EP4296514A1

EP4296514A1 - Method, device and medium for controlling air compressor in air compression station

Info

Publication number: EP4296514A1
Application number: EP23174400.4A
Authority: EP
Inventors: Xiang Lei; Ziye Zhou; Guohui Shen
Original assignee: Mogulinker Technology Shenzhen Co Ltd
Current assignee: Mogulinker Technology Shenzhen Co Ltd
Priority date: 2022-05-20
Filing date: 2023-05-19
Publication date: 2023-12-27
Also published as: CN114635844B; CN114635844A

Abstract

Embodiments of the present disclosure provide methods, devices and medium for controlling an air compression station. A method comprises: acquiring an instantaneous flow of the air compression station based on sampling time; determining relationship between an instantaneous flow of the air compression station and time based on the sampling time and the acquired instantaneous flow; determining one or more index values of a flow of the air compressor station during one or more time windows based on the determined relationship; determining a period during which a flow of an air compression station remains stable based on the determined one or more index values; and during the determined period, adjusting a combination of air compressors in the air compression station such that an air production amount and an air consumption amount of air compressors in the air compression station are matched. With such a method, it is possible to realize "active control" of an air compression station so as to combine air compressors to supply air in an optimal manner based on characteristics of the demand for air to reduce pressure fluctuation of a pipe network so as to achieve the purpose of energy saving.

Description

FIELD

Embodiments of the present disclosure generally relate to control of an air compressor, and more specifically, to methods, computing devices, and computer storage medium for controlling an air compressor of an air compressor station.

BACKGROUND

An air compressor (referred to as "compressor"), the core device of a pneumatic system, is used to provide air source power. At present, air compressors have been widely used in various industries and become one of the core devices in related enterprises. Based on the demand for environmental protection and energy saving, how to minimize unnecessary waste in a control system of an air compressor, for example, ensuring stable inlet and outlet pressure, a stable flow in a compression process, and finally achieving the purpose of energy saving, is the key problem to be solved in a control system under the premise of meeting normal production requirements.
A conventional scheme for controlling an air compressor in an air compression station is, for example: output of the air compressor is controlled based on a PID control technique, i.e., achieving a stable operation state of the air compressor based on proportional, integral and differential of an error generated by comparing a real-time data acquisition value of the controlled air compressor with a target given value. Although the control scheme based on PID control technology boasts simple principle, strong robustness, etc., since the PID control technology calculates a deviation between the actual output and the target given value based on the feedback of the current output and then adjusts the deviation by a specific method, there is a certain delay to an adjustment command. Besides, the target given value of the air compressor is usually not constant, for example, varying according to change of working conditions. Therefore, it is easy to lead to large fluctuation in output pressure and a flow of the air compressor, failing to maintain a stable state.
In summary, the conventional scheme for controlling the air compressor station has a problem of passive control of the air compressor only according to the feedback of fluctuation in the pressure of a dynamic pipe network.

