CN112087675A - Quasi-real-time data acquisition system and method adaptive to competitive power market - Google Patents

Abstract

A quasi-real-time data acquisition system adapted to the competitive power market, the system comprises: a distributed data collection unit, a centralized data collection unit and a collection master station, the distributed data collection unit is connected with a smart electric energy meter through its internal downlink communication module, Through its internal collection task and collection scheme configuration module, configure the parameters of the collected data items and task execution parameters, including: quasi-real-time collection tasks, 15-minute curve tasks, daily frozen data tasks, monthly frozen data tasks; centralized data collection unit through its internal The file conversion and uplink communication module is connected with the acquisition master station; the centralized data collection unit and several distributed data collection units are composed of the HPLC communication main module inside the centralized data collection unit and the HPLC communication sub-module inside the distributed data collection unit. HPLC local communication network connection. The invention realizes concurrent asynchronous reading, greatly improves the timeliness of electricity consumption data, and has good application prospects.

Description

A quasi-real-time data acquisition system and method adapting to the competitive power market

technical field

The invention belongs to the field of intelligent measurement and communication, and more particularly, relates to a quasi-real-time data acquisition system and method suitable for a competitive power market.

Background technique

my country's new round of power system reform has started the construction of the power market. The new electricity reform plans to further introduce competition by gradually liberalizing the electricity sales business, improve the operation mechanism of the electricity market, encourage more market players to participate in transactions, and give full play to the decisive role of the market in resource allocation. With the construction of the spot market and the continuous liberalization of the electricity sales market, the number of market players continues to increase, the types of players tend to be diversified, the market competition continues to increase, and the price mechanism is more flexible. At the same time, with a high proportion of renewable energy power generation coming online, a large number of distributed energy sources, electric vehicles, energy storage devices and other multiple loads are connected, and the use of flexible load resources on the demand side to participate in grid interaction will become an important control method for the power grid in the market environment. . Time-of-use price signals will appear in the market to guide grid-load interaction, users will respond to system prices and grid incentives, and flexibly adjust their own electricity demand.

The current electricity consumption information collection system supports the collection of daily frozen data, monthly frozen data, and 15-minute historical curve data of the previous day. For minute-level quasi-real-time data collection, the existing full-carrier and half-carrier local communication networks It is difficult to realize due to the structure, unified scheduling and acquisition mode based on the concentrator and the limitation of the communication speed between the carrier communication module and the serial port of the electric energy meter. Due to the large number of user nodes in local communication, the local communication network is susceptible to operating load interference. The traditional full-carrier mode and half-carrier mode network architecture based on centralized reading terminal task scheduling to collect electricity data collection efficiency is low, and quasi-real-time data collection is difficult. big. At present, during the implementation of the user-side demand response project, the main station is directly connected to the main station by installing additional data acquisition modules and using 4G and other remote communication units, resulting in huge repeated construction costs.

There is an urgent need in the technical field of a quasi-real-time data acquisition system and method suitable for the competitive power market, which can be compatible with the existing power consumption information acquisition system, and at the same time realize the quasi-real-time reporting of the power consumption data, so as to provide technology for the construction of the competitive power market. support.

SUMMARY OF THE INVENTION

In order to solve the deficiencies in the prior art, the purpose of the present invention is to provide a quasi-real-time data acquisition system and method suitable for the competitive power market, overcoming the problem of poor real-time data acquisition in the existing power consumption information acquisition system.

The present invention adopts the following technical solutions. A quasi-real-time data acquisition system adapting to the competitive power market, comprising: a distributed data collection unit, a centralized data collection unit and a collection master station, the distributed data collection unit is connected with a smart electric energy meter through its internal downlink communication module, and Its internal collection task and collection scheme configuration module configures the parameters of the collected data items and task execution parameters, including: quasi-real-time collection tasks, 15-minute curve tasks, daily frozen data tasks, monthly frozen data tasks; centralized data collection unit through its internal The file conversion and uplink communication module is connected with the acquisition master station; the centralized data collection unit and several distributed data collection units are composed of the HPLC communication main module inside the centralized data collection unit and the HPLC communication sub-module inside the distributed data collection unit. Local communication network connection.

