A quasi-real-time data acquisition system and method for a competitive power market

Abstract

A kind of quasi-real-time data acquisition system adapting competitive power market, system includes: distributed data collection unit, centralized data collection unit and acquisition master station, distributed data collection unit is connected with intelligent electric energy meter by its internal downlink communication module, and the acquisition data item parameter and task execution parameter are configured by its internal acquisition task and acquisition scheme configuration module, including: quasi-real-time acquisition task, 15 minute curve task, day frozen data task, month frozen data task;Centralized data collection unit is connected with acquisition master station by its internal file conversion and uplink communication module;Centralized data collection unit and several distributed data collection units are connected by HPLC local communication network formed by HPLC communication main module in centralized data collection unit and HPLC communication submodule in distributed data collection unit.The present application realizes concurrent asynchronous reading, greatly improves the timeliness of electric data, and has good application prospect.

Description

Technical Field

[0001] This invention belongs to the field of intelligent measurement and communication, and more specifically, relates to a near real-time data acquisition system and method adapted to a competitive electricity market. Background Technology

[0002] my country's new round of power system reform has launched the construction of the electricity market. The new reform aims to further introduce competition by gradually liberalizing electricity sales, improving the electricity market's operating mechanism, encouraging more market participants, and fully leveraging the market's decisive role in resource allocation. With the development of the spot market and the continuous liberalization of the electricity sales market, the number of market participants is increasing, their types are becoming more diversified, market competition is intensifying, and pricing mechanisms are becoming more flexible. Simultaneously, with a high proportion of renewable energy generation being connected to the grid, a large number of distributed energy sources, electric vehicles, energy storage devices, and other diverse loads are being integrated. Utilizing flexible demand-side load resources to participate in grid interaction will become an important means of grid regulation in a market environment. Time-of-use pricing signals will emerge in the market to guide grid-load interaction, allowing users to respond to system prices and grid incentives, flexibly adjusting their own electricity demand.

[0003] Current electricity consumption data collection systems support the collection of daily frozen data, monthly frozen data, and 15-minute historical curve data from the previous day. However, near real-time data collection at the minute level is difficult to achieve due to limitations in the existing full-carrier and half-carrier local communication network architecture, the centralized scheduling collection mode based on the concentrator, and the speed limitations of the serial communication between the carrier communication module and the electricity meter. Because of the large number of user nodes in local communication, the local communication network is susceptible to interference from operating loads. Furthermore, the traditional full-carrier and half-carrier network architectures, based on task scheduling of centralized meter reading terminals, result in low data collection efficiency and significant challenges in near real-time data collection. Currently, in the implementation of user-side demand response projects, additional data collection modules are mainly installed to directly connect to the main station using remote communication units such as 4G, leading to substantial redundant construction costs.

[0004] The relevant technical field urgently needs a near real-time data acquisition system and method adapted to a competitive electricity market, which can be compatible with existing electricity consumption information acquisition systems and simultaneously achieve near real-time reporting of electricity consumption data, providing technical support for the construction of a competitive electricity market. Summary of the Invention

[0005] To address the shortcomings of existing technologies, the present invention aims to provide a near real-time data acquisition system and method adapted to a competitive electricity market, overcoming the problem of poor real-time data acquisition in existing electricity consumption information acquisition systems.

[0006] The present invention adopts the following technical solution. A near real-time data acquisition system adapted to a competitive electricity market includes: a distributed data collection unit, a centralized data collection unit, and a master acquisition station. The distributed data collection unit is connected to a smart energy meter through its internal downlink communication module, and configures the data item parameters and task execution parameters through its internal acquisition task and acquisition scheme configuration module, including: near real-time acquisition tasks, 15-minute curve tasks, daily frozen data tasks, and monthly frozen data tasks. The centralized data collection unit is connected to the master acquisition station through its internal file conversion and uplink communication module. The centralized data collection unit and several distributed data collection units are connected through an HPLC local communication network composed of an HPLC communication master module within the centralized data collection unit and HPLC communication sub-modules within the distributed data collection units.

