A Method and Device for Elastic Resource Management of Distribution Substations Based on Business Middleware

Abstract

The present invention discloses a method and device for managing elastic resources in a distribution transformer area based on a business middle platform. The method includes: taking the transformer area as the smallest intelligent management unit, connecting various types of elastic resources to the distribution network through the ways of determining the interaction format, clarifying the device identifier, and device modeling; obtaining grid data through the grid resource business middle platform, analyzing the impact of the elastic resources in the transformer area on the elasticity of the distribution network, analyzing the elasticity of the distribution network, and combining the dynamic topology of the distribution network to fit the elastic resource map of the transformer area; and invoking the microservices of the grid resource business middle platform to obtain relevant data of the distribution network so as to realize macroscopic data monitoring.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid operation management, and more specifically, to a method and device for managing elastic resources of a distribution substation area based on a business middle platform. Background Art

[0002] The elasticity of a distribution network is defined as the ability of the system to resist various hazards, bear the consequences of an initial fault, and quickly return to the normal operating state within a certain period of time.

[0003] At present, the enterprise middle platform constructed by the State Grid Corporation includes a business middle platform and a data middle platform. Through the construction of the enterprise middle platform, the company's information system architecture is promoted to evolve towards "micro applications" (fast and flexible) + "large middle platforms" (integrated and reusable) + "strong backends" (powerful and stable). The business middle platform is positioned to provide shared services for core business processing, integrating the common content in the company's core businesses into shared services, and providing them for various front-end applications to call in the form of application services, so as to realize the rapid and flexible construction of business applications. The data middle platform is positioned to provide data sharing and analysis application services for various specialties and units. Based on the company's unified data center for all businesses, according to the needs of data sharing and analysis applications, the common data service capabilities are precipitated, and the data sharing, analysis and mining, and integration needs between different horizontal specialties and different vertical levels are met through data services.

[0004] In recent years, the State Grid Corporation has actively promoted the construction of the enterprise middle platform. This patent relies on the power grid resource business middle platform, which is one of the main construction achievements, and its functions mainly focus on the construction of distribution network side functions. By integrating the data of power grid equipment, topology, etc. scattered in various specialties, a "single network" of the whole network topology of all-source, network, load, and storage full-scale equipment in multiple time states is constructed; at the same time, through the precipitation of common services, enterprise-level shared services in multiple specialties, multiple time states, and multiple types such as power grid equipment resource management, asset (physical) management, and topology analysis are formed, realizing the unified standard, same-source maintenance, and unified management of the whole network data, and supporting the rapid and flexible construction of businesses such as power grid planning, production and maintenance, and customer service.

[0005] The elasticity of a power system can be defined as the ability of the power system to quickly recover in a disaster or respond to high-impact, low-probability events and quickly recover from these destructive events. The construction of a multi-source integrated and highly elastic power grid can significantly improve the safety and anti-interference ability of the power grid by improving the grid's auxiliary service ability without changing the physical form of the power grid, and the distribution network is the main part of the construction of the multi-source integrated and highly elastic power grid. On the load side of the distribution network, due to the lack of information, the user load resources are in a dormant state, the elastic support ability has not been established, and the power grid faces problems such as the lack of interaction between the source and the load and the lack of efficiency improvement means.

[0006] The existing evaluation methods for the resilience of distribution networks mainly focus on the existing resilience evaluation index system of distribution networks to achieve a comprehensive quantitative evaluation of the resilience of distribution networks under the background of integrated energy. It focuses on carrying out the resilience evaluation and analysis of distribution networks when the grid framework and distributed resources are fixed, without involving the changes of the grid framework and various distributed resources (such as distributed photovoltaics, electric vehicle charging devices, energy storage, and microgrids), nor the resource coordination between "power sources, grids, loads, and energy storage". In addition, it is also necessary to integrate and process the multi-system and multi-source data of the grid framework and various distributed resources, making it difficult to achieve online or real-time analysis. Summary of the Invention

[0007] In view of the deficiencies of the prior art, the present invention provides a method and device for managing resilient resources in a distribution substation area based on a business middle platform.