Preferably, the collection task and collection scheme configuration module of the distributed data collection unit is at least further configured to configure the collection scheme number, storage depth, collection method, electricity meter set, storage time stamp and electricity consumption data identifier.

Preferably, the distributed data collection unit further includes: a quasi-real-time data collection task module for starting the quasi-real-time data collection task module, which is connected to the collection task and collection scheme configuration module, and is used to start the quasi-real-time collection task according to the set order, the 15-minute curve task, the daily Freeze data tasks, freeze data tasks monthly.

Preferably, the quasi-real-time data acquisition task module is activated to receive the clock message of the HPLC communication main module via the HPLC communication sub-module.

Preferably, both the data storage module of the centralized data collection unit and the data storage module of the distributed data collection unit use FLASH memory.

Preferably, the centralized data collection unit includes: a data point copying module, configured to initiate data reporting by the data storage module in the distributed data collection unit by calling and copying the message.

Preferably, the HPLC communication main module of the centralized data collection unit is used for data interaction with the data point reading module through the concurrent meter reading mode. The HPLC communication main module supports a variety of communication baud rate parameters, and a higher communication baud rate is preferentially used parameters to communicate.

Preferably, the file conversion and uplink communication module in the centralized data collection unit is used to generate compressed files from the data in the data storage module of the centralized data collection unit, and perform data interaction with the collection master station.

The present invention also provides a quasi-real-time data acquisition method based on the quasi-real-time data acquisition system adapted to the competitive power market, comprising the following steps:

Step 1, the distributed data collection unit is powered on, the downlink communication module of the distributed data collection unit collects the power meter clock, and uses it as the distributed data collection unit clock;

Step 2, the HPLC communication sub-module of the distributed data collection unit and the HPLC communication main module of the centralized data collection unit carry out networking and clock synchronization interaction, if after receiving the clock message of the HPLC communication main module, then the distributed data collection unit The starting quasi-real-time data acquisition task module starts the quasi-real-time data task;

Step 3, the centralized data collection unit and the distributed data collection unit use the HPLC communication channel to carry out point copy data interaction;

Step 4, the centralized data collection unit summarizes the point-copying data of several distributed data collection units, generates a file and reports it to the collection master station.

Preferably, step 2 further includes: starting the 15-minute curve task, the daily data freezing task, and the monthly freezing task according to the set start sequence.

Preferably, the click-to-copy data interaction in step 3 specifically includes:

Step 3.1, the data point copying module of the centralized data collection unit sends the "calling on" message to the distributed data collection unit;

Step 3.2, after the distributed data collection unit receives the "roll call open" message, it sends the "data reporting" message to the data point copying module;

Step 3.3, after the data point copying module receives the "data reporting" message, it sends the "reporting confirmation" message to the distributed data collection unit;

Step 3.4, after the distributed data collection unit receives the "report confirmation" message, if there is data to continue to report, it will continue to send the "data report" message to the data point copying module, and return to step 3.3; if there is no data required Continue to report, then send a "data report denial/no follow-up frame" message to the data point copying module;

Step 3.5, after the data point copying module receives the "data reporting denial/no follow-up frame" message, it sends the "calling close" message to the distributed data collection unit;

Step 3.6, after the distributed data collection unit receives the "roll call close" message, it sends the "roll call close confirmation" message to the data point copying module; after completing one round of roll call copying, return to 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 a communication abnormality occurs and the reported data is abnormally lost, the data point copying module stops the current round of point copying according to the timeout processing. Task, return to step 3.1, in the next round of roll call and copy, the distributed data collection unit resends the "data report" message that was not reported successfully in the previous round.

