Data analysis method, device and equipment for space-time energy block of power system and medium

Abstract

The invention discloses a data analysis method, device and equipment for a space-time energy block of a power system and a medium, and the method comprises the steps: carrying out the structural definition of a general energy block model, obtaining an energy block architecture, and enabling the energy block architecture to comprise basic attributes, business attributes and solving conditions; carrying out primary dimension expansion on basic attributes, service attributes and solving conditions in the energy block architecture to obtain each dimension; performing secondary dimension expansion on the universal vector of each dimension to obtain a universal vector corresponding to each dimension; and constructing a space-time energy block model of the subsystem according to an operation principle and equipment characteristics, and performing data analysis on the space-time energy block model by using the universal vector corresponding to each dimension. The dimension of the general energy block model is greatly increased, the characterization capability of each link of the time-space energy block model of the subsystem is improved, the digitalization of each link of the power system is realized, and the structured data of the balance process of the power system is acquired.

Description

Technical Field

[0001] The present invention relates to the technical field of power system spatio-temporal energy blocks, and particularly relates to a data parsing method, device, equipment and medium for power system spatio-temporal energy blocks. Background Art

[0002] Continuously promoting the construction of medium- and long-term power supply is one of the important goals of power system construction. Building a multi-level energy supply system to improve the medium- and long-term planned energy supply adjustment mechanism, shorten the energy exchange cycle, increase the energy exchange frequency, and enrich the exchange methods are the main means to achieve this goal and an important link to ensure the stable and orderly operation of the power system energy exchange system.

[0003] With the transformation of the traditional power system into a new type of power system, the large-scale access of new energy sources such as wind power and photovoltaic power, and the inclusion of load themes such as electric vehicles, energy storage, and virtual power plants in the power supply link, the above reasons have all led to the current electricity trading mode being difficult to adapt to the development of new technologies.

[0004] Promoting the reform of the power trading system and improving the market-based trading mechanism are one of the key tasks of the new round of power system reform. With the continuous deepening of the power system reform and the continuous expansion of the power trading scale, the construction of the power market has gradually shifted towards exploring the establishment of a power spot market.

[0005] However, in the current electricity trading, the dimension of energy block modeling is very limited. For example, it only represents "buy / sell"; "capacity"; "time"; "price", and is defined as several fixed types, such as hour blocks, variable blocks, continuous blocks, etc. This has limited the application of energy blocks in the balance solution of power systems at the main, distribution, and micro levels to a certain extent. Summary of the Invention

[0006] The purpose of the embodiments of the present application is to propose a data parsing method, device, equipment and medium for power system spatio-temporal energy blocks to solve the problems of poor representation ability of the existing general energy block model and limited application.

[0007] To solve the above technical problems, the embodiments of the present application provide a data parsing method for power system spatio-temporal energy blocks, which adopts the following technical solutions, including:

[0008] Step 100: Structurally define a general energy block model to obtain an energy block architecture, where the energy block architecture includes basic attributes, service attributes, and solution conditions;

[0009] Step 200: Perform a one-dimensional expansion on the basic attributes, service attributes, and solution conditions in the energy block architecture to obtain:

[0010] The first dimension and the second dimension corresponding to the basic attributes;

[0011] The third dimension, the fourth dimension, and the fifth dimension corresponding to the service attributes;

[0012] The sixth dimension, the seventh dimension, and the eighth dimension corresponding to the solution conditions;

[0013] Wherein, the first dimension and the second dimension are an energy attribute vector and a spatial information vector respectively, the third dimension, the fourth dimension, and the fifth dimension are a service vector, a behavior vector, and an environment vector respectively, and the sixth dimension, the seventh dimension, and the eighth dimension are a task vector, a policy vector, and a balance vector respectively;

[0014] Step 300: Perform secondary dimension expansion on the general vectors of the first dimension, the second dimension, the third dimension, the fourth dimension, the fifth dimension, the sixth dimension, the seventh dimension, and the eighth dimension respectively to obtain the general vectors corresponding to each dimension;

[0015] Step 400: Obtain the operating principles and equipment characteristics of the subsystems in the power system, construct the spatio-temporal energy block model of the subsystems according to the operating principles and equipment characteristics, and perform data analysis on the spatio-temporal energy block model by using the general vectors corresponding to each dimension to obtain a structured data set corresponding to the spatio-temporal energy block model.

