CN115390948B - Method, computing device, and medium for determining an airtime of an air compression station - Google Patents
Method, computing device, and medium for determining an airtime of an air compression station Download PDFInfo
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Abstract
The invention provides a method, a computing device and a computer-readable storage medium for determining an empty-time parking time of an air compression station. The method comprises the following steps: acquiring pressure upper limit data of the air compression station and unloading duration data of a plurality of air compressors of the air compression station at each sampling moment of a plurality of sampling moments; determining an unloading time length distribution parameter of the air compression station, which is associated with a pressure bandwidth, based on the pressure upper limit data and the unloading time length data; determining an air compression station waste saving proportion associated with a pressure bandwidth adjustment value and an air time parking time of the air compression station based on the unloading time length distribution parameter; determining the starting times of the air compressor associated with the air compressor long-term parking time; and determining the optimal value of the air compressor stopping time on the basis of the starting times of the air compressor and the waste saving proportion of the air compressor station.
Description
Technical Field
The present invention relates generally to the field of industrial control, and more particularly, to a method, computing device, and computer-readable storage medium for determining an airtime parking time of an air compression station.
Background
An air compressor is an apparatus for compressing gas, and is currently widely used in construction, steel, mining, and chemical plants. In the case of a large gas demand, an air compression station including a plurality of air compressors is generally used to supply compressed gas to a gas end (or a user end). The gas end may be, for example, a factory or a workshop.
Before the operation of the air compression station, a lower pressure limit is usually specified by the air end according to the requirement of the air compression station, and an upper pressure limit allowed by the pressure transmitter is specified by a control system of the air compression station. In the operation process of the air compression station, the control system can control loading and unloading and startup and shutdown of the air compressor according to the measured air pressure of the air compression station. If the measured air pressure at the air compressor station exceeds a specified upper pressure limit, the control system will control the unloading of the air compressor to reduce the air pressure. The air compressor can have three states: shutdown, unload, and load. When the air compressor is in an unloading state, the motor idles, but does not generate gas. When the measured air pressure of the air compressor station is lower than the set air compressor loading pressure, the air compressor in the unloading state can be transferred to the loading state, the motor rotates and generates air, or when the conditions are unchanged, the air compressor is transferred to the shutdown state, and the motor stops rotating.
In the air compressor station control system, an idle stop time is also usually set, and the idle stop time is used for indicating the time interval between the time when the air compressor enters the unloading state and the time when the air compressor is shifted to the shutdown state, that is, the air compressor in the unloading state enters the shutdown state after the idle stop time elapses.
If the idle time is set to be too long, the idle time of the air compressor in the unloading state is too long, and a large amount of electric power is wasted. If reduce empty time of stopping for a long time, then can lead to the switching on and shutting down number of times to increase, too frequent switching chance leads to the air compressor machine to damage, influences the air compressor machine life-span. Similarly, since the state transition of the air compressor is also related to the upper pressure limit set by the air station control system, if the upper pressure limit is lowered, the number of times of turning on and off the air compressor is increased.
In addition, if the air-compressor stopping time and the upper pressure limit are set to be not good enough, a laminated pressure band appears in pressure expression along with loading and unloading of the air compressor, pressure fluctuation of the air compressor station becomes large, the pressure band needs to be translated in sections before other processing is carried out by using the data, and processing complexity is increased.
Therefore, how to reasonably set the upper pressure limit and the air-compressor long-time stopping time of the air compressor station so as to realize lower startup and shutdown times of the air compressor and better energy-saving effect is a problem to be considered.
Disclosure of Invention
In view of the above problems, the present invention provides a method for determining an optimum value for airtime parking by modeling the relationship between unloading duration and pressure bandwidth in combination with the waste saving of the air compression station.
