CN112087675A - Quasi-real-time data acquisition system and method adaptive to competitive power market - Google Patents
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- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
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- G01R22/061—Details of electronic electricity meters
- G01R22/063—Details of electronic electricity meters related to remote communication
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- H04Q2209/00—Arrangements in telecontrol or telemetry systems
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Abstract
A quasi-real-time data acquisition system adapted for a competitive power market, the system comprising: distributed data collection unit, concentrated data collection unit and collection master station, distributed data collection unit is connected with intelligent ammeter through its inside down communication module, and data item parameter and task execution parameter are gathered in the configuration module configuration of collection task and collection scheme through its inside collection task, include: collecting tasks in quasi-real time, 15-minute curve tasks, daily freezing data tasks and monthly freezing data tasks; the centralized data collection unit is connected with the acquisition master station through a file conversion and uplink communication module in the centralized data collection unit; the centralized data collection unit and the distributed data collection units are connected through an HPLC local communication network composed of an HPLC communication main module in the centralized data collection unit and an HPLC communication sub-module in the distributed data collection unit. The invention realizes the concurrent asynchronous reading, greatly improves the timeliness of the electricity data and has good application prospect.
Description
Technical Field
The invention belongs to the field of intelligent measurement and communication, and particularly relates to a quasi-real-time data acquisition system and a quasi-real-time data acquisition method suitable for a competitive power market.
Background
A new round of electric power system in China is reformed to start the construction of the electric power market. The new electricity is improved by gradually releasing electricity selling services to further introduce competition, the running mechanism of the electric power market is perfected, more market main bodies are encouraged to participate in trading, and the decisive role of the market in resource allocation is fully played. Along with the continuous release of the spot market construction and the power selling market, the number of market main bodies is continuously increased, the types of the main bodies tend to be diversified, the market competition is continuously enhanced, and the price mechanism is more flexible. Meanwhile, with the power generation and the internet surfing of high-proportion renewable energy sources, a large amount of distributed energy sources, electric vehicles, energy storage devices and other multi-load access are carried out, flexible load resources on the demand side are used for participating in power grid interaction, and the method becomes an important regulation and control means of the power grid in the market environment. Time-sharing price signals are generated in the market to guide network load interaction, and users respond to system price and power grid excitation to flexibly adjust own power consumption requirements.
The current electricity utilization information acquisition system supports the acquisition of daily freezing data, monthly freezing data and 15-minute historical curve data of the previous day, and the acquisition of the minute-level quasi-real-time data is difficult to realize due to the existing local communication network architecture of full carrier waves and half carrier waves, the centralized scheduling acquisition mode based on a concentrator and the limitation of the communication speed of a carrier communication module and an electric energy meter serial port. Due to the fact that the number of user nodes in local communication is large, a local communication network is prone to running load interference, collection efficiency of electricity data collected based on task scheduling of a centralized meter reading terminal under traditional full-carrier mode and half-carrier mode network architectures is low, and quasi-real-time data collection difficulty is large. At present, in the implementation process of user side demand response engineering, an additional data acquisition module is mainly installed, and remote communication units such as 4G are directly connected with a main station, so that the repeated construction cost is huge.
The technical field needs a quasi-real-time data acquisition system and a method suitable for a competitive power market, which can be compatible with the existing power utilization information acquisition system, and can report power utilization data in a quasi-real-time manner, thereby providing technical support for the construction of the competitive power market.
Disclosure of Invention
In order to solve the defects in the prior art, the invention aims to provide a quasi-real-time data acquisition system and a method suitable for a competitive power market, and solve the problem that the data acquisition real-time performance of the conventional power utilization information acquisition system is poor.
The invention adopts the following technical scheme. A quasi-real-time data acquisition system adapted for a competitive power market, comprising: distributed data collection unit, concentrated data collection unit and collection master station, distributed data collection unit is connected with intelligent ammeter through its inside down communication module, and data item parameter and task execution parameter are gathered in the configuration module configuration of collection task and collection scheme through its inside collection task, include: collecting tasks in quasi-real time, 15-minute curve tasks, daily freezing data tasks and monthly freezing data tasks; the centralized data collection unit is connected with the acquisition master station through a file conversion and uplink communication module in the centralized data collection unit; the centralized data collection unit and the distributed data collection units are connected through an HPLC local communication network composed of an HPLC communication main module in the centralized data collection unit and an HPLC communication sub-module in the distributed data collection unit.
