameter corresponding to each candidate target energy saving parameter, including:
obtaining search parameters corresponding to each candidate target energy-saving parameter in the candidate target energy-saving parameters, wherein the search parameters comprise a search probability value, a first preset coefficient, a second preset coefficient and a curvature value;
when the searching probability value is smaller than the first preset probability value, calculating a target second parameter corresponding to each candidate target energy-saving parameter according to the candidate target energy-saving parameter, the first preset coefficient, the second preset coefficient and the target initial energy-saving parameter;
and when the searching probability value is larger than the second preset probability value, calculating a target second parameter corresponding to each candidate target energy-saving parameter according to the candidate target energy-saving parameter, the first preset coefficient, the curvature value and the target initial energy-saving parameter.
In one possible implementation manner of the embodiment of the present application, calculating, according to the candidate target energy saving parameters, the first preset coefficient, the second preset coefficient and the target initial energy saving parameter, a target second parameter corresponding to each candidate target energy saving parameter includes:
Calculating a target second parameter corresponding to each candidate target energy-saving parameter according to the first corresponding relation;
the first corresponding relation is
Figure BDA0004015158410000041
Wherein (1)>
Figure BDA0004015158410000042
Figure BDA0004015158410000043
For the second parameter of interest, +.>
Figure BDA0004015158410000044
For a first preset coefficient, < >>
Figure BDA0004015158410000045
For the second preset coefficient, t is the current iteration update number, +.>
Figure BDA0004015158410000046
Energy saving parameters for candidate targets->
Figure BDA0004015158410000047
And (5) initial energy-saving parameters are target. />
In one possible implementation manner of the embodiment of the present application, calculating, according to the candidate target energy saving parameters, the first preset coefficient, the second preset coefficient and the target initial energy saving parameter, a target second parameter corresponding to each candidate target energy saving parameter includes:
calculating a target second parameter corresponding to each candidate energy-saving parameter according to the second corresponding relation;
the second corresponding relation is
Figure BDA0004015158410000048
And->
Figure BDA0004015158410000049
Figure BDA00040151584100000410
Wherein (1)>
Figure BDA00040151584100000411
For the second parameter of interest, +.>
Figure BDA00040151584100000412
For a first preset coefficient, < >>
Figure BDA00040151584100000413
T is the current iteration update number of times, which is the difference between the target initial energy saving parameter and the candidate target energy saving parameter, +.>
Figure BDA00040151584100000414
Energy saving parameters for candidate targets->
Figure BDA00040151584100000415
And l is a curvature value for the target initial energy-saving parameter.
In one possible implementation of an embodiment of the present application, the search parameter further includes a first random value; when the search probability value is smaller than the first preset probability value, calculating a target second parameter corresponding to each candidate target energy-saving parameter according to the candidate target energy-saving parameter, the first preset coefficient, the second preset coefficient and the target initial energy-saving parameter, wherein the method comprises the following steps:
When the searching probability value is smaller than a first preset probability value and the absolute value of the first random value is smaller than a preset threshold value, calculating a target second parameter corresponding to each candidate target energy-saving parameter according to the candidate target energy-saving parameter, the first preset coefficient, the second preset coefficient and the target initial energy-saving parameter;
when the searching probability value is smaller than a first preset probability value and the absolute value of the first random value is larger than or equal to a first preset threshold value, a random candidate parameter is randomly acquired according to the candidate target energy-saving parameters, and a target second parameter corresponding to each candidate energy-saving parameter is calculated according to the random candidate parameter, the first preset coefficient, the second preset coefficient and the target initial energy-saving parameter.
In a second aspect, an embodiment of the present application provides a control apparatus, including:
the first acquisition module is used for acquiring target data, wherein the target data comprise a freezing pump frequency, a cooling pump frequency and a cooling tower water outlet temperature;
the sampling module is used for randomly sampling the working frequencies of the working frequencies in the preset frequency ranges and the temperatures in the preset temperature ranges respectively in the target data according to the preset frequency ranges and the preset temperature ranges to obtain a plurality of sampling data sets;
A first calculation module for calculating the power consumption of the device according to the operating frequency and the temperature in the sampled data set;
the second calculation module is used for calculating the fitness function value according to the relation between the power consumption and the fitness function value;
the second acquisition module is used for determining the working frequency and the temperature in the data set corresponding to the minimum first fitness function value in the fitness function values as initial energy-saving parameters, and determining the working frequency and the temperature in the data set corresponding to a preset number of smaller fitness function values except the initial energy-saving parameters as candidate energy-saving parameters;
the optimization module is used for determining a target energy-saving parameter according to the initial energy-saving parameter and the candidate energy-saving parameter;
and the control module is used for controlling the system according to the target energy-saving parameters.
In a third aspect, an embodiment of the present application provides a control apparatus, including:
a processor and a memory storing computer program instructions;
the processor, when executing the computer program instructions, implements the control method as in the first aspect.
In a fourth aspect, embodiments of the present application provide a computer storage medium having stored thereon computer program instructions which, when executed by a processor, implement a control method as in the first aspect.