According to one aspect of the present invention, a method of determining an airtime of an air compression station is provided. The method comprises the following steps: acquiring pressure upper limit data of the air compression station and unloading duration data of a plurality of air compressors of the air compression station at each sampling moment of a plurality of sampling moments; determining an unloading time length distribution parameter of the air compression station, which is associated with a pressure bandwidth, based on the pressure upper limit data and the unloading time length data; determining an air compression station waste saving proportion associated with a pressure bandwidth adjustment value and an air compression station parking time of the air compression station based on the unloading time length distribution parameter; determining the starting times of the air compressor associated with the air compressor long-term parking time; and determining the optimal value of the air compressor stopping time based on the starting times of the air compressor and the waste saving ratio of the air compressor station.
In some embodiments, determining an unloading duration distribution parameter associated with a pressure bandwidth for the air compression station comprises: fitting unloading duration data of one sampling moment in the multiple sampling moments by using a truncated normal distribution function to determine unloading duration distribution of the sampling moment; determining a pressure bandwidth at each sampling moment based on the pressure upper limit data and the preset pressure lower limit data at each sampling moment; and determining an unloading time length distribution parameter of the air compression station, which is associated with the pressure bandwidth, based on the unloading time length distribution and the pressure bandwidth at each sampling moment.
In some embodiments, determining the empty-stop waste savings ratio associated with the pressure bandwidth adjustment value and the empty-time parking time of the empty-stop comprises: determining a high-pressure waste saving proportion of the air compression station based on a high-pressure energy saving coefficient and a pressure bandwidth adjustment value of the air compression station; determining an unloading waste reduction proportion of unloading duration larger than the air-driven long parking time based on the unloading duration distribution parameter; and determining the air compression station waste saving proportion based on the high pressure waste saving proportion and the unloading waste reduction proportion.
In some embodiments, determining the number of times the air compressor is turned on in association with the airtime includes: acquiring the total unloading times of the empty long parking time; obtaining the probability that the unloading duration is greater than the empty permanent parking time when the empty permanent parking time is reached; and determining the starting times of the air compression station associated with the parking time of the empty time based on the total unloading times and the probability that the unloading time length is greater than the parking time of the empty time.
In some embodiments, determining the optimal value for the airtime comprises: determining an empty and long parking time set with the starting times of the air compressor smaller than threshold starting times; and determining the empty time and the parking time when the waste saving proportion of the air compression station reaches the maximum value from the empty time and parking time set as the optimal value of the empty time and the parking time.
In some embodiments, the method further comprises: simultaneously determining an optimal value of the idle stop time and an optimal value of the pressure bandwidth by using a gradient descent method; and determining an optimal upper pressure limit based on the optimal value of the pressure bandwidth and predetermined lower pressure limit data.
According to another aspect of the invention, a computing device is provided. The computing device includes: at least one processor; and at least one memory coupled to the at least one processor and storing instructions for execution by the at least one processor, the instructions when executed by the at least one processor causing the computing device to perform steps according to the above-described method.
According to yet another aspect of the present invention, a computer-readable storage medium is provided, having stored thereon computer program code, which, when executed, performs the method as described above.
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The invention will be better understood and other objects, details, features and advantages thereof will become more apparent in the light of the following description of specific embodiments thereof, given with reference to the accompanying drawings.
Fig. 1 shows a schematic view of an air compression station for implementing an embodiment according to the invention.
Fig. 2 illustrates a flow chart of a method of determining an empty parking time of an air compression station according to some embodiments of the present invention.
Fig. 3 shows a further flowchart of a process of determining an unloading duration distribution parameter associated with a pressure bandwidth for an air compression station according to an embodiment of the present invention.
Fig. 4 illustrates a further detailed flow diagram of a process for determining a waste saving ratio for an air compression station according to some embodiments of the present invention.
FIG. 5 illustrates a further detailed flow chart of a process for determining the number of starts of an air compression station associated with an airtime parking time in accordance with some embodiments of the present invention.
FIG. 6 illustrates a block diagram of a computing device suitable for implementing embodiments of the present invention.
Detailed Description
Preferred embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While the preferred embodiments of the present invention are shown in the drawings, it should be understood that the present invention may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
In the following description, for the purposes of illustrating various inventive embodiments, certain specific details are set forth in order to provide a thorough understanding of the various inventive embodiments. One skilled in the relevant art will recognize, however, that an embodiment can be practiced without one or more of the specific details. In other instances, well-known devices, structures and techniques associated with this application may not be shown or described in detail to avoid unnecessarily obscuring the description of the embodiments.
