CN115225660B - Method, system, equipment and medium for processing communication data in energy storage system - Google Patents
Method, system, equipment and medium for processing communication data in energy storage system Download PDFInfo
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Abstract
The invention discloses a method, a system, equipment and a medium for processing communication data in an energy storage system. The processing method comprises the following steps: acquiring target full data at the current sampling moment; calculating a data difference value between a current sampling value corresponding to each data point in the target full data and a historical data uploading value corresponding to the same data point at the previous sampling moment; judging whether the data difference exceeds a target sensitivity threshold; if the data point is not exceeded, determining that the data point is not subjected to uplink data transmission. According to the invention, through analyzing the target full data in real time, whether each data point accords with a preset uploading condition is judged; the target sensitivity threshold is adaptively adjusted, the effectiveness and the accuracy based on the preset uploading condition are improved, the problem of frequent shifting uploading of invalid data points is solved, the occupation of communication bandwidth is reduced, and the communication data flow is saved.
Description
Technical Field
The present invention relates to the field of energy storage technologies, and in particular, to a method, a system, an apparatus, and a medium for processing communication data in an energy storage system.
Background
The energy storage system comprises a battery system, a battery management system, an environment monitoring system, an on-site control system and other devices, and has the characteristics of high integration level, good safety, strong environmental adaptability and the like. Therefore, the energy storage system is increasingly widely applied in the scenes of a power source side, a power grid side, a user side and the like.
The battery system is formed by a plurality of single batteries in series and parallel, the energy storage system comprises a plurality of real-time data such as single battery voltage, single battery temperature, single battery SOC (State of Charge), single battery SOH (State of Health), and the like, and the plurality of data can change in real time along with the reasons such as system operation and acquisition precision.
The data communication uploading mode generally comprises timing polling uploading and shifting active uploading, and under the normal condition of the timing polling mode, a host can send a communication protocol request instruction according to a certain time period, and a slave responds to uploading according to the communication protocol request, the timing polling mode is simple and reliable in communication, but low in instantaneity, low in communication efficiency and high in communication bandwidth requirement. The shift active uploading mode is to actively upload data to the host through the protocol when the slave data is changed. When the energy storage system stands still, a large amount of single battery information is basically unchanged, and the energy storage system preferably adopts a shifting active uploading mode for communication.
However, in the conventional communication method for active shift-up, invalid data points are frequently shifted up due to sampling errors and random interference.
Disclosure of Invention
The invention aims to overcome the defect that in the prior art, invalid data points are frequently shifted and sent due to sampling errors and random interference in a shifting active sending mode, and provides a processing method, a processing system, processing equipment and a processing medium of communication data in an energy storage system.
The invention solves the technical problems by the following technical scheme:
in a first aspect, the present invention provides a method for processing communication data in an energy storage system, where the processing method includes:
acquiring target full data at the current sampling moment; the target full-quantity data is running state data used for representing the energy storage system;
calculating a data difference value between a current sampling value corresponding to each data point in the target full data and a historical data uploading value corresponding to the same data point at the last sampling moment;
judging whether the data difference exceeds a target sensitivity threshold; each of the data points corresponds to one of the target sensitivity thresholds;
if the data point is not exceeded, determining that uplink data transmission is not performed on the data point.
Preferably, the step of determining uplink data transmission for the data point further includes:
and for the same data point, replacing and updating the corresponding historical data uploading value by using the current sampling value.
Preferably, the processing method further comprises:
determining the data deflection precision and the data partition value corresponding to each data point;
calculating to obtain an initial sensitivity threshold according to the historical data uploading value, the data displacement precision and the data partition value;
the target sensitivity threshold is determined based on the initial sensitivity threshold and a set sensitivity upper threshold.
Preferably, the step of determining the target sensitivity threshold based on the initial sensitivity threshold and a set sensitivity upper threshold includes:
if the initial sensitivity threshold is greater than the sensitivity upper threshold, taking the sensitivity upper threshold as the target sensitivity threshold;
if the initial sensitivity threshold is less than the sensitivity upper threshold, taking the initial sensitivity threshold as the target sensitivity threshold;
and/or the number of the groups of groups,
and if the initial sensitivity threshold is equal to the sensitivity upper limit threshold, taking the initial sensitivity threshold or the sensitivity upper limit threshold as the target sensitivity threshold.