According to the control method, the device, the equipment and the storage medium of the system, the refrigerating pump frequency, the cooling pump frequency and the cooling tower water outlet temperature are obtained to serve as target data, working frequencies of working frequencies in the target data in the preset frequency ranges are randomly sampled according to the preset frequency ranges, and meanwhile, temperatures in the target data are randomly sampled according to the preset temperature ranges, so that a plurality of sampled data sets are obtained. The power consumption of the equipment is calculated according to the working frequency and the temperature in each sampling data set, then the fitness function value of each equipment is calculated according to the relation between the power consumption and the fitness function value, the working frequency and the temperature in the data set corresponding to the minimum first fitness function value in the fitness function values are determined to be initial energy-saving parameters, and the working frequency and the temperature in the data sets corresponding to the preset number of smaller fitness function values except the initial energy-saving parameters are determined to be candidate energy-saving parameters. And then determining a target energy-saving parameter according to the initial energy-saving parameter and the candidate energy-saving parameter, and controlling the system according to the target energy-saving parameter. Because the target data is randomly sampled according to the preset frequency ranges and the preset temperature ranges when the sampling data set is obtained, when the initial energy-saving parameter and the candidate energy-saving parameter determine the target energy-saving parameter, the search probability of different working frequencies of different frequency ranges and different temperatures in different temperature ranges can be reduced, blind search is reduced, and the time required by search calculation is reduced in the process of determining the target energy-saving parameter according to the initial energy-saving parameter and the candidate energy-saving parameter, and the calculation cost is reduced.
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In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments of the present application will be briefly described, and it is possible for a person skilled in the art to obtain other drawings according to these drawings without inventive effort.
Fig. 1 is a schematic flow chart of a control method of a system according to an embodiment of the present application;
FIG. 2 is a second flow chart of a control method of a system according to the embodiment of the present application;
fig. 3 is a schematic structural diagram of a control device according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of a control device according to an embodiment of the present application.
Detailed Description
Features and exemplary embodiments of various aspects of the present application are described in detail below to make the objects, technical solutions and advantages of the present application more apparent, and to further describe the present application in conjunction with the accompanying drawings and the detailed embodiments. It should be understood that the specific embodiments described herein are intended to be illustrative of the application and are not intended to be limiting. It will be apparent to one skilled in the art that the present application may be practiced without some of these specific details. The following description of the embodiments is merely intended to provide a better understanding of the present application by showing examples of the present application.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, 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 … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises an element.
For ease of understanding, some of the matters related to the embodiments of the present application are described below:
along with the progress of industrial automation and informatization, in order to ensure the constant temperature of the production environment, a sampling temperature control system is often required to adjust the temperature of the environment, and a great amount of energy consumption is generated, so that in order to ensure the stability of the production environment and reduce the energy consumption, the control parameters of related equipment are required to be optimized, and the optimal control parameters are searched to control the temperature system. Heuristic optimization algorithms in the approach to parameter optimization are becoming increasingly popular in engineering applications because they rely on fairly simple concepts, are easy to implement, do not require gradient knowledge, can bypass local optimizations, and can be used to address a wide range of issues involving different disciplines.
The existing heuristic algorithms mainly comprise an ant colony algorithm, a genetic algorithm, a simulated annealing algorithm, a particle swarm algorithm and the like, however, the algorithms generally search in the whole safe value range of the control parameters of the equipment during searching, the number of times of optimizing attempts in the searching mode is relatively large, for example, the particle swarm algorithm needs to be sampled 30 multiplied by 300=9000 times when the number of particles is 30 and the iteration number is 300, so that an approximate optimal result can be found, in practice, for a system with more equipment, if the particle algorithm is adopted for sampling 9000 times, the data test sampling time as long as one year is needed, and the calculation cost is high.
For example, for a data center, tens of devices are set for one parameter, 30 minutes are required for single parameter adjustment setting and obtaining the optimal control parameter, and for a data center test for months or even years is required for a data center test for a heuristic algorithm such as a genetic algorithm, which is an optimization method requiring thousands of calculations, the time cost is very expensive, the data center is generally in a production running state, a large number of test calculations are also a great challenge for safe running of the data center.
In order to solve the above problems, embodiments of the present application provide a method, an apparatus, a device, and a computer storage medium for controlling a system.
The embodiment of the application provides a control method of a system, as shown in fig. 1, as follows:
s110, acquiring target data, wherein the target data comprise cooling pump frequency, freezing pump frequency and cooling tower water outlet temperature.
In some embodiments, the target data may include a variety of devices, each of which may include one or more. Taking a cold source system of a data center as an example, the cold source system can comprise a plurality of cold source devices such as a cooling pump, a freezing pump, a cooling tower and the like, wherein the number of the cooling pump, the freezing pump and the cooling tower can be one or more. The cooling pump frequency, the freezing pump frequency and the cooling tower water outlet temperature of the cold source system of the data center are taken as examples to be introduced, and the cooling pump frequency, the freezing pump frequency and the cooling tower water outlet temperature of the cold source system are obtained as target data.
S120, according to a plurality of preset frequency ranges and a plurality of temperature ranges, randomly sampling the working frequencies of the working frequencies in the preset frequency ranges in the target data respectively, and randomly sampling the temperatures of the target data in the preset temperature ranges respectively, so as to obtain a plurality of sampling data sets.
In some embodiments, by presetting a plurality of frequency ranges and a plurality of temperature ranges, different preset frequency ranges and temperature ranges have different sampling weights, that is, sampling intervals, so that the frequencies of working frequencies in the preset frequency ranges and the temperatures in the target data are randomly sampled, and important frequency values and temperature values, that is, frequency values and temperature values which enable the power consumption of the device to be lower, are more likely to be obtained. In particular, a higher sampling weight, i.e. a smaller sampling interval, may be given to the lower frequency part. Each sampling needs to randomly sample the cooling pump frequency, the freezing pump frequency and the cooling tower water outlet temperature, and the cooling pump frequency, the freezing pump frequency and the cooling tower water outlet temperature obtained by each sampling form a sampling data set, namely a multidimensional vector, and the frequency or the temperature of one device is one dimension.
S130, calculating the power consumption of the device according to the operating frequency and the temperature in the sampling data set.