Preferably, the collection task and collection scheme configuration module of the distributed data collection unit is at least further configured to configure a collection scheme number, a storage depth, a collection mode, an electricity meter set, a storage time scale and an electricity consumption data identifier.
Preferably, the distributed data aggregation unit further includes: and the starting quasi-real-time data acquisition task module is connected with the acquisition task and acquisition scheme configuration module and is used for starting the quasi-real-time acquisition task, the 15-minute curve task, the daily frozen data task and the monthly frozen data task according to a set sequence.
Preferably, the quasi-real-time data acquisition task module is started to receive the clock message of the HPLC communication main module through the HPLC communication sub-module.
Preferably, the data storage module of the centralized data collection unit and the data storage module of the distributed data collection unit both adopt FLASH memories.
Preferably, the centralized data gathering unit includes: and the data point copying module is used for starting data reporting of the data storage module in the distributed data collection unit through the roll call copying message.
Preferably, the HPLC communication main module of the centralized data collection unit is configured to perform data interaction with the data point reading module in a concurrent meter reading mode, and the HPLC communication main module supports multiple communication baud rate parameters, and preferentially uses a higher communication baud rate parameter for communication.
Preferably, the file conversion and uplink communication module in the centralized data collection unit is used for generating a compressed file from data in the data storage module of the centralized data collection unit, and performing data interaction with the acquisition master station.
The invention also provides a quasi-real-time data acquisition method based on the quasi-real-time data acquisition system adaptive to the competitive power market, which comprises the following steps:
step 1, a distributed data collection unit is powered on, and a downlink communication module of the distributed data collection unit collects an electric energy meter clock and uses the electric energy meter clock as a distributed data collection unit clock;
step 2, the HPLC communication submodule of the distributed data collection unit and the HPLC communication main module of the centralized data collection unit perform networking and clock synchronous interaction, and if the clock message of the HPLC communication main module is received, the quasi-real-time data collection task starting module of the distributed data collection unit starts a quasi-real-time data task;
step 3, the centralized data collection unit and the distributed data collection unit use an HPLC communication channel to carry out data click interaction;
and 4, the centralized data collection unit collects the point reading data of the distributed data collection units, generates a file and reports the file to the acquisition master station.
Preferably, step 2 further comprises: and starting the 15-minute curve task, the daily freezing data task and the monthly freezing task according to the set starting sequence.
Preferably, the interaction of the point data in step 3 specifically includes:
step 3.1, a data point copying module of the centralized data collection unit sends a roll call opening message to the distributed data collection unit;
step 3.2, after receiving the roll call opening message, the distributed data collection unit sends a data reporting message to the data point copying module;
step 3.3, after receiving the data report message, the data point copying module sends a report confirmation message to the distributed data collection unit;
step 3.4, after the distributed data collection unit receives the report confirmation message, if data needs to be reported continuously, the distributed data collection unit continuously sends the data report message to the data point copying module, and returns to the step 3.3; if no data needs to be reported continuously, sending a data reporting denial/no subsequent frame message to the data point copying module;
step 3.5, after the data point copying module receives the message of 'data reporting denial/no subsequent frame', the data point copying module sends a 'roll call closing' message to the distributed data collection unit;
step 3.6, after receiving the roll call closing message, the distributed data collection unit sends a roll call closing confirmation message to the data point copying module; and 3, completing one round of roll calling and reading, and returning to the step 3.1.
Preferably, in step 3, when the distributed data collection unit sends a "data report" message to the centralized data collection unit, if the communication is abnormal and the reported data is abnormally lost, the data point copying module stops the local round of data copying task according to timeout processing, and returns to step 3.1, and in the next round of roll call copying, the distributed data collection unit resends the "data report" message that is not successfully reported in the previous round.
Preferably, in step 3, when the centralized data collection unit sends a "report confirmation" message to the distributed data collection unit, if communication abnormality occurs and reported data is lost abnormally, the data point copying module stops the roll name copying in the current round according to timeout processing, and returns to step 3.1, and in the next round of roll name copying, the distributed data collection unit resends the "data report" message which is not reported successfully in the previous round.
