CN111625596B - Multi-source data synchronous sharing method and system for real-time new energy consumption scheduling - Google Patents
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Abstract
The invention discloses a multi-source data synchronous sharing method for new energy real-time consumption scheduling, which comprises the steps of obtaining names of all data sources; calculating the similarity between names; merging data source data with name similarity larger than a threshold value; transmitting the combined data to a data warehouse for storage; and in response to triggering data sharing, invoking the data to be shared according to the metadata of the data warehouse. Corresponding systems are also disclosed. According to the invention, data fusion is carried out based on similarity names, and the fused data are stored in a data warehouse, so that integrated management and interactive sharing of multi-source heterogeneous new energy data in different power grid dispatching systems are realized.
Description
Technical Field
The invention relates to a multi-source data synchronous sharing method and system for new energy real-time consumption scheduling, and belongs to the technical field of power system scheduling automation.
Background
The traditional thermal power generating unit is different, because of the characteristics of new energy sources such as wind power, photovoltaic and the like, the new energy source power generation is full of great uncertainty, and especially in the system construction of wind power, photovoltaic and thermal power AGC, all systems are mutually independent, the geographic positions of the new energy sources are scattered, related data interaction is difficult, comprehensive system advantages are difficult to develop, great difficulty is brought to the absorption and decision of the new energy sources, and a serious wind and light discarding phenomenon is caused.
Because the information data related to the new energy consumption decision is not uniform in design requirements at the initial stages of different system construction, the data generally have different formats and different service attributes, and the data presents the phenomenon that more structured data coexist with unstructured data; therefore, great difficulty is brought to synchronous sharing of data, and no effective multi-source synchronous sharing method for data exists.
Disclosure of Invention
The invention provides a multi-source data synchronous sharing method and system for new energy real-time consumption scheduling, which solve the problems disclosed in the background technology.
In order to solve the technical problems, the invention adopts the following technical scheme:
the multi-source data synchronous sharing method for real-time new energy consumption scheduling comprises,
acquiring names of all data sources;
calculating the similarity between names;
merging data source data with name similarity larger than a threshold value;
transmitting the combined data to a data warehouse for storage;
and in response to triggering data sharing, invoking the data to be shared according to the metadata of the data warehouse.
The similarity between names is calculated by the specific process,
decomposing each name into a word array according to a preset word stock;
similarity between names is calculated based on the segmentation.
In the process of calculating the similarity, a regularization method is adopted to convert special characters in the names, a plurality of continuous digital single words are connected as a whole, and fields representing the unique attributes of the equipment are subjected to feature transcoding.
If the name information is missing, the key field is used for filling in the name, and then similarity calculation is carried out.
And merging the data source data with the name similarity larger than the threshold value, removing redundancy, and sending the merged and redundancy-removed data to a data warehouse for storage.
The metadata of the data warehouse comprises a core layer and an extension layer; the core layer and the extension layer both contain metadata elements; the metadata elements of the core layer are features shared by the data, and the metadata elements of the extension layer are application features not shared by the data.
In the data warehouse, the increment data of the day is connected with the total data of the previous day in an all-out way.
The multi-source data synchronous sharing system for real-time new energy consumption scheduling comprises,
name acquisition module: acquiring names of all data sources;
similarity calculation module: calculating the similarity between names;
and a data merging module: merging data source data with name similarity larger than a threshold value;
and the sending storage module is used for: transmitting the combined data to a data warehouse for storage;
and (3) a calling module: and in response to triggering data sharing, invoking the data to be shared according to the metadata of the data warehouse.
A computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by a computing device, cause the computing device to perform a method of multi-source data synchronization sharing for new energy real-time consumption scheduling.
A computing device comprising one or more processors, memory, and one or more programs, wherein one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs comprising instructions for performing a multi-source data synchronization sharing method of new energy real-time consumption scheduling.
The invention has the beneficial effects that: according to the invention, data fusion is carried out based on similarity names, and the fused data are stored in a data warehouse, so that integrated management and interactive sharing of multi-source heterogeneous new energy data in different power grid dispatching systems are realized.
Drawings
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is a diagram of a metadata structure;
fig. 3 is an incremental data synchronization flow.
Detailed Description
The invention is further described below with reference to the accompanying drawings. The following examples are only for more clearly illustrating the technical aspects of the present invention, and are not intended to limit the scope of the present invention.
As shown in fig. 1, the method for synchronously sharing multi-source data for real-time new energy consumption scheduling includes the following steps:
and step 1, acquiring the names of all the data sources, namely acquiring the names of corresponding devices in the new energy system.
And 2, calculating the similarity between the names.
The method comprises the following steps: and decomposing each name into a word segmentation array according to a preset word stock, and calculating the similarity between the names based on the word segmentation.
Wherein, the following improvement is made in the process of calculating the similarity:
1. special characters in the names are converted by adopting a regularization method, such as special symbols of "," \ "," # ", and the like in the normalized processing equipment names.