Preferably, in step 3, when the centralized data collection unit sends the "report confirmation" message to the distributed data collection unit, if a communication abnormality occurs and the reported data is abnormally lost, the data point copying module stops the current round of call copying according to the timeout processing. Read, return to step 3.1, in the next round of roll call reading, the distributed data collection unit resends the "data reporting" message that was not reported successfully in the previous round.

Preferably, in step 4, the centralized data collection unit reports the data reporting reduction protocol to the collection master station, and the data reporting reduction protocol is based on the record type object attribute descriptor OAD, record selection descriptor RSD, one row record N column attribute descriptor ROAD and response The sequence of data is framed.

Preferably, in step 4, the response data is framed according to the sequence of the data type of the record column and the values of the multiple records.

The beneficial effect of the invention is that, compared with the prior art, the collection task and collection scheme are delegated to the distributed data collection module, and then each distributed data collection module is clicked through the centralized data collection unit, and the centralized data collection unit generates a file and reports it for collection. The main station realizes the concurrent asynchronous reading of the centralized data collection unit and the distributed data collection module, which greatly improves the timeliness of power consumption data and has a good application prospect.

Description of drawings

Fig. 1 is the system architecture of the quasi-real-time electricity consumption data collection system and method adapted to the competitive electricity market;

Fig. 2 is the first situation that centralized data collection unit and distributed data collection unit use HPLC communication channel to carry out point copy data interaction;

Fig. 3 is the second situation that the centralized data collection unit and the distributed data collection unit use the HPLC communication channel to carry out the point-and-click data interaction;

Fig. 4 is the third situation that the centralized data collection unit and the distributed data collection unit use the HPLC communication channel to carry out point copying data interaction;

FIG. 5 is a quasi-real-time electricity consumption data collection method based on a quasi-real-time electricity consumption data collection system adapted to the competitive electricity market.

Detailed ways

The present application will be further described below with reference to the accompanying drawings. The following examples are only used to more clearly illustrate the technical solutions of the present invention, and cannot be used to limit the protection scope of the present application.

Example 1: A Quasi-Real-Time Data Acquisition System Adapting to a Competitive Electricity Market

As shown in FIG. 1 , the present invention provides a quasi-real-time data collection system adapted to the competitive power market, including: a distributed data collection unit, a centralized data collection unit and a collection master station.

The distributed data collection unit includes: a downlink communication module, a quasi-real-time data collection task module, a collection task and collection plan configuration module, a data storage module and an HPLC communication sub-module.

The centralized data collection unit includes: file conversion and uplink communication module, data point copying module, data storage module and HPLC communication main module.

The distributed data collection unit is connected with the smart energy meter through the downlink communication module, the centralized data collection unit is connected with the acquisition master station through the file conversion and the uplink communication module, and the centralized data collection unit and several distributed data collection units communicate with the main module and the main module through HPLC. HPLC local communication network connection composed of HPLC communication sub-modules.

Those skilled in the art can arbitrarily configure the downlink communication module of the distributed data collection unit according to the actual situation on site. Preferably, but not limited to, the downlink communication module is RS485 communication or other communication methods.

The collection task and collection plan configuration module of the distributed data collection unit is used to configure the parameters of the collected data items and the task execution parameters, including but not limited to, the quasi-real-time collection task, the 15-minute curve task, the daily frozen data task, and the monthly frozen data task; As well as the collection scheme number, storage depth, collection method, electricity meter collection, storage time stamp and electricity data identification. Table 1 shows the task configuration scheme, Table 2 shows the three-phase meter acquisition scheme, and Table 3 shows the single-phase user acquisition scheme.