In some embodiments, the power consumption of each device is calculated based on the operating frequency and temperature in the sampled data set. For example, the power consumption of the cooling pump, the cooling pump and the cooling tower is calculated according to the working frequency of the cooling pump, the working frequency of the cooling pump and the water outlet temperature of the cooling tower, which are obtained by random sampling, and then the total power consumption of the cold source machine room in the cold source system of the data center is calculated according to the power consumption of the cooling pump, the cooling pump and the cooling tower.
And S140, calculating a first fitness function value of each device according to the relation between the power consumption and the fitness function value.
In some embodiments, the smaller the fitness function value, the closer the parameter corresponding to the fitness function value is to the optimal control parameter, and the better the energy-saving optimization effect.
For easy understanding, the fitness function of the application will be described by taking a cold source system of a data center as an example. The energy consumption equipment of the data center can comprise an IT machine room, a tail end precise air conditioner and a cold source machine room, and if the energy saving target is set to meet the minimum power consumption of the cold source machine room under the given power consumption of the IT machine room, the fitness function object=P IT /P cool Wherein P is IT For IT machine room power consumption, P cool Is the power consumption of the cold source machine room. The refrigerating equipment of the cold source machine room mainly comprises refrigerating equipment such as a chiller, a refrigerating pump, a cooling tower and the like, and the chiller, the refrigerating pump, the cooling pump and the cooling tower can be multiple. Therefore, the power consumption P of the cold source machine room cool The calculation can be performed by the formulas (1) to (4):
Figure BDA0004015158410000091
P freezing pump ＝f Freezing pump (x Frequency of cryopump ) (2)
P Cooling pump ＝f Cooling pump (x Cooling pump frequency ) (3)
P Cooling tower ＝f Cooling tower (x Water outlet temperature of cooling tower ) (4)
Wherein x is Frequency of cryopump For cryopump frequency x Cooling pump frequency To cool the pump frequency x Water outlet temperature of cooling tower P for cooling tower outlet water temperature Freezing pump P for power consumption of cryopump Cooling pump To cool the power consumption of the pump, P Cooling tower P for power consumption of cooling tower Others Is the power consumption of refrigeration equipment other than the cryopump, the cooling pump, and the cooling tower.
Acquiring cooling pump frequency, cooling pump frequency and cooling tower water outlet temperature in a cold source system as target data, randomly sampling the acquired cooling pump frequency and cooling pump frequency according to a plurality of preset frequency ranges, randomly sampling the acquired cooling tower water outlet temperature according to a plurality of preset temperature ranges to obtain a plurality of sampling data sets, calculating the power consumption of each device according to the cooling pump frequency, the cooling pump frequency and the cooling tower water outlet temperature, and calculating according to a formula (1) to obtain the power consumption P of a cold source machine room cool Thereby obtaining a corresponding fitness function object=p for each sampled data set IT /P cool I.e. the first fitness function value.
S150, determining the working frequency and the temperature in the data set corresponding to the minimum first fitness function value in the fitness function values as initial energy-saving parameters, and determining the working frequency and the temperature in the data set corresponding to a preset number of smaller fitness function values except the initial energy-saving parameters as candidate energy-saving parameters;
The initial energy-saving parameter and the candidate energy-saving parameter are multidimensional vectors formed by working frequencies and temperatures of a plurality of devices, the frequency or the temperature of one device is used as one dimension, for example, when the cooling pump, the freezing pump and the cooling tower are respectively one, the initial energy-saving parameter and the candidate energy-saving parameter are three-dimensional vectors formed by the cooling pump frequency, the freezing pump frequency and the cooling tower water outlet temperature, when the cooling pump, the freezing pump and the cooling tower are respectively two, the initial energy-saving parameter and the candidate energy-saving parameter are six-dimensional vectors formed by the cooling pump frequency, the freezing pump frequency and the cooling tower water outlet temperature, it is noted that the initial energy-saving parameter is the working frequency and the temperature corresponding to the smallest first fitness function in the first fitness function value, the candidate energy-saving parameter is the temperature corresponding to the working frequency and the working frequency in the sampling data set corresponding to the smaller fitness function value except the initial energy-saving parameter, the number of the candidate energy-saving parameter can be a plurality, and as an example, the preset number of the candidate energy-saving parameters can be 3 to 7.
As an example, the initial energy-saving parameters of the cold source system of the data center are the cooling pump frequency, the freezing pump frequency and the cooling tower water outlet temperature corresponding to the minimum first fitness function in the first fitness function values, and the candidate energy-saving parameters are the cooling pump frequency, the freezing pump frequency and the cooling tower water outlet temperature in the sampling data sets corresponding to the 3 smaller fitness function values except the initial energy-saving parameters.
S160, determining a target energy saving parameter according to the initial energy saving parameter and the candidate energy saving parameter.
In some embodiments, the target energy saving parameter is obtained by performing an iterative calculation, i.e., a search, based on the initial energy saving parameter and the candidate energy saving parameter. The target search parameter is a vector composed of operating frequencies and temperatures of a plurality of devices, the frequency or temperature of one device is used as one dimension, for example, the target energy-saving parameter of a cold source system of a data center is a vector composed of a cooling pump frequency, a freezing pump frequency and a cooling tower water outlet temperature, when the cooling pump, the freezing pump and the cooling tower are respectively one, the target energy-saving parameter is a three-dimensional vector composed of the cooling pump frequency, the freezing pump frequency and the cooling tower water outlet temperature, and when the cooling pump, the freezing pump and the cooling tower are respectively a plurality of, for example, when the cooling pump, the freezing pump and the cooling tower are respectively 2, the target energy-saving parameter is a six-dimensional vector composed of the cooling pump frequency, the freezing pump frequency and the cooling tower water outlet temperature.
S170, controlling the system according to the target energy-saving parameters.