Preferably, the formula for calculating the initial sensitivity threshold is as follows:
Δ＝|Xold*m/(floor(|Xold|/k)+1)|
wherein Δ represents the initial sensitivity threshold, xold represents the historical data upload value, m represents the data shift precision, k represents the data partition value, floor represents a downward rounding function.
In a second aspect, the present invention provides a processing system for communication data in an energy storage system, where the processing system includes an acquisition device and a controller, where the acquisition device includes an acquisition module, a first calculation module, and a judgment module;
the acquisition module is used for acquiring target full-quantity data at the current sampling moment; the target full-quantity data is running state data used for representing the energy storage system;
the first calculation module is used for calculating a data difference value between a current sampling value corresponding to each data point in the target full-volume data and a historical data uploading value corresponding to the same data point at the last sampling moment;
the judging module is used for judging whether the data difference value exceeds a target sensitivity threshold; each of the data points corresponds to one of the target sensitivity thresholds;
the controller is configured to determine to transmit uplink data to the data point when the data difference exceeds the target sensitivity threshold, and determine not to transmit uplink data to the data point when the data difference does not exceed the target sensitivity threshold.
Preferably, the controller is further configured to replace and update, for the same data point, the corresponding historical data upload value with the current sampling value.
Preferably, the acquisition device further comprises a second calculation module;
the second calculation module is used for determining the data deflection precision and the data partition value corresponding to each data point; calculating an initial sensitivity threshold according to the historical data uploading value, the data deflection precision and the data partition value; the target sensitivity threshold is determined based on the initial sensitivity threshold and a set sensitivity upper threshold.
Preferably, the second calculation module is further configured to take the sensitivity upper threshold as the target sensitivity threshold if the initial sensitivity threshold is greater than the sensitivity upper threshold; if the initial sensitivity threshold is less than the sensitivity upper threshold, taking the initial sensitivity threshold as the target sensitivity threshold; and if the initial sensitivity threshold is equal to the sensitivity upper limit threshold, taking the initial sensitivity threshold or the sensitivity upper limit threshold as the target sensitivity threshold.
Preferably, the formula for calculating the initial sensitivity threshold is as follows:
Δ＝|Xold*m/(floor(|Xold|/k)+1)|
wherein Δ represents the initial sensitivity threshold, xold represents the historical data upload value, m represents the data shift precision, k represents the data partition value, floor represents a downward rounding function.
Preferably, the acquisition module comprises a plurality of data collectors which are in communication connection with the controller, and the data collectors comprise at least one of a battery manager, an energy storage converter and an environment monitor.
In a third aspect, the present invention provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing a method of processing communication data in an energy storage system according to any one of the first aspects when the computer program is executed.
In a fourth aspect, the present invention provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a method for processing communication data in an energy storage system according to any of the first aspects.
The invention has the positive progress effects that: provided are a method, a system, a device and a medium for processing communication data in an energy storage system, wherein the processing method comprises the following steps: acquiring target full data at the current sampling moment; calculating a data difference value between a current sampling value corresponding to each data point in the target full data and a historical data uploading value corresponding to the same data point at the previous sampling moment; judging whether the data difference exceeds a target sensitivity threshold; if the data point is not exceeded, determining that the data point is not subjected to uplink data transmission. According to the invention, through analyzing the target full data in real time, whether each data point accords with a preset uploading condition is judged; the target sensitivity threshold is adaptively adjusted, the effectiveness and the accuracy based on the preset uploading condition are improved, the problem of frequent shifting uploading of invalid data points is solved, the occupation of communication bandwidth is reduced, and the communication data flow is saved.
Drawings
Fig. 1 is a flow chart of a method for processing communication data in an energy storage system according to embodiment 1 of the present invention.
Fig. 2 is a flow chart of a method for processing communication data in the energy storage system according to embodiment 2 of the present invention.
Fig. 3 is a schematic block diagram of a processing system for communication data in the energy storage system according to embodiment 3 of the present invention.
Fig. 4 is a schematic block diagram of a processing system for communication data in the energy storage system according to embodiment 4 of the present invention.
Fig. 5 is a schematic diagram of a system for processing communication data in the energy storage system according to embodiment 4 of the present invention.