Preferably, in step 4, the centralized data collection unit reports to the acquisition master station by using a data reporting reduced protocol, and the data reporting reduced protocol performs framing according to the order of the record-type object attribute descriptor OAD, the record selection descriptor RSD, a row of record N columns of attribute descriptors ROAD, and the response data.
Preferably, in step 4, the response data is framed in the order of the record column data type, the plurality of record data values.
Compared with the prior art, the method has the advantages that the collection tasks and the collection schemes are transferred to the distributed data collection modules, the distributed data collection modules are copied through the concentrated data collection units, the concentrated data collection units generate files to be reported to the collection master station, the concentrated data collection units and the distributed data collection modules are asynchronously copied, timeliness of electricity utilization data is greatly improved, and the method has a good application prospect.
Drawings
FIG. 1 is a system architecture of a quasi-real-time electricity consumption data acquisition system and method for a competitive power market;
FIG. 2 is a first scenario of clickthrough data interaction between a centralized data collection unit and a distributed data collection unit using HPLC communication channels;
FIG. 3 is a second scenario in which the centralized data aggregation unit and the distributed data aggregation unit perform clickthrough data interaction using HPLC communication channels;
FIG. 4 is a third scenario in which the centralized data aggregation unit and the distributed data aggregation unit perform clickthrough data interaction using HPLC communication channels;
FIG. 5 is a quasi-real-time power consumption data acquisition method based on a quasi-real-time power consumption data acquisition system for an adaptive competitive power market.
Detailed Description
The present application is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present application is not limited thereby.
Example 1: quasi-real-time data acquisition system adaptive to competitive power market
As shown in fig. 1, the present invention provides a quasi-real-time data acquisition system adapted to a competitive power market, comprising: the system comprises a distributed data collection unit, a centralized data collection unit and an acquisition master station.
The distributed data collection unit includes: the system comprises a downlink communication module, a module for starting a quasi-real-time data acquisition task, a module for configuring an acquisition task and an acquisition scheme, a data storage module and an HPLC communication sub-module.
The centralized data collection unit includes: the device comprises a file conversion and uplink communication module, a data point copying module, a data storage module and an HPLC communication main module.
The distributed data collection unit is connected with the intelligent electric energy meter through the downlink communication module, the concentrated data collection unit is connected with the acquisition main station through the file conversion and the uplink communication module, and the concentrated data collection unit and the distributed data collection units are connected through an HPLC local communication network formed by an HPLC communication main module and an HPLC communication sub-module.
The person skilled in the art can configure the downlink communication module of the distributed data aggregation unit according to the actual situation at will, and preferably, but not limited to, the downlink communication module is RS485 communication or other communication modes.
The acquisition task and acquisition scheme configuration module of the distributed data collection unit is used for configuring acquisition data item parameters and task execution parameters, including but not limited to a quasi-real-time acquisition task, a 15-minute curve task, a daily frozen data task and a monthly frozen data task; and acquiring scheme numbers, storage depth, acquisition modes, ammeter sets, storage time scales and electricity utilization data identifications. Table 1 shows a task configuration scheme, table 2 shows a three-phase table acquisition scheme, and table 3 shows a single-phase user acquisition scheme.
TABLE 1 task configuration scheme
| Serial number | Task ID | Execution frequency | Type of scenario | Plan numbering | Time delay | Description of the invention |
| 1 | 1 | 1 minute | General acquisition scheme | 1 | 0min | Three-phase meter acquisition task |
| 2 | 2 | 1 day | General acquisition scheme | 2 | 5min | Three-phase meter acquisition task |
| 3 | 3 | 1 month | General acquisition scheme | 3 | 5min | Three-phase meter acquisition task |
| 4 | 4 | 15 minutes | General acquisition scheme | 4 | 5min | Three-phase meter acquisition task |
| 5 | 5 | 1 minute | General acquisition scheme | 5 | 0min | Single-phase meter acquisition task |
| 6 | 6 | 1 day | General acquisition scheme | 6 | 5min | Single-phase meter acquisition task |
| 7 | 7 | 1 month | General acquisition scheme | 7 | 5min | Single-phase meter acquisition task |
| 8 | 8 | 15 minutes | General acquisition scheme | 8 | 5min | Single-phase meter acquisition task |
TABLE 2 three-phase Meter Collection protocol
TABLE 3 Single-phase user acquisition scheme
The functions of the module for starting the quasi-real-time data acquisition task of the distributed data collection unit comprise: after the distributed data collection unit is powered on, the downlink communication module collects the clock of the electric energy meter and uses the clock as the clock of the distributed data collection unit, and a starting quasi-real-time data collection task module of the distributed data collection unit starts a 15-minute curve task, a daily freezing data task and a monthly freezing task; and meanwhile, networking and clock synchronous interaction are carried out between the HPLC communication submodule of the distributed data collection unit and the HPLC communication main module of the concentrated data collection unit, and after a clock message of the HPLC communication main module is received, a quasi-real-time data collection task starting module of the distributed data collection unit starts a quasi-real-time data task.