[0007] Preferably, the data collection task and data collection scheme configuration module of the distributed data collection unit is also used to configure at least the data collection scheme number, storage depth, data collection method, electricity meter set, storage time stamp and electricity data identifier.

[0008] Preferably, the distributed data aggregation unit further includes: a module for starting near real-time data acquisition tasks, which is connected to the acquisition task and acquisition scheme configuration module, and is used to start near real-time acquisition tasks, 15-minute curve tasks, daily frozen data tasks, and monthly frozen data tasks in a set order.

[0009] Preferably, the near real-time data acquisition task module receives the clock message from the HPLC communication main module via the HPLC communication submodule.

[0010] Preferably, both the data storage module of the centralized data aggregation unit and the data storage module of the distributed data aggregation unit use FLASH memory.

[0011] Preferably, the centralized data collection unit includes: a data point copying module, used to initiate data reporting from the data storage module in the distributed data collection unit by reading the name copying message.

[0012] Preferably, the HPLC communication main module of the centralized data collection unit is used to interact with the data point reading module through a concurrent meter reading mode. The HPLC communication main module supports multiple communication baud rate parameters and prioritizes the use of higher communication baud rate parameters for communication.

[0013] Preferably, the file conversion and uplink communication module in the centralized data collection unit is used to generate compressed files from the data storage module of the centralized data collection unit and interact with the acquisition master station.

[0014] The present invention also provides a near real-time data acquisition method based on the aforementioned near real-time data acquisition system adapted to a competitive electricity market, comprising the following steps:

[0015] Step 1: The distributed data aggregation unit is powered on. The downlink communication module of the distributed data aggregation unit collects the clock of the electricity meter and uses it as the clock of the distributed data aggregation unit.

[0016] Step 2: The HPLC communication submodule of the distributed data collection unit and the HPLC communication main module of the centralized data collection unit interact with each other in a network and clock synchronization manner. If a clock message is received from the HPLC communication main module, the quasi-real-time data acquisition task module of the distributed data collection unit starts the quasi-real-time data task.

[0017] Step 3: The centralized data collection unit and the distributed data collection unit use the HPLC communication channel to exchange point-to-point data.

[0018] Step 4: The centralized data collection unit summarizes the point-collected data from several distributed data collection units, generates a file, and reports it to the main collection station.

[0019] Preferably, step 2 further includes: starting the 15-minute curve task, the daily frozen data task, and the monthly frozen task in the set startup order.

[0020] Preferably, the data interaction in step 3 specifically includes:

[0021] Step 3.1: The data point recording module of the centralized data collection unit sends a "name recording start" message to the distributed data collection unit;

[0022] Step 3.2: After receiving the "Roll Call Activation" message, the distributed data aggregation unit sends a "Data Reporting" message to the data point copying module.

[0023] Step 3.3: After receiving the "Data Reporting" message, the data point copying module sends a "Reporting Confirmation" message to the distributed data aggregation unit.

[0024] Step 3.4: After receiving the "report confirmation" message, if there is data that needs to be reported, the distributed data aggregation unit 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 that needs to be reported, it will send the "data report denial / no subsequent frame" message to the data point copying module.

[0025] Step 3.5: After receiving the "Data Reporting Denial / No Subsequent Frames" message, the data point copying module sends a "Roll Call Closure" message to the distributed data aggregation unit.

[0026] Step 3.6: After receiving the "Roll Call Closed" message, the distributed data aggregation unit sends a "Roll Call Closed Confirmation" message to the data point copying module; after completing one round of roll call reading, it returns to step 3.1.

[0027] Preferably, in step 3, if a communication abnormality occurs when the distributed data collection unit sends a "data reporting" message to the centralized data collection unit and the reported data is lost, the data point copying module stops the current round of data point copying task according to the timeout handling and returns to step 3.1. In the next round of data point copying, the distributed data collection unit resends the "data reporting" message that was not successfully reported in the previous round.