2. Connecting a plurality of continuous digital single words as a whole;
after word segmentation processing is carried out on the equipment names, a plurality of single word conditions appear, and continuous digital single words are connected and matched as a whole, so that the conditions of '500' or '330' and the like in the voltage class can be conveniently processed.
3. Fields that characterize the unique attributes of the device are feature transcoded to increase the importance and unique nature of the field, increasing the comparison weight when a similarity comparison is entered.
And (3) word stock construction: constructing a power grid structural feature, a paraphrasing word library, a transcoding word library and automatically expanding according to a comparison result; the specific program flow is as follows:
input: all device names
And (3) outputting: professional word stock of power equipment
Word segmentation: based on the Trie, completing feature structure word segmentation by a forward maximum matching algorithm; the specific program flow is as follows:
input: power equipment name
And (3) outputting: equipment name word segmentation array
The similarity calculation is carried out, and the specific program flow is as follows:
input: two power equipment word segmentation vectors T x ＝w 1 ,w 2 ,...,w n
And (3) outputting: similarity S
The names of the electric power equipment are usually composed of continuous characters, characters and numbers, the sequences of the characters and the numbers are different under the condition of lack of a spacer, the segmentation process is disagreement, the sequence of the segmented character strings is complex, and the identification of the names of the equipment is more complex than the processing of simple Chinese or English naming; in addition, because the system has no standardized management of geography and address names for a long time, multiple expression forms such as abbreviation records with local and personal habits aggravate the difficulty of identifying the names of the devices, for example, a ' Ma Zhuang 220 kV#4bus is recorded as a ' Ma Zhuang bus '. The above example results in the absence of keywords during the data sharing synchronization process.
If the name information is missing, the key field is used for filling in the name, and then similarity calculation is carried out. The Chinese word segmentation algorithm is mainly based on character string matching, and aiming at the missing keywords, character strings are scanned, if the substrings and words of the character strings are found to be identical, the matching is considered, and some heuristic rules, such as 'forward/reverse maximum matching', 'long word priority', and the like, are added.
Because the number of primary devices is large, the station to which the devices belong is set as the associated field, and data filtering is completed before word segmentation and similarity calculation, so that the efficiency is improved.
And 3, merging the data source data with the name similarity larger than the threshold value, and removing redundancy.
And step 4, sending the combined data to a data warehouse for storage.
Metadata is a logical structure of a data warehouse, which is data about data. Metadata may describe various data in the database in detail, be it data or instructions in the process. Metadata herein pertains to technical metadata, including data source information, descriptions of data transformations, definitions of objects and data structures within a data warehouse, and other specifications.
As shown in fig. 2, metadata of a data warehouse includes a core layer and an extension layer; the core layer and the extension layer both contain metadata elements; the metadata elements of the core layer are features shared by the data, the metadata of the core layer are used for describing the aggregate information of the power grid regulation data, and the most basic access information and the description of the features of the metadata when the metadata enter a data warehouse are recorded, so that the metadata has extremely strong applicability and compatibility; the metadata element of the extension layer is an application feature which is not shared by the data, and can be combined with the core layer to describe one type of metadata completely.
Taking a new energy real-time consumption scheduling auxiliary decision information sharing cloud platform based on metadata as an example, the metadata items mainly comprise power plant stations, regional (geographic) positions, unit types, scheduling relations, scheduling plan information, output information, electricity limiting reasons and time periods, deep scheduling types, compensation allocation types, spot transaction conditions and the like and contact information of related data. The extended metadata set of the data such as the scheduling decision of the new energy real-time consumption has to be extracted and generated aiming at the common meta information items. The core layer element table definition is shown in table 1.
Table 1 core layer element table definition
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Whether the core layer or the extension layer, each data element may have a name and a value, the attribute definition of which should contain the attribute values shown in table 2.
Table 4 attribute definition of metadata elements
The metadata element may extend the attribute definition to extend additional attributes of the metadata element. The extended attribute item mainly describes the special information item of a certain type of information data and the directory structure information of the resource in the shared vocabulary data set, so that the structural relation among the multi-source information data is revealed, and the extended attribute definition of the metadata element is shown in table 3.
Table 5 extended attribute definition for metadata elements
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And the metadata expansion principle in the new energy real-time consumption scheduling decision system conforms to the meaning expressed by the table. According to the characteristics of real-time consumption scheduling service and new energy information sharing of the whole new energy network, when the shared metadata is determined, the complexity and the data weight of the new energy service are fully considered, and the data sharing, service handling and information query are fully satisfied. Meanwhile, considering the complexity of the new energy business data, the metadata entity can be defined as a composite entity, namely the existing metadata entity can be used as a component part of the new entity, and the metadata is allowed to represent the existing metadata element value field with the self text instead of the value field. The number of parameters can be increased, but the extended attribute has the same logic as before extension.
In the batch synchronization of the power grid regulation data, the data volume is larger and larger along with the rich scale of the power grid service, if the full-volume data is synchronized at a certain period, errors are easy to occur and the efficiency is low, and the full-volume synchronization of a service system is not scientific in the face of massive data every day. The method can be set to only synchronize the new changed data which changes each time when the strategy is selected, and then the new changed data is combined with the full data acquired in the last synchronization period.
