CN116385208A - Method and system for processing data of energy storage power station - Google Patents
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Abstract
The invention discloses a processing method and a system of energy storage power station data, which relate to the technical field of data processing, wherein the processing method comprises the following steps: after data of various devices are collected, processed and stored, a plurality of items of data related to the isolation devices are obtained, the plurality of items of data are established through formulas, whether an early warning signal needs to be sent or not is judged according to a comparison result of the device coefficients and a gradient threshold value, a management scheme is generated, a first assignment is generated through the device coefficients, a second assignment is generated through the use frequency of the isolation devices, the first assignment and the second assignment are weighted and calculated to obtain a sorting value, all the isolation devices in the energy storage power station generate a sorting table according to the sorting value from large to small, and maintenance personnel select the maintenance sequence of the isolation devices according to the positive sequence of the sorting table. The invention effectively predicts the faults of the isolation equipment in advance, so that the maintenance can be carried out before the fault of the isolation equipment, the stable operation of the energy storage power station is ensured, and the occurrence of safety accidents is avoided.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a method and a system for processing data of an energy storage power station.
Background
The energy storage power station is an electric power facility capable of storing electric energy for a period of time, plays an important role in an energy system, can balance the supply and demand relationship in the electric power system, improves the stability and reliability of a power grid, supports the large-scale utilization of renewable energy sources, and has increasingly greater demands for data acquisition, storage and management along with the continuous expansion and increase of the number of the energy storage power station;
the data processing system of the energy storage power station is a system for collecting, storing and managing data of the energy storage power station, and has the main functions of collecting and storing various data in the energy storage power station, and monitoring, scheduling and managing the energy storage power station can be realized by analyzing and processing the data, so that the operation efficiency and reliability of the energy storage power station are improved.
The prior art has the following defects:
the power system in the energy storage power station comprises a high-voltage power supply and a low-voltage power supply, wherein the high-voltage power supply and the low-voltage power supply are usually isolated by using isolation equipment, when the isolation equipment is monitored by the existing energy storage power station, fault data are recorded and an alarm prompt is sent out only when the isolation equipment is in fault, however, when the isolation equipment is in fault, the power transmission of the energy storage power station needs to be cut off in time for maintenance, and if the isolation equipment is in fault and the power transmission of the energy storage power station is not cut off in time, a series of safety accidents (including electric fire accidents, electric shock accidents, short circuit accidents and the like) are easily caused;
therefore, a need exists for a method and a system for processing data of an energy storage power station, which can predict and early warn faults of isolation equipment in advance, and solve the above problems.
Disclosure of Invention
The invention aims to provide a method and a system for processing energy storage power station data, which are used for solving the defects in the background technology.
In order to achieve the above object, the present invention provides the following technical solutions: the processing method of the energy storage power station data comprises the following steps:
s1: the acquisition end acquires data of various devices in the energy storage power station, and the data are sent to the processing end;
s2: after preprocessing the collected data, the processing end integrates and fuses the data from different data sources, and the integrated and fused data is uploaded to a cloud database for storage;
s3: acquiring a plurality of items of data related to the isolation equipment, establishing equipment coefficients through a formula, judging whether an early warning signal needs to be sent out or not according to a comparison result of the equipment coefficients and a gradient threshold value, and generating a management scheme;
s4: generating a first assignment through the equipment coefficient, generating a second assignment through the frequency of use of the isolation equipment, and generating a ranking table according to the ranking value by all the isolation equipment in the energy storage power station after the ranking value is obtained through weighting calculation of the first assignment and the second assignment;
s5: and the maintenance personnel select the maintenance sequence of the isolation equipment according to the positive sequence of the sorting table.
