A load aggregation dispatching platform and system

Abstract

The present disclosure relates to the field of Internet technology, and provides a load aggregation scheduling platform and system. The platform includes: an information collection module, an information model building module, an equipment Internet of Things module, a data storage module, and a data transmission module. The information collection module is used to collect energy consumption data of energy users; the information model building module is used to build a public information model based on equipment data and basic information; the equipment Internet of Things module is used to obtain measurement point data and store it in a message queue cluster; the data storage module is used to pull and process measurement point time series data, obtain processed data and store it in a distributed database; the data transmission module is used to retrieve target processing data and send it to the load dispatcher according to the load dispatch invitation issued by the load dispatcher. The present disclosure can realize the technical docking of most domestic power grids, support multiple protocols, support a wide range of areas, and have strong scalability; at the same time, it has the advantages of high reliability, low latency, high precision, and data transmission security.

Description

Technical Field

[0001] The present disclosure relates to the field of Internet technology, and in particular to a load aggregation scheduling platform and system. Background Art

[0002] With the gradual deepening of energy trading time reform, energy-saving optimization and integrated energy scheduling in recent years, the demand for refined control of energy has become increasingly higher.

[0003] However, there are very few mature and general load dispatching systems on the market, and most of the current load dispatching systems still have problems such as inconsistent information and easy system confusion. In addition, the current systems can only support a single data interaction protocol and have poor scalability. Most data flows use traditional database storage methods, which results in time-consuming processes and high delays. Summary of the invention

[0004] In view of this, the embodiments of the present disclosure provide a load aggregation scheduling platform and system to solve the problems of inconsistent information and easy system confusion that most load scheduling systems in the prior art still have, and the current system can only support a single data interaction protocol with poor scalability; data flow mostly adopts traditional database storage methods, resulting in time-consuming processes and high delays.

[0005] A first aspect of an embodiment of the present disclosure provides a load aggregation scheduling platform, including:

[0006] An information collection module is configured to collect energy consumption data of energy users, the energy consumption data including basic information of energy users and device data of the device to be connected to the dispatching device;

[0007] An information model building module, configured to build a common information model based on device data and basic information;

[0008] The device IoT module is configured to obtain corresponding measurement point data based on the public information model using a preset gateway and temporarily store the measurement point data in a message queue cluster;

[0009] The data storage module is configured to pull the measurement point time series data from the message queue cluster, process the measurement point time series data to obtain processed data, and store the processed data in a preset distributed database;

[0010] The data transmission module is configured to retrieve target processing data from the distributed database according to the load scheduling invitation issued by the load scheduling party, and upload the target processing data to the load scheduling party, so that the load scheduling party can formulate load scheduling tasks according to the target processing data.

[0011] A second aspect of the embodiments of the present disclosure provides a load aggregation scheduling system, including:

[0012] The above-mentioned load aggregation and dispatching platform, and the load dispatching party and energy user which are respectively connected to the load aggregation and dispatching platform in communication.

[0013] Compared with the prior art, the embodiments of the present disclosure have at least the following beneficial effects: providing a load aggregation scheduling platform, including an information collection module, an information model building module, an equipment Internet of Things module, a data storage module, and a data transmission module, wherein the information collection module is configured to collect energy consumption data of energy users, and the energy consumption data includes basic information of the energy users and equipment data of the equipment to be connected to the scheduling equipment; the information model building module is configured to build a public information model according to the equipment data and the basic information; the equipment Internet of Things module is configured to obtain corresponding measurement point data based on the public information model using a preset gateway, and temporarily store the measurement point data in a message queue cluster; the data storage module is configured to pull measurement point time series data from the message queue cluster, process the measurement point time series data, obtain processing data, and store the processing data in a preset distributed database; the data transmission module is configured to retrieve target processing data from the distributed database according to the load scheduling invitation issued by the load dispatcher, and upload the target processing data to the load dispatcher, so that the load dispatcher formulates a load scheduling task according to the target processing data. The load aggregation and dispatching platform provided by the present disclosure can realize the technical connection of most domestic power grids, support WebService (Web service), RESTful API (an architecture style of application program interface (API) that uses HTTP requests to access or use data), Grid 101 protocol, etc., with wide support and strong scalability, and can ensure efficient power grid transactions. At the same time, the platform disclosed in the present disclosure has the advantages of high reliability, low latency, high accuracy and data transmission security, and has broad market prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0015] Figure 1 It is a structural diagram of a load aggregation scheduling platform provided by an embodiment of the present disclosure;

[0016] Figure 2 It is a structural diagram of a load aggregation scheduling system provided by an embodiment of the present disclosure;

[0017] Figure 3 It is a business process diagram of the load aggregation scheduling system provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0018] In the following description, specific details such as specific system structures and technologies are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present disclosure. However, it should be clear to those skilled in the art that the present disclosure may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid obstructing the description of the present disclosure with unnecessary details.