[0016] Further, the step 300 includes:

[0017] Step 310: Expand the dimension of the energy attribute vector, and expand the energy attribute vector to include:

[0018] Energy type parameter, energy power parameter, energy duration parameter, energy capacity parameter, energy price parameter;

[0019] Step 320: Expand the dimension of the spatial information vector, and expand the spatial information vector to include:

[0020] Latitude and longitude parameters, node parameters where located, voltage level parameters, subject parameters to which it belongs.

[0021] Further, the step 300 also includes:

[0022] Step 330: Expand the dimension of the service vector, and expand the service vector to include:

[0023] Service type vector, first market type vector, second market type vector, quotation declaration method vector, clearing method vector;

[0024] Step 340: Expand the dimension of the behavior vector, and expand the behavior vector to include:

[0025] Maintenance plan arrangement parameters, declaration behavior parameters;

[0026] Step 350: Expand the dimension of the environmental vector, and expand the environmental vector to include:

[0027] Season parameters, temperature parameters, humidity parameters, rainfall parameters, irradiation intensity parameters, wind speed parameters, wind direction parameters, terrain and landform parameters, extreme weather parameters.

[0028] Further, step 300 further includes:

[0029] Step 360: Expand the dimension of the task vector; expand the task vector to include:

[0030] Declaration parameters, scheduling parameters, and settlement parameters that the market entity needs to complete;

[0031] Step 370: Expand the dimension of the policy vector, and expand the policy vector to include:

[0032] Power generation plan parameters, power consumption plan parameters, declared volume parameters, cleared volume parameters, contract volume parameters;

[0033] Step 380: Expand the dimension of the balance vector, and expand the balance vector to include:

[0034] Injected power parameters of each node, outflow power parameters of each node.

[0035] Further, step 330 includes:

[0036] Step 331: Expand the dimension of the business type vector, and expand the business type vector to include:

[0037] Power trading parameters, power generation prediction parameters, power prediction parameters;

[0038] Step 332: Expand the dimension of the first market type vector, and expand the first market type vector to include:

[0039] Electric energy market parameters, capacity market parameters, ancillary service market parameters, financial market parameters;

[0040] Step 333: Expand the dimension of the second market type vector, and expand the second market type vector to include:

[0041] Medium- and long-term market parameters, day-ahead market parameters, intra-day market parameters, real-time market parameters.

[0042] Further, step 330 further includes:

[0043] Step 334. Expand the dimension of the quotation declaration mode vector, and expand the quotation declaration mode vector to include:

[0044] Quantity quotation parameter and quantity declaration without quotation parameter;

[0045] Step 335. Expand the dimension of the quotation declaration mode vector, and expand the quotation declaration mode vector to include:

[0046] Listed trading parameter, call auction parameter, bilateral negotiation parameter, rolling call parameter.

[0047] To solve the above problems, a data parsing device for spatio-temporal energy blocks of a power system is also provided. Using the data parsing method for spatio-temporal energy blocks of the power system, it includes:

[0048] A structured definition module for structurally defining a general energy block model to obtain an energy block architecture, where the energy block architecture includes basic attributes, service attributes, and solution conditions;

[0049] A first dimension expansion module for performing a first dimension expansion on the basic attributes, service attributes, and solution conditions in the energy block architecture to obtain:

[0050] A first dimension and a second dimension corresponding to the basic attributes;

[0051] A third dimension, a fourth dimension, and a fifth dimension corresponding to the service attributes;

[0052] A sixth dimension, a seventh dimension, and an eighth dimension corresponding to the solution conditions;

[0053] Among them, the first dimension and the second dimension are an energy attribute vector and a spatial information vector respectively, the third dimension, the fourth dimension, and the fifth dimension are a service vector, an action vector, and an environment vector respectively, and the sixth dimension, the seventh dimension, and the eighth dimension are a task vector, a strategy vector, and a balance vector respectively;