In a preferred embodiment, the plurality of data includes a device parameter and an environmental parameter, the device parameter includes a fuse resistance float value and a transformer heat dissipation rate, and the environmental parameter includes a temperature and humidity coefficient;
calculating the equipment coefficient of the fuse resistance floating value, the transformer heat dissipation rate and the temperature and humidity coefficient by using a formula, wherein the expression is as follows:
in the method, in the process of the invention,
for the device coefficients +.>
Is the floating value of fuse resistance, ">
Is the heat dissipation rate of the transformer->
Is the temperature and humidity coefficient%>
The ratio coefficients of the fuse resistance floating value, the transformer heat dissipation rate and the temperature and humidity coefficient are respectively +.>
。
In a preferred embodiment, the fuse resistance floats
The acquisition logic of (1) is: marking the safe range of the resistance value of the fuse as +.>
Marking the real-time monitored fuse resistance value as +.>
When (when)
At the time, the fuse resistance is floating>
The method comprises the steps of carrying out a first treatment on the surface of the When->
At the time, the fuse resistance is floating>
。
In a preferred embodiment, the transformer heat dissipation rate is calculated as:
In a preferred embodiment, the temperature and humidity coefficient
The calculated expression of (2) is:
for the real-time resistance value of the earthing switch, +.>
For the period of early warning of the rise of the ambient temperature, +.>
To isolate the partial discharge current of the device, +.>
And (5) increasing the early warning period for the humidity.
In a preferred embodiment, the gradient threshold comprises a first threshold
A second threshold +.>
And a first threshold +.>
Second threshold->
Acquiring device coefficients->
After that, the device coefficient is->
Is>
A second threshold +.>
Comparison was performed.
In a preferred embodiment, if the device coefficients are
Second threshold->
The processing system sends out a first-level early warning signal and generates a management scheme;
if the first threshold value
Device coefficient->
Second threshold->
The processing system sends out a secondary early warning signal;
if the device coefficients are
First threshold->
The processing system does not send out an early warning signal and generate a management scheme.
In a preferred embodiment, the calculation expression of the ranking value is:
the method comprises the steps of carrying out a first treatment on the surface of the In (1) the->
For the ranking value>
To assign one->
To assign two->
Weight coefficients assigned one and two respectively, and +.>
The value is 0.7%>
The value is 0.3.
The invention also provides a processing system of the energy storage power station data, which comprises an acquisition module, a processing module, a calculation module, a comparison module, a sequencing module and a management module;
the method comprises the steps that an acquisition module acquires data of various devices in an energy storage power station, the data are sent to a processing module and a calculation module, the processing module carries out preprocessing on the acquired data, then integrates and fuses the data from different data sources, the integrated and fused data are uploaded to a cloud database for storage, the calculation module acquires multiple data related to isolation devices, the multiple data are established into device coefficients through formulas, the device coefficients are sent to a comparison module and a sorting module, the comparison module judges whether an early warning signal needs to be sent or not and generates a management scheme according to the comparison result of the device coefficients and a gradient threshold value, the sorting module generates a first assignment through the device coefficients, a second assignment is generated through the use frequency of the isolation devices, after the first assignment and the second assignment are weighted and calculated to obtain a sorting value, all the isolation devices in the energy storage power station generate a sorting table according to the sorting value, the sorting table is sent to a management module, and the management module selects the maintenance sequence of the isolation devices according to the sorting table in sequence.
In the technical scheme, the invention has the technical effects and advantages that:
the method acquires, processes and stores the data of various devices, acquires a plurality of items of data related to the isolation device, establishes device coefficients through a formula, judges whether an early warning signal needs to be sent out or not and generates a management scheme according to the comparison result of the device coefficients and the gradient threshold value, and effectively predicts the fault of the isolation device in advance, so that the isolation device can be overhauled before the fault, the stable operation of the energy storage power station is ensured, and the occurrence of safety accidents is avoided;
according to the invention, the first assignment is generated through the equipment coefficient, the larger the equipment coefficient is, the larger the first assignment is, the second assignment is generated through the use frequency of the isolation equipment, the larger the use frequency of the isolation equipment is, the larger the second assignment is, after the first assignment and the second assignment are weighted and calculated to obtain the sorting value, a sorting table is generated by all the isolation equipment in the energy storage power station according to the sorting value from large to small, and maintenance personnel select the maintenance sequence of the isolation equipment according to the positive sequence of the sorting table, so that the management efficiency of the isolation equipment is effectively improved;
according to the invention, the equipment coefficient is calculated through a formula by using the fuse resistance floating value, the transformer heat dissipation rate and the temperature and humidity coefficient, multiple data are comprehensively processed, the processing efficiency of the data is effectively improved, and after the equipment coefficient is obtained, the equipment coefficient and the first threshold value are used for calculating the equipment coefficient
A second threshold +.>
And (3) judging whether an early warning signal needs to be sent out or not and generating a management scheme, and effectively ensuring the safe operation of the energy storage power station.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments described in the present invention, and other drawings may be obtained according to these drawings for a person having ordinary skill in the art.