[0008] According to one aspect of the present invention, there is provided a method for managing resilient resources in a distribution substation area based on a business middle platform, including:

[0009] By determining the interaction format, clarifying the device identifier, and device modeling, taking the substation area as the smallest intelligent management unit, various resilient resources are connected to the distribution network through the Internet of Things;

[0010] Obtain grid data through the grid resource business middle platform, analyze the impact of the resilient resources in the substation area on the resilience of the distribution network, analyze the resilience of the distribution network, and combine the dynamic topology of the distribution network to fit the resilient resource map of the substation area;

[0011] Invoke the microservices of the grid resource business middle platform to obtain relevant data of the distribution network to achieve macro data monitoring.

[0012] Optionally, in the distribution network architecture, the end device and the edge computing node adopt a binary-coded interaction format, and the edge computing node and the distribution network master station adopt a Json data interaction format.

[0013] Optionally, the device identifier of the distribution network is uniformly allocated by the IoT platform, corresponding one-to-one with the unique device identifier, and serving as the unique identifier for model generation and data flow during the interaction between the end device and the edge computing node, and between the edge computing node and the distribution network master station in the distribution network architecture, and is invisible to the business applications of the end device and the distribution network master station.

[0014] Optionally, through device modeling, the information model of the intelligent fusion terminal and low-voltage equipment in the substation area is obtained. The information model of the intelligent fusion terminal and low-voltage equipment in the substation area takes the intelligent fusion terminal in the substation area as the core, including the basic information of the intelligent fusion terminal in the substation area, the managed equipment and topology, and the asset information of the intelligent fusion terminal in the substation area.

[0015] Optionally, obtaining grid data through the grid resource business middle platform includes:

[0016] Obtain the basic grid framework information of the target power grid to be analyzed through the power grid resource business middleware platform;

[0017] Obtain the operation information of the distribution network through the power grid resource business middleware platform.

[0018] Optionally, obtain the basic grid framework information of the target power grid to be analyzed through the power grid resource business middleware platform, including:

[0019] Determine the key analysis equipment, and rely on the power grid resource business middleware platform to obtain the equipment ID of the key analysis equipment;

[0020] Starting from the key analysis equipment, obtain the power supply area of the target power grid through the equipment ID and relying on topological analysis, and form an equipment tree or an equipment aggregate;

[0021] Rely on the connection relationship of the equipment to form a target grid framework set containing all equipment and topological relationships.

[0022] Optionally, obtain the operation information of the distribution network through the power grid resource business middleware platform, including:

[0023] According to the equipment classification, determine three types of sub-equipment aggregates: load, new energy generation, and flexible resources;

[0024] Rely on the ID of the equipment to associate equipment characteristics and measurement information;

[0025] Obtain the maximum load, minimum load, and typical daily load curve of the load equipment;

[0026] Obtain the installed capacity, output characteristic curve, and typical daily processing curve of new energy generation;

[0027] Obtain the maximum capacity, used capacity, and control characteristic curve of flexible resources.

[0028] Optionally, analyze the impact of the flexible resources in the transformer substation area on the flexibility of the distribution network, including:

[0029] Analyze the output law of distributed photovoltaic;

[0030] Analyze the load characteristics and represent them through normal distribution;

[0031] Analyze the adjustable capacity of flexible loads and energy storage.

[0032] Optionally, analyze the flexibility of the distribution network, including:

[0033] The fault response process of the distribution network is divided into three stages: the pre-fault prevention stage, the fault penetration stage, and the fault recovery stage. Among them, the pre-fault prevention stage refers to the stage where the system absorbs faults and ensures normal operation. The fault penetration stage refers to the stage of performance degradation after the power grid fault, also known as the vulnerability stage. The fault recovery stage refers to the stage where the operator organizes the repair of the power grid and gradually restores the power grid to the normal operation level;

[0034] Establish corresponding power grid resilience models for the above three stages;

[0035] Based on the established power grid resilience models, calculate the loads of resilient resource interaction recovery in the above three stages to achieve quantitative analysis of resilient resources.

[0036] Optionally, establishing corresponding power grid resilience models for the above three stages includes:

[0037] For the pre-fault prevention stage, establish a power grid fault model to simulate power grid fault scenarios;

[0038] For the fault penetration stage, establish a power grid vulnerability model to simulate the power grid vulnerability process;

[0039] For the fault recovery stage, establish a power grid recovery process model to simulate the repair process of faulty components.