SUMMARY

With regard to the above-mentioned problems, the present disclosure provides methods, computing devices, and computer-readable storage medium for controlling an air compressor in an air compression station. With such a method, it is possible to realize "active control" of an air compression station so as to combine air compressors to supply air in an optimal manner based on characteristics of the demand for air to reduce fluctuation in the pressure of a pipe network so as to achieve the purpose of energy saving.
In a first aspect of the present disclosure, there is provided a method of controlling an air compressor in an air compression. The method comprises: acquiring an instantaneous flow of the air compression station based on sampling time; determining relationship between an instantaneous flow of the air compression station and time based on the sampling time and the acquired instantaneous flow; determining one or more index values of a flow of the air compressor station during one or more time windows based on the determined relationship; determining a period during which a flow of an air compression station remains stable based on the determined one or more index values; and during the determined period, adjusting a combination of air compressors in the air compression station such that an air production amount and an air consumption amount of air compressors in the air compression station are matched.
In a second aspect of the present disclosure, there is provided a computing device comprising: at least one processor and a memory communicatively coupled to the at least one processor, and the memory stores instructions which can be executed by at least one processor, and the instructions are executed by at least one processor to enable the at least one processor execute the method of the first aspect.
In a third aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium storing computer instructions, and the computer instructions enable the computer to execute the method of the first aspect.
In an embodiment, acquiring an instantaneous flow of the air compression station comprises: checking whether there are missing values of the acquired instantaneous flow of the air compression station; and in response to the presence of missing values of the acquired instantaneous flow, supplementing the missing values with the instantaneous flow acquired at last sampling time.
In an embodiment, determining relationship between an instantaneous flow of the air compression station and time comprises: determining an air consumption amount trend function representing an instantaneous flow of the air compression station versus time; determining a repetitive air consumption amount function representing an instantaneous flow of the air compression station versus time; determining a special date air consumption amount function representing an instantaneous flow of the air compression station versus time; and determining relationship between an instantaneous flow of the air compression station and time based on the determined air consumption amount trend function, the repetitive air consumption amount function, and the special date air consumption amount function.
In an embodiment, determining relationship between an instantaneous flow of the air compression station and time further comprises: determining a relationship coefficient and an error term representing relationship between the instantaneous flow of the air compression and time based on an optimization algorithm.
In an embodiment, determining one or more index values of the flow of the air compressor station during one or more time windows comprises determining an average value and a standard deviation value of the instantaneous flow of the air compressor station during the one or more time windows.
In an embodiment, determining a period during which a flow of an air compression station remains stable comprises: acquiring a threshold or a threshold range about remaining a flow of an air compression station stable; comparing the one or more index values to the threshold or the threshold range; and in response to the one or more index values being less than the threshold value or being within the threshold value range, determining a period during which a flow of an air compressor station remains stable.
In an embodiment, determining a period during which a flow of an air compressor station remains stable comprises: determining a first period during which a flow remains stable under repetitive air consumption, according to the determined repetitive air consumption amount function; determining a second period during which a flow remains stable on a special day based on the determined special date air consumption amount function; determining a third period during which a flow remains stable on a special day based on the determined air consumption amount trend function; and determining a periodically-smooth period having a smooth trend during which a flow of an air compression station remains stable based on the determined first period, the second period and the third period,
In an embodiment, adjusting a combination of air compressors in the air compression station such that an air production amount and an air consumption amount of air compressors in the air compression station are matched comprises: determining a flow level corresponding to the determined period based on the determined period; and determining a combination of air compressors according to a specific power, air production, stop time for no load for long time, and operation time of air compressors in the air compression station, based on the determined flow level, such that an air production amount and an air consumption amount of air compressors in the air compression station are matched.
It should be appreciated that this Summary is not intended to identify key features or essential features of the present disclosure, nor is it intended to be used to limit the scope of the present disclosure. Other features of the present disclosure will become readily apparent from the following description.

BRIEF DESCRIPTION OF THE DRAWINGS

Through the drawings with reference to the detailed depiction, the above and other objectives, features, and advantages of example embodiments of the present disclosure will become more apparent. In the drawings, the same reference numerals usually refer to the same or similar components.

FIG. 1 illustrates a system 100 for implementing a method of generating a data report in accordance with an embodiment of the present disclosure.
FIG. 2 illustrates a flow diagram of a method 200 of generating a data report in accordance with an embodiment of the present disclosure.
FIG. 3 illustrates a block diagram of an electronic device in accordance with an embodiment of the present disclosure.