[0028] Preferably, in step 3, if a communication abnormality occurs and the reported data is lost due to abnormal packet loss when the centralized data collection unit sends a "reporting confirmation" message to the distributed data collection unit, the data point copying module stops the current round of name copying according to the timeout handling and returns to step 3.1. In the next round of name copying, the distributed data collection unit resends the "data reporting" message that was not successfully reported in the previous round.

[0029] Preferably, in step 4, the centralized data collection unit reports to the acquisition master station using the simplified data reporting specification. The simplified data reporting specification is framed in the order of record object attribute descriptor (OAD), record selection descriptor (RSD), one row record N column attribute descriptor (ROAD), and response data.

[0030] Preferably, in step 4, the response data is framed according to the data type of the record column and the order of the data values ​​of multiple records.

[0031] The beneficial effects of this invention are that, compared with the prior art, the data collection task and scheme are delegated to the distributed data collection module, and then the data collection unit collects data from each distributed data collection module. The centralized data collection unit generates files and reports them to the main collection station, realizing concurrent asynchronous reading between the centralized data collection unit and the distributed data collection module, which greatly improves the timeliness of electricity data and has good application prospects. Attached Figure Description

[0032] Figure 1 To adapt to the system architecture of near real-time electricity consumption data acquisition systems and methods in competitive electricity markets;

[0033] Figure 2 This is the first scenario where the centralized data collection unit and the distributed data collection unit use the HPLC communication channel to exchange point-based data;

[0034] Figure 3 This is the second scenario where the centralized data collection unit and the distributed data collection unit use the HPLC communication channel to exchange point-based data;

[0035] Figure 4 This is the third scenario where the centralized data collection unit and the distributed data collection unit use the HPLC communication channel to exchange point-based data.

[0036] Figure 5 This paper proposes a near real-time electricity consumption data acquisition method based on a near real-time electricity consumption data acquisition system adapted to a competitive electricity market. Detailed Implementation

[0037] The present application will be further described below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention, and should not be construed as limiting the scope of protection of the present application.

[0038] Example 1: A near real-time data acquisition system adapted to a competitive electricity market

[0039] like Figure 1 As shown, the present invention provides a near real-time data acquisition system adapted to a competitive electricity market, comprising: a distributed data collection unit, a centralized data collection unit, and a data acquisition master station.

[0040] The distributed data aggregation unit includes: a downlink communication module, a module for initiating near real-time data acquisition tasks, a module for configuring acquisition tasks and acquisition schemes, a data storage module, and an HPLC communication submodule.

[0041] The centralized data collection unit includes: a file conversion and uplink communication module, a data point copying module, a data storage module, and an HPLC communication main module.

[0042] The distributed data collection unit is connected to the smart energy meter through the downlink communication module, the centralized data collection unit is connected to the acquisition master station through the file conversion and uplink communication module, and the centralized data collection unit and several distributed data collection units are connected through an HPLC local communication network composed of an HPLC communication master module and an HPLC communication sub-module.

[0043] Technical personnel in the relevant field can configure the downlink communication module of the distributed data aggregation unit according to the actual site conditions. Preferred, but not limited to, the downlink communication module is RS485 communication or other communication methods.

[0044] The distributed data aggregation unit's acquisition task and acquisition scheme configuration module is used to configure the parameters of the acquired data items and the task execution parameters, including but not limited to: near real-time acquisition tasks, 15-minute curve tasks, daily frozen data tasks, and monthly frozen data tasks; as well as the acquisition scheme number, storage depth, acquisition method, meter set, storage time scale, and electricity consumption data identifier. 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.