[0040] Optionally, call the microservices of the power grid resource business middle platform to obtain relevant data of the distribution network, including:

[0041] Obtain the information of equipment resources through the power grid resource center to establish basic power grid information data;

[0042] Obtain the operating status of the equipment by calling the equipment status center;

[0043] Obtain the current topology through the power grid topology center, obtain resilient resource information, and obtain the resilient resource evaluation result through calculation;

[0044] Obtain the corresponding electrical diagram through the power grid graphics center and display it through the APP.

[0045] According to another aspect of the present invention, there is provided a resilient resource management device for a distribution transformer area based on a business middle platform, including:

[0046] A resilient resource IoT access module, which is used to connect various resilient resources to the distribution network through the IoT in the form of determining the interaction format, clarifying the device identifier, and device modeling, with the transformer area as the smallest intelligent management unit;

[0047] The transformer area elastic resource analysis module is used to obtain power grid data through the power grid resource business middle platform, analyze the impact of the transformer area elastic resources on the distribution network elasticity, analyze the distribution network elasticity, and combine the distribution network dynamic topology to fit the transformer area elastic resource map;

[0048] The micro-application module is used to call the microservices of the power grid resource business middle platform to obtain relevant data of the distribution network, so as to realize macro data monitoring.

[0049] According to another aspect of the present invention, there is provided a computer-readable storage medium storing a computer program for executing the method according to any one of the above aspects of the present invention.

[0050] According to another aspect of the present invention, there is provided an electronic device, which includes: a processor; a memory for storing executable instructions executable by the processor; the processor is configured to read the executable instructions from the memory and execute the instructions to implement the method according to any one of the above aspects of the present invention.

[0051] Thus, the present invention takes the transformer area as the smallest intelligent management unit to realize the Internet of Things access and rapid modeling of various intelligent distributed resources. Relying on the power grid resource business middle platform, it analyzes the electricity consumption laws of multiple loads and the output capabilities of distributed resources, combines the distribution network dynamic topology, fits the transformer area elastic resource map, and realizes online analysis. Finally, it provides a micro-application for the Internet of Things analysis of the distribution transformer area elastic resources based on the power grid resource business middle platform. The present invention can realize the lightweight layout of the management analysis system in the form of service calls. The present invention's technology for rapid access and modeling of distribution network elastic resources based on the business middle platform can realize automatic identification, automatic registration, and automatic modeling of elastic resources after they are connected to the power grid. Based on the real-time operation data, load data, and performance of elastic resources of the power grid, the present invention can analyze the elasticity of the distribution transformer area online in real time, providing a scientific means for the real-time operation control of the transformer area. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] By referring to the following drawings, the exemplary embodiments of the present invention can be more completely understood:

[0053] Figure 1 is a schematic flowchart of a method for managing distribution transformer area elastic resources based on a business middle platform provided by an exemplary embodiment of the present invention;

[0054] Figure 2 is a framework diagram of a distribution transformer area elastic resource management system provided by an exemplary embodiment of the present invention;

[0055] Figure 3 is a schematic diagram of device identification description provided by an exemplary embodiment of the present invention;

[0056] Figure 4It is a framework diagram of the information model provided by an exemplary embodiment of the present invention;

[0057] Figure 5 It is a schematic flow diagram of elastic resource data acquisition based on an enterprise middle platform provided by an exemplary embodiment of the present invention;

[0058] Figure 6 It is a schematic diagram of the analysis of the elastic process of the distribution network provided by an exemplary embodiment of the present invention;

[0059] Figure 7 It is a schematic diagram of a micro-application for the analysis of the elastic resources of a distribution transformer area based on a power grid resource business middle platform provided by an exemplary embodiment of the present invention;

[0060] Figure 8 It is the overall logic diagram of the micro-application platform for the analysis of the elastic resources of a distribution transformer area provided by an exemplary embodiment of the present invention;

[0061] Figure 9 It is a schematic structural diagram of a device for managing the elastic resources of a distribution transformer area based on a business middle platform provided by an exemplary embodiment of the present invention;

[0062] Figure 10 It is the structure of an electronic device provided by an exemplary embodiment of the present invention. Detailed implementation manners

[0063] Next, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments of the present invention. It should be understood that the present invention is not limited by the exemplary embodiments described herein.