Throughout the specification and claims, the word "comprise" and variations thereof, such as "comprises" and "comprising", will be understood to have an open, inclusive meaning, i.e., will be interpreted to mean "including, but not limited to", unless the context requires otherwise.
Reference throughout this specification to "one embodiment" or "some embodiments" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment. Thus, the appearances of the phrases "in one embodiment" or "in some embodiments" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
Furthermore, the terms first, second and the like used in the description and the claims are used for distinguishing objects for clarity, and do not limit the size, other order and the like of the described objects.
Fig. 1 shows a schematic view of an air compression station 1 for implementing an embodiment according to the invention. As shown in fig. 1, the air compressing station 1 may include a plurality of air compressors 10 (5 air compressors 10-1, 10-2, 10-3, 10-4, and 10-5 are exemplarily shown in fig. 1), a main pipe 20, and a gas using end 30, wherein the plurality of air compressors 10 transmit the generated compressed gas to the gas using end 30 through the main pipe 20.
The air compression station 1 further comprises a computing device 40 for executing the method for determining the airtime of the air compression station 1 according to the invention. The computing device 40 may be part of the control system of the air compression station 1 or may be located outside the control system but may be in communication therewith.
The computing device 40 may include at least one processor 42 and at least one memory 44 coupled to the at least one processor 42, the memory 44 having stored therein instructions 46 executable by the at least one processor 42, the instructions 46 when executed by the at least one processor 42 performing at least a portion of a method as described below. The specific structure of computing device 40 may be described, for example, in connection with FIG. 6, below.
Fig. 2 illustrates a flow chart of a method 200 of determining an empty parking time of an air compression station according to some embodiments of the present invention. Method 200 may be performed by computing device 40 in air compression station 1 shown in fig. 1. The method 200 is described below in conjunction with fig. 1-6.
As shown in fig. 2, method 200 includes a block 210 in which upper pressure limit data for air compressor station 1 and unloading duration data for a plurality of air compressors 10 are obtained at each of a plurality of sampling instants.
The pressure upper limit data is a pressure upper limit preset for the air compressing station 1, and the pressure upper limit data of the air compressing station 1 at different sampling moments may be the same or different. In this context, in order to determine the relationship between the unloading time period and the pressure bandwidth, the upper pressure limit data for the selected sampling instants should be as different as possible. This upper pressure limit data may be pre-stored in the computing device 40 or may be stored in other parts of the control system of the air compression station 1 and read by the computing device 40 at block 210.
The unloading duration refers to a time interval between the time when the air compressor 10 enters the unloading state and the time when the air compressor is transferred out of the unloading state, that is, the time interval between the time when the air compressor is transferred from the unloading state to the shutdown state or the loading state. The control system of the air compression station 1 may acquire the state of each air compressor 10 in real time or periodically and form a state transition record of each air compressor 10. The calculation device 40 can determine unloading duration data of each air compressor 10 at various sampling moments based on the state transition records.
At block 220, the computing device 40 may determine an unloading period distribution parameter of the air compressing station 1 associated with the pressure bandwidth based on the pressure upper limit data and the unloading period data acquired at block 210.
On the one hand, for each sampling time, in the case where there is no serious air leakage from the air compression station 1, the pipe air pressure of the air compression station 1 is determined by the volume (air tank, pipe size) of the air compression station 1, the displacement of each air compressor 10, and the air consumption of the air consumption end 30. There may be fluctuations in air usage at some time, which typically follow a normal distribution, and thus, in the absence of the air time-out limit, fluctuations in air usage above a certain threshold may cause the air compressor 10 to unload until the air usage fluctuates back to a normal level. Therefore, the unloading duration of the air compressor 10 also follows the normal distribution, i.e., the probability density function of the unloading duration is the normal distribution. Considering that the unloading duration is always positive, the unloading duration is further considered to follow a truncated normal distribution.