DETAILED DESCRIPTION OF EMBODIMENTS

The following depiction of exemplary embodiments of the present disclosure, taken in conjunction with the drawings, includes various details of the embodiments of the present disclosure to facilitate understanding and should be construed as exemplary only. Accordingly, those skilled in the art would recognize that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Also, depiction of well-known functions and constructions are omitted from the following description for clarity and conciseness.
As used herein, the term "includes" and its variants are to be read as open-ended terms that mean "includes, but is not limited to." The term "or" is to be read as "and/or" unless the context clearly indicates otherwise. The term "based on" is to be read as "based at least in part on." The terms "one example embodiment" and "one embodiment" are to be read as "at least one example embodiment." The term "a further embodiment" is to be read as "at least a further embodiment." The terms "first", "second" and so on can refer to same or different objects. The following text also can include other explicit and implicit definitions.
As described above, a conventional scheme for controlling an air compressor in an air compression station is, for example: output of the air compressor is controlled based on a PID control technique, i.e., achieving a stable operation state of the air compressor based on proportional, integral and differential of an error generated by comparing a real-time data acquisition value of the controlled air compressor with a target given value. Although the control scheme based on PID control technology boasts simple principle, strong robustness, etc., since the PID control technology calculates a deviation between the actual output and the target given value based on the feedback of the current output and then adjusts the deviation by a specific method, there is a certain delay to an adjustment command. Besides, the target given value of the air compressor is usually not constant, for example, varying according to change of working conditions. Therefore, it is easy to lead to large fluctuation in output pressure and a flow of the air compressor, failing to maintain a stable state.
For example, there is generally a difference between an air production amount of an air compression station and demand for an air amount at an air consumption end, leading to fluctuation in the pressure of the pipe network. The reason for the fluctuation is that since the current control logic is mostly "passive control" and the actual air demand is unknown, the control is based on the feedback of pressure only. Once the air production amount is found to be greater than the demand for air amount, an air compressor is unloaded or turned off; once the demand for air amount is found to be greater than the air production amount, an air compressor is loaded or turned on.
To at least partially address one or more of the above problems and other potential problems, example embodiments of the present disclosure provide a scheme for controlling an air compressor in an air compression station. Specifically, the solution establishes a time series model of an air compression station by acquiring historical data of air consumption of the air compression station (namely, integral flow meter data) to find time characteristics of demand for air consumption of the air compression station and the corresponding smooth flow. An optimal combination of turned on air compressors is determined according to the time characteristics and the stable flow of the demand for air consumption as well as factors of the air compressors in the air compressor such as specific power, air production amount and operation time, thereby realizing the "active control" of the air compressors and to realize the energy-saving for air compressor operation.
FIG. 1 illustrates a system 100 for implementing a method of generating a data report in accordance with an embodiment of the present disclosure. As shown in FIG. 1, the system 100 includes a computing device 110, an air compressor data management device 130 and a network 140. The computing device 110 and the air compressor data management device 130 may perform data interaction through the network 140 (e.g., the Internet).
The air compressor data management device 130, which can store, for example, a plurality of different types of air compressor data, and acquire, for example, sensor data of a flow sensor for detecting an instantaneous flow of a parent pipe in an air compressor station. The flow sensor may collect the instantaneous flow of the parent pipe in the air compression station according to a set predetermined time interval, for example, 30 seconds, 1 minute, 5 minutes. As described above, although there is a difference between an actual air production amount and demand for an air amount of an air compression station, if a time window for observations is enlarged to half an hour or more, the actual air production amount and the air consumption amount of the air compression station at that time are almost identical. Thus, the instantaneous flow of the parent pipe in the air compression station may be approximately equal to the currently required air production amount. Based on this principle, the characteristics of demand for air consumption under corresponding working conditions can be automatically acquired from historical data on air consumption of the air compression station through the time series model, and the air compressors can be combined in the optimal way to supply air based on the characteristics of demand for air consumption to finally achieve the purpose of energy saving. The air compressor data management device 130 may further receive an air compressor adjustment instruction determined by the computing device 110 to adjust the air compressor of the air compressor station so that the air compressor of the air compressor station is maintained in an optimal operation state.
With regard to the computing device 110, for example, it is for receiving air compressor data from the air compressor data management device 130, for example, an instantaneous flow of the parent pipe of the air compressor station corresponding to the predetermined time interval. Thus, the air production amount of the air compressor can be predicted based on the acquired flow. The computing device 110 may have one or more processing units, including special purpose processing units such as GPUs, FPAir, and ASICs, and general purpose processing units such as CPUs. In addition, one or more virtual machines may also run on each the computing device 110. In some embodiments, the computing device 110 and the air compressor data management device 130 may be integrated together or provided separately from each other. In some embodiments, the computing device 110 includes, for example, an acquisition module 112, a shifting module 114, a decimation module 116, a determination module 118, and a mapping module 120.
The acquisition module 112 is configured to acquire an instantaneous flow of the air compression station based on sampling time.
A relationship determination module 114 is configured to determine relationship between the instantaneous flow of the air compression station and time based on the sampling time and the acquired instantaneous flow.
An index value determination module 116 is configured to determine one or more index values of a flow of the air compressor station during one or more time windows based on the determined relationship.
A period determination module 118 is configured to determine a period during which the flow of the air compression station remains stable based on the determined one or more index values.
An adjustment module 120 is configured to, during the determined period, adjust a combination of air compressors in the air compression station such that an air production amount and an air consumption amount of the air compressors in the air compression station are matched