[0064] It should be noted that: unless otherwise specifically stated, the relative arrangements of components and steps, numerical expressions and values set forth in these embodiments do not limit the scope of the present invention.

[0065] Those skilled in the art can understand that the terms "first", "second", etc. in the embodiments of the present invention are only used to distinguish different steps, devices or modules, etc., and neither represent any specific technical meaning nor indicate an inevitable logical order between them.

[0066] It should also be understood that in the embodiments of the present invention, "a plurality of" may refer to two or more, and "at least one" may refer to one, two or more.

[0067] It should also be understood that for any component, data or structure mentioned in the embodiments of the present invention, unless otherwise clearly defined or given a contrary indication in the context, it can generally be understood as one or more.

[0068] In addition, the term "and / or" in the present invention is merely a description of the relationship between associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in the present invention generally indicates that the associated objects before and after are in an "or" relationship.

[0069] It should also be understood that the description of each embodiment of the present invention emphasizes the differences between the embodiments. The same or similar parts can be referred to each other. For the sake of brevity, they will not be described in detail one by one.

[0070] At the same time, it should be understood that for the convenience of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship.

[0071] The following description of at least one exemplary embodiment is actually only illustrative and in no way restrictive of the present invention and its application or use.

[0072] Well-known technologies, methods, and devices for those of ordinary skill in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods, and devices should be regarded as part of the specification.

[0073] It should be noted that like reference numerals and letters in the following figures represent like items. Therefore, once an item is defined in one figure, it does not need to be further discussed in subsequent figures.

[0074] Embodiments of the present invention can be applied to electronic devices such as terminal devices, computer systems, servers, etc., which can operate with many other general-purpose or special-purpose computing system environments or configurations. Examples of well-known terminal devices, computing systems, environments, and / or configurations suitable for use with electronic devices such as terminal devices, computer systems, servers, etc. include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, network personal computers, small computer systems, large computer systems, and distributed cloud computing technology environments including any of the above systems, and so on.

[0075] Electronic devices such as terminal devices, computer systems, and servers can be described in the general context of computer system-executable instructions (such as program modules) executed by a computer system. Generally, program modules can include routines, programs, object programs, components, logics, data structures, etc., which perform specific tasks or implement specific abstract data types. The computer system / server can be implemented in a distributed cloud computing environment, where tasks are executed by remote processing devices linked through a communication network. In a distributed cloud computing environment, program modules can be located on local or remote computing system storage media including storage devices.

[0076] Exemplary method

[0077] Figure 1 It is a schematic flowchart of a method for elastic resource management of a distribution transformer area based on a business middle platform provided by an exemplary embodiment of the present invention. This embodiment can be applied to an electronic device, such as Figure 1 As shown, the method 100 for elastic resource management of a distribution transformer area based on a business middle platform includes the following steps:

[0078] Step 101, taking the transformer area as the smallest intelligent management unit, connect various types of elastic resources to the distribution network through the ways of determining the interaction format, clarifying the device identifier, and device modeling.

[0079] In the embodiment of the present invention, the power grid enterprise middle platform mainly includes a data middle platform and a business middle platform, and the hardware structures of the middle platforms are all arranged on the cloud platform of the power grid company. Among them, the data middle platform provides data services for the whole business chain of the power grid enterprise, including data asset management and data analysis management. The business middle platform involved in this patent is mainly the power grid resource business middle platform.

[0080] The power grid resource business middle platform conducts digital modeling on the "physical one network" of power generation, transmission, transformation, distribution, and utilization based on the unified data model SG-CIM, integrates data such as power grid resources and equipment assets scattered in various specialties, realizes unified standards, homologous maintenance, and unified management of the whole network data from the power source, power grid to users, realizes "one data source" for power grid resources, forms "one power grid map" with the power grid framework topology as the core, realizes homologous maintenance and application of multi-state power grids in planning, construction, and operation, constructs twelve major shared service centers such as power grid resources, assets, topology, and graphics, provides "one map, multiple layers, and multi-state" one-stop shared services, and supports the front-end applications of "one business line" for various specialties of business departments such as planning, materials, infrastructure, dispatching, operation and maintenance, and marketing.