FIG. 1 is a flow chart of the method of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
Referring to fig. 1, the method for processing data of an energy storage power station according to the present embodiment includes the following steps:
the method comprises the steps that an acquisition end acquires data of various devices in an energy storage power station, the data are sent to a processing end, the processing end carries out preprocessing on the acquired data, then integrates and fuses the data from different data sources, the integrated and fused data are uploaded to a cloud database for storage, multiple data related to isolation devices are acquired, the multiple data are established through formulas, whether early warning signals need to be sent or not and a management scheme is generated is judged according to a comparison result of the device coefficients and gradient threshold values, assignment one is generated through the device coefficients, the assignment one is larger, the assignment two is generated through the use frequency of the isolation devices, the use frequency of the isolation devices is larger, the assignment two is larger, after a sorting value is obtained through weighting calculation of the assignment one and the assignment two, a sorting table is generated by all the isolation devices in the energy storage power station according to the sorting value, and maintenance personnel select the maintenance sequence of the isolation devices according to the sorting table.
After the data of various devices are collected, processed and stored, a plurality of data related to the isolation device are obtained, the device coefficients are established through a formula, whether an early warning signal needs to be sent or not is judged according to the comparison result of the device coefficients and the gradient threshold value, and a management scheme is generated, so that the isolation device is effectively subjected to fault prediction in advance, the isolation device can be overhauled before the isolation device breaks down, the stable operation of the energy storage power station is guaranteed, and the occurrence of safety accidents is avoided.
The method and the system also generate the first assignment through the equipment coefficient, the larger the equipment coefficient is, the larger the first assignment is, the larger the use frequency of the isolation equipment is, the larger the second assignment is, after the first assignment and the second assignment are weighted and calculated to obtain the sorting value, all the isolation equipment in the energy storage power station generates the sorting table from large to small according to the sorting value, and maintenance personnel select the maintenance sequence of the isolation equipment according to the normal sequence of the sorting table, so that the management efficiency of the isolation equipment is effectively improved.
In this embodiment, the method for preprocessing collected data by the processing end includes: removing abnormal values and repeated data and filling missing data;
the method for removing abnormal values and repeating data of the data of various devices of the energy storage power station comprises the following steps:
(1) Data deduplication: in the process of data acquisition, the condition that the same piece of data is acquired for multiple times is likely to occur, so that duplicate removal processing is needed, and the uniqueness of each piece of data is ensured;
(2) Abnormal value detection: carrying out abnormal value detection on the data by a statistical method, and regarding the numerical value exceeding the normal range as an abnormal value;
(3) Outlier processing: for the detected abnormal value, the abnormal value can be processed in a deleting, replacing or interpolating mode, and the abnormal value deleting is the most common mode, but the abnormal value needs to be carefully processed, so that the effective data is prevented from being deleted by mistake;
(4) Data conversion: converting the data into a processable format, for example converting a character string into numeric data;
(5) Formatting data: the data is arranged and organized in a format to facilitate subsequent data analysis and processing.