On the other hand, at different sampling times, the upper pressure limit may be different, resulting in different pressure bandwidths (difference between the upper pressure limit and the lower pressure limit, assuming that the lower pressure limit specified by the gas end is not changed). The variation of the pressure bandwidth enables the time for the pressure of the air compression station 1 to drop from the upper pressure limit to the lower pressure limit to vary correspondingly, and the unloading time of the air compressor 10 also varies correspondingly. The distribution of unloading duration with variation of the upper pressure limit (pressure bandwidth) is a variant of the above-mentioned truncated normal distribution.
Fig. 3 shows a further flowchart of the procedure of determining an unloading duration distribution parameter associated with the pressure bandwidth of the air compression station 1 (block 220) according to an embodiment of the invention.
As shown in fig. 3, at block 222, computing device 40 may fit unloading duration data for one sampling instant (e.g., the first sampling instant) of the plurality of sampling instants obtained at block 210 using a truncated normal distribution function to determine an unloading duration distribution for the sampling instant.
As described above, at each sampling timing, the unloading period of each air compressor 10 is longtdA truncated normal distribution can be expressed as:
wherein the content of the first and second substances,tdthe length of the unloading time is shown,
represents the mean of the truncated normal distribution,
represents the variance of the truncated normal distribution, and 0 represents the truncation of the truncated normal distribution from 0 (i.e., a positive value).
At block 222, computing device 40 may determine an unload duration distribution, i.e., a mean, for a sample time by fitting the unload duration data for the sample time
Sum variance
。
At block 224, computing device 40 may determine a pressure bandwidth for each sampling time based on the upper pressure limit data and the predetermined lower pressure limit data for that sampling time. Here, it is assumed that the lower pressure limit is specified by the gas usage end 30 and remains unchanged. The pressure bandwidth is equal to the upper pressure limit data minus the lower pressure limit data.
At block 226, the computing device 40 may determine an unloading duration distribution parameter of the air compression station 1 associated with the pressure bandwidth based on the unloading duration distribution and the pressure bandwidth at each sampling instant.
Assume the unload duration distribution (mean) at the first sample instant
Sum variance
) For reference, the distribution of unloading time length after the pressure bandwidth change can be expressed as a mean value
Sum variance
. Wherein the coefficients
And
compliance with pressure bandwidth relationships
The pressure bandwidth relationship
In relation to the pressure bandwidth and the volume of the air compression station 1 (assuming here that the volume of the air compression station 1 is constant).
At block 226, the computing device 40 may fit a pressure unloading time duration distribution and a pressure bandwidth based on the pressure unloading time duration distribution and the pressure bandwidth at each sampling time
To determine an unloading time period distribution parameter associated with the pressure bandwidthI.e. mean value
、Variance (variance)
And pressure bandwidth relationship
。
Continuing with fig. 2, at block 230, computing device 40 may determine an air pressure station waste savings ratio associated with the pressure bandwidth adjustment value (d 1-d 2) and the airtime parking time for air pressure station 1 based on the unloading duration distribution parameter determined at block 220.
Here, it is assumed that the pressure bandwidth is adjusted from d1 to d2 due to the change in the upper pressure limit. The air compression station waste savings is embodied in two aspects, one is high pressure waste savings and the other is unloading waste reduction.
Fig. 4 illustrates a further detailed flow chart of a process for determining a waste saving ratio for an air compression station (block 230) according to some embodiments of the present invention.
As shown in fig. 4, at block 232, computing device 40 may determine a high-pressure waste saving ratio C1 for air compressor station 1 based on the high-pressure energy saving coefficient and the pressure bandwidth adjustment value for air compressor station 1.
The high pressure waste of the air compression station 1 is usually only related to the pressure bandwidth, so the saving ratio C1 of the high pressure waste caused by the adjustment of the pressure bandwidth from d1 to d2 can be expressed as:
where d1 and d2 are the pressure bandwidths before and after adjustment, respectively, and α is the high pressure energy saving coefficient, which is an empirical constant, e.g., 7%.