In some embodiments, in order to reduce the power consumption, each device of the system is set by adopting the target energy saving parameter, so as to reduce the power consumption of the system. For example, when the target energy-saving parameter is a three-dimensional vector consisting of the cooling pump frequency, the freezing pump frequency and the cooling tower water outlet temperature, each frequency value and temperature value in the target energy-saving parameter are sampled to set corresponding equipment.
In some embodiments, to give a higher sampling weight to the lower frequency portion, that is, a smaller sampling interval, before S120, a control method of a system provided in an embodiment of the present application may further include:
dividing the frequency of the target data into a plurality of first frequency range with different preset lengths according to the frequency in the target data;
according to the temperature in the target data, the temperature in the target data is divided into a plurality of first temperature ranges with different preset lengths.
The method comprises the steps of firstly dividing the frequency in target data into a plurality of frequency band ranges with different lengths, dividing the temperature into a plurality of temperature ranges with different lengths, and obtaining a plurality of first frequency band ranges and a plurality of first temperature ranges so that different preset frequency bands and preset temperature ranges have different sampling intervals.
In order to improve the possibility of obtaining the optimal control parameter, after dividing the frequency of the target data into a plurality of first frequency ranges with different preset lengths according to the frequency of the target data and dividing the temperature of the target data into a plurality of first temperature ranges with different preset lengths according to the temperature of the target data, before S120, the control method of the system provided in the embodiment of the present application may further include:
Dividing each first frequency range into a plurality of second frequency ranges uniformly to obtain a plurality of preset frequency ranges;
and uniformly dividing each first temperature range into a plurality of second temperature ranges to obtain a plurality of preset temperature ranges.
The first frequency range and the plurality of first temperature ranges are further evenly divided into the plurality of second frequency ranges and the plurality of second temperature ranges, so that the frequency and the temperature distribution obtained by sampling are more reasonable.
In some embodiments, the device generally consumes less power at lower frequencies, and thus, the time to find the optimal control parameters can be reduced by giving higher sampling weights, i.e., smaller sampling intervals, to lower frequency portions. For example, the number of the first frequency band ranges with different preset lengths may be 3, and the ratio of the preset lengths of the first frequency band ranges with different preset lengths may be 3 along the direction from the maximum frequency value to the minimum frequency value in the target data of each device: 2:1.
as an example, the safe operating frequency range of the cryopump is 30 to 50 hertz, the safe operating frequency range of the cooling pump is 30 to 50 hertz, and the safe temperature range of the cooling tower outlet temperature is 30 to 50 degrees celsius. The safe frequency ranges of the freezing pump and the cooling pump are respectively divided into 3 frequency ranges with different interval lengths, specifically, 50 Hz to 40 Hz are a first frequency range, 40 Hz to 33 Hz are a first frequency range, and 33 Hz to 30 Hz are a first frequency range. The temperature range is divided in a similar manner to the frequency band, specifically, the safe temperature range of the outlet water temperature of the cooling tower is divided into 3 different temperature ranges with different interval lengths, specifically, the temperature range can be 50-40 ℃ as a first temperature range, 40-33 ℃ as a first temperature range, and 33-30 ℃ as a first temperature range. Then each first frequency range and each first temperature range are respectively divided into a plurality of second frequency ranges and a plurality of second temperature ranges in average so as to obtain a plurality of preset frequency ranges and a plurality of preset temperature ranges
Then, randomly sampling working frequencies falling into different frequency ranges in target data, randomly sampling temperatures falling into different temperature ranges in the target data, and obtaining sampling data sets of a plurality of devices, wherein the working frequencies of the cooling pump, the working frequencies of the freezing pump and the water outlet temperature of the cooling tower obtained by each sampling are in one-to-one correspondence.
For the sake of understanding, the process of searching for the optimal control parameter may be understood as a process of continuously updating the search position to the optimal position, where the search position is a position vector composed of the operating frequencies and temperatures of the plurality of devices, and the optimal position is an optimal position vector composed of the operating frequencies and temperatures corresponding to the optimal control parameter, and the search for obtaining the optimal control parameter is to continuously update the search position to approach the optimal position. In this process, since the optimal position is not known a priori, in the embodiment of the present application, it is assumed that the current optimal position is close to the optimal position vector, so that the search position is continuously close to the optimal position by iteratively updating to obtain the optimal control parameter.
Based on this, in some embodiments, as shown in fig. 2, S160 may include the steps of:
S161, calculating target first parameters corresponding to each candidate energy-saving parameter according to the frequency deviation and the temperature deviation of each candidate energy-saving parameter in the candidate energy-saving parameters and the initial energy-saving parameter. Specifically, a deviation between the frequency value of each candidate energy saving parameter and the frequency value of the initial energy saving parameter and a deviation between the temperature value of each candidate energy saving parameter and the temperature value of the initial energy saving parameter are calculated.
S162, respectively calculating the power consumption of the device corresponding to the target first parameter, and determining a second fitness function value corresponding to each power consumption according to the relation between the power consumption of the device and the fitness function.
S163, determining the target working frequency and the target temperature corresponding to the smallest second fitness function value in the second fitness function values as target initial energy-saving parameters, and determining the working frequency and the temperature corresponding to the second fitness function values with smaller preset numbers except the target working frequency and the target temperature as candidate target energy-saving parameters.
And taking the position vector corresponding to the initial energy-saving parameter obtained after sampling as the current optimal position, calculating the frequency deviation and the temperature deviation of the initial energy-saving parameter and the candidate energy-saving parameter according to the initial energy-saving parameter and the candidate energy-saving parameter to obtain a corresponding target first parameter, namely searching around the candidate energy-saving parameter, and updating the searching position to be close to the optimal position. And taking the working frequency and the temperature of the target first parameter corresponding to the minimum second fitness function value as initial target energy-saving parameters, and taking the preset number of candidate target energy-saving parameters divided by the working frequency and the temperature of the target first parameter corresponding to the smaller second fitness function value.