[0054] A second dimension expansion module for respectively performing a second dimension expansion on the general vectors of the first dimension, the second dimension, the third dimension, the fourth dimension, the fifth dimension, the sixth dimension, the seventh dimension, and the eighth dimension to obtain general vectors corresponding to each dimension;

[0055] An analysis module for obtaining the operating principle of the subsystem and the device characteristics, constructing the spatio-temporal energy block model of the subsystem according to the operating principle and the device characteristics, and analyzing the spatio-temporal energy block model by using the general vectors corresponding to each dimension to obtain a structured data set corresponding to the spatio-temporal energy block model.

[0056] To solve the above problems, an embodiment of the present application also proposes a computer device, including a memory and a processor. Computer-readable instructions are stored in the memory, and when the processor executes the computer-readable instructions, the steps of a data parsing method for spatio-temporal energy blocks of a power system are implemented.

[0057] To solve the above problems, an embodiment of the present application also proposes a computer-readable storage medium. Computer-readable instructions are stored on the computer-readable storage medium, and when the computer-readable instructions are executed by a processor, the steps of a data parsing method for spatio-temporal energy blocks of a power system are implemented.

[0058] Compared with the prior art, by structurally defining the general energy block model and performing a first-dimensional expansion and a second-dimensional expansion on each component in the structure respectively, the dimension of the general energy block model is greatly increased, and the representation ability of each link of the subsystem spatio-temporal energy block model is improved. By using the general vectors of each dimension after the expansion of the general energy block model to perform data parsing on the constructed spatio-temporal energy block model, a structured data set is obtained, which is beneficial to realizing the digitization of each link of the power system and obtaining the structured data of the power system balance process. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] To more clearly illustrate the solutions in the present application, the following will briefly introduce the drawings required for the description of the embodiments of the present application. Obviously, the drawings in the following description are some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0060] Figure 1 It is a flowchart of an embodiment of a data parsing method for spatio-temporal energy blocks of a power system of the present application;

[0061] Figure 2 is Figure 1 a flowchart of a specific implementation manner of S300 in;

[0062] Figure 3 is Figure 2 a flowchart of a specific implementation manner after S320 in;

[0063] Figure 4 is Figure 3 a flowchart of a specific implementation manner of S330 in;

[0064] Figure 5 is Figure 4 a flowchart of a specific implementation manner after S333 in;

[0065] Figure 6 is Figure 2Flowchart of a specific implementation after S350 in the Chinese context;

[0066] Figure 7 It is a schematic diagram of the module structure of an embodiment of a data parsing device for spatio-temporal energy blocks in a power system of the present application;

[0067] Figure 8 It is a schematic diagram of the module structure of a computer device of the present application. Specific implementation

[0068] Next, the technical solutions in the present invention will be clearly and completely described in conjunction with the accompanying drawings in the invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments in the present invention, other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of the present invention.

[0069] Referring to "embodiment" herein means that the specific features, structures, or characteristics described in connection with the embodiment can be included in at least one embodiment of the present application. The phrase appears in various places in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0070] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which this application belongs; the terms used in the specification of this application are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" and any variations thereof in the specification and claims of this application and the above accompanying drawings are intended to cover non-exclusive inclusion.

[0071] In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of this application, "a plurality" means two or more unless otherwise specifically defined.

[0072] The purpose of the embodiments of this application is to propose a spatio-temporal energy block modeling method, device, equipment, and medium suitable for power system balance solution to solve the problems of poor characterization ability of existing general energy block models and limited applications.

[0073] To solve the above technical problems, an embodiment of the present application provides a method for parsing data of spatio-temporal energy blocks in a power system, and adopts the following technical solutions, as Figure 1 , Figure 1 is a flowchart of an embodiment of a method for parsing data of spatio-temporal energy blocks in a power system of the present application; it includes:

[0074] Step 100: Structurally define a general energy block model to obtain an energy block architecture, where the energy block architecture includes basic attributes, service attributes, and solution conditions;

[0075] In this embodiment, the general energy block model is structurally defined into three parts, including basic attributes, service attributes, and solution conditions. Among them, the basic attributes represent the implicit energy information that affects the energy block, the service attributes represent the node users and service characteristics related to the energy data, and the solution conditions represent the boundary condition parameters of the energy task.