FIG. 2 illustrates a flow diagram of a method 200 for generating a data report in accordance with an embodiment of the present disclosure. The method 200 may be performed by the computing device 110 as shown in FIG. 1, or may be performed at an electronic device 300 as shown in FIG. 3. It should be appreciated that method 200 may also include additional blocks not shown and/or may omit blocks shown, and the scope of the present disclosure is not limited in this respect.
In step 202, the computing device 110 may acquire the instantaneous flow of the air compression station based on the sampling time.
In one embodiment, the computing device 110 may receive data from a sensor for collecting the instantaneous flow of the parent pipe of the air compression station, and the data may be the instantaneous flow of the air compression station, i.e., the instantaneous flow of the parent pipe of the air compression station, acquired at a predetermined interval sampling time.
The sensor may collect the instantaneous flow of the parent pipe in the air compression station according to the set predetermined time interval, for example, 30 seconds, 1 minute, 5 minutes. As described above, although there is a difference between an actual air production amount and demand for an air amount of an air compression station, if a time window for observations is enlarged to half an hour or more, the actual air production amount and the air consumption amount of the air compression station at that time are almost identical. Thus, the instantaneous flow of the parent pipe in the air compression station may be approximately equal to the currently required air production amount. Based on this principle, the characteristics of demand for air consumption under corresponding working conditions can be automatically acquired from historical data on air consumption of the air compression station through the time series model, and the air compressors can be combined in the optimal way to supply air based on the characteristics of demand for air consumption to finally achieve the purpose of energy saving.
In one embodiment, the computing device 110 can also fill missing values of the collected instantaneous flow of the parent pipe of the air compression station. Firstly, the computing device 110 checks whether there is missing values of the acquired instantaneous flow of the air compression station.
In response to the absence of the missing values of the acquired instantaneous flow, the missing values are supplemented with the instantaneous flow acquired at a last sampling time. For example, when a plurality of instantaneous flows are continuously collected according to the sampling time, a part of the missing values for the instantaneous flow value may be lost for communication reasons. Thus, the missing data values corresponding to the last sample time may be filled with the last valid data on the instantaneous flow.
In step 204, the computing device 110 may determine a relationship between instantaneous flow and time for the air compression station based on the sampling time and the acquired instantaneous flow.
In one embodiment, computing device 110 may construct relationship of the instantaneous flow of the air compression station in a time series. The relationship considers principles of variation of a predicted value of the flow of the air compression station with time. In particular, the relationship may represent the principles of variation of the total instantaneous flow of the air compressor station with time so as to formulate the control logic of the air compressor according to these principles. Through analysis of historical data on the flow of the air compression station, the operating conditions of the air compression station can be generally divided into three cases: an overall air consumption trend, i.e., main air consumption under the corresponding working conditions, whether the flow increases slowly or maintains stable, etc.; repetitive air consumption, i.e., the flow is very similar in corresponding periods of each day, with a strong regular cycle; and air consumption under special conditions, i.e., occasional overtime, rest or holiday. Therefore, the relationship between the instantaneous flow of the air compression station and the time can be mainly expressed as three parts, namely, an air consumption amount trend function, a repetitive air consumption function and a special date air consumption amount function.
The computing device 110 may determine the air consumption amount trend function tendency(t) representing the instantaneous flow of the air compression station versus time, the a repetitive air consumption amount function period(t) representing the instantaneous flow of the air compression station versus time; a special date air consumption amount function special(t) representing the instantaneous flow of the air compression station versus time.
The computing device 110 may determine relationship between the instantaneous flow of the air compression station and time based on the determined air consumption amount trend function tendency(t), the repetitive air consumption amount function period(t), and the special date air consumption amount function special(t) Therefore, the relationship between the instantaneous flow of the air compression station and the time can be expressed according to Expression (1).
$flow (t) = tendency (t) + period (t) + special (t) + ε_{t}$
As described above, in the Expression (1), flow(t) represents the instantaneous flow of the air compression station, tendency(t) represents the air consumption amount trend function, period(t) represents the repetitive air consumption amount function, special(t) represents the special date air consumption amount function, and ∈_t represents an error term.
In one embodiment, the air amount trend function tendency(t) may be expressed according to Expression (2).
$tendency (t) = (k + a (t) δ) \cdot t + (m + a {(t)}^{T} γ)$
In the Expression (2), a parameter k represents an initial growth rate of the overall air consumption, which does not change with time t; a(t)represents an indicator function adjusting a growth rate of an overall air consumption trend; in one embodiment, since the overall air consumption trend does not necessarily maintain linearity over a long period, but can be considered to be linear within a certain period, the time can be fitted by segmenting: based on setting s abrupt points, $a_{j} (t) = {\begin{matrix} 1, if t \geq s_{j} \\ 0, otherwise \end{matrix}$
,wherein s_j represents time corresponding to the j^th abrupt point (j = 1, ...... S); δ represents an adjustment amount of the growth rate, and δ_j represents the adjustment amount of the growth rate at the j^th abrupt point, and δ_j can be expressed as follow Laplace(0,τ) distribution; m represents an offset parameter which can be determined in synchronization with the k and does not change with time; γ represents the adjustment amount of an offset amount, and γ_j can be expressed as being equal to -s_jδ_j.
In one embodiment, since the repetitive air consumption amount generally has a repetitive periodic principle, it can be represented by sine and cosine functions. Specifically, the repeatability air amount function period(t) may be expressed according to Expression (3).
$period (t) = \sum_{n = 1}^{N} (a_{n} \cos (\frac{2 πnt}{P}) + b_{n} \sin (\frac{2 πnt}{P}))$
In the Expression (3), the parameter P indicates a time length of the repetitive cycle, which may be set to 7, indicating a cycle of a week; the value of the parameter N is related to P, in general, N is equal to 10 when P is equal to 365.25, i.e., in a cycles of a year, and N is equal to 3 when P is equal to 7, i.e., in a cycle of a week.
In one embodiment, the repetitive air consumption amount function period(t) may be converted to a matrix form. Expressions (4) and (5) show the matrix form of the repetitive air amount function period(t).
$period (t) = X (t) β$