The clock synchronization packet extension is shown in table 4 below:
table 4 new message ID
| Message ID | Means of | Message port number |
| 0x0070 | Clock synchronization message | 0x11 |
The clock synchronization message format is shown in table 5 below:
TABLE 5 HPLC COMMUNICATION MODULE CLOCK SYNCHRONIZATION MESSAGES FORMAT
Protocol version number: the version is fixed to take value 1.
Message header length: indicating the message length.
RTC clock: the RTC clock representing the time when the message was created, BCD code, and format YYMMDDhhmmss (Small endian transmission, no "X week" data bits).
NTB time: the time of the entire network NTB at the moment of creating the message, unit NTB.
The data storage module of the distributed data collection unit is used for storing the data which are required to be copied and read in the acquisition task and acquisition scheme configuration module, the FLASH memory is used for storing the data, the data are not lost after power failure, and the storage mode adopts first-in first-out and circular storage.
The data point copying module of the centralized data collection unit is used for starting data report of the data storage module in the distributed data collection unit through the roll call copying message, reporting a 15-minute curve task, a daily frozen data task and a monthly frozen data task by adopting an object-oriented data exchange protocol conventional report protocol, reporting a quasi-real-time data task by adopting a simplified report protocol, and executing data copying and response of data point copying according to a data copying interaction flow.
The HPLC communication main module of the centralized data collection unit is used for carrying out data interaction with the data point reading module in a concurrent meter reading mode, the communication baud rate parameter A is defaulted in the HPLC communication main module, the centralized data collection unit inquires whether the HPLC communication main module supports the higher baud rate B, and if the communication baud rate parameter A supports the higher baud rate B, the centralized data collection unit automatically adjusts the baud rate parameter of the HPLC communication main module to be B.
More specifically, data interaction is carried out between the HPLC communication main module and the data point reading module through a concurrent meter reading mode, the communication baud rate parameter 1 is defaulted to 9600bps in the HPLC communication main module, the centralized data collection unit is expanded to 115200bps by inquiring whether the HPLC communication main module supports the higher baud rate parameter 2, and if the communication baud rate parameter is supported, the baud rate parameter of the HPLC communication main module is automatically adjusted to be the parameter 2, namely, the parameter 115200bps by the centralized data collection unit.
And the data storage module of the centralized data collection unit is used for storing the data point copied back by the data point copying module in a FLASH memory.
The file conversion and uplink communication module of the centralized data collection unit is used for generating a compressed file from data in the data storage module of the centralized data collection unit according to a configurable file format, and supporting data acquisition and reporting of file transmission.
The file contains data items: datatime, 20000201 (phase a voltage), 20000202 (phase B voltage), 20000203 (phase C voltage), 20010201 (phase a current), 20010202 (phase B current), 20010203 (phase C current), 20010400 (zero line current), and the like.