[0076] Step 200: Perform a first-dimensional expansion on the basic attributes, service attributes, and solution conditions in the energy block architecture to obtain the first dimension and the second dimension corresponding to the basic attributes; the third dimension, the fourth dimension, and the fifth dimension corresponding to the service attributes; the sixth dimension, the seventh dimension, and the eighth dimension corresponding to the solution conditions; where the first dimension and the second dimension are the energy attribute vector and the spatial information vector respectively, the third dimension, the fourth dimension, and the fifth dimension are the service vector, the behavior vector, and the environment vector respectively, and the sixth dimension, the seventh dimension, and the eighth dimension are the task vector, the strategy vector, and the balance vector respectively.

[0077] In this embodiment, a first-dimensional expansion is performed on the basic attributes, service attributes, and solution conditions. The basic attributes are expanded into two dimensions, namely the energy attribute vector and the spatial information vector, the service attributes are expanded into three dimensions, namely the service vector, the behavior vector, and the environment vector, and the solution conditions are expanded into three dimensions, namely the task vector, the strategy vector, and the balance vector.

[0078] Step 300: Perform a second-dimensional expansion on the general vectors of the first dimension, the second dimension, the third dimension, the fourth dimension, the fifth dimension, the sixth dimension, the seventh dimension, and the eighth dimension respectively to obtain the general vectors corresponding to each dimension.

[0079] In a preferred embodiment, as Figure 2 , Figure 2 is Figure 1Flow chart of a specific implementation manner of S300; Step 300 includes: Step 310, expanding the dimension of the energy attribute vector, and expanding the energy attribute vector to include an energy type parameter, an energy power parameter, an energy duration parameter, an energy capacity parameter, and an energy price parameter; Step 320, expanding the dimension of the spatial information vector, and expanding the spatial information vector to include: longitude and latitude parameters, a node parameter where it is located, a voltage level parameter, and an affiliated entity parameter.

[0080] In a preferred implementation manner, such as Figure 3 , Figure 3 is Figure 2 Flow chart of a specific implementation manner after S320 in; Step 300 further includes:

[0081] Step 330, expanding the dimension of the service vector, and expanding the service vector to include a service type vector, a first market type vector, a second market type vector, a quotation declaration method vector, and a clearing method vector; Step 340, expanding the dimension of the behavior vector, and expanding the behavior vector to include an overhaul plan arrangement parameter and a declaration behavior parameter; Step 350, expanding the dimension of the environment vector, and expanding the environment vector to include a season parameter, a temperature parameter, a humidity parameter, a rainfall parameter, an irradiation intensity parameter, a wind speed parameter, a wind direction parameter, a terrain and landform parameter, and an extreme weather parameter.

[0082] In a preferred implementation manner, such as Figure 4 , Figure 4 is Figure 3 Flow chart of a specific implementation manner of S330 in; Step 330 includes Step 331, expanding the dimension of the service type vector, and expanding the service type vector to include a power trading parameter, a power generation prediction parameter, and a power prediction parameter; Step 332, expanding the dimension of the first market type vector, and expanding the first market type vector to include an electric energy market parameter, a capacity market parameter, an ancillary service market parameter, and a financial market parameter; Step 333, expanding the dimension of the second market type vector, and expanding the second market type vector to include a medium- and long-term market parameter, a day-ahead market parameter, an intraday market parameter, and a real-time market parameter.

[0083] In a preferred implementation manner, such as Figure 5 , Figure 5 is Figure 4 Flow chart of a specific implementation manner after S333 in; Step 330 further includes Step 334, expanding the dimension of the quotation declaration method vector, and expanding the quotation declaration method vector to include a quantity and price quotation parameter and a quantity without price quotation parameter; Step 335, expanding the dimension of the quotation declaration method vector, and expanding the quotation declaration method vector to include a listing trading parameter, a call auction parameter, a bilateral negotiation parameter, and a rolling call parameter.