[0045] Table 1 Task Configuration Scheme

[0046] Serial Number Task ID Execution frequency Scheme type Scheme Number Delay illustrate 1 1 1 minute Standard data acquisition scheme 1 0min Three-phase meter data acquisition task 2 2 1 day Standard data acquisition scheme 2 5min Three-phase meter data acquisition task 3 3 January Standard data acquisition scheme 3 5min Three-phase meter data acquisition task 4 4 15 minutes Standard data acquisition scheme 4 5min Three-phase meter data acquisition task 5 5 1 minute Standard data acquisition scheme 5 0min Single-phase meter data acquisition task 6 6 1 day Standard data acquisition scheme 6 5min Single-phase meter data acquisition task 7 7 January Standard data acquisition scheme 7 5min Single-phase meter data acquisition task 8 8 15 minutes Standard data acquisition scheme 8 5min Single-phase meter data acquisition task

[0047] Table 2 Three-phase meter data acquisition scheme

[0048]

[0049]

[0050]

[0051] Table 3 Single-phase user data acquisition scheme

[0052]

[0053]

[0054] The functions of the distributed data aggregation unit's quasi-real-time data acquisition task module include: after the distributed data aggregation unit is powered on, the downlink communication module collects the electricity meter clock and uses it as the distributed data aggregation unit's clock; the distributed data aggregation unit's quasi-real-time data acquisition task module starts the 15-minute curve task, the daily frozen data task, and the monthly frozen task; at the same time, the distributed data aggregation unit's HPLC communication submodule and the centralized data aggregation unit's HPLC communication main module network and clock synchronization interaction. If a clock message is received from the HPLC communication main module, the distributed data aggregation unit's quasi-real-time data acquisition task module starts the quasi-real-time data task.

[0055] The clock synchronization message extension is shown in Table 4 below:

[0056] Table 4 New Message IDs

[0057] Message ID meaning Message port number 0x0070 Clock synchronization message 0x11

[0058] The clock synchronization message format is shown in Table 5 below:

[0059] Table 5. Clock synchronization message format of HPLC communication module

[0060]

[0061] Protocol version number: This version has a fixed value of 1.

[0062] Header length: Indicates the length of the message.

[0063] RTC Clock: Indicates the RTC clock at the time this message was created. It is BCD encoded and in the format YYMMDDhhmmss (little-endian transmission, without "week X" data bits).

[0064] NTB time: Represents the network-wide NTB time at the moment this message was created, in NTB units.

[0065] The data storage module of the distributed data aggregation unit is used to store the data to be copied in the acquisition task and acquisition scheme configuration module. It uses FLASH memory to ensure that the data is not lost after power failure. The storage method adopts first-in-first-out and circular storage.

[0066] The data point copying module of the centralized data collection unit is used to initiate data reporting of the data storage module in the distributed data collection unit by reading the name copying message. For 15-minute curve tasks, daily frozen data tasks and monthly frozen data tasks, the object-oriented data exchange protocol is used for regular reporting protocol messages. For near real-time data tasks, the simplified reporting protocol messages are used for reporting. The reading and response of data point copying are executed according to the data point copying interaction process.

[0067] The HPLC communication main module of the centralized data collection unit is used to interact with the data point reading module through concurrent meter reading mode. The default communication baud rate parameter of the HPLC communication main module is A. The centralized data collection unit queries whether the HPLC communication main module supports a higher baud rate B. If it does, the centralized data collection unit automatically adjusts the baud rate parameter of the HPLC communication main module to B.

[0068] More specifically, the HPLC communication main module and the data point reading module interact with each other through a concurrent meter reading mode. The HPLC communication main module has a default communication baud rate parameter of 1, which is 9600bps. The centralized data collection unit checks whether the HPLC communication main module supports a higher baud rate parameter of 2, which is 115200bps. If it does, the centralized data collection unit automatically adjusts the baud rate parameter of the HPLC communication main module to parameter 2, i.e., 115200bps.

[0069] 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.

[0070] The file conversion and uplink communication module of the centralized data collection unit is used to generate compressed files from the data storage module of the centralized data collection unit according to a configurable file format, and supports data acquisition and reporting for file transfer. A preferred but non-limiting implementation is to use the SFTP transfer protocol for data transmission.

[0071] The file contains the following data items: datetime (data time), 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 (neutral current), etc.