S164, respectively calculating target second parameters corresponding to each candidate energy-saving parameter according to the frequency deviation and the temperature deviation of each candidate energy-saving parameter in the candidate target energy-saving parameters and the target initial energy-saving parameters.
S165, respectively calculating the device power consumption corresponding to the target second parameter, and determining a third fitness function value corresponding to each power consumption according to the relation between the device power consumption and the fitness function.
And taking the position vector corresponding to the target initial energy-saving parameter obtained in the step S163 as the current optimal position for executing the steps S164 to S165 for the first time, calculating the frequency deviation and the temperature deviation of the target initial energy-saving parameter and the candidate target energy-saving parameter according to the target initial energy-saving parameter and the candidate target energy-saving parameter to obtain a corresponding target second parameter, namely searching around the candidate target energy-saving parameter, and updating the searching position to be close to the optimal position. And taking the working frequency and the temperature of the target second parameter corresponding to the minimum third fitness function value as the optimal position in the next iteration updating, and taking the working frequency and the temperature of the target second parameter corresponding to the third fitness function value with smaller dividing preset number as candidate target energy-saving parameters.
S166, when the times of calculating the third fitness function value reach the preset iteration updating times, determining the working frequency and the temperature corresponding to the smallest third fitness function value in the third fitness function value as the target energy-saving parameter.
And (3) before the preset iteration updating times are reached, performing S164 to S165 in a circulating way, and continuously updating the initial target energy-saving parameter and the candidate target energy-saving parameter to parameters with smaller fitness function values, so that the search position is continuously close to the optimal position, namely, the searched parameter value is continuously close to the optimal control parameter. When the calculated times of the third fitness function value reach the preset iteration updating times, the working frequency and the temperature corresponding to the minimum third fitness function value obtained by the last iteration updating are used as target energy-saving parameters.
In some embodiments, to further reduce the time for searching for optimal control parameters, S164 may include the steps of:
obtaining search parameters corresponding to each candidate target energy-saving parameter in the candidate target energy-saving parameters, wherein the search parameters comprise a search probability value, a first preset coefficient, a second preset coefficient and a curvature value;
when the searching probability value is smaller than the first preset probability value, calculating a target second parameter corresponding to each candidate target energy-saving parameter according to the candidate target energy-saving parameter, the first preset coefficient, the second preset coefficient and the target initial energy-saving parameter;
And when the searching probability value is larger than the second preset probability value, calculating a target second parameter corresponding to each candidate target energy-saving parameter according to the candidate target energy-saving parameter, the first preset coefficient, the curvature value and the target initial energy-saving parameter.
In some embodiments, in order to obtain the control parameter that makes the system energy consumption minimum in the whole safe value range, when the search probability value is smaller than the first preset probability value, calculating the target second parameter corresponding to each candidate energy saving parameter according to the candidate target energy saving parameter, the first preset coefficient, the second preset coefficient and the target initial energy saving parameter, when the search probability value is greater than the second preset probability value, calculating the target second parameter corresponding to each candidate target energy saving parameter according to the candidate target energy saving parameter, the first preset coefficient, the curvature value and the target initial energy saving parameter, calculating the target second parameter in two ways, increasing the diversity of the target second parameter, and making the finally obtained target energy saving parameter closer to the control parameter that makes the system energy consumption minimum in the whole safe value range.
Based on this, in some embodiments, according to the candidate target energy saving parameters, the first preset coefficient, the second preset coefficient and the target initial energy saving parameter, a target second parameter corresponding to each candidate target energy saving parameter is calculated, which may specifically be:
And calculating a target second parameter corresponding to each candidate target energy-saving parameter according to the first corresponding relation. Wherein the first corresponding relation is
Figure BDA0004015158410000141
Wherein (1)>
Figure BDA0004015158410000142
For the second parameter of interest, +.>
Figure BDA0004015158410000143
For a first preset coefficient, < >>
Figure BDA0004015158410000144
For the second preset coefficient, t is the current iteration update number, +.>
Figure BDA0004015158410000145
Energy saving parameters for candidate targets->
Figure BDA0004015158410000146
And (5) initial energy-saving parameters are target.
Wherein,,
Figure BDA0004015158410000147
and->
Figure BDA0004015158410000148
Can be obtained by calculation of the formula (5) and the formula (6).
Figure BDA0004015158410000149
Figure BDA00040151584100001410
Throughout the iterative process
Figure BDA00040151584100001411
Linearly decreasing from 2 to 0; r is (r) 1 And r 2 Is [0,1 ]]Is a random vector in (a).
In some embodiments, in order to make the possibility of searching the control parameter that minimizes the energy consumption of the system greater and reduce the searching time, the target second parameter corresponding to each candidate target energy saving parameter is calculated according to the candidate target energy saving parameter, the first preset coefficient, the second preset coefficient and the target initial energy saving parameter, which may specifically be:
and calculating a target second parameter corresponding to each candidate target energy-saving parameter according to the second corresponding relation. Wherein the second corresponding relation is
Figure BDA00040151584100001412
And->
Figure BDA00040151584100001413
Figure BDA0004015158410000151
Wherein (1)>
Figure BDA0004015158410000152
For the second parameter of interest, +.>
Figure BDA0004015158410000153
For a first preset coefficient, < >>
Figure BDA0004015158410000154
T is the current iteration update number of times, which is the difference between the target initial energy saving parameter and the candidate target energy saving parameter, +. >
Figure BDA0004015158410000155
Energy saving parameters for candidate targets->
Figure BDA0004015158410000156
And l is a curvature value for the target initial energy-saving parameter.