[0084] In a preferred embodiment, as Figure 6 , Figure 6 is Figure 2 a flowchart of a specific embodiment after S350 in

[0085] Step 360: Expand the dimension of the task vector; expand the task vector to include declaration parameters, scheduling parameters, and settlement parameters that the market entity needs to complete; Step 370: Expand the dimension of the policy vector, and expand the policy vector to include power generation plan parameters, power consumption plan parameters, declared volume parameters, cleared volume parameters, and contract volume parameters; Step 380: Expand the dimension of the balance vector, and expand the balance vector to include injection power parameters of each node and outflow power parameters of each node.

[0086] Step 400: Obtain the operating principle and equipment characteristics of the subsystem, construct a spatio-temporal energy block model of the subsystem according to the operating principle and equipment characteristics, and use the general vectors corresponding to each dimension to analyze the spatio-temporal energy block model to obtain a structured data set corresponding to the spatio-temporal energy block model.

[0087] In the power system, it includes various types of subsystems. For example, power generation energy blocks such as traditional thermal power, hydropower, wind power, and photovoltaic power, as well as energy storage batteries and pumped-storage hydroelectricity, are constructed into spatio-temporal energy block models for each subsystem.

[0088] For the power generation energy block model: According to the power generation principle and equipment characteristics, establish equations such as the heat balance equation of a thermal power generation unit, the turbine characteristic equation of a hydropower unit, the power curve equation of a wind turbine, and the photovoltaic conversion equation of a photovoltaic cell to describe the relationship between its output and related factors.

[0089] For example, for the spatio-temporal energy block modeling of wind power generation, wind power generation relies on blades to capture wind energy and drives a generator to generate electricity through a transmission system. Its output power is closely related to the wind speed. Its power curve model: The most commonly used is a piecewise function model. In terms of dynamic characteristics, consider the inertia time constant and blade adjustment time constant of the wind turbine, establish a torque balance equation, and simulate the response characteristics of the wind turbine when the wind speed suddenly changes. For example, when the wind speed suddenly increases, how the blade adjusts the angle of attack to delay the sharp rise in power.

[0090] After the model is constructed, the selected features and corresponding algorithms (such as machine learning, deep learning, or optimization algorithms) are used to train the model. By using the test data set to evaluate the trained model, the accuracy and effectiveness of the model are determined. According to the results, the model is adjusted and optimized to improve its prediction accuracy and robustness. By structurally defining the general energy block model and performing a first-dimensional expansion and a second-dimensional expansion on each component in the structure respectively, the dimension of the general energy block model is greatly increased, and the representation ability of each link of the subsystem spatio-temporal energy block model is improved. By using the general vectors of each dimension after the expansion of the general energy block model to parse the data of the constructed spatio-temporal energy block model, a structured data set is obtained, which is conducive to realizing the digitization of each link of the power system and obtaining the structured data of the power system balance process.

[0091] To solve the above problems, a data parsing device for the spatio-temporal energy blocks of a power system is also provided, and a data parsing method for the spatio-temporal energy blocks of a power system is adopted, such as Figure 7 , Figure 7 is a schematic module structure diagram of an embodiment of a data parsing device 500 for the spatio-temporal energy blocks of a power system in this application; it includes:

[0092] A structural definition module 501, configured to structurally define the general energy block model to obtain an energy block architecture, and the energy block architecture includes basic attributes, service attributes, and solution conditions;

[0093] A first-dimensional expansion module 502, configured to perform a first-dimensional expansion on the basic attributes, service attributes, and solution conditions in the energy block architecture to obtain:

[0094] A first dimension and a second dimension corresponding to the basic attributes;

[0095] A third dimension, a fourth dimension, and a fifth dimension corresponding to the service attributes;

[0096] A sixth dimension, a seventh dimension, and an eighth dimension corresponding to the solution conditions;

[0097] Among them, the first dimension and the second dimension are an energy attribute vector and a spatial information vector respectively, the third dimension, the fourth dimension, and the fifth dimension are a service vector, a behavior vector, and an environment vector respectively, and the sixth dimension, the seventh dimension, and the eighth dimension are a task vector, a policy vector, and a balance vector respectively;