[0072] The real-time data content JSONArray begins with the first JSONObject representing the column header of the measurement point data column, using the column header as the key and the OAD encoding of the data item plus its Chinese meaning as the value. From the second JSONObject onwards, the JSONArray contains the measurement point data. The data format is as follows:

[0073] Example 2: A near real-time data acquisition method adapted to a competitive electricity market

[0074] A near real-time data acquisition method based on the near real-time data acquisition system adapted to a competitive electricity market as described in Embodiment 1 includes the following steps:

[0075] Step 1: The distributed data aggregation unit is powered on. The downlink communication module of the distributed data aggregation unit collects the clock of the electricity meter and uses it as the clock of the distributed data aggregation unit.

[0076] Step 2 involves the HPLC communication submodule of the distributed data aggregation unit networking and clock synchronization with the HPLC communication main module of the centralized data aggregation unit. Upon receiving a clock message from the HPLC communication main module, the distributed data aggregation unit's quasi-real-time data acquisition task module initiates the quasi-real-time data task. Step 2 also includes initiating a 15-minute curve task, a daily frozen data task, and a monthly frozen task. It is worth noting that those skilled in the art can arbitrarily set the start order of each task according to actual field needs. A preferred but non-limiting implementation is to start each task according to its priority.

[0077] Step 3: The centralized data collection unit and the distributed data collection unit use the HPLC communication channel to exchange point-to-point data.

[0078] The first scenario involves the centralized data collection unit and the distributed data collection unit using the HPLC communication channel to exchange point-based data, as follows: Figure 2 As shown, the data interaction in step 3 specifically includes:

[0079] Step 3.1: The data point recording module of the centralized data collection unit sends a "name recording start" message to the distributed data collection unit;

[0080] Step 3.2: After receiving the "Roll Call Activation" message, the distributed data aggregation unit sends a "Data Reporting" message to the data point copying module.

[0081] Step 3.3: After receiving the "Data Reporting" message, the data point copying module sends a "Reporting Confirmation" message to the distributed data aggregation unit.

[0082] Step 3.4: After receiving the "report confirmation" message, if there is data that needs to be reported, the distributed data aggregation unit 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 that needs to be reported, it will send the "data report denial / no subsequent frame" message to the data point copying module.

[0083] Step 3.5: After receiving the "Data Reporting Denial / No Subsequent Frames" message, the data point copying module sends a "Roll Call Closure" message to the distributed data aggregation unit.

[0084] Step 3.6: After receiving the "Roll Call Closed" message, the distributed data aggregation unit sends a "Roll Call Closed Confirmation" message to the data point copying module; after completing one round of roll call reading, it returns to step 3.1.

[0085] The second scenario involves the centralized data collection unit and the distributed data collection unit using the HPLC communication channel to exchange point-based data, as follows: Figure 3 As shown, when the distributed data collection unit sends a "data reporting" message to the centralized data collection unit, if a communication abnormality occurs and the reported data is lost, the data point copying module will stop the current round of data point copying task according to the timeout handling and return to step 3.1.

[0086] The third scenario involves centralized data collection units and distributed data collection units using HPLC communication channels for point-to-point data exchange, as follows: Figure 4 As shown, when the centralized data collection unit sends a "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 will stop the current round of name copying according to the timeout handling and return to step 3.1.

[0087] like Figure 3 , 4 As shown, in the next round of roll call and copying, the distributed data aggregation unit resends the "data reporting" message that was not successfully reported in the previous round.

[0088] Step 4: The centralized data collection unit summarizes the point-collected data from several distributed data collection units, generates a file, and reports it to the main collection station.

[0089] The simplified data reporting specification breaks down composite data into individual data items, and then frames them in the order of "Record Object Attribute Descriptor (OAD)," "Record Selection Descriptor (RSD)," "One Row Record N Column Attribute Descriptor (ROAD)," and "Response Data." The response data is framed in the order of "Record Column Data Type A-SimplifyRecordRowDataType" and "M Record Data Values ​​SEQUENCE OF A-SimplifyRecordRow."

[0090] The newly designed streamlined protocol architecture also imposes constraints on applications, requiring special agreements for complex data in the field of electricity information collection. Clever use of this transmission method can improve transmission efficiency.