As shown in fig. 3, in the data warehouse, the increment data of the current day and the full data of the previous day are all externally connected, the latest full data is reloaded, and under the condition of large-scale data volume, the efficiency is much higher than that of the traditional method of inserting and updating, so that the latest full version can be obtained through updating every day. Meanwhile, when the operation of physically deleting the data table exists in the service system table of the new energy real-time consumption schedule, the batch synchronization mode of the incremental data is selected under the condition that the data warehouse guarantees the advantage of the historical data, so that the latest data snapshot can be reserved permanently, and the stability, safety and accuracy of the service system are ensured.
And step 5, responding to triggering data sharing, and calling the data to be shared according to the metadata of the data warehouse.
According to the method, data fusion is carried out based on similarity names, and the fused data are stored in a data warehouse, so that integrated management and interactive sharing of multi-source heterogeneous new energy data in different power grid dispatching systems are realized.
The multi-source data synchronous sharing system for real-time new energy consumption scheduling comprises,
name acquisition module: acquiring names of all data sources;
similarity calculation module: calculating the similarity between names;
and a data merging module: merging data source data with name similarity larger than a threshold value;
and the sending storage module is used for: transmitting the combined data to a data warehouse for storage;
and (3) a calling module: and in response to triggering data sharing, invoking the data to be shared according to the metadata of the data warehouse.
A computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by a computing device, cause the computing device to perform a method of multi-source data synchronization sharing for new energy real-time consumption scheduling.
A computing device comprising one or more processors, memory, and one or more programs, wherein one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs comprising instructions for performing a multi-source data synchronization sharing method of new energy real-time consumption scheduling.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The foregoing is illustrative of the present invention and is not to be construed as limiting thereof, but rather as providing for the use of additional embodiments and advantages of all such modifications, equivalents, improvements and similar to the present invention are intended to be included within the scope of the present invention as defined by the appended claims.
Claims (8)
1. The multi-source data synchronous sharing method for real-time new energy consumption scheduling is characterized by comprising the following steps of: comprising the steps of (a) a step of,
acquiring names of all data sources;
decomposing each name into a word segmentation array according to a preset word stock, and calculating the similarity between the names based on word segmentation; wherein, the similarity is the weighted sum of semantic similarity and word sequence similarity;
in the process of calculating the similarity, converting special characters in the names by adopting a regularization method, connecting a plurality of continuous digital single words as a whole, performing feature transcoding on fields representing unique attributes of equipment, and increasing comparison proportion when similarity comparison is performed;
merging data source data with name similarity larger than a threshold value;
transmitting the combined data to a data warehouse for storage;
and in response to triggering data sharing, invoking the data to be shared according to the metadata of the data warehouse.
2. The multi-source data synchronous sharing method for new energy real-time consumption scheduling according to claim 1, wherein the method is characterized by comprising the following steps: if the name information is missing, the key field is used for filling in the name, and then similarity calculation is carried out.
3. The multi-source data synchronous sharing method for new energy real-time consumption scheduling according to claim 1, wherein the method is characterized by comprising the following steps: and merging the data source data with the name similarity larger than the threshold value, removing redundancy, and sending the merged and redundancy-removed data to a data warehouse for storage.
4. The multi-source data synchronous sharing method for new energy real-time consumption scheduling according to claim 1, wherein the method is characterized by comprising the following steps: the metadata of the data warehouse comprises a core layer and an extension layer; the core layer and the extension layer both contain metadata elements; the metadata elements of the core layer are features shared by the data, and the metadata elements of the extension layer are application features not shared by the data.
5. The multi-source data synchronous sharing method for new energy real-time consumption scheduling according to claim 1, wherein the method is characterized by comprising the following steps: in the data warehouse, the increment data of the day is connected with the total data of the previous day in an all-out way.
6. The multi-source data synchronous sharing system for real-time new energy consumption scheduling is characterized in that: comprising the steps of (a) a step of,
name acquisition module: acquiring names of all data sources;
similarity calculation module: decomposing each name into a word segmentation array according to a preset word stock, and calculating the similarity between the names based on word segmentation; wherein, the similarity is the weighted sum of semantic similarity and word sequence similarity;
in the process of calculating the similarity, converting special characters in the names by adopting a regularization method, connecting a plurality of continuous digital single words as a whole, performing feature transcoding on fields representing unique attributes of equipment, and increasing comparison proportion when similarity comparison is performed;
and a data merging module: merging data source data with name similarity larger than a threshold value;
and the sending storage module is used for: transmitting the combined data to a data warehouse for storage;
and (3) a calling module: and in response to triggering data sharing, invoking the data to be shared according to the metadata of the data warehouse.
7. A computer readable storage medium storing one or more programs, characterized by: the one or more programs include instructions, which when executed by a computing device, cause the computing device to perform any of the methods of claims 1-5.
8. A computing device, characterized by: comprising the steps of (a) a step of,
one or more processors, memory, and one or more programs, wherein one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs comprising instructions for performing any of the methods of claims 1-5.
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