[0019] A load aggregation scheduling platform and system according to an embodiment of the present disclosure will be described in detail below with reference to the accompanying drawings.

[0020] Figure 1 Schematic diagram of a load aggregation scheduling platform provided by an embodiment of the present disclosure. Figure 1 As shown, the load aggregation scheduling platform includes:

[0021] The information collection module 101 is configured to collect energy usage data of energy users, where the energy usage data includes basic information of the energy users and device data of the devices to be connected to the scheduling device.

[0022] In one embodiment, the energy usage data of the energy user may be collected through the following steps: loading an information entry template corresponding to a preset energy usage service scenario; and receiving energy usage data entered by the energy user based on the information entry template.

[0023] Among them, the energy user refers to the user of the load energy. Specifically, different energy users can be defined according to the type of load energy. For example, the electricity user (the load energy is electricity), the water user (the load energy is water), the gas user (the load energy is natural gas, fuel gas, etc.), etc.

[0024] The preset energy consumption service scenarios can set different energy consumption service scenarios according to different business scenarios. For example, the power business corresponds to the electricity consumption service scenario, the water business corresponds to the water consumption service scenario, etc.

[0025] The information entry template may be an information entry form, which may include row and column names (eg, company name, business qualifications, energy use contract, etc.) and corresponding information upload areas.

[0026] As an example, the load aggregation scheduling platform can load the information entry template corresponding to the preset energy service scenario by starting the information collection module, and receive the basic information entered by the energy user based on the information entry template and the equipment data of the scheduling equipment to be connected.

[0027] Among them, basic information includes information such as company name, business qualifications, and energy use contracts. Equipment to be connected to the dispatch includes various energy-consuming equipment of the energy user. For example, various electrical equipment of the electricity user (such as computers, boilers, production equipment (such as boiler equipment, etc.), lighting equipment, electric heating equipment, electric vehicles, etc.). Equipment data includes the equipment name, equipment model, and equipment measurement points (such as current, power, electricity, etc.) of the equipment to be connected to the dispatch.

[0028] The information model building module 102 is configured to build a public information model according to the device data and basic information.

[0029] In one embodiment, the public information model can be specifically constructed according to the following steps: processing the equipment data to generate standardized information, the standardized information includes equipment classification codes and load measurement point codes; and constructing the public information model based on the standardized information and basic information.

[0030] Specifically, after obtaining the above-mentioned equipment data, the information model building module can first standardize the equipment data and generate standardized information including equipment classification codes, current, power, electricity and other measurement point codes corresponding to each to-be-connected dispatching equipment. For example, the equipment data of the to-be-connected dispatching equipment A includes the equipment name A, the equipment type B, and the measuring equipment including the current meter, the electricity meter, and the electric power meter. Then, the equipment data of the to-be-connected dispatching equipment A can be standardized to generate a coding sequence [A, B, 1, 2, 3] corresponding to "[equipment name, equipment type, current meter, electricity meter, electric power meter]". Then, a public information model is built based on these standardized information and the basic information of the energy user.

[0031] Among them, the Common Information Model (CIM) is an abstract model that describes all major objects of energy users (e.g., power companies), especially objects related to power operation. By providing a standard method for representing power system resources using object classes and attributes and the relationships between them, CIM facilitates the integration of energy management system (EMS) applications independently developed by different energy suppliers, the integration between multiple independently developed complete EMS systems, and the integration between EMS systems and other systems involving different aspects of power system operation, such as power generation or distribution systems. This is achieved by defining a common language (i.e., syntax and semantics) based on CIM, so that these applications or systems can access common data and exchange information without relying on the internal representation of information.

[0032] The device IoT module 103 is configured to obtain corresponding measurement point data using a preset gateway based on a public information model, and temporarily store the measurement point data in a message queue cluster.

[0033] The preset gateway may be determined based on the network protocol used by the platform and the energy user. For example, if the platform and the energy user negotiate to use the TCP / IP protocol for communication and data exchange, the preset gateway may be a gateway that supports the TCP / IP protocol.