Fig. 6 is a schematic hardware structure of an electronic device according to embodiment 5 of the present invention.
Detailed Description
The invention is further illustrated by means of the following examples, which are not intended to limit the scope of the invention.
Example 1
The embodiment provides a method for processing communication data in an energy storage system, as shown in fig. 1, the method includes:
s1, acquiring target full data at the current sampling moment; the target full-scale data is operational state data used for representing the energy storage system.
S2, calculating a data difference value between a current sampling value corresponding to each data point in the target full data and a historical data uploading value corresponding to the same data point at the last sampling moment.
S3, judging whether the data difference exceeds a target sensitivity threshold; each data point corresponds to one of the target sensitivity thresholds; if yes, step S41 is executed, and if no, step S42 is executed.
S41, determining to send uplink data to the data points, and continuing to execute the step S5.
S42, determining that uplink data transmission is not performed on the data points.
S5, for the same data point, replacing and updating the corresponding historical data uploading value by adopting the current sampling value.
For the above step S1, the energy storage system includes a battery system, a battery management system, an environment monitoring system, an in-situ control system, and other devices. And acquiring the running state data of the energy storage system at the current sampling moment, wherein the running state data comprises battery system running data, battery state data, battery cell voltage data, battery temperature data, energy storage converter running data, power environment data and the like.
For the above step S2, taking 1 second as an example of the sampling time, each data point a in the target full-volume data is sequentially calculated N (N is more than or equal to 1 and N is an integer) corresponding to the current sampling value M N The same data point A as the sampling time of the last second N Corresponding historical data uploading value P N Data difference between |M N -P N | a. The invention relates to a method for producing a fibre-reinforced plastic composite. If the target total data comprises 100 data points, 100 current sampling values and 100 historical data uploading values exist, the data difference between the current sampling values and the historical data uploading values can be calculated step by step according to the type of the data points, or the data difference between the current sampling values and the historical data uploading values can be calculated step by step according to the sequence of data point acquisition.
For the above step S3, the target sensitivity threshold may be preset and fixed, or may be calculated by an algorithm and may be adjusted. Each data point may correspond to the same target sensitivity threshold, or each data point may correspond to a different target sensitivity threshold, and the embodiment is not particularly limited. This approach changes the sensitivity of the data change for each data point by dynamically adjusting the target sensitivity threshold. When the data point exceeds the target sensitivity threshold, indicating that the data point meets the conditions for uploading the data, the data point is uploaded to a remote monitoring platform in communication with the energy storage system. When the data point does not exceed the target sensitivity threshold, indicating that the data point does not meet the conditions for uploading the data, the data point is not uploaded to a remote monitoring platform in communication with the energy storage system.
For the step S5, if the data point is sent to the remote monitoring platform communicatively connected to the energy storage system, the current sampling value M is obtained N Replacing with historical data uploading value P N And stored in a database of settings. It will be appreciated that the current sample value M N The historical data uploading value of the data point at the next sampling moment is used for calculating the data difference value, so that the real-time adjustment of the acquisition precision of each data point is guaranteed, the effectiveness of the uploaded data point is improved, and the communication efficiency of the active uploading communication mode is improved.
In this embodiment, a method for processing communication data in an energy storage system is provided, and a data difference value between a current sampling value corresponding to each data point in target full-volume data and a historical data uploading value corresponding to the same data point at the previous sampling time is calculated; if the data difference exceeds the target sensitivity threshold, determining that uplink data transmission is performed on the data point, and if the data difference does not exceed the target sensitivity threshold, determining that uplink data transmission is not performed on the data point. According to the invention, the target full data is analyzed in real time to judge whether each data point meets the uploading condition, so that the problem of frequent shifting uploading of invalid data points is solved, the occupation of communication bandwidth is reduced, and the communication data flow is saved.
Example 2
On the basis of embodiment 1, this embodiment provides a method for processing communication data in an energy storage system, as shown in fig. 2, which is improved compared with embodiment 1, and the method further includes the following steps:
s21, determining the data deflection precision and the data partition value corresponding to each data point.
S22, calculating to obtain an initial sensitivity threshold according to the historical data uploading value, the data deflection precision and the data partition value.