At block 234, computing device 40 may determine an unload duration based on the unload duration distribution parameter determined at block 220tdGreater than empty long parking timet 0 Unloading waste reduction ratio ofC2。
With the demand unchanged, the total length of unloading and shutdown actually required is unchanged, so the unloading waste reduction rate is actually the rate of shutdown increase. In block 220, the determined unload duration distribution parameter associated with the pressure bandwidth includes a mean value
、Variance (variance)
And pressure bandwidth relationship
According to the parameters, the unloading duration under any pressure bandwidth can be obtainedxProbability density function of
. Therefore, the unloading durationxGreater than empty long parking timet 0 The unloading waste reduction ratio C2 of (a) can be expressed as:
at block 236, the computing device 40 may determine the air compression station waste saving ratio C based on the high voltage waste saving ratio C1 and the unload waste reduction ratio C2.
In some implementations, the air compression station waste saving ratio C may be equal to the sum of the high voltage waste saving ratio C1 and the unload waste reduction ratio C2.
In other implementations, the empty station waste savings ratio C may be equal to a weighted sum of the high voltage waste savings ratio C1 and the unload waste reduction ratio C2, where the weight may be an empirical value.
Continuing with FIG. 2, at block 240, computing device 40 may determine a time to empty parkingt 0 And the number of times of starting the associated air compressor.
FIG. 5 illustrates a use according to some embodiments of the inventionsIn determining the time of leaving a vehicle emptyt 0 A further detailed flow chart of the process of the number of starts of the associated air compression station 1 (block 240).
As shown in FIG. 5, at block 242, computing device 40 may retrieve any empty parking timest 0 Total number of unloads of hour
. This total number of unloads may be obtained, for example, from the state transition records described above.
At block 244, computing device 40 may obtain the empty parking timet 0 Time to unloadtdGreater than the empty long parking timet 0 The probability of (c).
An unload duration distribution parameter is determined (i.e., the unload duration is determined) at block 220tdProbability density function) of the load, the unload duration can be easily knowntdCumulative distribution function ofP(td)。
Thus, at block 244, the unload duration may be based ontdCumulative distribution function ofP(td) Determining offload durationtdGreater than empty long parking timet 0 Has a probability ofP(td>t 0 )。
At block 246, computing device 40 may base the total number of unloads on
And length of offloadtdGreater than empty long parking timet 0 Probability of (2)P(td>t 0 ) Determining the time of parking in the airt 0 Associated number of times of starting air compressor
I.e. assuming the empty and long parking time ast 0 The starting times of the air compressor are as follows:
continuing with FIG. 2, at block 250, computing device 40 may be based on the number of times that the air compressor was turned on
And the waste saving proportion C of the air compression station determines the air long parking timet 0 The optimum value of (2).
In actual air compressor control, it is generally considered that if the number of times the air compressor is turned on per unit time is greater than a certain value, the air compressor will be damaged, which may cause problems such as head jamming and turn-to-turn short circuit of the motor, and therefore the determination of the optimal air time should satisfy the constraint condition of the number of times the air compressor is turned on per unit time, that is, the number of times the air compressor is turned on in block 240 should be less than a certain threshold number of times.
Specifically, according to the above formula (4), the number of times of starting the air compressor can be determined
Idle time less than a given threshold number of power-ont 0 I.e. all the empty parking times that satisfy the constraint.
Then, the empty time when the empty station waste saving ratio C reaches the maximum value may be determined from the set of empty time as the optimum value of the empty time.
Specifically, as described above, the air compression station waste saving ratio C is determined by the high-pressure waste saving ratio C1 and the unloading waste reducing ratio C2, while the high-pressure waste saving ratio C1 is determined by the pressure bandwidth adjustment value (in the case where the pressure bandwidth d1 before adjustment is known, the high-pressure waste saving ratio C1 depends only on the adjusted pressure bandwidth d 2), and the unloading waste reducing ratio C2 depends on the air time parking timet 0 (empty long parking time)t 0 The smaller the unloading waste reduction ratio C2, but the longer the idle stop timet 0 The smaller the air compressor is, the starting times
The larger the compressor is, the more the number of times the compressor is started
Limited by threshold startup times), there is a time spent idling that causes the air compression station to waste savings ratio C to a maximum valuet 0 And a pressure bandwidth d2, i.e. an optimal airtime and an optimal pressure bandwidth.