[0098] A second-dimensional expansion module 503, configured to perform a second-dimensional expansion on the general vectors of the first dimension, the second dimension, the third dimension, the fourth dimension, the fifth dimension, the sixth dimension, the seventh dimension, and the eighth dimension respectively to obtain the general vectors corresponding to each dimension;

[0099] The parsing module 504 is used to obtain the operating principles of the subsystem and the device characteristics, construct a spatio-temporal energy block model of the subsystem according to the operating principles and device characteristics, and parse the spatio-temporal energy block model by using the general vectors corresponding to each dimension to obtain a structured data set corresponding to the spatio-temporal energy block model.

[0100] To solve the above problems, an embodiment of the present application also proposes a computer device, including a memory and a processor. A computer-readable instruction is stored in the memory, and when the processor executes the computer-readable instruction, the steps of a data parsing method for spatio-temporal energy blocks of a power system are implemented.

[0101] The computer device can be a device such as a computer, a server, a workstation, etc., or a mobile device such as a mobile phone, a tablet, a vehicle-mounted mobile terminal, etc., or other devices with program execution capabilities. The internal structure diagram of the computer device can be as Figure 8 shown Figure 8 is a schematic structural diagram of an embodiment of a computer device according to the present application. The computer device includes a processor, a memory, and a communication module. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile and / or volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, instructions, or code. The internal memory provides an environment for the operation of the operating system and instructions or code in the non-volatile storage medium. When the instructions or code are executed by the processor, the functions or steps of a data parsing method for spatio-temporal energy blocks of a power system as described above are implemented. The communication module of the computer device may include a network interface and / or a wireless communication module, and the computer device can communicate with other devices or service platforms through the communication module. In addition, the computer device may further include a display screen, an input device, etc.

[0102] Among them, the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions. When the processor executes the instructions or code, the following steps are implemented:

[0103] Step 100: Structurally define a general energy block model to obtain an energy block architecture, where the energy block architecture includes basic attributes, service attributes, and solution conditions;

[0104] Step 200: Perform a one-dimensional expansion on the basic attributes, service attributes, and solution conditions in the energy block architecture to obtain:

[0105] The first dimension and the second dimension corresponding to the basic attributes;

[0106] The third dimension, the fourth dimension, and the fifth dimension corresponding to the service attributes;

[0107] The sixth dimension, the seventh dimension, and the eighth dimension corresponding to the solution conditions;

[0108] Among them, the first dimension and the second dimension are an energy attribute vector and a spatial information vector respectively, the third dimension, the fourth dimension, and the fifth dimension are a service vector, a behavior vector, and an environment vector respectively, and the sixth dimension, the seventh dimension, and the eighth dimension are a task vector, a policy vector, and a balance vector respectively;

[0109] Step 300: Perform secondary dimension expansion on the general vectors of the first dimension, the second dimension, the third dimension, the fourth dimension, the fifth dimension, the sixth dimension, the seventh dimension, and the eighth dimension respectively to obtain the general vectors corresponding to each dimension;

[0110] Step 400: Obtain the operating principle of the subsystem and the device characteristics, construct the spatio-temporal energy block model of the subsystem according to the operating principle and the device characteristics, and use the general vectors corresponding to each dimension to analyze the spatio-temporal energy block model to obtain a structured data set corresponding to the spatio-temporal energy block model.

[0111] To solve the above problems, an embodiment of the present application also proposes a computer-readable storage medium, on which computer-readable instructions are stored. When the computer-readable instructions are executed by a processor, the steps of a data parsing method for spatio-temporal energy blocks of a power system are implemented.

[0112] The computer-readable storage medium stores a computer program, and the computer program includes program instructions. When the program instructions are executed by a processor, the processor executes a data parsing method for spatio-temporal energy blocks of a power system.

