CN114548653A - Power grid load regulation and control platform data acquisition method and system and electronic equipment - Google Patents
Power grid load regulation and control platform data acquisition method and system and electronic equipment Download PDFInfo
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Abstract
The invention provides a power grid load regulation and control platform data acquisition method, a system and electronic equipment, which comprehensively utilize data through a mechanism and means for integrating the data, can well provide support for decision analysis, improve the return rate of system investment, can effectively fuse the data of various service systems, intensively manage the data in a unified way, convert the data into valuable information, provide unified data support for related service application, really realize one data, one inlet, unified outlet and multilevel application, automatically acquire related data from various heterogeneous data sources, carry out validity check according to the attribute relationship of the data, realize the operation modes of automatic calculation, statistics, summarization and automatic definition, and meet the requirements of different service scene applications and different service fields for providing application.
Description
Technical Field
The disclosure relates to the technical field of power system control, in particular to a power grid load regulation and control platform data acquisition method, a system and electronic equipment.
Background
Nowadays, the scale of power enterprises is continuously getting bigger and bigger, the interconnection degree of power systems is also getting higher and higher, and the system is gradually evolving to a system with a large amount of data and information calculation convergence. Information integration is a core technology for realizing information sharing, eliminating information isolated islands and providing decision support, and an intelligent power grid dispatching system is a data center which is used as a basis of a power information integration system and is a core problem to be solved in equipment planning for building a strong intelligent power grid. Meanwhile, in the reform of power enterprises in China, new technical support of a smart grid dispatching system is sought, and the problem of ensuring safe, stable and efficient operation of power marketization becomes the problem which needs to be solved urgently at present.
Although the current power grid enterprises have built service data centers and operation monitoring data centers for different application requirements, a data sharing framework based on the traditional SOA architecture is slightly insufficient in data expandability, fault tolerance mechanism and data safety, so that the data layer does not really realize centralized control, comprehensive treatment and high sharing of data resources. With the continuous and deep application of information technology in the field of power grid dispatching operation, the access of each service system planned and constructed is continuously increased, and the association of each service is more and more intimate. In addition, the development of power grid services and the improvement of management requirements are increased, the requirements for information sharing and cooperation among service applications, between scheduling and other departments of a company and between upper and lower scheduling mechanisms are higher and higher, and the problems of difficult information sharing, incapability of managing and controlling data, island form and the like are more and more prominent. In order to meet the requirements of power grid service development and fine management of scheduling operation, a data support platform capable of integrating and managing various information such as a multi-level scheduling power grid model, data and graphs is urgently needed, efficient application analysis of a large-scale complex power grid is met, technical support is provided for each application system, analysis and evaluation of system operation data are achieved on the basis, and a data basis is provided for other comprehensive data application.
It is to be noted that the information disclosed in the above background section is only for enhancement of understanding of the background of the present disclosure, and thus may include information that does not constitute prior art known to those of ordinary skill in the art.
Disclosure of Invention
The invention aims to provide a power grid load regulation and control platform data acquisition method, a system and electronic equipment, which are used for overcoming the problem that the data resources of a power grid dispatching system cannot be intensively controlled and controlled due to the limitations and defects of the related technology at least to a certain extent.
According to one aspect of the disclosure, a method for acquiring data of a power grid load regulation and control platform is provided, which includes:
acquiring basic data of a virtual power plant and service data of each service system;
scheduling and decomposing the basic data and the service data acquired by the data acquisition layer through a preset instruction to form declaration data;
after receiving the declaration data, carrying out statistical accounting to form settlement data;
and performing revenue analysis and operation analysis on the settlement data to form business analysis data.
According to another aspect of the present disclosure, there is provided a power grid load regulation and control platform data acquisition system, including:
the data acquisition layer is used for acquiring basic data of the virtual power plant and service data of each service system;
the data scheduling layer is used for scheduling and decomposing the basic data and the service data acquired by the data acquisition layer through a preset instruction to form declared data;
the data settlement layer is used for receiving the declaration data and then carrying out statistical accounting to form settlement data;
and the data analysis layer is used for carrying out income analysis and operation analysis on the settlement data to form business analysis data.
In an exemplary embodiment of the present disclosure, the base data includes virtual plant archive data, equipment management data, and agent contract data.
In an exemplary embodiment of the present disclosure, the business data includes equipment operation state data, real-time power generation and utilization data, regulation and control management data, and transaction constraint information.
In an exemplary embodiment of the present disclosure, the preset scheduling instruction includes a DER scheduling policy and an instruction decomposition algorithm.
In an exemplary embodiment of the present disclosure, the declaration data includes resource prediction data and declaration scheme data.