In some implementations, a gradient descent method may be utilized to determine optimal values for both the airtime and the pressure bandwidth. The gradient descent method is an iterative algorithm widely used to solve the optimal solution for linear and nonlinear models by fitting independent variables (dead-time parking time)t 0 And pressure bandwidth d 2) is iteratively calculated according to a step size adjustment to find the argument at which the loss function is minimal. Here, the loss function refers to a difference function of the air compression station waste saving ratios C before and after the iteration.
By utilizing the method, the maximum empty-duration parking time and pressure bandwidth which are wasted and saved by the air compression station under the given constraint condition can be determined by modeling the relation between the unloading duration and the pressure bandwidth and combining the waste saving condition of the air compression station, namely the optimal values of the empty-duration parking time and the pressure bandwidth to be set.
Further, after determining the optimal value for the space parking time, the method 200 may also determine an optimal value for the upper pressure limit based on the optimal value for the pressure bandwidth.
Specifically, the optimum upper pressure limit may be determined based on the optimum value of the pressure bandwidth d2 and predetermined lower pressure limit data.
According to the method, a mechanism model of an upper pressure limit (pressure bandwidth), the air-to-air shutdown time, the startup and shutdown times and the unloading duration is constructed by means of hydrodynamics and an air compressor unloading mechanism, then an air compressor energy loss function is constructed, and the optimal upper pressure limit and the air-to-air shutdown time are obtained based on an optimization theory. Compared with the traditional manual parameter adjustment, the method can more scientifically find the optimal parameters, reduce the parameter adjustment times and improve the control effect.
FIG. 6 illustrates a block diagram of a computing device 600 suitable for implementing embodiments of the present invention. The computing device 600 may be, for example, the computing device 40 in the air compression station 1 as described above.
As shown in fig. 6, computing device 600 may include one or more Central Processing Units (CPUs) 610 (only one shown schematically) that may perform various suitable actions and processes in accordance with computer program instructions stored in a Read Only Memory (ROM) 620 or loaded from a storage unit 680 into a Random Access Memory (RAM) 630. In the RAM 630, various programs and data required for the operation of the computing device 600 may also be stored. The CPU 610, ROM 620, and RAM 630 are connected to each other via a bus 640. An input/output (I/O) interface 650 is also connected to bus 640.
A number of components in computing device 600 are connected to I/O interface 650, including: an input unit 660 such as a keyboard, a mouse, etc.; an output unit 670 such as various types of displays, speakers, and the like; a storage unit 680 such as a magnetic disk, optical disk, or the like; and a communication unit 690 such as a network card, modem, wireless communication transceiver, etc. The communication unit 690 allows the computing device 600 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunications networks.
The method 200 described above may be performed, for example, by the CPU 610 of one or more computing devices 600. For example, in some embodiments, method 200 may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 680. In some embodiments, part or all of the computer program may be loaded and/or installed onto computing device 600 via ROM 620 and/or communications unit 690. When the computer program is loaded into RAM 630 and executed by CPU 610, one or more of the operations of method 200 described above may be performed. Further, the communication unit 690 may support wired or wireless communication functions.
Those skilled in the art will appreciate that the computing device 600 illustrated in FIG. 6 is merely illustrative. In some embodiments, computing device 600 may contain more or fewer components than shown in FIG. 6.
A method 200 of determining an airtime parking of an air compression station and a computing device 600 that may be used to implement the method 200 in accordance with the present invention are described above with reference to the accompanying drawings. However, it will be appreciated by those skilled in the art that the performance of the steps of the method 200 is not limited to the order shown in the figures and described above, but may be performed in any other reasonable order. Further, the computing device 600 also need not include all of the components shown in FIG. 6, it may include only some of the components necessary to perform the functions described in this disclosure, and the manner in which these components are connected is not limited to the form shown in the figures.
The present invention may be methods, apparatus, systems and/or computer program products. The computer program product may include a computer-readable storage medium having computer-readable program instructions embodied therewith for carrying out aspects of the invention.