$X (t) = [\cos (\frac{2 π (1) t}{P}), \sin (\frac{2 π (1) t}{P}), \dots, \cos (\frac{2 π (n) t}{P}), \sin (\frac{2 π (n) t}{P})]$
In the Expressions (4) and (5), β is equal to [a ₁, b ₁,···,a_n,b_n ] ^T and β can be represented as follow Normal(0,σ ²) distribution.
In one embodiment, the special date air consumption amount function special(t) may be expressed in accordance with Expression (6) since air consumption in special cases is typically associated with holidays or occasional overtime.
$special (t) = Z (t) κ$
In the Expression (6), Z(t) = [1(t ∈ D ₁),···,1(t ∈ D_L )], D_i represents a set of all dates or dates corresponding to the holiday i with overtime; κ = [κ ₁,···,κ_L ] ^T and κ may be represented as follow Normal(0,ν² ) distribution.
Through the above Expressions (2)-(6), the computing device 110 can determine the overall air consumption amount trend function expression tendency(t), the repetitive air consumption function expression period(t), and the special date air consumption amount functions special(t), respectively, so as to acquire flow relationship of the air compression station.
In one embodiment, by taking the time and the flow sampled in step 202, the computing device 110 may solve for parameter terms not determined in the formula by algorithms such as quasi-Newton methods, L-BFGS optimization algorithms, etc. The total instantaneous flow of an original air compressor station is thus decomposed into the three parts defined above and the error term.
In one embodiment, the following actual data can be taken for the acquired flow and sampling time of the air compression station: in the overall air consumption trend function expression tendency(t), an abrupt point S = 25, k is in Normal(0,5), m is in Normal(0,5), and δ_j is in Laplace(0,0.05); in the repetitive air consumption amount function period(t), P = 7, N = 3, β is in Normal(0, 10); in the special date air consumption amount function special(t), D is a date corresponding to an weekend, a holiday and the overtime, and κ is in Normal(0,10).
Parameters in the Expression (2) can be solved by the L-BFGS optimization algorithm, and the relationship between the instantaneous flow of a decomposed air compression station and the time can be acquired.
In step 206, the computing device 110 may determine one or more index values of the flow of the air compressor station during one or more time windows based on the determined relationship.
In one embodiment, the computing device 110 may divide the flow according to the time window determined based on an actual situation. The time window may be larger than the sampling time interval. For example, the time window may be 5 minutes when the sampling time is 1 minute. In such a window, five sample values are included.
The computing device 110 may calculate statistics such as mean, variance, standard deviation, etc. of the flow within each time window.
In step 208, the computing device 110 may determine a period during which the flow of the air compression station remains stable based on the determined one or more index values.
In one embodiment, the computing device 110 may acquire a threshold or a threshold range about remaining the flow of the air compression station stable. The threshold or the threshold range may be set to a flow value or a flow value range. The computing device 110 may compare the one or more index values to the threshold or the threshold range and, in response to the one or more index values being less than the threshold value or being within the threshold value range, determine time window during which the flow of the air compressor station remains stable if the statistical data such as the mean, the variance, the standard deviation, etc. of the flow acquired in step 206 is below the threshold or between the threshold range. One or more such time windows for the flow function flow (t) may be combined into a period to during which the air pressure station flow remains stationary.
In a further embodiment, it is also possible to calculate whether the time window shows stable or not for the three functions of the repetitive air consumption amount function, the special date air consumption amount function, and the air consumption amount trend function.
For example, the computing device 110 may acquire the index value of the flow of the repetitive air consumption amount within the time window based on the determined repetitive air consumption amount function period(t). With the threshold or threshold range as described above, the computing device 110 may compare the one or more index values to the threshold or the threshold range and, in response to the one or more index values of the repetitive air consumption amount being less than the threshold value or being within the threshold value range, determine time window during which the flow of the repetitive air consumption of the air compressor station remains stable if the statistical data such as the mean, the variance, the standard deviation, etc. of the flow acquired in step 206 is below the threshold or between the threshold range. The time window may correspond to the period. One or more such time windows based on the repetitive air consumption amount function period(t) may be combined into a period t₁ during which the repetitive air consumption amount of the air pressure station remains stable. The period t₁ may be determined as a first period during which the flow remains stable under repetitive air consumption.
For example, the computing device 110 may acquire the index values of the flow of the special date air consumption amount within the time window based on the determined special date air consumption amount function special(t) With the threshold or threshold range as described above, the computing device 110 may compare the one or more index values to the threshold or the threshold range and, in response to the one or more index values of the special date air consumption amount being less than the threshold value or being within the threshold value range, determine time window during which the flow of the special date air consumption amount of the air compressor station remains stable if the statistical data such as the mean, the variance, the standard deviation, etc. of the flow acquired in step 206 is below the threshold or between the threshold range. The time window may correspond to the period. One or more such time windows based on the special date air consumption amount function special(t) may be combined into a period t₂ during which the air consumption amount on a special day of the air pressure station remains stable. The period t₂ may be determined as a second period during which the flow remains stable under special date air consumption amount.