Table 1 Task configuration scheme

serial number task id execution frequency Scheme type Scheme number delay illustrate 1 1 1 minute Common collection plan 1 0min Three-phase meter acquisition task 2 2 1 day Common collection plan 2 5min Three-phase meter acquisition task 3 3 January Common collection plan 3 5min Three-phase meter acquisition task 4 4 15 minutes Common collection plan 4 5min Three-phase meter acquisition task 5 5 1 minute Common collection plan 5 0min Single-phase meter acquisition tasks 6 6 1 day Common collection plan 6 5min Single-phase meter acquisition tasks 7 7 January Common collection plan 7 5min Single-phase meter acquisition tasks 8 8 15 minutes Common collection plan 8 5min Single-phase meter acquisition tasks

Table 2 Three-phase meter acquisition scheme

Table 3 Single-phase user acquisition scheme

The functions of the quasi-real-time data collection task module for starting the distributed data collection unit include: after the distributed data collection unit is powered on, the downlink communication module collects the power meter clock and uses it as the distributed data collection unit clock. Start the quasi-real-time data acquisition task module to start the 15-minute curve task, the daily freezing data task, and the monthly freezing task; at the same time, the HPLC communication sub-module of the distributed data collection unit and the HPLC communication main module of the centralized data collection unit conduct networking and clock synchronization interaction , if the clock message of the HPLC communication main module is received, the quasi-real-time data acquisition task module of the distributed data collection unit starts the quasi-real-time data task.

The extension of the clock synchronization message is shown in Table 4 below:

Table 4 Newly added message IDs

message ID meaning Packet port number 0x0070 clock synchronization message 0x11

The format of the clock synchronization message is shown in Table 5 below:

Table 5 Format of clock synchronization message of HPLC communication module

Protocol version number: The value of this version is fixed at 1.

Packet Header Length: Indicates the packet length.

RTC clock: Indicates the RTC clock at the time when this message was created, BCD encoded, format is YYMMDDhhmmss (little endian transmission, no "week X" data bit).

NTB time: Indicates the network-wide NTB time when this packet is created, in NTB.

The data storage module of the distributed data collection unit is used to store the data required to be read in the acquisition task and the acquisition scheme configuration module. It is stored in FLASH memory to ensure that the data will not be lost after power failure. The storage method adopts first-in first-out and cyclic storage. .

The data point copying module of the centralized data collection unit is used to start the data reporting of the data storage module in the distributed data collection unit by calling and copying the message. Object-oriented data is used for the 15-minute curve task, the daily frozen data task and the monthly frozen data task. The exchange protocol routinely reports statutes for message reporting. For quasi-real-time data tasks, the simplified reporting statutes are used for message reporting. The data point copying and response are performed according to the point copying data exchange process.

The HPLC communication main module of the centralized data collection unit is used for data interaction with the data point reading module through the concurrent meter reading mode. The HPLC communication main module defaults to the communication baud rate parameter A, and the centralized data collection unit queries whether the HPLC communication main module supports updating. High baud rate B, if supported, the centralized data collection unit will automatically adjust the baud rate parameter of the HPLC communication main module to B.

More specifically, the HPLC communication main module and the data point reading module exchange data through the concurrent meter reading mode. The default communication baud rate parameter of the HPLC communication main module is 1, which is 9600bps by default. The centralized data collection unit queries whether the HPLC communication main module supports The higher baud rate parameter 2 is extended to 115200bps. If supported, the centralized data collection unit will automatically adjust the baud rate parameter of the HPLC communication main module to parameter 2, that is, 115200bps.

The data storage module of the centralized data collection unit is used to store the data copied back by the data point copying module in the FLASH memory.

The file conversion and uplink communication module of the centralized data collection unit is used to generate compressed files from the data in the data storage module of the centralized data collection unit according to the configurable file format, and supports the data acquisition and reporting of file transmission. A preferred but non-restrictive The implementation manner is to use the SFTP transmission protocol for data transmission.

The file contains data items: datetime (data time), 20000201 (A-phase voltage), 20000202 (B-phase voltage), 20000203 (C-phase voltage), 20010201 (A-phase current), 20010202 (B-phase current), 20010203 (C-phase current) current), 20010400 (neutral current), etc.