In one or more exemplary designs, the functions described herein may be implemented in hardware, software, firmware, or any combination thereof. For example, if implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium.
The units of the apparatus disclosed herein may be implemented using discrete hardware components, or may be integrally implemented on a single hardware component, such as a processor. For example, the various illustrative logical blocks, modules, and circuits described in connection with the present invention may be implemented or performed with a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein.
Those of skill would further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both.
The previous description of the disclosure is provided to enable any person skilled in the art to make or use the disclosure. Various modifications to the disclosure will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other variations without departing from the spirit or scope of the disclosure. Thus, the present invention is not intended to be limited to the examples and designs described herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (8)
1. A method of determining an airtime parking of an air compression station, comprising:
acquiring pressure upper limit data of the air compression station and unloading duration data of a plurality of air compressors of the air compression station at each sampling moment of a plurality of sampling moments;
determining an unloading time length distribution parameter of the air compression station, which is associated with a pressure bandwidth, based on the pressure upper limit data and the unloading time length data;
determining an air compression station waste saving proportion associated with a pressure bandwidth adjustment value and an air time parking time of the air compression station based on the unloading time length distribution parameter;
determining the starting times of the air compressor associated with the air time; and
and determining the optimal value of the air compressor stopping time based on the starting times of the air compressor and the waste saving ratio of the air compressor station.
2. The method of claim 1, wherein determining an unloading duration distribution parameter of the air compression station associated with a pressure bandwidth comprises:
fitting the unloading duration data of one sampling moment in the plurality of sampling moments by using a truncated normal distribution function to determine the unloading duration distribution of the sampling moment;
determining a pressure bandwidth at each sampling moment based on the pressure upper limit data and the preset pressure lower limit data at the sampling moment; and
and determining an unloading time length distribution parameter of the air compression station, which is associated with the pressure bandwidth, based on the unloading time length distribution and the pressure bandwidth at each sampling moment.
3. The method of claim 1, wherein determining the percentage of empty station waste savings associated with the pressure bandwidth adjustment value and the empty time parking of the empty station comprises:
determining a high-pressure waste saving proportion of the air compression station based on a high-pressure energy saving coefficient and a pressure bandwidth adjustment value of the air compression station;
determining an unloading waste reduction proportion that the unloading duration is greater than the empty duration parking time based on the unloading duration distribution parameter; and
determining the air compression station waste saving ratio based on the high pressure waste saving ratio and the unloading waste reduction ratio.
4. The method of claim 1, wherein determining the number of compressor turn-ons associated with the airtime includes:
acquiring the total unloading times of the empty long parking time;
obtaining the probability that the unloading duration is longer than the empty long parking time when the empty long parking time is used; and
and determining the starting times of the air compression station associated with the parking time based on the total unloading times and the probability that the unloading time is greater than the parking time.
5. The method of claim 1, wherein determining the optimal value for the airtime comprises:
determining an empty and long parking time set with the starting times of the air compressor smaller than threshold starting times; and
and determining the empty long parking time when the waste saving proportion of the empty compression station reaches the maximum value from the empty long parking time set as the optimal value of the empty long parking time.
6. The method of claim 1, further comprising:
simultaneously determining an optimal value of the idle stop time and an optimal value of the pressure bandwidth by using a gradient descent method; and
an optimal upper pressure limit is determined based on the optimal value of the pressure bandwidth and predetermined lower pressure limit data.
7. A computing device, comprising:
at least one processor; and
at least one memory coupled to the at least one processor and storing instructions for execution by the at least one processor, the instructions when executed by the at least one processor causing the computing device to perform the steps of the method of any of claims 1-6.
8. A computer readable storage medium having stored thereon computer program code which when executed performs the method of any of claims 1 to 6.
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| JP2014134146A (en) * | 2013-01-10 | 2014-07-24 | Miura Co Ltd | System for controlling number of compressor |
| CN106499617A (en) * | 2016-11-02 | 2017-03-15 | 苏州能讯高能半导体有限公司 | A kind of air compressor energy-saving regulation and control method, apparatus and system |
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