[0091] The simplified specifications are as follows:

[0092]

[0093] A-ResultSimplifyRecord definition:

[0094]

[0095]

[0096] The following are some examples of simplified data reporting messages:

[0097]

[0098]

[0099] / / Table 1, 10 records, TSA: 0x000000000001

[0100] 11 11 22 22 22 22 33 33 33 33 44 44 55 55 / / REC1(Voltage: 0x1111, Current: 0x2222222, Zero-sequence current: 0x33333333, Total power factor: 0x4444, Single-phase power factor: 0x5555)

[0101] 11 11 22 22 22 22 33 33 33 33 44 44 55 55 / / REC2

[0102] FF FF 22 22 22 22FF FF FF FF FF FF FF FF / / REC3(Voltage:NULL, Current:0x2222222, Zero-sequence current:NULL, Total power factor:NULL, Single-phase power factor:NULL)

[0103] 11 11 22 22 22 22 33 33 33 33 44 44 55 55 / / REC4

[0104] 11 11 22 22 22 22 33 33 33 33 44 44 55 55 / / REC5

[0105] 11 11 22 22 22 22 33 33 33 33 44 44 55 55 / / REC6

[0106] FF FF FF FF FF FF FF FF FF FF FF FF FF FF FF / / REC7(Voltage:NULL, Current:NULL, Zero-sequence current:NULL, Total power factor:NULL, Single-phase power factor:NULL)

[0107] 11 11 22 22 22 22 33 33 33 33 44 44 55 55 / / REC8

[0108] 11 11 22 22 22 22 33 33 33 33 44 44 55 55 / / REC9

[0109] 11 11 22 22 22 22 33 33 33 33 44 44 55 55 / / REC10

[0110] / / Table 2, 10 records, TSA: 0x000000000002

[0111] 11 11 22 22 22 22 33 33 33 33 44 44 55 55 / / REC1(Voltage: 0x1111, Current: 0x2222222, Zero-sequence current: 0x33333333, Total power factor: 0x4444, Single-phase power factor: 0x5555)

[0112] 11 11 22 22 22 22 33 33 33 33 44 44 55 55 / / REC2

[0113] FF FF 22 22 22 22FF FF FF FF FF FF FF FF / / REC3(Voltage:NULL, Current:0x2222222, Zero-sequence current:NULL, Total power factor:NULL, Single-phase power factor:NULL)

[0114] 11 11 22 22 22 22 33 33 33 33 44 44 55 55 / / REC4

[0115] 11 11 22 22 22 22 33 33 33 33 44 44 55 55 / / REC5

[0116] 11 11 22 22 22 22 33 33 33 33 44 44 55 55 / / REC6

[0117] FF FF FF FF FF FF FF FF FF FF FF FF FF FF FF / / REC7(Voltage:NULL, Current:NULL, Zero-sequence current:NULL, Total power factor:NULL, Single-phase power factor:NULL)

[0118] 11 11 22 22 22 22 33 33 33 33 44 44 55 55 / / REC8

[0119] 11 11 22 22 22 22 33 33 33 33 44 44 55 55 / / REC9

[0120] FF FF FF FF FF FF FF FF FF FF FF FF FF FF FF / / REC10(Voltage:NULL, Current:NULL, Zero-sequence current:NULL, Total power factor:NULL, Single-phase power factor:NULL)

[0121] / / Table 3, 10 records, TSA: 0x000000000003

[0122] 11 11 22 22 22 22 33 33 33 33 44 44 55 55 / / REC1(Voltage: 0x1111, Current: 0x2222222, Zero-sequence current: 0x33333333, Total power factor: 0x4444, Single-phase power factor: 0x5555)

[0123] 11 11 22 22 22 22 33 33 33 33 44 44 55 55 / / REC2

[0124] FF FF 22 22 22 22FF FF FF FF FF FF FF FF / / REC3(Voltage:NULL, Current:0x2222222, Zero-sequence current:NULL, Total power factor:NULL, Single-phase power factor:NULL)