Real-time data content JSONArray The first JSONObject represents the column header of the measurement point data column, the columnhead is used as the key value, and the data item OAD code + (Chinese meaning) is used as the value value; JSONArray is the measurement point data starting from the second JSONObject. The data format is as follows:

Example 2: A Quasi-Real-Time Data Collection Method Adapting to a Competitive Electricity Market

A quasi-real-time data collection method based on the quasi-real-time data collection system adapted to the competitive power market described in Embodiment 1, comprising the following steps:

Step 1, the distributed data collection unit is powered on, the downlink communication module of the distributed data collection unit collects the power meter clock, and uses it as the distributed data collection unit clock;

Step 2, the HPLC communication sub-module of the distributed data collection unit and the HPLC communication main module of the centralized data collection unit carry out networking and clock synchronization interaction, if after receiving the clock message of the HPLC communication main module, then the distributed data collection unit The start quasi-real-time data collection task module starts the quasi-real-time data task. Step 2 further includes: starting a 15-minute curve task, a daily data freezing task, and a monthly freezing task. It is worth noting that those skilled in the art can arbitrarily set the start sequence of each task according to the actual needs of the site. A preferred but non-limiting implementation is to start each task according to the priority order of each task.

In step 3, the centralized data collection unit and the distributed data collection unit use the HPLC communication channel to exchange point-to-point data.

The first situation in which the centralized data collection unit and the distributed data collection unit use the HPLC communication channel to carry out point copy data interaction is shown in Figure 2, and the point copy data interaction in step 3 specifically includes:

Step 3.1, the data point copying module of the centralized data collection unit sends the "calling on" message to the distributed data collection unit;

Step 3.2, after the distributed data collection unit receives the "roll call open" message, it sends the "data reporting" message to the data point copying module;

Step 3.3, after the data point copying module receives the "data reporting" message, it sends the "reporting confirmation" message to the distributed data collection unit;

Step 3.4, after the distributed data collection unit receives the "report confirmation" message, if there is data to continue to report, it will continue to send the "data report" message to the data point copying module, and return to step 3.3; if there is no data required Continue to report, then send a "data report denial/no follow-up frame" message to the data point copying module;

Step 3.5, after the data point copying module receives the "data reporting denial/no follow-up frame" message, it sends the "calling close" message to the distributed data collection unit;

Step 3.6, after the distributed data collection unit receives the "roll call close" message, it sends the "roll call close confirmation" message to the data point copying module; after completing one round of roll call copying, return to step 3.1.

The second situation in which the centralized data collection unit and the distributed data collection unit use the HPLC communication channel to exchange point-and-click data is shown in Figure 3. When the distributed data collection unit sends a "data report" message to the centralized data collection unit, if If there is a communication abnormality, and the reported data is abnormally lost, the data point copying module stops the current point copying task according to the timeout processing, and returns to step 3.1.

The third situation in which the centralized data collection unit and the distributed data collection unit use the HPLC communication channel to exchange point-to-point data is shown in Figure 4. When the centralized data collection unit sends a "report confirmation" message to the distributed data collection unit, if If a communication abnormality occurs, and the reported data is abnormally lost, the data point copying module stops the current round of roll call copying according to the timeout processing, and returns to step 3.1.

As shown in Figures 3 and 4, in the next round of roll call reading, the distributed data collection unit resends the "data reporting" messages that were not reported successfully in the previous round.

Step 4, the centralized data collection unit summarizes the point-copying data of several distributed data collection units, generates a file and reports it to the collection master station.

The data reporting reduction protocol disassembles the composite data into a single data item, and then according to the "record object attribute descriptor OAD", "record selection descriptor RSD", "one row record N column attribute descriptor ROAD", "response data" Framing is performed in sequence, wherein the response data is framed according to the sequence of "record column data type A-SimplifyRecordRowDataType" and "M record data value SEQUENCE OF A-SimplifyRecordRow".

The newly designed streamlined protocol architecture also imposes constraints on the application. It is necessary to make special arrangements for the composite data in the field of electricity information collection. The clever use of this transmission method can improve the transmission efficiency.