S23, determining a target sensitivity threshold based on the initial sensitivity threshold and the set sensitivity upper limit threshold.
For the step S21, the data shift precision represents the default maximum relative variation of the historical data uploading value corresponding to each data point, and the data partition value represents the historical data uploading value P corresponding to each data point N And dividing the intervals, wherein the maximum relative change amount of the historical data uploading values of the same interval is the same. The same data shift accuracy and data partition value may be set for each data point, or different data shift accuracy and data partition value may be set for different data points. The method can automatically update the data deflection precision and the data partition value, thereby adjusting the initial sensitivity threshold value corresponding to each data point, and further improving the effectiveness of data point judgment.
For the above steps S22-S23, the value P is uploaded based on the history data N The initial sensitivity threshold is calculated by the data displacement precision and the data partition value through a data operation mode, and the operation mode can be set according to actual conditions and is not particularly limited. The same upper sensitivity threshold may be set for each data point, different upper sensitivity thresholds may be set for different data points, or the same upper sensitivity threshold may be set for the same type of data point. For example, the upper limit threshold of sensitivity corresponding to all data points belonging to the battery system operation data is D1, the upper limit threshold of sensitivity corresponding to all data points belonging to the battery state data is D2, and the upper limit threshold of sensitivity corresponding to all data points belonging to the battery temperature data is D3.
And comparing the initial sensitivity threshold with the sensitivity upper limit threshold, and judging one of the initial sensitivity threshold and the set sensitivity upper limit threshold as a target sensitivity threshold according to the comparison result. By setting a target sensitivity threshold, the amplitude limiting adjustment of the sensitive interval is realized, and the displacement precision of the data points is improved.
In one possible implementation, in step S22, the formula corresponding to the initial sensitivity threshold is calculated as follows:
Δ＝|Xold*m/(floor(|Xold|/k)+1)|
delta represents an initial sensitivity threshold, xold represents a history data up-feed value, m represents data shift accuracy, k represents a data partition value, and floor represents a down-rounding function.
The above formula analysis shows that the initial sensitivity threshold is automatically updated according to the magnitude of the historical data upload value corresponding to each data point. The larger the historical data upload value within the same interval, the larger the initial sensitivity threshold corresponding to the data point, indicating that the data point is less sensitive to changes. The difference in the historical data upload values for the two data points is an integer multiple of k, indicating that the initial sensitivity thresholds for the two data points are the same.
In one embodiment, step S23 specifically includes:
and if the initial sensitivity threshold is greater than the sensitivity upper threshold, taking the sensitivity upper threshold as a target sensitivity threshold.
And if the initial sensitivity threshold is smaller than the sensitivity upper limit threshold, taking the initial sensitivity threshold as a target sensitivity threshold.
And if the initial sensitivity threshold is equal to the sensitivity upper limit threshold, taking the initial sensitivity threshold or the sensitivity upper limit threshold as a target sensitivity threshold.
For example, a data point A 1 The initial sensitivity threshold of (a) is delta 1 The same data point A 1 The sensitivity upper threshold of (a) is delta max By |delta 1 Determining the magnitude of the initial sensitivity threshold and the upper sensitivity threshold, or using Δmax%The magnitudes of the initial sensitivity threshold and the sensitivity upper threshold are determined, and the minimum value of the two is taken as the target sensitivity threshold. If the initial sensitivity threshold is equal to the upper sensitivity threshold, either one of the two is used as the target sensitivity threshold.
In this embodiment, a method for processing communication data in an energy storage system is provided, where a target sensitivity threshold corresponding to each data point in target full data is dynamically adjusted, and then a data difference value between a current sampling value corresponding to each data point and a historical data uploading value corresponding to the same data point at the previous sampling time and the calculated target sensitivity threshold are determined, so as to determine whether the data point is uploaded. According to the invention, the target sensitivity threshold is adaptively adjusted, so that the effectiveness and accuracy of judging whether to upload each data point are improved, the data points which do not meet uploading conditions are removed in time, the occupation of communication bandwidth is reduced, the communication data flow is saved, and the problem of frequent dislocation uploading of invalid data points is solved.
Example 3
The present embodiment provides a processing system for communication data in an energy storage system, as shown in fig. 3, where the processing system includes an acquisition device 100 and a controller 200, and the acquisition device 100 includes an acquisition module 110, a first calculation module 120 and a determination module 130.