In some embodiments, in order to search for the control parameter that is a parameter that minimizes the energy consumption of the system within the local scope, the search parameter may further include a first random value, where the search probability value is less than a first preset probability value.
Based on this, according to the candidate target energy saving parameters, the first preset coefficient, the second preset coefficient and the target initial energy saving parameters, calculating a target second parameter corresponding to each candidate target energy saving parameter includes:
when the searching probability value is smaller than a first preset probability value and the absolute value of the first random value is smaller than a preset threshold value, calculating a target second parameter corresponding to each candidate target energy-saving parameter according to the candidate target energy-saving parameter, the first preset coefficient, the second preset coefficient and the target initial energy-saving parameter;
when the searching probability value is smaller than a first preset probability value and the absolute value of the first random value is larger than or equal to a first preset threshold value, a random candidate parameter is randomly acquired according to the candidate target energy-saving parameters, and a target second parameter corresponding to each candidate target energy-saving parameter is calculated according to the random candidate parameter, the first preset coefficient, the second preset coefficient and the target initial energy-saving parameter.
In the searching process, a searching mode of random searching is added, so that when the absolute value of a first random value is larger than or equal to a first preset threshold value, a target second parameter corresponding to each candidate target energy-saving parameter is calculated according to the random candidate parameter, the first preset coefficient, the second preset coefficient and the target initial energy-saving parameter, and the finally obtained target energy-saving parameter is a control parameter which enables the energy consumption of the system to be the lowest in the whole safe value range.
The calculating, according to the random candidate parameters, the first preset coefficient, the second preset coefficient and the initial target energy-saving parameter, the target second parameter corresponding to each candidate target energy-saving parameter may specifically be:
and calculating a target second parameter corresponding to each candidate target energy-saving parameter according to the third corresponding relation.
Wherein the third corresponding relation is
Figure BDA0004015158410000157
Figure BDA0004015158410000158
Figure BDA0004015158410000159
For the second parameter of interest, +.>
Figure BDA00040151584100001510
For a first preset coefficient, < >>
Figure BDA00040151584100001511
For the second preset coefficient, t is the current iteration update number, +.>
Figure BDA00040151584100001512
Energy saving parameters for candidate targets->
Figure BDA00040151584100001513
For the random candidate parameters obtained at the time of the t+1st iteration update,
Figure BDA00040151584100001514
and the random candidate parameter obtained in the t-th iteration updating is obtained.
It should be noted that, the various optional implementations described in the embodiments of the present application may be implemented in combination with each other without collision, or may be implemented separately, which is not limited to the embodiments of the present application.
Based on the control method of the system provided by the embodiment, correspondingly, the application also provides a specific implementation mode of the control device. Please refer to the following examples.
Referring to fig. 3, a control device provided in an embodiment of the present application may include:
the first obtaining module 301 is configured to obtain target data, where the target data includes a cryopump frequency, a cooling pump frequency, and a cooling tower water outlet temperature;
the sampling module 302 is configured to randomly sample the working frequencies of the target data in the preset frequency ranges and randomly sample the temperatures of the target data in the preset temperature ranges according to the preset frequency ranges and the preset temperature ranges, so as to obtain a plurality of sampling data sets;
a first calculation module 303, configured to calculate power consumption of the device according to the operating frequency and the temperature in the sampled data set;
a second calculation module 304, configured to calculate an fitness function value according to the power consumption and the relationship with the fitness function value;
a second obtaining module 305, configured to determine a working frequency and a temperature in a data set corresponding to a minimum first fitness function value of the fitness function values as an initial energy-saving parameter, and determine a working frequency and a temperature in a data set corresponding to a preset number of smaller fitness function values other than the initial energy-saving parameter as candidate energy-saving parameters;
An optimizing module 306, configured to determine a target energy saving parameter according to the initial energy saving parameter and the candidate energy saving parameter;
control module 307 for controlling the system according to the target energy saving parameter
The control device provided in the embodiment of the present application can implement each step in the method embodiment of fig. 1 and achieve a corresponding technical effect, and in order to avoid repetition, a detailed description is omitted here.
The embodiment of the application also provides a control device, which comprises: a processor and a memory storing computer program instructions. Wherein the processor, when executing the computer program instructions, implements the control method as in the first aspect.
Fig. 4 shows a schematic hardware structure of a control device according to an embodiment of the present application.
A processor 401 may be included in the control device as well as a memory 402 in which computer program instructions are stored.
In particular, the processor 401 described above may include a Central Processing Unit (CPU), or an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), or may be configured to implement one or more integrated circuits of embodiments of the present application.
Memory 402 may include mass storage for data or instructions. By way of example, and not limitation, memory 402 may comprise a Hard Disk Drive (HDD), floppy Disk Drive, flash memory, optical Disk, magneto-optical Disk, magnetic tape, or universal serial bus (Universal Serial Bus, USB) Drive, or a combination of two or more of the foregoing. Memory 402 may include removable or non-removable (or fixed) media, where appropriate. Memory 402 may be internal or external to the integrated gateway disaster recovery device, where appropriate. In a particular embodiment, the memory 402 is a non-volatile solid state memory.
The Memory may include Read-Only Memory (ROM), random-access Memory (Random Access Memory, RAM), magnetic disk storage media devices, optical storage media devices, flash Memory devices, electrical, optical, or other physical/tangible Memory storage devices. Thus, in general, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software comprising computer-executable instructions and when the software is executed (e.g., by one or more processors) it is operable to perform the operations described with reference to methods in accordance with aspects of the present disclosure.
The processor 401 implements any of the control methods of the above embodiments by reading and executing computer program instructions stored in the memory 402.
In one example, the control device may also include a communication interface 403 and a bus 410. As shown in fig. 3, the processor 401, the memory 402, and the communication interface 403 are connected by a bus 410 and perform communication with each other.