[0125] 11 11 22 22 22 22 33 33 33 33 44 44 55 55 / / REC4

[0126] 11 11 22 22 22 22 33 33 33 33 44 44 55 55 / / REC5

[0127] FF FF FF FF FF FF FF FF FF FF FF FF FF FF FF / / REC6(Voltage:NULL, Current:NULL, Zero-sequence current:NULL, Total power factor:NULL, Single-phase power factor:NULL)

[0128] FF FF FF FF FF FF FF FF FF FF FF FF FF FF FF / / REC7(Voltage:NULL, Current:NULL, Zero-sequence current:NULL, Total power factor:NULL, Single-phase power factor:NULL)

[0129] 11 11 22 22 22 22 33 33 33 33 44 44 55 55 / / REC8

[0130] 11 11 22 22 22 22 33 33 33 33 44 44 55 55 / / REC9

[0131] 11 11 22 22 22 22 33 33 33 33 44 44 55 55 / / REC10

[0132] 00 00B9 7E 16

[0133] The beneficial effects of this invention are as follows: Compared with the prior art, this invention proposes a near real-time electricity consumption data acquisition system and method adapted to a competitive electricity market. The acquisition tasks and schemes are delegated to distributed data aggregation modules. Then, a centralized data aggregation unit reads data from each distributed data aggregation module. During the data reading interaction, the near real-time acquisition task uses a simplified protocol for reporting, enabling centralized reporting of multiple electricity meters and multiple data items. It fully utilizes the HPLC communication channel, and then the centralized data aggregation unit generates a file and reports it to the acquisition master station. This achieves concurrent asynchronous reading between the centralized data aggregation unit and the distributed data aggregation modules, greatly improving the timeliness of electricity consumption data and showing promising application prospects. Simultaneously, a new simplified protocol architecture has been designed, and constraints have been imposed on the application, requiring special agreements for composite data in the field of electricity consumption information acquisition. The clever use of this transmission method can improve transmission efficiency.

[0134] The applicant of this invention has provided a detailed description of the embodiments of the invention in conjunction with the accompanying drawings. However, those skilled in the art should understand that the above embodiments are merely preferred embodiments of the invention. The detailed description is only intended to help readers better understand the spirit of the invention and is not intended to limit the scope of protection of the invention. On the contrary, any improvements or modifications made based on the inventive spirit of the invention should fall within the scope of protection of the invention.

Claims

1. A quasi-real-time data acquisition system for a competitive electric power market, comprising: The distributed data collection unit, the centralized data collection unit and the acquisition master station are characterized in that: The distributed data collection unit is connected with the smart electric energy meter through the internal downlink communication module, and the collection task and collection scheme configuration module are configured with the collection data item parameters and task execution parameters, including: quasi-real-time collection task, 15-minute curve task, daily frozen data task and monthly frozen data task; The centralized data collection unit is connected with the acquisition master station through the internal file conversion and uplink communication module; The centralized data collection unit and the plurality of distributed data collection units are connected through the HPLC local communication network composed of the HPLC communication master module in the centralized data collection unit and the HPLC communication sub-module in the distributed data collection unit; The centralized data collection unit and the distributed data collection module are concurrently asynchronous reading; the centralized data collection unit includes a data point reading module for starting the data reporting of the data storage module in the distributed data collection unit through the point reading message.

2. The quasi-real-time data acquisition system adapted to the competitive electricity market according to claim 1, characterized in that: The collection task and collection scheme configuration module of the distributed data collection unit is further configured with at least the collection scheme number, storage depth, collection method, electric meter set, storage time mark and power consumption data identifier.

3. The quasi-real-time data acquisition system adapted to the competitive electricity market according to claim 2, characterized in that: The distributed data collection unit further includes a quasi-real-time data acquisition task starting module connected with the collection task and collection scheme configuration module, for starting the quasi-real-time collection task, 15-minute curve task, daily frozen data task and monthly frozen data task in the set order.

4. The quasi-real-time data acquisition system adapted to the competitive electricity market according to claim 1, characterized in that: The quasi-real-time data acquisition task starting module receives the clock message of the HPLC communication master module through the HPLC communication sub-module.