The acquiring module 110 is configured to acquire target full-scale data at a current sampling time; the target full-scale data is operational state data used for representing the energy storage system.
The first calculating module 120 is configured to calculate a data difference between a current sampling value corresponding to each data point in the target full-scale data and a historical data uploading value corresponding to the same data point at a previous sampling time.
A judging module 130 for judging whether the data difference exceeds a target sensitivity threshold; each data point corresponds to a target sensitivity threshold.
And a controller 200 for determining to transmit uplink data to the data point when the data difference exceeds the target sensitivity threshold, and determining not to transmit uplink data to the data point when the data difference does not exceed the target sensitivity threshold.
The energy storage system comprises a battery system, a battery management system, an environment monitoring system, an in-situ control system and the like. The acquisition module 110 acquires operation state data of the energy storage system at the current sampling time, where the operation state data includes battery system operation data, battery state data, battery cell voltage data, battery temperature data, energy storage converter operation data, power environment data, and the like.
Taking 1 second as an example of sampling time, the first calculation module 120 calculates each data point in the target full-scale data in turnA N (N is more than or equal to 1 and N is an integer) corresponding to the current sampling value M N The same data point A as the sampling time of the last second N Corresponding historical data uploading value P N Data difference between |M N -P N | a. The invention relates to a method for producing a fibre-reinforced plastic composite. If the target total data comprises 100 data points, 100 current sampling values and 100 historical data uploading values exist, the data difference between the current sampling values and the historical data uploading values can be calculated step by step according to the type of the data points, or the data difference between the current sampling values and the historical data uploading values can be calculated step by step according to the sequence of data point acquisition.
The target sensitivity threshold can be preset and fixed, or can be calculated by an algorithm and can be adjusted. Each data point may correspond to the same target sensitivity threshold, or each data point may correspond to a different target sensitivity threshold, and the embodiment is not particularly limited. This approach changes the sensitivity of the data change for each data point by dynamically adjusting the target sensitivity threshold. The determination module 130, upon determining that the data point exceeds the target sensitivity threshold, indicates that the data point meets the conditions for uploading the data, and the controller 200 uploads the data point to a remote monitoring platform in communication with the energy storage system. The determination module 130 indicates that the data point does not meet the conditions for uploading data when it is determined that the data point does not exceed the target sensitivity threshold, and the controller 200 does not upload the data point to a remote monitoring platform in communication with the energy storage system.
The controller 200 is further configured to replace and update the corresponding historical data uploading value with the current sampling value for the same data point.
If the data point is sent to the remote monitoring platform in communication with the energy storage system, the controller 200 also sends the current sampling value M N Replacing with historical data uploading value P N And stored in a database of settings. It will be appreciated that the current sample value M N The historical data of the data point at the next sampling moment is uploaded to be used as a calculation parameter of the data difference value, so that the acquisition precision of each data point is ensured to be realizedAnd the time adjustment improves the effectiveness of the data points sent up and improves the communication efficiency of the active position-changing sending-up communication mode.
In this embodiment, a processing system for communication data in an energy storage system is provided, where a first calculation module calculates a data difference between a current sampling value corresponding to each data point in target full data and a historical data uploading value corresponding to the same data point at a previous sampling time; if the data difference exceeds the target sensitivity threshold, the controller determines that uplink data transmission is performed on the data point, and if the data difference does not exceed the target sensitivity threshold, the controller determines that uplink data transmission is not performed on the data point. According to the invention, the target full data is analyzed in real time to judge whether each data point meets the uploading condition, so that the problem of frequent shifting uploading of invalid data points is solved, the occupation of communication bandwidth is reduced, and the communication data flow is saved.
Example 4
On the basis of embodiment 3, this embodiment provides a processing system for communication data in an energy storage system, as shown in fig. 4, and compared with embodiment 3, the collecting device 100 further includes a second calculating module 121.
A second calculation module 121, configured to determine a data displacement precision and a data partition value corresponding to each data point; calculating an initial sensitivity threshold according to the historical data uploading value, the data deflection precision and the data partition value; a target sensitivity threshold is determined based on the initial sensitivity threshold and the set sensitivity upper threshold.