[0113] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program, and the computer program includes program instructions. When the program instructions are executed by a processor, the following is implemented Figures 1 to 6 the steps of a data parsing method for spatio-temporal energy blocks of a power system provided in each step. For the specific implementation manner provided in each step, reference may be made to the implementation manners provided in the above steps, which will not be elaborated here.

[0114] The above computer-readable storage medium may be a data parsing device for spatio-temporal energy blocks of a power system provided in any of the foregoing embodiments, or an internal storage unit of the above terminal device, such as a hard disk or a memory of a computer device. The computer-readable storage medium may also be an external storage device of the computer device, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the computer device.

[0115] Further, the computer-readable storage medium may further include both the internal storage unit of the computer device and external storage devices. The computer-readable storage medium is used to store the computer program and other programs and data required by the computer device. The computer-readable storage medium may also be used to temporarily store data that has been output or is to be output.

[0116] However, it should be understood that it is not required to implement all the components shown, and more or fewer components may be implemented alternatively. Among them, those skilled in the art of the present technology can understand that the computer device herein is a device capable of automatically performing numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0117] The computer device may be a computing device such as a desktop computer, a notebook, a palm computer, and a cloud server. The computer device can interact with the user through means such as a keyboard, a mouse, a remote control, a touchpad, or a voice control device.

[0118] Compared with the prior art, by structurally defining the general energy block model and respectively performing a first-dimensional expansion and a second-dimensional expansion on each component in the structure, the dimension of the general energy block model is greatly increased, and the representation ability of each link of the subsystem spatio-temporal energy block model is improved. By using the general vectors of each dimension after the expansion of the general energy block model to perform data parsing on the constructed spatio-temporal energy block model, a structured data set is obtained, which is beneficial to realizing the digitization of each link of the power system and obtaining the structured data in the power system balance process.

[0119] The non-company software tools or components appearing in the embodiments of the present application are only introduced by way of example and do not represent actual use.

[0120] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A data analysis method for a power system spatiotemporal energy block, characterized in that it includes: Step 100: structurally define the general energy block model to obtain an energy block architecture, wherein the energy block architecture includes basic attributes, business attributes and solution conditions; Step 200: Perform a dimensional expansion on the basic attributes, business attributes and solution conditions in the energy block architecture to obtain: A first dimension and a second dimension corresponding to the basic attribute; The third dimension, the fourth dimension, and the fifth dimension corresponding to the business attributes; The sixth dimension, the seventh dimension, and the eighth dimension corresponding to the solution conditions; Among them, the first dimension and the second dimension are energy attribute vector and space information vector respectively, the third dimension, the fourth dimension and the fifth dimension are business vector, behavior vector and environment vector respectively, the sixth dimension, the seventh dimension and the eighth dimension are task vector, strategy vector and balance vector respectively; Step 300: Perform secondary dimensional expansion on the general vectors of the first dimension, the second dimension, the third dimension, the fourth dimension, the fifth dimension, the sixth dimension, the seventh dimension, and the eighth dimension respectively to obtain general vectors corresponding to the respective dimensions; Step 400: Obtain the operating principle and equipment characteristics of the subsystem in the power system, construct a spatiotemporal energy block model of the subsystem based on the operating principle and equipment characteristics, and use the general vector corresponding to each dimension to perform data analysis on the spatiotemporal energy block model to obtain a structured data set corresponding to the spatiotemporal energy block model.

2. The data analysis method of the spatiotemporal energy block of the power system according to claim 1 is characterized in that: The step 300 includes: Step 310: Expand the dimension of the energy attribute vector to include: Energy type parameters, energy power parameters, energy duration parameters, energy capacity parameters, energy price parameters; Step 320: Expand the dimension of the spatial information vector to include: Longitude and latitude parameters, node parameters, voltage level parameters, and entity parameters.

3. The data analysis method of the spatiotemporal energy block of the power system according to claim 2 is characterized in that: After step 320, step 300 further includes: Step 330: Expand the dimension of the business vector to include: Business type vector, first market type vector, second market type vector, quotation declaration method vector, clearing method vector; Step 340: Expand the dimension of the behavior vector to include: Maintenance plan arrangement parameters and declaration behavior parameters; Step 350: Expand the dimension of the environment vector to include: Seasonal parameters, temperature parameters, humidity parameters, rainfall parameters, radiation intensity parameters, wind speed parameters, wind direction parameters, topography parameters, and extreme weather parameters.