[0034] As an example, the load measurement point code of each energy user's to-be-connected dispatching device can be determined based on the public information model. According to the load measurement point code, the corresponding measurement point data (such as current, electricity, electric power, etc.) can be obtained through the gateway, and the obtained measurement point data can be temporarily stored in the message queue cluster. In the message queue cluster, the measurement point data can be sorted according to the measurement time sequence, and can be recorded as a message in the form of "[energy user, to-be-connected dispatching device, measurement point data]".

[0035] In the disclosed embodiments, the Internet of Things technology can be applied to realize some Internet of Things service functions of the device Internet of Things module. The Internet of Things is an important part of the new generation of information technology. The IT industry is also called: pan-interconnection, which means that everything is connected and everything is connected. Its English name is "The Internet of things". Therefore, "the Internet of Things is the Internet of Things where everything is connected". This has two meanings: first, the core and foundation of the Internet of Things is still the Internet, which is an extension and expansion of the Internet; second, its user end extends and expands to any object and object to exchange and communicate information. Therefore, the definition of the Internet of Things is to connect any object to the Internet through information sensing devices such as radio frequency identification (RFID), infrared sensors, global positioning systems, laser scanners, etc., according to the agreed protocol, to exchange and communicate information, so as to realize the intelligent identification, positioning, tracking, monitoring and management of objects.

[0036] The Internet of Things technology can realize communication and information exchange between the platform and the energy user's waiting-to-connect dispatching equipment, so that the platform can perform remote real-time regulation of each energy user's waiting-to-connect equipment according to the load dispatching tasks issued by the load dispatcher, thereby realizing load dispatching control.

[0037] The data storage module 104 is configured to pull the measurement point time series data from the message queue cluster, process the measurement point time series data to obtain processed data, and store the processed data in a preset distributed database.

[0038] As an example, messages in a message queue cluster are usually sorted according to the acquisition time or collection time of the measurement point data.

[0039] Exemplarily, the messages in the message queue cluster may be arranged and displayed in the form shown in Table 1 below.

[0040] Table 1 Message arrangement table in message queue cluster

[0041]

[0042] In one embodiment, according to different business requirements, one or more rows of data in Table 1 above can be pulled for data processing to obtain processed data, and the processed data can be stored in a preset distributed database (HBASE). A unified API interface can also be provided here to facilitate users to query and download the above-mentioned processed data or the measurement point time series data of the energy user.

[0043] In the embodiment of the present disclosure, by processing the measurement point time series data pulled from the message queue cluster to obtain processed data, and storing the processed data in a distributed database, while providing a unified API interface, the data flow efficiency can be effectively improved and the data transmission delay can be reduced.

[0044] The data transmission module 105 is configured to retrieve target processing data from the distributed database according to the load scheduling invitation issued by the load scheduling party, and upload the target processing data to the load scheduling party, so that the load scheduling party formulates load scheduling tasks according to the target processing data.

[0045] In some embodiments, the load scheduling invitation includes a scheduling period and a scheduling amount. According to the load scheduling invitation issued by the load scheduling party, target processing data that meets the scheduling period and scheduling amount can be retrieved from the distributed database according to preset retrieval rules.

[0046] As an example, a 24-hour day can be divided into 96 time periods with a granularity of 15 minutes, each of which is 15 minutes. The scheduling period can be any one or more of the 96 time periods. Of course, the granularity can be flexibly set according to actual conditions, for example, it can be 30 minutes, 1 hour, 2 hours, etc.

[0047] The dispatching amount specifically refers to the dispatching amount corresponding to each dispatching period, or the total dispatching amount. For example, the dispatching period is 0:15 in the operation cycle (1 day) of the power equipment, and its corresponding dispatching amount is X kWh. For another example, the dispatching period is 96 periods (each period corresponds to 15 minutes) in the operation of the power equipment for 1 day (24 hours), and the total dispatching amount is Y kWh.

[0048] The preset call rule may be to pull the corresponding processing data in order from top to bottom according to the time sequence of the message queue.

[0049] As an example, assuming that the load scheduling invitation is "the scheduling period is 10:15, and the scheduling amount is X kilowatt-hours", the preset retrieval rule is to pull the processing data from top to bottom in the chronological order of the message queue. Then, you can start from the scheduling amount corresponding to the first message in the message queue, and accumulate the corresponding scheduling amounts one by one until the accumulated scheduling amount is greater than or equal to the scheduling amount in the above load scheduling invitation. Then pull the first message down to the message whose accumulated scheduling amount meets the scheduling amount in the load scheduling invitation, and determine this part of the messages as the target processing data.