The first JSONObject of the JSONARray content of the real-time data represents the column head of a measuring point data column, the coluumhead is used as a key value, and the OAD code + (Chinese meaning) of a data item is used as a value; the JSONArray is the station data starting with the second JSONObject. The data format is as follows:
example 2: quasi-real-time data acquisition method adaptive to competitive power market
A quasi-real-time data acquisition method of a quasi-real-time data acquisition system adapted to a competitive power market, based on embodiment 1, includes the steps of:
step 1, a distributed data collection unit is powered on, and a downlink communication module of the distributed data collection unit collects an electric energy meter clock and uses the electric energy meter clock as a distributed data collection unit clock;
and 2, networking and clock synchronous interaction are carried out between the HPLC communication submodule of the distributed data collection unit and the HPLC communication main module of the concentrated data collection unit, and after the clock message of the HPLC communication main module is received, the quasi-real-time data collection task starting module of the distributed data collection unit starts a quasi-real-time data task. The step 2 further comprises: starting a 15-minute curve task, a daily freezing data task and a monthly freezing task. It should be noted that the starting sequence of the tasks can be set arbitrarily by those skilled in the art according to actual requirements in the field, and a preferred but non-limiting embodiment is to start the tasks according to the priority sequence of the tasks.
And 3, performing point reading data interaction between the centralized data collection unit and the distributed data collection unit by using an HPLC communication channel.
A first situation that the centralized data collection unit and the distributed data collection unit perform the data transcription interaction by using the HPLC communication channel is shown in fig. 2, and the data transcription interaction in step 3 specifically includes:
step 3.1, a data point copying module of the centralized data collection unit sends a roll call opening message to the distributed data collection unit;
step 3.2, after receiving the roll call opening message, the distributed data collection unit sends a data reporting message to the data point copying module;
step 3.3, after receiving the data report message, the data point copying module sends a report confirmation message to the distributed data collection unit;
step 3.4, after the distributed data collection unit receives the report confirmation message, if data needs to be reported continuously, the distributed data collection unit continuously sends the data report message to the data point copying module, and returns to the step 3.3; if no data needs to be reported continuously, sending a data reporting denial/no subsequent frame message to the data point copying module;
step 3.5, after the data point copying module receives the message of 'data reporting denial/no subsequent frame', the data point copying module sends a 'roll call closing' message to the distributed data collection unit;
step 3.6, after receiving the roll call closing message, the distributed data collection unit sends a roll call closing confirmation message to the data point copying module; and 3, completing one round of roll calling and reading, and returning to the step 3.1.
The second situation that the centralized data collection unit and the distributed data collection unit use the HPLC communication channel for data logging interaction is shown in fig. 3, when the distributed data collection unit sends a "data report" message to the centralized data collection unit, if communication is abnormal, the reported data is lost abnormally, and the data point logging module stops the data logging task according to timeout processing, and returns to step 3.1.
A third situation that the centralized data collection unit and the distributed data collection unit perform data reading interaction by using an HPLC communication channel is shown in fig. 4, when the centralized data collection unit sends a "report confirmation" message to the distributed data collection unit, if communication is abnormal, the report data is lost abnormally, the data point reading module stops the roll name reading in the current round according to timeout processing, and the step returns to step 3.1.
As shown in fig. 3 and 4, in the next round of roll call reading, the distributed data aggregation unit retransmits the "data report" message that was not reported successfully in the previous round.
And 4, the centralized data collection unit collects the point reading data of the distributed data collection units, generates a file and reports the file to the acquisition master station.
The data reporting reduction protocol disassembles the composite data into single data items, and then frames the data items according to the SEQUENCE OF 'record type object attribute descriptor OAD', 'record selection descriptor RSD', 'record N columns OF attribute descriptors ROAD' and 'response data', wherein the response data are framed according to the SEQUENCE OF 'record column data type A-SimplifyRecordRowDataType' and 'M record data values SEQUENCE OF A-SimplifyRecordRow'.
The newly designed simplified protocol architecture also restricts the application, special agreement needs to be carried out on the composite data in the field of power consumption information acquisition, and the transmission efficiency can be improved by skillfully applying the transmission mode.