The data shift precision represents the default maximum relative variation of the historical data uploading value corresponding to each data point, and the data partition value represents the historical data uploading value P corresponding to each data point N And dividing the intervals, wherein the maximum relative change amount of the historical data uploading values of the same interval is the same. The second calculation module 121 may set the same data shift precision and data partition value for each data point, or may set different data shift precision and data partition value for different data points. The method can automatically update the data deflection precision and the data partition value, thereby adjusting the initial sensitivity threshold value corresponding to each data point.
The second calculation module 121Uploading a value P based on historical data N The initial sensitivity threshold is calculated by the data displacement precision and the data partition value through a data operation mode, and the operation mode can be set according to actual conditions and is not particularly limited. The same upper sensitivity threshold may be set for each data point, different upper sensitivity thresholds may be set for different data points, or the same upper sensitivity threshold may be set for the same type of data point. For example, the upper limit threshold of sensitivity corresponding to all data points belonging to the battery system operation data is D1, the upper limit threshold of sensitivity corresponding to all data points belonging to the battery state data is D2, and the upper limit threshold of sensitivity corresponding to all data points belonging to the battery temperature data is D3.
And comparing the initial sensitivity threshold with the sensitivity upper limit threshold, and judging one of the initial sensitivity threshold and the set sensitivity upper limit threshold as a target sensitivity threshold according to the comparison result.
In one possible implementation, the formula for calculating the initial sensitivity threshold is as follows:
Δ＝|Xold*m/(floor(|Xold|/k)+1)|
delta represents an initial sensitivity threshold, xold represents a history data up-feed value, m represents data shift accuracy, k represents a data partition value, and floor represents a down-rounding function.
The above formula analysis shows that the initial sensitivity threshold is automatically updated according to the magnitude of the historical data upload value corresponding to each data point. The larger the historical data upload value within the same interval, the larger the initial sensitivity threshold corresponding to the data point, indicating that the data point is less sensitive to changes. The difference in the historical data upload values for the two data points is an integer multiple of k, indicating that the initial sensitivity thresholds for the two data points are the same.
The second calculation module 121 is further configured to set the sensitivity upper threshold as the target sensitivity threshold if the initial sensitivity threshold is greater than the sensitivity upper threshold; if the initial sensitivity threshold is smaller than the sensitivity upper limit threshold, taking the initial sensitivity threshold as a target sensitivity threshold; and if the initial sensitivity threshold is equal to the sensitivity upper limit threshold, taking the initial sensitivity threshold or the sensitivity upper limit threshold as a target sensitivity threshold.
For example, a data point A 1 The initial sensitivity threshold of (a) is delta 1 The same data point A 1 The sensitivity upper threshold of (a) is delta max By |delta 1 Determining the magnitude of the initial sensitivity threshold and the upper sensitivity threshold, or using Δmax%The magnitudes of the initial sensitivity threshold and the sensitivity upper threshold are determined, and the minimum value of the two is taken as the target sensitivity threshold. If the initial sensitivity threshold is equal to the upper sensitivity threshold, either one of the two is used as the target sensitivity threshold.
In one possible implementation, the acquisition module 110 includes a number of data collectors communicatively coupled to the controller 200, including but not limited to a battery manager, an energy storage converter, and an environmental monitor.
Specifically, as shown in fig. 5, the remote monitoring platform is communicatively connected to an in-situ control system, which has a controller 200 installed therein, and the in-situ control system is communicatively connected to the battery manager, the energy storage converter, and the environmental monitor. The battery manager collects battery system operation data, the energy storage converter collects power grid information data and operation data of equipment for storing energy, and the environment monitor collects temperature, humidity data and power environment data of the energy storage system. After each data collector sends the collected operation state data representing the energy storage system to the on-site control system, after the collected target full-volume data is analyzed and processed by the controller 200, part or all data points in the target full-volume data meeting the uploading condition are sent to the remote monitoring platform, and part of data points in the target full-volume data not meeting the uploading condition maintain the corresponding historical data uploading value unchanged.