[0050] In some embodiments, uploading the target processing data to the load dispatcher so that the load dispatcher formulates a load dispatching task according to the target processing data includes:

[0051] Extracting measurement time points and measurement values ​​from target processing data;

[0052] Divide the measurement time points according to the preset time intervals to obtain the measurement time periods;

[0053] Summarize the measurement values ​​corresponding to the measurement period to obtain a summary value;

[0054] A load curve is generated based on the measurement period and summary value, and the load curve is uploaded to the load dispatcher so that the load dispatcher can formulate load dispatch tasks based on the load curve.

[0055] The above-mentioned target processing data includes one or more messages pulled from the message queue, each message corresponding to a measurement time point (ie, measurement data collection time or acquisition time) and a measurement value (such as current measurement value, power measurement value, electric power measurement value).

[0056] The preset time interval may be to divide 24 hours a day into 96 time intervals at a granularity of 15 minutes.

[0057] As an example, by extracting the measurement time points and measurement values ​​in the target processing data and summarizing the measurement values ​​corresponding to each time interval (measurement period), a summary value is obtained, that is, the dispatchable load corresponding to each time interval is obtained.

[0058] For example, it is assumed that the target processing data includes data 01, data 02 and data 03, wherein data 01 is [0:15, energy user 1, to be connected to the scheduling device A, the current at the measurement point 1 is X1], data 02 is [0:30, energy user 1, to be connected to the scheduling device A, the current at the measurement point 1 is X2], and data 03 is [0:45, energy user 1, to be connected to the scheduling device A, the current at the measurement point 1 is X3]. Then the measurement time points extracted from the target processing data include 0:15, 0:30 and 0:45. If the granularity is 15 minutes and 24 hours a day is divided into 96 time intervals, three measurement periods of 0:15, 0:30 and 0:45 can be obtained. The measurement value corresponding to 0:15 in the measurement period is X1 (also a summary value in this example), the measurement value corresponding to 0:30 in the measurement period is X2 (also a summary value in this example), and the measurement value corresponding to 0:45 in the measurement period is X3 (also a summary value in this example). Afterwards, a load curve with time as the horizontal axis and summary value as the vertical axis can be generated according to the above measurement period and summary value, and the load curve can be uploaded to the load dispatcher (such as the power grid dispatcher). At this time, the load dispatcher can formulate specific load dispatching tasks in combination with the load curves of other regions and the total amount of energy.

[0059] In some embodiments, the above step of uploading the target processing data to the load dispatcher includes:

[0060] encrypting target processing data to obtain encrypted data;

[0061] Upload the encrypted data to the load dispatcher.

[0062] As an example, the load aggregation scheduling platform can download the public key from the load dispatcher, and use the public key to encrypt the target processing data to obtain encrypted data, and upload the encrypted data to the load dispatcher. The load dispatcher can use its private key (a pair of symmetric keys with the public key) to decrypt the encrypted data to obtain decrypted data.

[0063] As another example, the load dispatcher may decrypt the encrypted data based on a data exchange protocol agreed upon with the load aggregation dispatching platform to obtain decrypted data, determine the load dispatching task according to the decrypted data, and send it to the load aggregation dispatching platform.

[0064] Among them, the data exchange agreement may include the agreed content such as signing and encryption and decryption through digital certificates, as well as the communication protocol used by both parties.

[0065] In some embodiments, the platform further comprises:

[0066] The load dispatching control module is configured to receive a load dispatching task, formulate a load dispatching response plan according to the load dispatching task, and execute the load dispatching response plan.

[0067] The load dispatch response plan usually includes the energy user, the equipment to be connected to the dispatch, the response dispatch period, the response dispatch amount, etc.

[0068] As an example, assuming that the load dispatching task received from the load dispatcher (such as the power grid dispatcher) is "0:15, dispatch K kilowatt-hours of electricity", then the load aggregation dispatching platform can determine at least one target energy user based on the energy consumption data of the energy user, as well as the dispatching equipment to be connected (electrical equipment) corresponding to each target energy user, the response dispatching time period (0:15), and the response dispatching amount (≥K ten million hours).