4. The data analysis method of the spatiotemporal energy block of the power system according to claim 3 is characterized in that: After step 350, step 300 further includes: Step 360: Expand the dimension of the task vector; expand the task vector to include: The declaration parameters, dispatch parameters, and settlement parameters that market entities need to complete; Step 370: Expand the dimension of the strategy vector to include: Power generation plan parameters, power consumption plan parameters, declared quantity parameters, cleared quantity parameters, contract quantity parameters; Step 380: Expand the dimension of the balance vector to include: The injection power parameters of each node and the outflow power parameters of each node.

5. The data analysis method of the spatiotemporal energy block of the power system according to claim 3 is characterized in that: The step 330 includes: Step 331: Expand the dimension of the service type vector to include: Electricity trading parameters, generation forecast parameters, power forecast parameters; Step 332: Expand the dimension of the first market type vector to include: Electricity market parameters, capacity market parameters, ancillary service market parameters, and financial market parameters; Step 333: Expand the dimension of the second market type vector to include: Medium- and long-term market parameters, day-ahead market parameters, intraday market parameters, and real-time market parameters.

6. The data analysis method of the spatiotemporal energy block of the power system according to claim 5 is characterized in that: After step 333, step 330 further includes: Step 334: Expand the dimension of the quotation submission method vector to include: Parameters for quotation of quantity and parameters for quotation of quantity without quotation; Step 335: Expand the dimension of the quotation submission method vector to include: Listing trading parameters, centralized bidding parameters, bilateral negotiation parameters, and rolling matching parameters.

7. A data analysis device for a spatiotemporal energy block of an electric power system, using the data analysis method for a spatiotemporal energy block of an electric power system according to any one of claims 1 to 6, characterized in that: include: A structured definition module is used to perform structured definition on the general energy block model to obtain an energy block architecture, wherein the energy block architecture includes basic attributes, business attributes and solution conditions; The first dimension expansion module is used to perform a dimension expansion on the basic attributes, business attributes and solution conditions in the energy block architecture to obtain: A first dimension and a second dimension corresponding to the basic attribute; The third dimension, the fourth dimension, and the fifth dimension corresponding to the business attributes; The sixth dimension, the seventh dimension, and the eighth dimension corresponding to the solution conditions; Among them, the first dimension and the second dimension are energy attribute vector and space information vector respectively, the third dimension, the fourth dimension and the fifth dimension are business vector, behavior vector and environment vector respectively, the sixth dimension, the seventh dimension and the eighth dimension are task vector, strategy vector and balance vector respectively; A second dimension expansion module is used to perform secondary dimension expansion on the universal vectors of the first dimension, the second dimension, the third dimension, the fourth dimension, the fifth dimension, the sixth dimension, the seventh dimension, and the eighth dimension, respectively, to obtain universal vectors corresponding to each dimension; The parsing module is used to obtain the operating principles and equipment characteristics of the subsystems in the power system, construct a spatiotemporal energy block model of the subsystem according to the operating principles and equipment characteristics, and parse the spatiotemporal energy block model using the general vectors corresponding to the dimensions to obtain a structured data set corresponding to the spatiotemporal energy block model.

8. The data analysis device for the spatiotemporal energy block of the power system according to claim 7, characterized in that: The second dimension expansion module is further used for: Expanding the dimension of the energy attribute vector to include energy type parameters, energy power parameters, energy duration parameters, energy capacity parameters, and energy price parameters; The spatial information vector is dimensionally expanded to include: Longitude and latitude parameters, node parameters, voltage level parameters, and entity parameters.

9. A computer device, characterized in that: It comprises a memory and a processor, wherein the memory stores computer-readable instructions, and the processor executes the steps of the data analysis method of the spatiotemporal energy block of the power system according to any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-readable instructions, which, when executed by a processor, implement the steps of the data analysis method for the spatiotemporal energy block of a power system according to any one of claims 1 to 6.

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