In this embodiment, a processing system for communication data in an energy storage system is provided, where a second calculation module dynamically adjusts a target sensitivity threshold corresponding to each data point in target full data, and a judgment module judges a data difference value between a current sampling value corresponding to each data point and a historical data uploading value corresponding to the same data point at a previous sampling time and the calculated target sensitivity threshold, so as to determine whether the data point is uploaded. According to the invention, the target sensitivity threshold is adaptively adjusted, so that the effectiveness and accuracy of judging whether to upload each data point are improved, the data points which do not meet uploading conditions are removed in time, the occupation of communication bandwidth is reduced, the communication data flow is saved, and the problem of frequent dislocation uploading of invalid data points is solved.
Example 5
Fig. 6 is a schematic structural diagram of an electronic device according to the present embodiment. The electronic device includes a memory, a processor, and a computer program stored in the memory and capable of running on the processor, where the processor executes the program to implement the method for processing communication data in the energy storage system of embodiment 1 or embodiment 2, and the electronic device 60 shown in fig. 6 is merely an example, and should not impose any limitation on the functions and the application scope of the embodiments of the present invention.
The electronic device 60 may be in the form of a general purpose computing device, which may be a server device, for example. Components of electronic device 60 may include, but are not limited to: the at least one processor 61, the at least one memory 62, a bus 63 connecting the different system components, including the memory 62 and the processor 61.
The bus 63 includes a data bus, an address bus, and a control bus.
Memory 62 may include volatile memory such as Random Access Memory (RAM) 621 and/or cache memory 622, and may further include Read Only Memory (ROM) 6 23.
Memory 62 may also include a program/utility 625 having a set (at least one) of program modules 324, such program modules 624 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment.
The processor 61 executes various functional applications and data processing such as the processing method of communication data in the energy storage system of embodiment 1 or embodiment 2 of the present invention by running the computer program stored in the memory 62.
The electronic device 60 may also communicate with one or more external devices 64 (e.g., keyboard, pointing device, etc.). Such communication may occur through an input/output (I/O) interface 65. Also, the model-generating device 60 may also communicate with one or more networks, such as a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the internet, through a network adapter 66. As shown, the network adapter 66 communicates with other modules of the model-generating device 60 via the bus 63. It should be appreciated that although not shown in the figures, other hardware and/or software modules may be used in connection with the model-generating device 60, including, but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (disk array) systems, tape drives, data backup storage systems, and the like.
It should be noted that although several units/modules or sub-units/modules of an electronic device are mentioned in the above detailed description, such a division is merely exemplary and not mandatory. Indeed, the features and functionality of two or more units/modules described above may be embodied in one unit/module in accordance with embodiments of the present invention. Conversely, the features and functions of one unit/module described above may be further divided into ones that are embodied by a plurality of units/modules.
Example 6
The present embodiment provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the method for processing communication data in the energy storage system of embodiment 1 or embodiment 2.
More specifically, among others, readable storage media may be employed including, but not limited to: portable disk, hard disk, random access memory, read only memory, erasable programmable read only memory, optical storage device, magnetic storage device, or any suitable combination of the foregoing.
In a possible embodiment, the invention may also be implemented in the form of a program product comprising program code for causing a terminal device to carry out the steps of the method of carrying out the communication data processing method in the energy storage system of embodiment 1 or embodiment 2 when said program product is run on the terminal device.
Wherein the program code for carrying out the invention may be written in any combination of one or more programming languages, which program code may execute entirely on the user device, partly on the user device, as a stand-alone software package, partly on the user device and partly on the remote device or entirely on the remote device.
While specific embodiments of the invention have been described above, it will be appreciated by those skilled in the art that this is by way of example only, and the scope of the invention is defined by the appended claims. Various changes and modifications to these embodiments may be made by those skilled in the art without departing from the principles and spirit of the invention, but such changes and modifications fall within the scope of the invention.
Claims (11)
1. A method for processing communication data in an energy storage system, the method comprising:
acquiring target full data at the current sampling moment; the target full-quantity data is running state data used for representing the energy storage system;
calculating a data difference value between a current sampling value corresponding to each data point in the target full data and a historical data uploading value corresponding to the same data point at the last sampling moment;
judging whether the data difference exceeds a target sensitivity threshold; each of the data points corresponds to one of the target sensitivity thresholds;
if yes, determining to send uplink data to the data point, and if not, determining not to send uplink data to the data point;
the processing method further comprises the following steps:
determining the data deflection precision and the data partition value corresponding to each data point;
calculating to obtain an initial sensitivity threshold according to the historical data uploading value, the data displacement precision and the data partition value;
the target sensitivity threshold is determined based on the initial sensitivity threshold and a set sensitivity upper threshold.