In an exemplary embodiment of the present disclosure, the settlement data includes trade clearing data, resource actual power generation and utilization data, and settlement result data.
In an exemplary embodiment of the present disclosure, the business analysis data includes user response revenue analysis data, overall operation analysis data, and post-transaction evaluation data.
According to another aspect of the present disclosure, there is provided an electronic device including:
a memory; and
a processor coupled to the memory, the processor configured to execute the grid load regulation platform data collection method as described above based on instructions stored in the memory.
According to another aspect of the present disclosure, there is provided a computer readable storage medium, on which a program is stored, which when executed by a processor implements the grid load regulation platform data collection method according to claim 1.
The data acquisition layer is arranged in the data acquisition system of the power grid load regulation and control platform and used for acquiring basic data of a virtual power plant and service data of each service system; the data scheduling layer is used for scheduling and decomposing the basic data and the service data acquired by the data acquisition layer through a preset instruction to form declaration data; the data settlement layer is used for receiving the declaration data and then carrying out statistical accounting to form settlement data; and the data analysis layer is used for performing income analysis and operation analysis on the settlement data to form business analysis data, realizing the functions of management, auxiliary service declaration, resource regulation and control response, allocation settlement and the like on user resources, and solving the problem that the data resources of the power grid dispatching system cannot be centrally controlled.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure. It is to be understood that the drawings in the following description are merely exemplary of the disclosure, and that other drawings may be derived from those drawings by one of ordinary skill in the art without the exercise of inventive faculty.
Fig. 1 schematically shows a flowchart of a method 100 for acquiring data of a power grid load regulation and control platform in a first embodiment of the present disclosure.
Fig. 2 schematically shows a schematic diagram of a power grid load regulation and control platform data acquisition system 200 in a second embodiment of the present disclosure.
Fig. 3 schematically shows a schematic diagram of a data acquisition layer in the data acquisition system 200 of the power grid load control platform in fig. 2.
Fig. 4 schematically shows a schematic diagram of declared data in the data acquisition system 200 of the power grid load regulation platform in fig. 2.
Fig. 5 schematically shows a schematic diagram of settlement data in the data acquisition system 200 of the power grid load control platform in fig. 2.
Fig. 6 schematically shows a schematic diagram of service analysis data in the data collection system 200 of the power grid load control platform in fig. 2.
Fig. 7 schematically illustrates a block diagram of an electronic device 700 in an exemplary embodiment of the disclosure.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the disclosure. One skilled in the relevant art will recognize, however, that the subject matter of the present disclosure can be practiced without one or more of the specific details, or with other methods, components, devices, steps, and the like. In other instances, well-known technical solutions have not been shown or described in detail to avoid obscuring aspects of the present disclosure.
Further, the drawings are merely schematic illustrations of the present disclosure, in which the same reference numerals denote the same or similar parts, and thus, a repetitive description thereof will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices.
The following detailed description of exemplary embodiments of the disclosure refers to the accompanying drawings.
Fig. 1 schematically shows a flowchart of a method 100 for acquiring data of a power grid load regulation and control platform in a first embodiment of the present disclosure.
Fig. 2 schematically shows a schematic diagram of a power grid load regulation and control platform data acquisition system 200 in a second embodiment of the present disclosure.
Fig. 3 schematically shows a schematic diagram of a data acquisition layer in the data acquisition system 200 of the power grid load control platform in fig. 2.
Fig. 4 schematically shows a schematic diagram of declared data in the data acquisition system 200 of the power grid load regulation platform in fig. 2.
Fig. 5 schematically shows a schematic diagram of settlement data in the data acquisition system 200 of the power grid load control platform in fig. 2.
Fig. 6 schematically shows a schematic diagram of service analysis data in the data collection system 200 of the power grid load control platform in fig. 2.
Referring to fig. 1, a method 100 for collecting data of a power grid load regulation platform may include:
step S102, collecting basic data of a virtual power plant and service data of each service system;
step S104, scheduling and decomposing the basic data and the service data acquired by the data acquisition layer through a preset instruction to form declaration data;
step S106, after receiving the declaration data, carrying out statistical accounting to form settlement data;
and step S108, performing income analysis and operation analysis on the settlement data to form service analysis data.
The business system comprises a scheduling system and an auxiliary service system. The disclosed power grid load regulation and control platform data acquisition method enables data to be comprehensively utilized through a mechanism and means for integrating the data, can well provide support for decision analysis, improve the return rate of system investment, can effectively fuse the data of all service systems, intensively manage the data in a unified manner, convert the data into valuable information, provide unified data support for related service applications, really realize one data, one inlet, unified outlet and multilevel application, automatically acquire related data from various heterogeneous data sources, carry out validity check according to the attribute relationship of the data, realize automatic calculation, statistics, summarization and automatic definition operation modes, and meet the requirements of different service scene applications and different service fields for providing applications.