The abbreviated specification is as follows:

A-ResultSimplifyRecord definition:

The main example messages for simplified data reporting are as follows:

//10 records in the first block table TSA: 0x000000000001

11 11 22 22 22 22 33 33 33 33 44 44 55 55//REC1 (voltage value: 0x1111, current: 0x2222222, zero sequence current: 0x33333333, 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 22 22 22 22FF 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

//10 records in the second block table TSA: 0x000000000002

11 11 22 22 22 22 33 33 33 33 44 44 55 55//REC1 (voltage value: 0x1111, current: 0x2222222, zero sequence current: 0x33333333, 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 22 22 22 22FF 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)

//The 3rd table 10 records TSA: 0x000000000003

11 11 22 22 22 22 33 33 33 33 44 44 55 55//REC1 (voltage value: 0x1111, current: 0x2222222, zero sequence current: 0x33333333, 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 22 22 22 22FF 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 beneficial effect of the present invention is that, compared with the prior art, the present invention proposes a quasi-real-time power consumption data acquisition system and method suitable for the competitive power market. The centralized data collection unit clicks and copies each distributed data collection module, and the quasi-real-time collection tasks are reported in a simplified protocol during the click-and-copy interaction process, realizing the centralized reporting of multiple electric energy meters and multiple data items, making full use of the HPLC communication channel, and then through the centralized data The collection unit generates a file and reports it to the collection master station, which realizes the concurrent asynchronous reading of the centralized data collection unit and the distributed data collection module, which greatly improves the timeliness of electricity consumption data and has a good application prospect. At the same time, the simplified protocol architecture is newly designed, and the application is also constrained. It is necessary to make a special agreement on the composite data in the field of electricity consumption information collection. The clever use of this transmission method can improve the transmission efficiency.

The applicant of the present invention has described and described the embodiments of the present invention in detail with reference to the accompanying drawings, but those skilled in the art should understand that the above embodiments are only preferred embodiments of the present invention, and the detailed description is only to help readers better It should be understood that the spirit of the present invention is not intended to limit the protection scope of the present invention. On the contrary, any improvement or modification made based on the spirit of the present invention should fall within the protection scope of the present invention.

Claims (15)