Filling missing data for data of various devices of the energy storage power station comprises the following steps:
(1) And (3) missing value detection: detecting the data to find the position and the number of the missing values;
(2) Judging the type of the missing value: judging the types of the missing values, including random missing, non-random missing, complete missing and the like;
(3) Filling up the missing value: filling the missing values by adopting a proper method according to the types and the data characteristics of the missing values, wherein the common method comprises the following steps:
(3.1) mean filling: filling the missing value by using the average value of the variable;
(3.2) filling in the median: filling the missing value with the median of the variable;
(3.3) mode filling: filling the missing value by using the mode of the variable;
(3.4) interpolation: filling missing values by interpolation, including linear interpolation, polynomial interpolation, spline interpolation and the like;
(3.5) regression method: missing values are predicted by building regression models, such as linear regression, logistic regression, etc.
In this embodiment, filling the missing value by interpolation is exemplified as follows:
1) Determining the position and the number of the missing values: firstly, checking the missing value condition in a data set, and determining the row and column where the missing value is located and the number of the missing values;
2) Determining an interpolation method: selecting a proper interpolation method according to the type of the data and the distribution condition of the missing values, for example, for continuous numerical value data, linear interpolation, polynomial interpolation, spline interpolation and other methods can be adopted for filling; for discrete data, filling can be carried out by adopting methods such as mode interpolation based on frequency, random interpolation based on probability and the like;
3) Interpolation calculation is carried out: interpolation is performed on the missing values according to the interpolation method selected, for example, for linear interpolation, the missing values can be calculated using the linear relationship between the known data points; for spline interpolation, the missing value can be filled by fitting a spline curve;
4) Checking interpolation results: after filling, the filling result needs to be checked to judge whether obvious abnormal values or contradiction phenomena exist or not, and the abnormal values need to be processed.
Integrating and fusing data from different data sources, and uploading the integrated and fused data to a cloud database for storage, wherein the method comprises the following steps of:
(1) Determining a data source and a data format: firstly, determining data sources and data formats, including information such as data types, data structures, data headers and the like;
(2) Data integration and fusion: integrating and fusing the preprocessed data, including operations such as field matching, data merging, association, connection, duplicate removal and the like, and it is noted that the data integration and fusion need to be operated according to actual requirements, and consistency, integrity and accuracy of the data need to be ensured;
(3) Uploading data to a cloud database: uploading the integrated and fused data to a cloud database for storage, wherein the operations comprise selecting a proper cloud platform, creating the database, creating a data table, setting rights and the like;
(4) Database maintenance and management: and maintaining and managing the data uploaded to the cloud database, including operations such as backup, recovery, optimized query, performance monitoring and the like. .
Example 2
And acquiring a plurality of items of data related to the isolation equipment, establishing equipment coefficients through a formula, judging whether an early warning signal needs to be sent out or not according to a comparison result of the equipment coefficients and the gradient threshold value, and generating a management scheme.
The method for establishing the equipment coefficient by using the formula comprises the following steps of:
acquiring a plurality of data related to isolation equipment, wherein the plurality of data comprise equipment parameters and environment parameters, the equipment parameters comprise a fuse resistance floating value and a transformer heat dissipation rate, and the environment parameters comprise a temperature and humidity coefficient;
calculating the equipment coefficient of the fuse resistance floating value, the transformer heat dissipation rate and the temperature and humidity coefficient by using a formula, wherein the expression is as follows:
in the method, in the process of the invention,
for the device coefficients +.>
Is the floating value of fuse resistance, ">
Is the heat dissipation rate of the transformer->
Is the temperature and humidity coefficient%>
The ratio coefficients of the fuse resistance floating value, the transformer heat dissipation rate and the temperature and humidity coefficient are respectively +.>
。
Fuse resistance float value
The acquisition logic of (1) is: the excessive resistance value of the fuse causes the voltage drop under the rated current to be increased, so that the voltage in the circuit becomes unstable, equipment faults or even damage can be caused, and in addition, the increased resistance value of the fuse can also indicate that the fuse is aged or damaged and needs to be replaced in time; the overload of the circuit can be caused by the too small resistance value of the fuse, so that the short circuit or overcurrent of the equipment can be caused, and the equipment is damaged or the safety accident is caused; therefore, the stable operation of the isolation device can be ensured only when the resistance value of the fuse is within the safety range, and the safety range of the resistance value of the fuse is marked as +.>
Marking the real-time monitored fuse resistance value as +.>
When->
At the time, the fuse resistance is floating>
The method comprises the steps of carrying out a first treatment on the surface of the When->
At the time of fuse resistance floating value
The calculation expression of the heat dissipation rate of the transformer is as follows:
the method comprises the steps of carrying out a first treatment on the surface of the In (1) the->
For the loss power of the transformer core, +.>
For the power loss of the transformer coil, +.>
Represents the effective surface area of the transformer, wherein +.>
Is the sum of the effective surface areas of the transformers, and comprises a shell, a radiator, a bracket, an insulating sleeve and the like.