Referring to fig. 2, the grid load regulation platform data acquisition system 200 may include:
the data acquisition layer 10 is used for acquiring basic data 11 of the virtual power plant and service data 12 of each service system;
the data scheduling layer 20 schedules and decomposes the basic data and the service data collected by the data collecting layer through a preset instruction 21 to form declared data 22;
a data settlement layer 30, configured to receive the declaration data and perform statistical accounting to form settlement data 31;
and the data analysis layer 40 is used for carrying out revenue analysis and operation analysis on the settlement data to form business analysis data 41.
Referring to FIG. 3, the base data 11 in the data collection layer 10 includes virtual plant archive data 111, equipment management data 112, and agent contract data 113. The business data 12 includes equipment operating state data 121, real-time power generation and utilization data 122, regulation and control management data 123, and transaction constraint information 124. The data acquisition system in the embodiment can receive the auxiliary service market demand information issued by the power dispatching mechanism and the power trading market demand information issued by the power trading mechanism. The business data 12 is derived from auxiliary service market related information, including real-time information, daily information, and monthly information, and mainly includes peak shaving service compensation and allocation objects, time periods, electric power, electric quantity, price, cost, and the like.
Referring to fig. 4, the declaration data 22 includes resource prediction data 221 and declaration scheme data 222. The power grid load regulation and control platform scheduling system applicable to the data acquisition system in the embodiment needs to have an auxiliary service transaction declaration function, acquire market clearing data, perform plan decomposition and issue, and realize data exchange with auxiliary service transactions such as peak shaving, frequency modulation and standby of a regional power market, so that the data acquisition system in the embodiment also manages declaration data synchronously. In addition, the pre-set scheduling instructions 21 include a DER scheduling policy 211 and an instruction decomposition algorithm 212. The DER scheduling strategy 211 means that the power scheduling center predicts a reference power price in the next time period according to load data fed back by DER users, the DER users obtain a grid-connected bidding strategy according to the reference power price and the DER user output, and after the grid-connected bidding strategy is fed back to the power scheduling center, the power scheduling center responds to the bidding strategy of the DER users, and the DER users select an optimal grid-connected bidding strategy according to a target function.
Referring to fig. 5, the settlement data 31 includes transaction clearing data 311, actual power generation and consumption data 312 of resources, and settlement result data 313. The settlement data 31 is mainly used for settling the peak shaving transaction performed on the load side resource participating in the auxiliary service according to the peak shaving electric quantity and the corresponding market clearing price. Referring to fig. 6, the business analysis data 41 includes user response profit analysis data 411, overall operation analysis data 412, and post-transaction evaluation data 413. The data acquisition system in this embodiment performs virtual power plant invocation according to the power grid operation conditions by acquiring a market trading contract determined by the power trading organization through clearing and by the power scheduling system, analyzes the execution conditions of resource invocation of the virtual power plant in the market trading contract, calculates market profit by using the contract, and automatically calculates the contribution degree and allocation profit of each resource subject according to a built-in settlement mechanism.
The power grid load regulation and control platform data acquisition system disclosed by the invention comprehensively utilizes data through a mechanism and means for integrating the data, can well provide support for decision analysis, improve the return rate of system investment, can effectively fuse the data of each service system, intensively manage the data in a unified manner, convert the data into valuable information, provide unified data support for related service applications, really realize one data, one inlet, unified outlet and multilevel application, automatically acquire related data from various heterogeneous data sources, carry out validity check according to the attribute relationship of the data, realize the operation modes of automatic calculation, statistics, summarization and automatic definition, and meet the requirements of different service scene applications and different service fields for providing applications.
It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.
In an exemplary embodiment of the present disclosure, an electronic device capable of implementing the above method is also provided.
As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or program product. Thus, various aspects of the invention may be embodied in the form of: an entirely hardware embodiment, an entirely software embodiment (including firmware, microcode, etc.) or an embodiment combining hardware and software aspects that may all generally be referred to herein as a "circuit," module "or" system.
An electronic device 700 according to this embodiment of the invention is described below with reference to fig. 7. The electronic device 700 shown in fig. 7 is only an example and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 7, electronic device 700 is embodied in the form of a general purpose computing device. The components of the electronic device 700 may include, but are not limited to: a memory 720, and a processor 710 coupled to the memory 720, the processor 710 configured to execute the energy storage system SOC correction adjustment method 100 described above based on instructions stored in the memory 720. Data is transferred between memory 720 and processor 710 via bus 730.