5. The quasi-real-time data acquisition system adapted to the competitive electricity market according to any one of claims 1 to 4, characterized in that: The data storage module of the centralized data collection unit and the data storage module of the distributed data collection unit both use FLASH memory.

6. The quasi-real-time data acquisition system adapted to the competitive electricity market according to claim 1, characterized in that: The HPLC communication master module of the centralized data collection unit is used for data interaction with the data point reading module through the concurrent meter reading mode, and the HPLC communication master module supports multiple communication baud rate parameters, and higher communication baud rate parameters are preferentially used for communication.

7. The quasi-real-time data acquisition system adapted to the competitive electricity market according to claim 6, characterized in that: The file conversion and uplink communication module in the centralized data collection unit is used for generating a compressed file of the data in the data storage module of the centralized data collection unit, and interacting with the acquisition master station.

8. A quasi-real-time data acquisition method for a quasi-real-time data acquisition system for a competitive electricity market according to any one of claims 1 to 7, characterized in that: The method comprises the following steps: Step 1, the distributed data collection unit is powered on, and the downlink communication module of the distributed data collection unit collects the clock of the electric energy meter and sets it as the clock of the distributed data collection unit; 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 synchronization interaction, and if the clock message of the HPLC communication main module is received, the quasi-real-time data collection task module of the distributed data collection unit 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 perform point copy data interaction; Step 4, the centralized data collection unit aggregates the point copy data of the several distributed data collection units to generate a file and report to the collection master station.

9. The quasi-real-time data collection method according to claim 8, wherein: Step 2 further comprises: starting the 15-minute curve task, the daily frozen data task, and the monthly frozen task according to the set starting order.

10. The quasi-real-time data collection method according to claim 8 or 9, wherein: Step 3, the point copy data interaction specifically comprises: Step 3.1, the data point copy module of the centralized data collection unit sends a "point-on opening" message to the distributed data collection unit; Step 3.2, after receiving the "point-on opening" message, the distributed data collection unit sends a "data reporting" message to the data point copy module; Step 3.3, after receiving the "data reporting" message, the data point copy module sends a "reporting confirmation" message to the distributed data collection unit; Step 3.4, after receiving the "reporting confirmation" message, if there is data to be reported, the distributed data collection unit continues to send a "data reporting" message to the data point copy module and returns to step 3.3; if there is no data to be reported, the distributed data collection unit sends a "data reporting denial / no subsequent frame" message to the data point copy module; Step 3.5, after receiving the "data reporting denial / no subsequent frame" message, the data point copy module sends a "point-off closing" message to the distributed data collection unit; Step 3.6, after receiving the "point-off closing" message, the distributed data collection unit sends a "point-off closing confirmation" message to the data point copy module; one round of point copy reading is completed, and the process returns to step 3.

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11. The quasi-real-time data collection method according to claim 10, wherein: In step 3, when the distributed data collection unit sends a "data reporting" message to the centralized data collection unit, if a communication abnormality occurs, the reported data is abnormally lost, the data point copy module stops the current round of point copy task according to the timeout processing, and returns to step 3.1; in the next round of point copy reading, the distributed data collection unit re-sends the "data reporting" message of the last round which is not successfully reported.

12. The quasi-real-time data collection method according to claim 10, wherein: In step 3, when the centralized data collection unit sends the "report confirmation" message to the distributed data collection unit, if communication abnormality occurs, the reported data is abnormally lost, the data point copying module stops the current round of point copying according to the timeout processing, returns to step 3.1, and in the next round of point copying, the distributed data collection unit re-sends the "data report" message of the last round which is not successfully reported.

13. The quasi-real-time data acquisition method according to claim 11 or 12, characterized in that: In step 4, the centralized data collection unit reports the data to the collection master station in a data reporting simplified protocol, and the data reporting simplified protocol is framed according to the order of a record type object attribute descriptor OAD, a record selection descriptor RSD, a one-row record N-column attribute descriptor ROAD, and response data.

14. The quasi-real-time data acquisition method according to claim 13, characterized in that: In step 4, the response data is framed according to the order of record column data type and multiple record data values.

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