2. The method of claim 1, wherein the determining the uplink data transmission to the data point further comprises:
and for the same data point, replacing and updating the corresponding historical data uploading value by using the current sampling value.
3. The method of processing communication data in an energy storage system of claim 1, wherein said step of determining said target sensitivity threshold based on said initial sensitivity threshold and a set upper sensitivity threshold comprises:
if the initial sensitivity threshold is greater than the sensitivity upper threshold, taking the sensitivity upper threshold as the target sensitivity threshold;
if the initial sensitivity threshold is less than the sensitivity upper threshold, taking the initial sensitivity threshold as the target sensitivity threshold;
and/or the number of the groups of groups,
and if the initial sensitivity threshold is equal to the sensitivity upper limit threshold, taking the initial sensitivity threshold or the sensitivity upper limit threshold as the target sensitivity threshold.
4. The method of claim 1, wherein the formula for calculating the initial sensitivity threshold corresponds to the following:
Δ＝|Xold*m/(floor(|Xold|/k)+1)|
wherein Δ represents the initial sensitivity threshold, xold represents the historical data upload value, m represents the data shift precision, k represents the data partition value, floor represents a downward rounding function.
5. The processing system of communication data in the energy storage system is characterized by comprising an acquisition device and a controller, wherein the acquisition device comprises an acquisition module, a first calculation module and a judgment module;
the acquisition module is used for acquiring target full-quantity data at the current sampling moment; the target full-quantity data is running state data used for representing the energy storage system;
the first calculation module is used for calculating a data difference value between a current sampling value corresponding to each data point in the target full-volume data and a historical data uploading value corresponding to the same data point at the last sampling moment;
the judging module is used for judging whether the data difference value exceeds a target sensitivity threshold; each of the data points corresponds to one of the target sensitivity thresholds;
the controller is used for determining that uplink data transmission is performed on the data point when the data difference value exceeds the target sensitivity threshold value, and determining that uplink data transmission is not performed on the data point when the data difference value does not exceed the target sensitivity threshold value;
the acquisition device further comprises a second calculation module;
the second calculation module is used for determining the data deflection precision and the data partition value corresponding to each data point; calculating an initial sensitivity threshold according to the historical data uploading value, the data deflection precision and the data partition value; the target sensitivity threshold is determined based on the initial sensitivity threshold and a set sensitivity upper threshold.
6. The system for processing communication data in an energy storage system of claim 5,
and the controller is also used for replacing and updating the corresponding historical data uploading value by adopting the current sampling value for the same data point.
7. The system for processing communication data in an energy storage system of claim 5,
the second calculation module is further configured to take the sensitivity upper limit threshold as the target sensitivity threshold if the initial sensitivity threshold is greater than the sensitivity upper limit threshold; if the initial sensitivity threshold is less than the sensitivity upper threshold, taking the initial sensitivity threshold as the target sensitivity threshold; and if the initial sensitivity threshold is equal to the sensitivity upper limit threshold, taking the initial sensitivity threshold or the sensitivity upper limit threshold as the target sensitivity threshold.
8. The system for processing communication data in an energy storage system of claim 5, wherein the formula for calculating the initial sensitivity threshold is as follows:
Δ＝|Xold*m/(floor(|Xold|/k)+1)|
wherein Δ represents the initial sensitivity threshold, xold represents the historical data upload value, m represents the data shift precision, k represents the data partition value, floor represents a downward rounding function.
9. The system for processing communication data in an energy storage system of claim 5, wherein said acquisition module comprises a plurality of data collectors in communication with said controller, said data collectors comprising at least one of a battery manager, an energy storage converter, and an environmental monitor.
10. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements a method of processing communication data in an energy storage system as claimed in any one of claims 1-4 when the computer program is executed by the processor.
11. A computer readable storage medium, wherein a computer program is stored on the computer readable storage medium, which computer program, when being executed by a processor, implements a method for processing communication data in an energy storage system according to any one of claims 1-4.
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