The simplified protocol is as follows:
A-ResultSimplifyRecord definition:
the main example messages for simplified data reporting are as follows:
// Block 1 Table 10 records TSA 0x000000000001
1111222222223333333344445555// REC1 (voltage value: 0x1111, current: 0x2222222, zero sequence current: 0x 3333333333, total power factor: 0x4444, single phase power factor: 0x5555)
11 11 22 22 22 22 33 33 33 33 44 44 55 55//REC2
FF FF 22222222 FF FF FF FF FF FF FF FF// REC3 (Voltage value: NULL, Current: 0x2222222, zero sequence Current: NULL, Total Power factor: NULL, Single phase Power factor: NULL)
11 11 22 22 22 22 33 33 33 33 44 44 55 55//REC4
11 11 22 22 22 22 33 33 33 33 44 44 55 55//REC5
11 11 22 22 22 22 33 33 33 33 44 44 55 55//REC6
FF FF FF FF FF FF FF FF FF FF FF FF FF FF// REC7 (voltage value: NULL, current: NULL, zero sequence current: NULL, total power factor: NULL, single phase power factor: NULL)
11 11 22 22 22 22 33 33 33 33 44 44 55 55//REC8
11 11 22 22 22 22 33 33 33 33 44 44 55 55//REC9
11 11 22 22 22 22 33 33 33 33 44 44 55 55//REC10
// Block 2 Table 10 records TSA 0x000000000002
1111222222223333333344445555// REC1 (voltage value: 0x1111, current: 0x2222222, zero sequence current: 0x 3333333333, total power factor: 0x4444, single phase power factor: 0x5555)
11 11 22 22 22 22 33 33 33 33 44 44 55 55//REC2
FF FF 22222222 FF FF FF FF FF FF FF FF// REC3 (Voltage value: NULL, Current: 0x2222222, zero sequence Current: NULL, Total Power factor: NULL, Single phase Power factor: NULL)
11 11 22 22 22 22 33 33 33 33 44 44 55 55//REC4
11 11 22 22 22 22 33 33 33 33 44 44 55 55//REC5
11 11 22 22 22 22 33 33 33 33 44 44 55 55//REC6
FF FF FF FF FF FF FF FF FF FF FF FF FF FF// REC7 (voltage value: NULL, current: NULL, zero sequence current: NULL, total power factor: NULL, single phase power factor: NULL)
11 11 22 22 22 22 33 33 33 33 44 44 55 55//REC8
11 11 22 22 22 22 33 33 33 33 44 44 55 55//REC9
FF FF FF FF FF FF FF FF FF FF FF FF FF FF// REC10 (voltage value: NULL, current: NULL, zero sequence current: NULL, total power factor: NULL, single phase power factor: NULL)
// block 3 Table 10 records TSA 0x000000000003
1111222222223333333344445555// REC1 (voltage value: 0x1111, current: 0x2222222, zero sequence current: 0x 3333333333, total power factor: 0x4444, single phase power factor: 0x5555)
11 11 22 22 22 22 33 33 33 33 44 44 55 55//REC2
FF FF 22222222 FF FF FF FF FF FF FF FF// REC3 (Voltage value: NULL, Current: 0x2222222, zero sequence Current: NULL, Total Power factor: NULL, Single phase Power factor: NULL)
11 11 22 22 22 22 33 33 33 33 44 44 55 55//REC4
11 11 22 22 22 22 33 33 33 33 44 44 55 55//REC5
FF FF FF FF FF FF FF FF FF FF FF FF FF FF// REC6 (voltage value: NULL, current: NULL, zero sequence current: NULL, total power factor: NULL, single phase power factor: NULL)
FF FF FF FF FF FF FF FF FF FF FF FF FF FF// REC7 (voltage value: NULL, current: NULL, zero sequence current: NULL, total power factor: NULL, single phase power factor: NULL)
11 11 22 22 22 22 33 33 33 33 44 44 55 55//REC8
11 11 22 22 22 22 33 33 33 33 44 44 55 55//REC9
11 11 22 22 22 22 33 33 33 33 44 44 55 55//REC10
00 00B9 7E 16
The system and the method have the advantages that compared with the prior art, the acquisition task and the acquisition scheme are transferred to the distributed data collection modules, the distributed data collection modules are point-copied through the concentrated data collection unit, the quasi-real-time acquisition task is reported by a simplified protocol in the point-copying interaction process, the concentrated reporting of a plurality of electric energy meters and a plurality of data items is realized, an HPLC communication channel is fully utilized, a file is generated by the concentrated data collection unit and reported to the acquisition master station, the concurrent asynchronous reading of the concentrated data collection unit and the distributed data collection modules is realized, the timeliness of the electricity data is greatly improved, and the system and the method have good application prospects. Meanwhile, a simplified protocol architecture is newly designed, application is also restricted, special agreement needs to be carried out on the composite data in the field of power utilization information acquisition, and the transmission efficiency can be improved by skillfully applying the transmission mode.