[0069] For example, it is assumed that according to the above load dispatching task, it is determined that at 0:15, 3 target energy users need to respond to the dispatch of K kWh of electricity, and each target energy user bears K / 3 of the dispatch amount. Then, the following load dispatching response plan can be formulated: "Target energy user 01, dispatch period 0:15, dispatch amount K / 3 kWh", "Target energy user 02, dispatch period 0:15, dispatch amount K / 3 kWh", "Target energy user 03, dispatch period 0:15, dispatch amount K / 3 kWh", and sent to the corresponding target energy users.

[0070] In some embodiments, executing a load dispatch response plan includes:

[0071] According to the load dispatch response plan, the opening and closing of the energy switch of the energy user's device to be connected to the dispatch device is controlled, and / or the operating power of the device to be connected to the dispatch device is adjusted.

[0072] In combination with the above example, assuming that the above-mentioned target energy users 01, 02, and 03 all confirm the load scheduling response plan issued to them by the response platform, and report the equipment data of their respective devices that can participate in the regulation to the platform, the platform can control the opening and closing of the energy switches of the devices that can participate in the regulation reported by each target energy user according to its device IoT module, and / or adjust the operating power of the equipment to be connected to the scheduling, so as to complete the load scheduling response plan.

[0073] The technical solution provided by the embodiment of the present disclosure provides a load aggregation scheduling platform, including an information collection module, an information model building module, a device Internet of Things module, a data storage module, and a data transmission module, wherein the information collection module is configured to collect energy consumption data of energy users, and the energy consumption data includes basic information of the energy users and device data of the scheduling devices to be connected; the information model building module is configured to build a public information model according to the device data and basic information; the device Internet of Things module is configured to obtain corresponding measurement point data based on the public information model using a preset gateway, and temporarily store the measurement point data in a message queue cluster; the data storage module is configured to pull measurement point time series data from the message queue cluster, process the measurement point time series data, obtain processing data, and store the processing data in a preset distributed database; the data transmission module is configured to retrieve target processing data from the distributed database according to the load scheduling invitation issued by the load dispatcher, and upload the target processing data to the load dispatcher, so that the load dispatcher formulates load scheduling tasks according to the target processing data. The load aggregation and dispatching platform provided by the present disclosure can realize the technical connection of most domestic power grids, support WebService (Web service), RESTful API (an architecture style of application program interface (API) that uses HTTP requests to access or use data), Grid 101 protocol, etc., with wide support and strong scalability, and can ensure efficient power grid transactions. At the same time, the platform disclosed in the present disclosure has the advantages of high reliability, low latency, high accuracy and data transmission security, and has broad market prospects.

[0074] All the above optional technical solutions can be arbitrarily combined to form optional embodiments of the present application, which will not be described one by one here.

[0075] Figure 2 Schematic diagram of a load aggregation scheduling system provided by an embodiment of the present disclosure. Figure 2 As shown, the load aggregation scheduling system includes:

[0076] The above-mentioned load aggregation scheduling platform 201, and the load dispatching party 202 and the energy user 203 which are respectively connected to the load aggregation scheduling platform 201 for communication.

[0077] The technical solution provided by the embodiments of the present disclosure can achieve technical docking of most domestic power grids, support WebService (Web service), RESTful API (an architecture style that uses HTTP requests to access or use data application program interface (API)), Grid 101 protocol, etc., with wide support and strong scalability, and can ensure efficient power grid transactions. At the same time, the platform disclosed in the present disclosure has the advantages of high reliability, low latency, high precision and data transmission security, and has broad market prospects.

[0078] Figure 3 It is a business process diagram of the load aggregation scheduling system provided by an embodiment of the present disclosure.

[0079] Load aggregation business services can achieve technical docking with most domestic power grids, support WebService, RestfulAPI, power grid 101 protocol, etc., with wide support and strong scalability, and can ensure efficient power grid transactions. The core modules of power grid transactions mainly include plan declaration function, total data upload function, single model data upload function, single measurement data upload function, instruction issuance function, data clearing function and data supplementary recruitment function.

[0080] The operation platform can formulate and manage the declaration plans of each enterprise and view the historical declaration data. It can summarize and analyze various real-time and historical measurement point data of the connected equipment.

[0081] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present disclosure.

[0082] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0083] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0084] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this disclosure.

[0085] In the embodiments provided in the present disclosure, it should be understood that the disclosed devices / electronic devices and methods can be implemented in other ways. For example, the device / electronic device embodiments described above are merely schematic. For example, the division of modules or units is only a logical function division. There may be other division methods in actual implementation. Multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, indirect coupling or communication connection of devices or units, which may be electrical, mechanical or other forms.