[0081] Optionally, in the distribution network architecture, the end device and the edge computing node adopt a binary-coded interaction format, and the edge computing node and the distribution network master station adopt a Json data interaction format.

[0082] Optionally, the device identifiers of the distribution network are uniformly assigned by the IoT platform, corresponding one-to-one with the unique device identifiers, and serving as the unique identifiers for model generation and data transfer during the interaction between end devices and edge computing nodes, and between edge computing nodes and the distribution network master station in the distribution network architecture, which are invisible to the business applications of end devices and the distribution network master station.

[0083] Optionally, the information models of the intelligent integrated terminal in the substation area and low-voltage devices are obtained through device modeling. The information models of the intelligent integrated terminal in the substation area and low-voltage devices are centered around the intelligent integrated terminal in the substation area, including the basic information of the intelligent integrated terminal in the substation area, the managed devices and topologies, and the asset information of the intelligent integrated terminal in the substation area.

[0084] In the embodiments of the present invention, as Figure 2 shown, the elastic resource IoT access enables the master station to actively discover newly installed or replaced devices in the system. On the premise of model and communication standardization, it enables devices to be put into operation with zero configuration, reduces the configuration workload at the construction site, and improves the accuracy of data collection. The plug-and-play of the distribution IoT includes two parts: the plug-and-play of end devices automatically registering with the cloud master station through edge devices and the plug-and-play of edge devices automatically registering with the cloud master station. To achieve the IoT access and rapid modeling of intelligent distributed resources, it mainly includes three aspects: interaction format, device identifier, and device modeling.

[0085] (1) Interaction format

[0086] The model description format of the distribution IoT master station (cloud master station) should preferably adopt the Extensible Markup Language (XML), and its schema uses the Resource Description Framework (RDF) specification language. In the distribution IoT architecture, the end devices (end side) and edge computing nodes (edge side) should preferably adopt the binary encoding method, and the edge side and the master station side should preferably adopt the Json data exchange format.

[0087] The interaction between the end side and the edge side is implemented based on the binary stream encoding method, and its content includes the asset information, measurement information, metering information, control commands, configuration information, etc. of the end device. The interaction between the edge side and the cloud master station is implemented based on the framework of the information model, and its content includes the model files of the end and edge devices, the substation area topology model file, and the asset information, measurement information, metering information, control commands, configuration information, etc. of the end and edge devices.

[0088] (2) Device identifier

[0089] The device identifier is as attached Figure 3As shown in the figure. The serial number SN is the unique identifier of the device, which is internally solidified at the time of factory production. The IoT device management identifier deviceID is uniformly assigned by the IoT platform and corresponds one-to-one with the SN. It serves as the unique identifier for model generation and data transfer during the interaction between the edge side and the cloud master station in the IoT architecture, and is invisible to the business applications of the end device and the cloud master station. The main resource identifier mRID is uniformly assigned by the cloud master station and is associated with the deviceID, serving as the unique identifier for resources in the cloud master station. The device serial number SN and the IoT device management identifier deviceID will disappear with the retirement of the device, while the main resource identifier mRID, as the running ID, will not change.

[0090] (3) Device Modeling

[0091] The overall framework of the information model of the substation area intelligent fusion terminal and low-voltage equipment is as attached Figure 4 As shown in the figure, with the substation area intelligent fusion terminal as the core, it includes the basic information of the substation area intelligent fusion terminal, the managed equipment and topology, and the asset information of the substation area intelligent fusion terminal. When the device is connected to the substation area intelligent fusion terminal, the device type and main parameters are obtained through information interaction, and the device self-registration is completed through the built-in standard information model.

[0092] Step 102, obtain power grid data through the power grid resource business middle platform, analyze the impact of the elastic resources in the substation area on the elasticity of the distribution network, analyze the elasticity of the distribution network, and combine the dynamic topology of the distribution network to fit the elastic resource map of the substation area.