Coefficient of temperature and humidity
The calculated expression of (2) is: />
For the real-time resistance value of the earthing switch, +.>
For the period of early warning of the rise of the ambient temperature, +.>
To isolate the partial discharge current of the device, +.>
And (5) increasing the early warning period for the humidity.
The gradient threshold value includes a first threshold value
A second threshold +.>
And a first threshold +.>
Second threshold->
Acquiring device coefficients->
After that, the device coefficient is->
Is>
A second threshold +.>
Comparing;
if the device coefficient is
Second threshold->
The processing system predicts that the isolation equipment will fail, and sends out a first-level early warning signal and generates a management scheme;
if at firstA threshold value
Device coefficient->
Second threshold->
The processing system predicts that the isolating equipment is likely to fail in the future, and sends out a secondary early warning signal at the moment;
if the device coefficient is
First threshold->
The processing system predicts that the isolation equipment will not fail in the future, and does not send out an early warning signal and generate a management scheme.
The management scheme comprises the following steps: the processing system generates a power-off scheme instruction, sends the power-off scheme instruction to the remote control center, and controls the energy storage power station to be powered off after the remote control center receives the power-off scheme instruction, and overhauls the isolation equipment in time after an overhauling personnel receives the primary early warning signal;
when the maintainer receives the second-level early warning signal, the isolation equipment can also support the operation of the energy storage power station, and the maintainer checks and overhauls the isolation equipment.
According to the method, the device coefficient is calculated through a formula by using the fuse resistance floating value, the transformer heat dissipation rate and the temperature and humidity coefficient, multiple data are comprehensively processed, the processing efficiency of the data is effectively improved, and after the device coefficient is obtained, the device coefficient and the first threshold value are calculated according to the device coefficient
A second threshold +.>
Whether an early warning signal needs to be sent or not is judged according to the comparison result of the energy storage power station, and a management scheme is generated, so that the safe operation of the energy storage power station is effectively ensured。
Example 3
As can be seen from the calculation formula of the device coefficient in the above embodiment 2, the larger the device coefficient of the isolation device is, the worse the operation state of the isolation device is;
therefore, the first assignment is generated through the equipment coefficient, the larger the equipment coefficient is, the larger the first assignment is, the second assignment is generated through the use frequency of the isolation equipment, the larger the use frequency of the isolation equipment is, the larger the second assignment is, after the first assignment and the second assignment are weighted and calculated to obtain the sorting value, the sorting table is generated by all the isolation equipment in the energy storage power station according to the sorting value from large to small, and the maintenance personnel select the maintenance sequence of the isolation equipment according to the positive sequence of the sorting table as follows:
generating a first assignment through the equipment coefficient, generating a second assignment through the use frequency of the isolation equipment, and obtaining a sorting value through weighting calculation of the first assignment and the second assignment, wherein the calculation expression of the sorting value is as follows:
the method comprises the steps of carrying out a first treatment on the surface of the In (1) the->
For the ranking value>
To assign one->
To assign two->
Weight coefficients assigned one and two respectively, and +.>
The value is 0.7%>
The value is 0.3, after the sorting value is obtained by calculation, all the isolation devices of the energy storage power station are sorted according to the sorting value from large to small to generate a sorting table,the larger the ordering value of the quarantine device, the more the quarantine device needs to be managed.