Wherein the memory 720 stores program code that is executable by the processor 710 to cause said processor 710 to perform steps according to various exemplary embodiments of the present invention as described in the above section "exemplary method" of the present specification. For example, the processor 710 may execute step S102 shown in fig. 1, and collect basic data of the virtual power plant and business data of each business system; step S104, scheduling and decomposing the basic data and the service data acquired by the data acquisition layer through a preset instruction to form declaration data; step S106, after receiving the declaration data, carrying out statistical accounting to form settlement data; and step S108, performing income analysis and operation analysis on the settlement data to form service analysis data.
The memory 720 may include readable media in the form of volatile memory units, such as a random access memory unit (RAM)7201 and/or a cache memory unit 7202, and may further include a read only memory unit (ROM) 7203.
The electronic device 700 may also communicate with one or more external devices 800 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 700, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 700 to communicate with one or more other computing devices. Such communication may occur via an input/output (I/O) interface 750. Also, the electronic device 700 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network such as the Internet) via the network adapter 760. As shown, the network adapter 760 communicates with the other modules of the electronic device 700 via the bus 730. It should be appreciated that although not shown in the figures, other hardware and/or software modules may be used in conjunction with the electronic device 700, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.
In an exemplary embodiment of the present disclosure, there is also provided a computer-readable storage medium having stored thereon a program product capable of implementing the above-described method of the present specification. In some possible embodiments, aspects of the invention may also be implemented in the form of a program product comprising program code means for causing a terminal device to carry out the steps according to various exemplary embodiments of the invention described in the above section "exemplary methods" of the present description, when said program product is run on the terminal device.
The program product for implementing the above method according to an embodiment of the present invention may employ a portable compact disc read only memory (CD-ROM) and include program codes, and may be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited in this regard and, in the present document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
A computer readable signal medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable signal medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In situations involving remote computing devices, the remote computing devices may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to external computing devices (e.g., through the internet using an internet service provider).
Furthermore, the above-described figures are merely schematic illustrations of processes involved in methods according to exemplary embodiments of the invention, and are not intended to be limiting. It will be readily understood that the processes shown in the above figures are not intended to indicate or limit the chronological order of the processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, e.g., in multiple modules.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice in the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
Claims (10)
1. A data acquisition method for a power grid load regulation and control platform is characterized by comprising the following steps:
acquiring basic data of a virtual power plant and service data of each service system;
scheduling and decomposing the basic data and the service data acquired by the data acquisition layer through a preset instruction to form declaration data;
after receiving the declaration data, carrying out statistical accounting to form settlement data;
and performing revenue analysis and operation analysis on the settlement data to form business analysis data.
2. The utility model provides a power grid load regulation and control platform data acquisition system which characterized in that includes:
the data acquisition layer is used for acquiring basic data of the virtual power plant and service data of each service system;
the data scheduling layer is used for scheduling and decomposing the basic data and the service data acquired by the data acquisition layer through a preset instruction to form declaration data;
the data settlement layer is used for receiving the declaration data and then carrying out statistical accounting to form settlement data;
and the data analysis layer is used for carrying out income analysis and operation analysis on the settlement data to form business analysis data.
3. The grid load regulation platform data collection system of claim 2, wherein the base data comprises virtual plant archive data, equipment management data, and agent contract data.
4. The grid load regulation platform data collection system of claim 2, wherein the business data comprises equipment operating state data, real-time power generation and utilization data, regulation management data, and transaction constraint information.
5. The power grid load regulation platform data acquisition system of claim 2, wherein the preset scheduling instructions comprise DER scheduling policies and instruction decomposition algorithms.
6. The grid load regulation platform data collection system of claim 2, wherein the declaration data comprises resource prediction data and declaration scheme data.
7. The power grid load regulation platform data acquisition system of claim 2, wherein: the settlement data comprises transaction clearing data, resource actual power generation and power consumption data and settlement result data.
8. The grid load regulation platform data collection system of claim 2, wherein the business analysis data comprises user response revenue analysis data, overall operation analysis data, and post-transaction assessment data.
9. An electronic device, comprising:
a memory; and
a processor coupled to the memory, the processor configured to execute the grid load regulation platform data collection method of claim 1 based on instructions stored in the memory.
10. A computer-readable storage medium, on which a program is stored, which when executed by a processor implements the grid load regulation platform data collection method according to claim 1.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111656526.1A CN114548653A (en) | 2021-12-30 | 2021-12-30 | Power grid load regulation and control platform data acquisition method and system and electronic equipment |
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