For example, the computing device 110 may acquire the index values of the flow of the overall air consumption amount trend within the time window based on the determined overall air consumption amount expression tendency(t). With the threshold or threshold range as described above, The computing device 110 may compare the one or more index values to the threshold or the threshold range and, in response to the one or more index values of the special date air consumption amount being less than the threshold value or being within the threshold value range, determine time window during which the flow of the overall air consumption amount of the air compressor station remains stable if the statistical data such as the mean, the variance, the standard deviation, etc. of the flow acquired in step 206 is below the threshold or between the threshold range. The time window may correspond to the period. One or more such time windows based on the overall air consumption amount function tendency(t) may be combined into a period t₃ during which the overall air consumption amount of the air pressure station remains stable. The period t₃ may be determined as a third period during which the flow remains stable under overall air consumption.
Based on the determined first, second, and third periods t₁, t₂, and t₃, and the period t₀ acquired based on the function flow (t), the computing device 110 may determine an intersection of the four periods, i.e., a period during which the flow represented by the function flow (t), the function tendency(t), the function special(t), and the function period(t) remains stable (i.e., the period during which the value is less than the predetermined threshold or between the predetermined threshold range). The intersection period of the periods t₀, t₁, t₂, and t₃ may be determined as a periodically-smooth period having a smooth trend during which the flow of the air compression station remains stable.
In step 210, the computing device 110 may adjust the combination of the air compressors in the air compression station such that the air production amount and the air consumption amount of air compressors in the air compression station are matched.
In one embodiment, the computing device 110 may determine, on the basis of periodically-smooth period having a smooth trend during which the flow of the air compression station remains stable determined in step 208, the flow level corresponding to the period, i.e., the flow level of the parent pipe of the air compressor during such a period.
Based on the determined flow level, the computing device 110 may determine, on the basis of the specific power, the air production, the stop time for no load for long time, and the operation time of the air compressors of the air compression station, the combination of the air compressors, such that the air production amount and the air consumption amount of the air compressors in the air compression station are matched.
By using the above-mentioned technical means, the characteristics of demand for air consumption under corresponding working conditions can be automatically acquired from historical data on air consumption of the air compression station, and the air compressors can be combined in the optimal way to supply air based on the characteristics of demand for air consumption in advance to enable the air production amount to approach the demand for actual amount so as to achieve "active control". Based on the characteristics of demand for air, air compressors are combined in an optimal way to supply air to reduce fluctuation in the pressure of a pipe network so as to achieve the purpose of energy saving.
FIG. 3 illustrates a block diagram of an electronic device 300 in accordance with an embodiment of the present disclosure. For example, a host 110 shown in FIG. 1 can be implemented by the device 300. As shown, the device 300 includes a central process unit (CPU) 301, which can execute various suitable actions and processing based on the computer program instructions stored in the read-only memory (ROM) 302 or computer program instructions loaded in the random-access memory (RAM) 303 from a storage unit 308. The RAM 303 can also store all kinds of programs and data required by the operations of the device 300. CPU 301, ROM 302 and RAM 303 are connected to each other via a bus 304. The input/output (I/O) interface 305 is also connected to the bus 304.
A plurality of components in the device 300 is connected to the I/O interface 305, including: an input unit 306, such as keyboard, mouse and the like; an output unit 307, e.g., various kinds of display and loudspeakers etc.; a storage unit 308, such as magnetic disk and optical disk etc.; and a communication unit 309, such as network card, modem, wireless transceiver and the like. The communication unit 309 allows the device 300 to exchange information/data with other devices via the computer network, such as Internet, and/or various telecommunication networks.
The above described each procedure and processing, such as the method 200 can also be executed by the processing unit 301. For example, in some embodiments, the method 200 can be implemented as a computer software program tangibly included in the machine-readable medium, e.g., storage unit 308. In some embodiments, the computer program can be partially or fully loaded and/or mounted to the device 300 via ROM 302 and/or communication unit 309. When the computer program is loaded to RAM 303 and executed by the CPU 301, one or more steps of the above described method 200 can be implemented.
The present disclosure can be method, apparatus, system, electronic device and/or computer program product. The computer program product can include a computer-readable storage medium, on which the computer-readable program instructions for executing various aspects of the present disclosure are loaded.