The communication interface 403 is mainly used to implement communication between each module, device, unit and/or apparatus in the embodiments of the present application.
Bus 410 includes hardware, software, or both, coupling the components of xx devices to each other. By way of example, and not limitation, the buses may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an infiniband interconnect, a Low Pin Count (LPC) bus, a memory bus, a micro channel architecture (MCa) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a video electronics standards association local (VLB) bus, or other suitable bus, or a combination of two or more of the above. Bus 410 may include one or more buses, where appropriate. Although embodiments of the present application describe and illustrate a particular bus, the present application contemplates any suitable bus or interconnect.
In addition, in combination with the control method in the above embodiment, the embodiment of the application may be implemented by providing a computer storage medium. The computer storage medium has stored thereon computer program instructions; which when executed by a processor, implement any of the control methods of the above embodiments.
It should be clear that the present application is not limited to the particular arrangements and processes described above and illustrated in the drawings. For the sake of brevity, a detailed description of known methods is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method processes of the present application are not limited to the specific steps described and illustrated, and those skilled in the art can make various changes, modifications, and additions, or change the order between steps, after appreciating the spirit of the present application.
The functional blocks shown in the above block diagrams may be implemented in hardware, software, firmware, or a combination thereof. When implemented in hardware, it may be, for example, an electronic circuit, an Application Specific Integrated Circuit (ASIC), suitable firmware, a plug-in, a function card, or the like. When implemented in software, the elements of the present application are the programs or code segments used to perform the required tasks. The program or code segments may be stored in a machine readable medium or transmitted over transmission media or communication links by a data signal carried in a carrier wave. A "machine-readable medium" may include any medium that can store or transfer information. Examples of machine-readable media include electronic circuitry, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio Frequency (RF) links, and the like. The code segments may be downloaded via computer networks such as the internet, intranets, etc.
It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, the present application is not limited to the order of the above-described steps, that is, the steps may be performed in the order mentioned in the embodiments, may be different from the order in the embodiments, or several steps may be performed simultaneously.
Aspects of the present disclosure are described above with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions/acts specified in the flowchart and/or block diagram block or blocks. Such a processor may be, but is not limited to being, a general purpose processor, a special purpose processor, an application specific processor, or a field programmable logic circuit. It will also be understood that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware which performs the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In the foregoing, only the specific embodiments of the present application are described, and it will be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the systems, modules and units described above may refer to the corresponding processes in the foregoing method embodiments, which are not repeated herein. It should be understood that the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive various equivalent modifications or substitutions within the technical scope of the present application, which are intended to be included in the scope of the present application.

Claims (11)

1. A method for controlling a system, comprising:
obtaining target data, wherein the target data comprise a freezing pump frequency, a cooling pump frequency and a cooling tower water outlet temperature;
according to a plurality of preset frequency ranges and a plurality of temperature ranges, randomly sampling the working frequencies of the working frequencies in the target data in the plurality of preset frequency ranges respectively, and randomly sampling the temperatures of the target data in the plurality of preset temperature ranges respectively to obtain a plurality of sampling data sets;
calculating the power consumption of the equipment according to the working frequency and the temperature in the sampling data set;
Calculating a first fitness function value according to the relation between the power consumption and the fitness function value;
determining the working frequency and the temperature in the sampling data set corresponding to the minimum first fitness function value in the first fitness function values as initial energy-saving parameters, and determining the working frequency and the temperature in the sampling data set corresponding to a preset number of smaller fitness function values except the initial energy-saving parameters as candidate energy-saving parameters;
determining a target energy saving parameter according to the initial energy saving parameter and the candidate energy saving parameter;
and controlling the system according to the target energy-saving parameter.
2. The control method according to claim 1, wherein before the operating frequencies of the target data in the preset frequency ranges and the temperature ranges are randomly sampled, respectively, and the temperatures of the target data in the preset temperature ranges are randomly sampled, respectively, to obtain a plurality of sampled data sets, the method further comprises:
dividing the frequency in the target data into a plurality of first frequency range with different preset lengths according to the frequency in the target data;
And dividing the temperature in the target data into a plurality of first temperature ranges with different preset lengths according to the temperature in the target data.
3. The control method according to claim 2, wherein after dividing the frequency in the target data into a plurality of first frequency band ranges of different preset lengths and the temperature in the target data into a plurality of first temperature ranges of different preset lengths, the method further comprises, before randomly sampling the operating frequency in the target data in a plurality of preset frequency band ranges and the operating frequency in a plurality of temperature ranges, respectively, and randomly sampling the temperature in the target data in a plurality of preset temperature ranges, respectively, to obtain a plurality of sampled data sets, according to the frequency in the target data:
dividing each first frequency range into a plurality of second frequency ranges uniformly to obtain a plurality of preset frequency ranges;
and uniformly dividing each first temperature range into a plurality of second temperature ranges to obtain a plurality of preset temperature ranges.
4. The control method according to claim 1, wherein the determining a target energy saving parameter from the initial energy saving parameter and the candidate energy saving parameter includes:
According to the frequency deviation and the temperature deviation of each candidate energy-saving parameter in the candidate energy-saving parameters and the initial energy-saving parameter, respectively calculating a target first parameter corresponding to each candidate energy-saving parameter;
respectively calculating the equipment power consumption corresponding to the target first parameter, and determining a second fitness function value corresponding to each power consumption according to the relation between the equipment power consumption and the fitness function;
determining a target working frequency and a target temperature corresponding to a minimum second fitness function value in the second fitness function values as target initial energy-saving parameters, and determining working frequencies and temperatures corresponding to a preset number of smaller second fitness function values except the target working frequency and the target temperature as candidate target energy-saving parameters;
according to the frequency deviation and the temperature deviation of each candidate target energy-saving parameter in the candidate target energy-saving parameters and the target initial energy-saving parameters, respectively calculating a target second parameter corresponding to each candidate target energy-saving parameter;
respectively calculating the equipment power consumption corresponding to the target second parameter, and determining a third fitness function value corresponding to each power consumption according to the relation between the equipment power consumption and the fitness function;
When the times of calculating the third fitness function value reach the preset iteration updating times, determining the working frequency and the temperature corresponding to the smallest third fitness function value in the third fitness function value as target energy-saving parameters.