Example 4
The processing system of the energy storage power station data comprises an acquisition module, a processing module, a calculation module, a comparison module, a sequencing module and a management module;
wherein:
and the acquisition module is used for: the system comprises a processing module, a calculation module, a data acquisition module, a data transmission module and a data transmission module, wherein the data acquisition module is used for acquiring data of various devices in an energy storage power station;
the processing module is used for: preprocessing the acquired data, integrating and fusing the data from different data sources, and uploading the integrated and fused data to a cloud database for storage;
the calculation module: acquiring multiple data related to the isolation equipment, establishing equipment coefficients by a formula, and sending the equipment coefficients to a comparison module and a sequencing module;
and a comparison module: judging whether an early warning signal needs to be sent out or not according to a comparison result of the equipment coefficient and the gradient threshold value, and generating a management scheme;
and a sequencing module: generating a first assignment through the equipment coefficient, generating a second assignment through the use frequency of the isolation equipment, generating a sorting table according to the sorting value by all the isolation equipment in the energy storage power station from large to small after the sorting value is obtained through weighting calculation of the first assignment and the second assignment, and sending the sorting table to the management module;
and a management module: and selecting the maintenance sequence of the isolation equipment according to the positive sequence of the sorting table.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas with a large amount of data collected for software simulation to obtain the latest real situation, and preset parameters in the formulas are set by those skilled in the art according to the actual situation.
The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the processes or functions described in accordance with the embodiments of the present application are all or partially produced. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center by wired or wireless means (e.g., infrared, wireless, microwave, etc.). The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains one or more sets of available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium may be a solid state disk.
It should be understood that the term "and/or" is merely an association relationship describing the associated object, and means that three relationships may exist, for example, a and/or B may mean: there are three cases, a alone, a and B together, and B alone, wherein a, B may be singular or plural. In addition, the character "/" herein generally indicates that the associated object is an "or" relationship, but may also indicate an "and/or" relationship, and may be understood by referring to the context.
In the present application, "at least one" means one or more, and "a plurality" means two or more. "at least one of" or the like means any combination of these items, including any combination of single item(s) or plural items(s). For example, at least one (one) of a, b, or c may represent: a, b, c, a-b, a-c, b-c, or a-b-c, wherein a, b, c may be single or plural.
It should be understood that, in various embodiments of the present application, the sequence numbers of the foregoing processes do not mean the order of execution, and the order of execution of the processes should be determined by the functions and internal logic thereof, and should not constitute any limitation on the implementation process of the embodiments of the present application.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.
In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a random access memory (random access memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing is merely specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily think about changes or substitutions within the technical scope of the present application, and the changes and substitutions are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (9)
1. The processing method of the energy storage power station data is characterized by comprising the following steps of: the processing method comprises the following steps:
s1: the acquisition end acquires data of various devices in the energy storage power station, and the data are sent to the processing end;
s2: after preprocessing the collected data, the processing end integrates and fuses the data from different data sources, and the integrated and fused data is uploaded to a cloud database for storage;
s3: acquiring a plurality of items of data related to the isolation equipment, establishing equipment coefficients through a formula, judging whether an early warning signal needs to be sent out or not according to a comparison result of the equipment coefficients and a gradient threshold value, and generating a management scheme;
s4: generating a first assignment through the equipment coefficient, generating a second assignment through the frequency of use of the isolation equipment, and generating a ranking table according to the ranking value by all the isolation equipment in the energy storage power station after the ranking value is obtained through weighting calculation of the first assignment and the second assignment;
s5: and the maintenance personnel select the maintenance sequence of the isolation equipment according to the positive sequence of the sorting table.