[0086] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0087] In addition, each functional unit in each embodiment of the present disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0088] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present disclosure implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. The computer program may include computer program code, and the computer program code may be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electric carrier signals and telecommunication signals.

[0089] The above embodiments are only used to illustrate the technical solutions of the present disclosure, rather than to limit them. Although the present disclosure has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present disclosure, and should all be included in the protection scope of the present disclosure.

Claims

1. A load aggregation and dispatching platform, characterized in that: include: An information collection module is configured to collect energy consumption data of energy users, wherein the energy consumption data includes basic information of the energy users and device data of the device to be connected to the scheduling device; An information model building module, configured to build a common information model according to the device data and basic information; The device IoT module is configured to obtain corresponding measurement point data using a preset gateway based on the public information model, and temporarily store the measurement point data in a message queue cluster; the messages in the message queue cluster are usually sorted according to the acquisition time or collection time of the measurement point data; A data storage module is configured to pull the measurement point time series data from the message queue cluster, process the measurement point time series data to obtain processed data, and store the processed data in a preset distributed database; A data transmission module is configured to retrieve target processing data from the distributed database according to the load scheduling invitation issued by the load scheduling party, and upload the target processing data to the load scheduling party, so that the load scheduling party formulates a load scheduling task according to the target processing data; The load dispatch invitation includes a dispatch period and a dispatch amount; The step of retrieving target processing data from the distributed database according to the load scheduling invitation issued by the load scheduling party includes: According to the load scheduling invitation issued by the load scheduling party, according to the preset calling rules, the target processing data that meets the scheduling period and scheduling amount is called from the distributed database. The preset calling rules are to pull the corresponding processing data from top to bottom in the chronological order of the message queue, starting from the scheduling amount corresponding to the first message in the message queue, and accumulating the corresponding scheduling amounts one by one until the accumulated scheduling amount is greater than or equal to the scheduling amount in the load scheduling invitation.

2. The load aggregation and dispatching platform according to claim 1, characterized in that: The energy consumption data collected from the energy user includes: Loading the information entry template corresponding to the preset energy service scenario; Receive the energy usage data entered by the energy user based on the information entry template.

3. The load aggregation and dispatching platform according to claim 1, characterized in that: The building of a public information model according to the device data and basic information includes: Processing the equipment data to generate standardized information, wherein the standardized information includes equipment classification code and load measurement point code; A public information model is constructed according to the standardized information and the basic information.

4. The load aggregation and dispatching platform according to claim 1, characterized in that: The uploading of the target processing data to the load dispatcher so that the load dispatcher formulates a load dispatching task according to the target processing data includes: Extracting measurement time points and measurement values ​​from the target processing data; Dividing the measurement time points according to preset time intervals to obtain measurement time periods; Summarizing the measurement values ​​corresponding to the measurement period to obtain a summary value; A load curve is generated according to the measurement period and the summary value, and the load curve is uploaded to the load dispatcher so that the load dispatcher formulates a load dispatching task according to the load curve.

5. The load aggregation and dispatching platform according to claim 1, characterized in that: The uploading of the target processing data to the load dispatcher comprises: encrypting the target processed data to obtain encrypted data; The encrypted data is uploaded to the load dispatcher.

6. The load aggregation and dispatching platform according to claim 5, characterized in that: The load dispatching party formulates a load dispatching task according to the target processing data, including: The load dispatcher, based on the data exchange protocol agreed upon with the load aggregation dispatching platform, decrypts the encrypted data to obtain decrypted data, determines the load dispatching task according to the decrypted data, and sends it to the load aggregation dispatching platform.

7. The load aggregation and dispatching platform according to claim 6, characterized in that: The platform also includes: The load dispatching control module is configured to receive the load dispatching task, formulate a load dispatching response plan according to the load dispatching task, and execute the load dispatching response plan.

8. The load aggregation and dispatching platform according to claim 7, characterized in that: Executing the load dispatch response plan includes: According to the load dispatch response plan, the opening and closing of the energy switch of the energy user's device to be connected to the dispatch device is controlled, and / or the operating power of the device to be connected to the dispatch device is adjusted.

9. A load aggregation dispatching system, characterized in that: include: A load aggregation and dispatching platform as claimed in any one of claims 1 to 8, and a load dispatching party and an energy user respectively connected to the load aggregation and dispatching platform in communication.

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