The present applicant has described and illustrated embodiments of the present invention in detail with reference to the accompanying drawings, but it should be understood by those skilled in the art that the above embodiments are merely preferred embodiments of the present invention, and the detailed description is only for the purpose of helping the reader to better understand the spirit of the present invention, and not for limiting the scope of the present invention, and on the contrary, any improvement or modification made based on the spirit of the present invention should fall within the scope of the present invention.
Claims (15)
1. A quasi-real-time data acquisition system adapted for a competitive power market, comprising: distributed data collection unit, concentrated data collection unit and collection master station, its characterized in that:
the distributed data collection unit is connected with the intelligent electric energy meter through a downlink communication module inside the distributed data collection unit, and configures collected data item parameters and task execution parameters through a collection task and collection scheme configuration module inside the distributed data collection unit, wherein the distributed data collection unit comprises: collecting tasks in quasi-real time, 15-minute curve tasks, daily freezing data tasks and monthly freezing data tasks;
the centralized data collection unit is connected with the acquisition master station through a file conversion and uplink communication module in the centralized data collection unit;
the centralized data collection unit and the distributed data collection units are connected through an HPLC local communication network composed of an HPLC communication main module in the centralized data collection unit and an HPLC communication sub-module in the distributed data collection unit.
2. The quasi-real-time data collection system for a competitive power market as claimed in claim 1 wherein:
the acquisition task and acquisition scheme configuration module of the distributed data collection unit is at least used for configuring an acquisition scheme number, a storage depth, an acquisition mode, an electric meter set, a storage time scale and an electricity utilization data identifier.
3. The quasi-real-time data acquisition system adapted for a competitive power market as claimed in claim 2 wherein:
the distributed data collection unit further includes: and the starting quasi-real-time data acquisition task module is connected with the acquisition task and acquisition scheme configuration module and is used for starting the quasi-real-time acquisition task, the 15-minute curve task, the daily frozen data task and the monthly frozen data task according to a set sequence.
4. The quasi-real-time data collection system for a competitive power market as claimed in claim 1 wherein:
and the quasi-real-time data acquisition task module is started to receive the clock message of the HPLC communication main module through the HPLC communication sub-module.
5. A quasi-real time data acquisition system to accommodate a competitive power market as claimed in any one of claims 1 to 4 wherein:
the data storage modules of the centralized data collection unit and the data storage modules of the distributed data collection unit both adopt FLASH memories.
6. A quasi-real time data collection system to accommodate a competitive power market as claimed in any one of claims 1 to 5 wherein:
the centralized data collection unit includes: and the data point copying module is used for starting data reporting of the data storage module in the distributed data collection unit through the roll call copying message.
7. The quasi real-time data collection system adapted for competitive power markets of claims 1 to 6, wherein:
the HPLC communication main module of the centralized data collection unit is used for carrying out data interaction with the data point reading module through a concurrent meter reading mode, supports various communication baud rate parameters, and preferentially uses higher communication baud rate parameters for communication.
8. The quasi real-time data collection system adapted for competitive power markets of claims 1 to 7, wherein:
and the file conversion and uplink communication module in the centralized data collection unit is used for generating a compressed file from the data in the data storage module of the centralized data collection unit and performing data interaction with the acquisition master station.
9. A quasi real-time data acquisition method of a quasi real-time data acquisition system adapted to a competitive power market based on any one of claims 1 to 8, characterized in that: the method comprises the following steps:
step 1, a distributed data collection unit is powered on, and a downlink communication module of the distributed data collection unit collects an electric energy meter clock and uses the electric energy meter clock as a distributed data collection unit clock;
step 2, the HPLC communication submodule of the distributed data collection unit and the HPLC communication main module of the centralized data collection unit perform networking and clock synchronous interaction, and if the clock message of the HPLC communication main module is received, the quasi-real-time data collection task starting module of the distributed data collection unit starts a quasi-real-time data task;
step 3, the centralized data collection unit and the distributed data collection unit use an HPLC communication channel to carry out data click interaction;
and 4, the centralized data collection unit collects the point reading data of the distributed data collection units, generates a file and reports the file to the acquisition master station.