1. A quasi-real-time data acquisition system adapted to a competitive power market, comprising: a distributed data collection unit, a centralized data collection unit and a collection master station, characterized in that: The distributed data collection unit is connected to the smart energy meter through its internal downlink communication module, and configures the acquisition data item parameters and task execution parameters through its internal acquisition task and acquisition scheme configuration module, including: quasi-real-time acquisition tasks, 15-minute curve tasks , daily freeze data task, monthly freeze data task; The centralized data collection unit is connected with the acquisition master station through its internal file conversion and uplink communication module; The centralized data collection unit and several distributed data collection units are connected through the HPLC local communication network composed of the HPLC communication main module inside the centralized data collection unit and the HPLC communication sub-module inside the distributed data collection unit. 2. The quasi-real-time data acquisition system adapting to the competitive power market according to claim 1, is characterized in that: The collection task and collection scheme configuration module of the distributed data collection unit is at least further used to configure the collection scheme number, storage depth, collection method, electricity meter set, storage time stamp and electricity consumption data identification. 3. The quasi-real-time data acquisition system adapting to the competitive power market according to claim 2, is characterized in that: The distributed data collection unit also includes: a quasi-real-time data collection task module, which is connected to the collection task and collection scheme configuration module, and is used to start the quasi-real-time collection task, the 15-minute curve task, and the daily frozen data task according to the set order. , Monthly Freeze Data Task. 4. The quasi-real-time data acquisition system adapting to the competitive power market according to claim 1, is characterized in that: Start the quasi-real-time data acquisition task module to receive the clock message of the HPLC communication main module through the HPLC communication sub-module. 5. The quasi-real-time data acquisition system adapted to the competitive power market according to any one of claims 1 to 4, characterized in that: Both the data storage module of the centralized data collection unit and the data storage module of the distributed data collection unit use FLASH memory. 6. The quasi-real-time data acquisition system adapted to the competitive power market according to any one of claims 1 to 5, characterized in that: The centralized data collection unit includes: a data point copying module, which is used to start the data reporting of the data storage module in the distributed data collection unit by calling and copying the message. 7. The quasi-real-time data acquisition system adapted to the competitive power market according to claims 1 to 6, characterized in that: The HPLC communication main module of the centralized data collection unit is used to exchange data with the data point reading module through the concurrent meter reading mode. The HPLC communication main module supports a variety of communication baud rate parameters, and preferably uses higher communication baud rate parameters for communication . 8. The quasi-real-time data acquisition system adapted to the competitive power market according to claims 1 to 7, characterized in that: The file conversion and uplink communication module in the centralized data collection unit is used to generate compressed files from the data in the data storage module of the centralized data collection unit, and perform data interaction with the collection master station. 9. A quasi-real-time data collection method based on the quasi-real-time data collection system adapted to the competitive power market according to any one of claims 1 to 8, characterized in that: comprising the following steps: Step 1, the distributed data collection unit is powered on, the downlink communication module of the distributed data collection unit collects the power meter clock, and uses it as the distributed data collection unit clock; Step 2, the HPLC communication sub-module of the distributed data collection unit and the HPLC communication main module of the centralized data collection unit carry out networking and clock synchronization interaction, if after receiving the clock message of the HPLC communication main module, then the distributed data collection unit The starting quasi-real-time data acquisition task module starts the quasi-real-time data task; Step 3, the centralized data collection unit and the distributed data collection unit use the HPLC communication channel to carry out point copy data interaction; Step 4, the centralized data collection unit summarizes the point-copying data of several distributed data collection units, generates a file and reports it to the collection master station. 10. quasi-real-time data collection method according to claim 9, is characterized in that: Step 2 further includes: starting the 15-minute curve task, the daily data freezing task, and the monthly freezing task according to the set startup sequence. 11. The quasi-real-time data collection method according to claim 9 or 10, characterized in that: The click-to-copy data interaction in step 3 specifically includes: Step 3.1, the data point copying module of the centralized data collection unit sends the "calling on" message to the distributed data collection unit; Step 3.2, after the distributed data collection unit receives the "roll call open" message, it sends the "data reporting" message to the data point copying module; Step 3.3, after the data point copying module receives the "data reporting" message, it sends the "reporting confirmation" message to the distributed data collection unit; Step 3.4, after the distributed data collection unit receives the "report confirmation" message, if there is data to continue to report, it will continue to send the "data report" message to the data point copying module, and return to step 3.3; if there is no data required Continue to report, then send a "data report denial/no follow-up frame" message to the data point copying module; Step 3.5, after the data point copying module receives the "data reporting denial/no follow-up frame" message, it sends the "calling close" message to the distributed data collection unit; Step 3.6, after the distributed data collection unit receives the "roll call close" message, it sends the "roll call close confirmation" message to the data point copying module; after completing one round of roll call copying, return to 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 the "data reporting" message to the centralized data collection unit, if a communication abnormality occurs, the reported data is abnormally lost, and the data point copying module stops the current round of point copying tasks according to the timeout processing, and returns. Go to step 3.1, in the next round of roll call reading, the distributed data collection unit resends the "data reporting" message that was 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 the "report confirmation" message to the distributed data collection unit, if a communication abnormality occurs, the reported data is abnormally lost, and the data point copying module stops the current round of roll call reading according to the timeout processing, and returns. Go to step 3.1, in the next round of roll call reading, the distributed data collection unit resends the "data reporting" message that was not reported successfully in the previous round. 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 the data reporting reduction protocol to the collection master station, and the data reporting reduction protocol is in the order of the record type object attribute descriptor OAD, the record selection descriptor RSD, the row record N column attribute descriptor ROAD and the response data. Do framing. 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 data type of the record column and the sequence of the data values of the multiple records.

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