The computer-readable storage medium can be a tangible apparatus that maintains and stores instructions utilized by the instruction executing apparatuses. The computer-readable storage medium can be, but not limited to, such as electrical storage device, magnetic storage device, optical storage device, electromagnetic storage device, semiconductor storage device or any appropriate combinations of the above. More concrete examples of the computer-readable storage medium (non-exhaustive list) include: portable computer disk, hard disk, random-access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash), static random-access memory (SRAM), portable compact disk read-only memory (CD-ROM), digital versatile disk (DVD), memory stick, floppy disk, mechanical coding devices, punched card stored with instructions thereon, or a projection in a slot, and any appropriate combinations of the above. The computer-readable storage medium utilized here is not interpreted as transient signals per se, such as radio waves or freely propagated electromagnetic waves, electromagnetic waves propagated via waveguide or other transmission media (such as optical pulses via fiber-optic cables), or electric signals propagated via electric wires.
The described computer-readable program instruction can be downloaded from the computer-readable storage medium to each computing/processing device, or to an external computer or external storage via Internet, local area network, wide area network and/or wireless network. The network can include copper-transmitted cable, optical fiber transmission, wireless transmission, router, firewall, switch, network gate computer and/or edge server. The network adapter card or network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium of each computing/processing device.
The computer program instructions for executing operations of the present disclosure can be assembly instructions, instructions of instruction set architecture (ISA), machine instructions, machine-related instructions, microcodes, firmware instructions, state setting data, or source codes or target codes written in any combinations of one or more programming languages, wherein the programming languages consist of object-oriented programming languages, e.g., Smalltalk, C++ and so on, and traditional procedural programming languages, such as "C" language or similar programming languages. The computer-readable program instructions can be implemented fully on the user computer, partially on the user computer, as an independent software package, partially on the user computer and partially on the remote computer, or completely on the remote computer or server. In the case where remote computer is involved, the remote computer can be connected to the user computer via any type of networks, including local area network (LAN) and wide area network (WAN), or to the external computer (e.g., connected via Internet using the Internet service provider). In some embodiments, state information of the computer-readable program instructions is used to customize an electronic circuit, e.g., programmable logic circuit, field programmable gate array (FPGA) or programmable logic array (PLA). The electronic circuit can execute computer-readable program instructions to implement various aspects of the present disclosure.
Various aspects of the present disclosure are described here with reference to flow chart and/or block diagram of method, apparatus (system) and computer program products according to embodiments of the present disclosure. It should be understood that each block of the flow chart and/or block diagram and the combination of various blocks in the flow chart and/or block diagram can be implemented by computer-readable program instructions.
The computer-readable program instructions can be provided to the processing unit of general-purpose computer, dedicated computer or other programmable data processing apparatuses to manufacture a machine, such that the instructions that, when executed by the processing unit of the computer or other programmable data processing apparatuses, generate an apparatus for implementing functions/actions stipulated in one or more blocks in the flow chart and/or block diagram. The computer-readable program instructions can also be stored in the computer-readable storage medium and cause the computer, programmable data processing apparatus and/or other devices to work in a particular manner, such that the computer-readable medium stored with instructions contains an article of manufacture, including instructions for implementing various aspects of the functions/actions stipulated in one or more blocks of the flow chart and/or block diagram.
The computer-readable program instructions can also be loaded into computer, other programmable data processing apparatuses or other devices, so as to execute a series of operation steps on the computer, other programmable data processing apparatuses or other devices to generate a computer-implemented procedure. Therefore, the instructions executed on the computer, other programmable data processing apparatuses or other devices implement functions/actions stipulated in one or more blocks of the flow chart and/or block diagram.
The flow chart and block diagram in the drawings illustrate system architecture, functions and operations that may be implemented by system, method and computer program product according to multiple implementations of the present disclosure. In this regard, each block in the flow chart or block diagram can represent a module, a part of program segment or code, wherein the module and the part of program segment or code include one or more executable instructions for performing stipulated logic functions. In some alternative implementations, it should be noted that the functions indicated in the block can also take place in an order different from the one indicated in the drawings. For example, two successive blocks can be in fact executed in parallel or sometimes in a reverse order dependent on the involved functions. It should also be noted that each block in the block diagram and/or flow chart and combinations of the blocks in the block diagram and/or flow chart can be implemented by a hardware-based system exclusive for executing stipulated functions or actions, or by a combination of dedicated hardware and computer instructions.
Various implementations of the present disclosure have been described above and the above description is only exemplary rather than exhaustive and is not limited to the implementations of the present disclosure. Many modifications and alterations, without deviating from the scope and spirit of the explained various implementations, are obvious for those skilled in the art. The selection of terms in the text aims to best explain principles and actual applications of each implementation and technical improvements made in the market by each embodiment, or enable other ordinary skilled in the art to understand implementations of the present disclosure.