5. The control method according to claim 4, wherein the calculating the target second parameter corresponding to each candidate target energy saving parameter according to the frequency deviation and the temperature deviation of each candidate target energy saving parameter from the target initial energy saving parameter includes:
obtaining search parameters corresponding to each candidate target energy-saving parameter in the candidate target energy-saving parameters, wherein the search parameters comprise a search probability value, a first preset coefficient, a second preset coefficient and a curvature value;
when the searching probability value is smaller than a first preset probability value, calculating a target second parameter corresponding to each candidate target energy-saving parameter according to the candidate target energy-saving parameter, the first preset coefficient, the second preset coefficient and the target initial energy-saving parameter;
and when the searching probability value is larger than a second preset probability value, calculating a target second parameter corresponding to each candidate target energy-saving parameter according to the candidate target energy-saving parameter, the first preset coefficient, the curvature value and the target initial energy-saving parameter.
6. The control method according to claim 5, wherein calculating a target second parameter corresponding to each candidate target energy saving parameter according to the candidate target energy saving parameter, the first preset coefficient, the second preset coefficient, and the target initial energy saving parameter comprises:
calculating a target second parameter corresponding to each candidate target energy-saving parameter according to the first corresponding relation;
the first corresponding relation is that
Figure FDA0004015158400000031
Wherein (1)>
Figure FDA0004015158400000032
For the target second parameter, +.>
Figure FDA0004015158400000033
For said first preset coefficient, +.>
Figure FDA0004015158400000034
For the second preset coefficient, t is the current iteration update time, and +.>
Figure FDA0004015158400000035
Energy saving parameters for the candidate object, +.>
Figure FDA0004015158400000036
And initializing energy-saving parameters for the target.
7. The control method according to claim 5, wherein calculating a target second parameter corresponding to each candidate target energy saving parameter according to the candidate target energy saving parameter, the first preset coefficient, the second preset coefficient, and the target initial energy saving parameter comprises:
calculating a target second parameter corresponding to each candidate energy-saving parameter according to the second corresponding relation;
the second corresponding relation is
Figure FDA0004015158400000041
And->
Figure FDA0004015158400000042
Figure FDA0004015158400000043
Wherein (1)>
Figure FDA0004015158400000044
For the target second parameter, +. >
Figure FDA0004015158400000045
For said first preset coefficient, +.>
Figure FDA0004015158400000046
T is the current iteration update number of times and is the difference between the target initial energy saving parameter and the candidate target energy saving parameter>
Figure FDA0004015158400000047
Energy saving parameters for the candidate object, +.>
Figure FDA0004015158400000048
And (3) for the target initial energy-saving parameter, l is the curvature value.
8. The energy saving control method of claim 5, wherein the search parameter further comprises a first random value; when the search probability value is smaller than a first preset probability value, calculating a target second parameter corresponding to each candidate target energy-saving parameter according to the candidate target energy-saving parameter, the first preset coefficient, the second preset coefficient and the target initial energy-saving parameter, including:
when the search probability value is smaller than a first preset probability value and the absolute value of the first random value is smaller than a preset threshold value, calculating a target second parameter corresponding to each candidate target energy-saving parameter according to the candidate target energy-saving parameter, the first preset coefficient, the second preset coefficient and the target initial energy-saving parameter;
when the search probability value is smaller than a first preset probability value and the absolute value of the first random value is larger than or equal to a first preset threshold value, randomly acquiring a random candidate parameter according to the candidate target energy-saving parameters, and calculating a target second parameter corresponding to each candidate energy-saving parameter according to the random candidate parameter, the first preset coefficient, the second preset coefficient and the target initial energy-saving parameter.
9. A control apparatus, characterized in that the apparatus comprises:
the first acquisition module is used for acquiring target data, wherein the target data comprise a freezing pump frequency, a cooling pump frequency and a cooling tower water outlet temperature;
the sampling module is used for randomly sampling the working frequencies of the working frequencies in the target data in the preset frequency ranges and the temperature in the target data in the preset temperature ranges according to the preset frequency ranges and the temperature ranges, so as to obtain a plurality of sampling data sets;
a first calculation module for calculating the power consumption of the device according to the operating frequency and the temperature in the sampling data set;
the second calculation module is used for calculating the fitness function value according to the relation between the power consumption and the fitness function value;
the second acquisition module is used for determining the working frequency and the temperature in the data set corresponding to the minimum first fitness function value in the fitness function values as initial energy-saving parameters and determining the working frequency and the temperature in the sampling data set corresponding to a preset number of smaller fitness function values except the initial energy-saving parameters as candidate energy-saving parameters;
The optimization module is used for determining a target energy-saving parameter according to the initial energy-saving parameter and the candidate energy-saving parameter;
and the control module is used for controlling the system according to the target energy-saving parameter.
10. A control apparatus, characterized in that the apparatus comprises: a processor and a memory storing computer program instructions;
the processor, when executing the computer program instructions, implements the control method of any one of claims 1 to 8.
11. A computer readable storage medium, characterized in that the computer readable storage medium has stored thereon computer program instructions, which when executed by a processor, implement the control method according to any of claims 1 to 8.
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