2. The method for processing energy storage power station data according to claim 1, wherein: the plurality of data comprise equipment parameters and environmental parameters, the equipment parameters comprise a fuse resistance floating value and a transformer heat dissipation rate, and the environmental parameters comprise a temperature and humidity coefficient;
calculating the equipment coefficient of the fuse resistance floating value, the transformer heat dissipation rate and the temperature and humidity coefficient by using a formula, wherein the expression is as follows:
in the method, in the process of the invention,
for the device coefficients +.>
Is the floating value of fuse resistance, ">
Is the heat dissipation rate of the transformer->
Is the temperature and humidity coefficient%>
Respectively the fuse resistance floating value and the transformer heat dissipation rateAnd the ratio of the temperature and humidity coefficients, and
。
3. the method for processing energy storage power station data according to claim 2, wherein: the fuse resistance floating value
The acquisition logic of (1) is: marking the safe range of the resistance value of the fuse as +.>
Marking the real-time monitored fuse resistance value as +.>
When->
At the time, the fuse resistance is floating>
The method comprises the steps of carrying out a first treatment on the surface of the When->
At the time, the fuse resistance is floating>
。
4. A method of processing energy storage plant data according to claim 3, wherein: the calculation expression of the heat dissipation rate of the transformer is as follows:
the method comprises the steps of carrying out a first treatment on the surface of the In (1) the->
For the loss power of the transformer core, +.>
For the power loss of the transformer coil, +.>
Indicating the effective surface area of the transformer.
5. The method for processing energy storage power station data according to claim 4, wherein: the temperature and humidity coefficient
The calculated expression of (2) is: />
For the real-time resistance value of the ground switch,
for the period of early warning of the rise of the ambient temperature, +.>
To isolate the partial discharge current of the device, +.>
And (5) increasing the early warning period for the humidity.
6. The method for processing energy storage power station data according to claim 5, wherein: the gradient threshold value includes a first threshold value
A second threshold +.>
And a first threshold +.>
Second threshold->
Acquiring device coefficients->
After that, the device coefficient is->
Is>
A second threshold +.>
Comparison was performed.
7. The method for processing energy storage power station data according to claim 6, wherein: if the device coefficients are
Second threshold->
The processing system sends out a first-level early warning signal and generates a management scheme;
if the first threshold value
Device coefficient->
Second threshold->
The processing system sends out a secondary early warning signal;
if the device coefficients are
First threshold->
The processing system does not send out an early warning signal and generate a management scheme.
8. The method for processing energy storage power station data according to claim 7, wherein: the calculation expression of the sorting value is as follows:
the method comprises the steps of carrying out a first treatment on the surface of the In (1) the->
For the ranking value>
To assign one->
For the assignment of two,
weight coefficients assigned one and two respectively, and +.>
The value is 0.7%>
The value is 0.3.
9. A processing system for energy storage power station data, for implementing the processing method according to any one of claims 1 to 8, characterized in that: the system comprises an acquisition module, a processing module, a calculation module, a comparison module, a sequencing module and a management module;
the method comprises the steps that an acquisition module acquires data of various devices in an energy storage power station, the data are sent to a processing module and a calculation module, the processing module carries out preprocessing on the acquired data, then integrates and fuses the data from different data sources, the integrated and fused data are uploaded to a cloud database for storage, the calculation module acquires multiple data related to isolation devices, the multiple data are established into device coefficients through formulas, the device coefficients are sent to a comparison module and a sorting module, the comparison module judges whether an early warning signal needs to be sent or not and generates a management scheme according to the comparison result of the device coefficients and a gradient threshold value, the sorting module generates a first assignment through the device coefficients, a second assignment is generated through the use frequency of the isolation devices, after the first assignment and the second assignment are weighted and calculated to obtain a sorting value, all the isolation devices in the energy storage power station generate a sorting table according to the sorting value, the sorting table is sent to a management module, and the management module selects the maintenance sequence of the isolation devices according to the sorting table in sequence.
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