Claims

A method of controlling an air compressor in an air compression station, comprising:
acquiring an instantaneous flow of the air compression station based on sampling time;

determining relationship between an instantaneous flow of the air compression station and time based on the sampling time and the acquired instantaneous flow;

determining one or more index values of a flow of the air compressor station during one or more time windows based on the determined relationship;

determining a period during which a flow of the air compression station remains stable based on the determined one or more index values; and

during the determined period, adjusting a combination of air compressors in the air compression station such that an air production amount and an air consumption amount of air compressors in the air compression station are matched.
The method of claim 1, acquiring an instantaneous flow of the air compression station comprising:
checking whether there are missing values of the acquired instantaneous flow of the air compression station; and

in response to the presence of missing values of the acquired instantaneous flow, supplementing the missing values with the instantaneous flow acquired at last sampling time.
The method of claim 1, determining relationship between an instantaneous flow of the air compression station and time comprising:
determining an air consumption amount trend function representing an instantaneous flow of the air compression station versus time;

determining a repetitive air consumption amount function representing an instantaneous flow of the air compression station versus time;

determining a special date air consumption amount function representing an instantaneous flow of the air compression station versus time; and

determining relationship between an instantaneous flow of the air compression station and time based on the determined air consumption amount trend function, the repetitive air consumption amount function, and the special date air consumption amount function.
The method of claim 3, determining relationship between an instantaneous flow of the air compression station and time further comprising:
determining a relationship coefficient and an error term representing relationship between the instantaneous flow of the air compression and time based on an optimization algorithm.
The method of claim 1, determining one or more index values of the flow of the air compressor station during one or more time windows comprising:
determining an average value and a standard deviation value of the instantaneous flow of the air compressor station during the one or more time windows.
The method of claim 3, determining a period during which a flow of an air compression station remains stable comprising:
acquiring a threshold or a threshold range about remaining a flow of an air compression station stable;

comparing the one or more index values to the threshold or the threshold range; and

in response to the one or more index values being less than the threshold value or being within the threshold value range, determining a period during which a flow of an air compressor station remains stable.
The method according to claim 3 or 6, determining a period during which a flow of an air compressor station remains stable comprising:
determining a first period during which a flow remains stable under repetitive air consumption, according to the determined repetitive air consumption amount function;

determining a second period during which a flow remains stable on a special day based on the determined special date air consumption amount function;

determining a third period during which a flow remains stable on a special day based on the determined air consumption amount trend function; and

determining a periodically-smooth period having a smooth trend during which a flow of an air compression station remains stable based on the determined first period, the second period and the third period.
The method of claim 1, adjusting a combination of air compressors in the air compression station such that an air production amount and an air consumption amount of air compressors in the air compression station are matched comprising:
determining a flow level corresponding to the determined period based on the determined period; and

determining a combination of air compressors according to a specific power, air production, stop time for no load for long time, and operation time of air compressors in the air compression station, based on the determined flow level, such that an air production amount and an air consumption amount of air compressors in the air compression station are matched.
A computing device comprising:
at least one processor; and

a memory communicatively coupled to the at least one processor;

the memory storing instructions which, executed by the at least one processor, enables the at least one processor to execute the method of any of claims 1-8.
A non-transitory computer-readable storage medium storing computer instructions for enabling the computer to execute the method of any of claims 1-8.