10. The quasi real-time data acquisition method of claim 9, wherein:
the step 2 further comprises: and starting the 15-minute curve task, the daily freezing data task and the monthly freezing task according to the set starting sequence.
11. The quasi real-time data acquisition method according to claim 9 or 10, wherein:
the data copying interaction in the step 3 specifically comprises the following steps:
step 3.1, a data point copying module of the centralized data collection unit sends a roll call opening message to the distributed data collection unit;
step 3.2, after receiving the roll call opening message, the distributed data collection unit sends a data reporting message to the data point copying module;
step 3.3, after receiving the data report message, the data point copying module sends a report confirmation message to the distributed data collection unit;
step 3.4, after the distributed data collection unit receives the report confirmation message, if data needs to be reported continuously, the distributed data collection unit continuously sends the data report message to the data point copying module, and returns to the step 3.3; if no data needs to be reported continuously, sending a data reporting denial/no subsequent frame message to the data point copying module;
step 3.5, after the data point copying module receives the message of 'data reporting denial/no subsequent frame', the data point copying module sends a 'roll call closing' message to the distributed data collection unit;
step 3.6, after receiving the roll call closing message, the distributed data collection unit sends a roll call closing confirmation message to the data point copying module; and 3, completing one round of roll calling and reading, and returning to the step 3.1.
12. The quasi real-time data acquisition method according to any one of claims 9 to 11, wherein:
in step 3, when the distributed data collection unit sends a data report message to the centralized data collection unit, if abnormal communication occurs and the reported data is lost abnormally, the data point copying module stops the data point copying task in the round according to overtime processing, the step 3.1 is returned, and in the next round of roll call copying, the distributed data collection unit resends the data report message which is not reported successfully in the previous round.
13. The quasi real-time data acquisition method according to any one of claims 9 to 12, wherein:
in step 3, when the centralized data collection unit sends a report confirmation message to the distributed data collection unit, if abnormal communication occurs and reported data is lost abnormally, the data point copying module stops the roll name copying in the current round according to overtime processing, the step 3.1 is returned, and in the next round of roll name copying, the distributed data collection unit sends a data report message which is not reported successfully in the previous round again.
14. The quasi real-time data acquisition method according to any one of claims 9 to 13, wherein:
in step 4, the centralized data collection unit reports to the acquisition master station by using a data reporting simplified protocol, and the data reporting simplified protocol performs framing according to the sequence of the record type object attribute descriptor OAD, the record selection descriptor RSD, a row of record N columns of attribute descriptors ROAD and the response data.
15. The quasi real-time data acquisition method according to any one of claims 9 to 14, wherein:
in step 4, the response data is framed according to the record column data type and the sequence of the plurality of record data values.
Priority Applications (4)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010965981.9A CN112087675A (en) | 2020-09-15 | 2020-09-15 | Quasi-real-time data acquisition system and method adaptive to competitive power market |
| AU2021269381A AU2021269381A1 (en) | 2020-09-15 | 2021-09-14 | Quasi-real-time data collection system and method for competitive power market |
| PCT/CN2021/118341 WO2022057798A1 (en) | 2020-09-15 | 2021-09-14 | Quasi-real-time data collection system and method adapted to competitive power market |
| US17/611,174 US11821929B2 (en) | 2020-09-15 | 2021-09-14 | Quasi-real-time data collection system and method for competitive power market |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2022057798A1 (en) * | 2020-09-15 | 2022-03-24 | 国网江苏省电力有限公司营销服务中心 | Quasi-real-time data collection system and method adapted to competitive power market |
| CN115276720A (en) * | 2022-09-26 | 2022-11-01 | 北京智芯半导体科技有限公司 | High-speed carrier data transmission device and method and electronic equipment |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2022057798A1 (en) * | 2020-09-15 | 2022-03-24 | 国网江苏省电力有限公司营销服务中心 | Quasi-real-time data collection system and method adapted to competitive power market |
| CN115276720A (en) * | 2022-09-26 | 2022-11-01 | 北京智芯半导体科技有限公司 | High-speed carrier data transmission device and method and electronic equipment |
| CN115276720B (en) * | 2022-09-26 | 2023-01-20 | 北京智芯半导体科技有限公司 | High-speed carrier data transmission device and method and electronic equipment |
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