[0093] Optionally, obtain power grid data through the power grid resource business middle platform, including: obtain the basic grid framework information of the target power grid to be analyzed through the power grid resource business middle platform; obtain the operation information of the distribution network through the power grid resource business middle platform.

[0094] Optionally, obtain the basic grid framework information of the target power grid to be analyzed through the power grid resource business middle platform, including: determine the key analysis equipment, and obtain the device ID of the key analysis equipment relying on the power grid resource business middle platform; starting from the key analysis equipment, obtain the power supply area of the target power grid through the device ID and relying on topological analysis to form a device tree or a device aggregate; rely on the connection relationship of the equipment to form a target grid set including all equipment and topological relationships.

[0095] Optionally, obtain the operation information of the distribution network through the power grid resource business middle platform, including: according to the equipment classification, determine the three sub-device aggregates of load, new energy power generation, and elastic resources; rely on the ID of the equipment to associate the equipment characteristics and measurement information; obtain the maximum load, minimum load, and typical daily load curve of the load equipment; obtain the installed capacity, output characteristic curve, and typical daily processing curve of the new energy power generation; obtain the maximum capacity, used capacity, and control characteristic curve of the elastic resources.

[0096] Optionally, analyze the impact of flexible resources in the substation area on the flexibility of the distribution network, including: analyzing the output law of distributed photovoltaics; analyzing the load characteristics and characterizing them through normal distribution; analyzing the adjustable capacity of flexible loads and energy storage.

[0097] Optionally, analyze the flexibility of the distribution network, including: dividing the fault response process of the distribution network into three stages: the pre-fault prevention stage, the fault penetration stage, and the fault recovery stage. The pre-fault prevention stage refers to the stage where the system absorbs faults and ensures normal operation. The fault penetration stage refers to the stage of performance degradation after the power grid fault, also known as the vulnerability stage. The fault recovery stage refers to the stage where the operator organizes the repair of the power grid and gradually restores the power grid to the normal operation level; establish corresponding power grid flexibility models for the above three stages; based on the established power grid flexibility models, calculate the loads restored by the interaction of flexible resources in the above three stages to achieve quantitative analysis of flexible resources.

[0098] Optionally, establish corresponding power grid flexibility models for the above three stages, including: for the pre-fault prevention stage, establish a power grid fault model to simulate power grid fault scenarios; for the fault penetration stage, establish a power grid vulnerability model to simulate the power grid vulnerability process; for the fault recovery stage, establish a power grid recovery process model to simulate the repair process of faulty components.

[0099] Optionally, call the microservices of the power grid resource business middle platform to obtain relevant data of the distribution network, including: obtain the information of equipment resources by calling the power grid resource center to establish basic power grid information data; obtain the operating status of equipment by calling the equipment status center; obtain the current topology by calling the power grid topology center, obtain flexible resource information, and obtain the flexible resource evaluation result through calculation; obtain the corresponding electrical diagram by calling the power grid graphics center and display it through the APP.

[0100] In the embodiment of the present invention, the analysis of flexible resources in the substation area mainly includes equipment data acquisition, power grid flexibility analysis, and flexible resource atlas of the substation area.

[0101] (1) Data acquisition; as Figure 5 shown, rely on the enterprise middle platform to complete the acquisition of power grid data.

[0102] A) Acquisition of basic grid framework information of the target power grid to be analyzed.

[0103] A1), determine the key analysis equipment and rely on the power grid resource business middle platform to obtain the equipment ID. The key equipment can be a transformer, a feeder, or the starting equipment of the target grid framework to be analyzed.

[0104] A2), starting from the key equipment, obtain the power supply area of the target power grid through the equipment ID and rely on topological analysis to form an equipment tree or an equipment aggregate.

[0105] A3), relying on the connection relationships of the devices, form a target grid network set that includes all devices and topological relationships.

[0106] B) Obtain operation information based on the target grid network set.

[0107] B1) According to device classification, determine three types of sub-device aggregates: load, new energy power generation, and flexible resources.

[0108] B2) Relying on the IDs of the devices, associate operation information such as device characteristics and measurements.

[0109] For load devices, obtain the maximum load, minimum load, and typical daily load curve.

[0110] For new energy power generation, obtain the installed capacity, output characteristic curve, and typical daily processing curve.

[0111] For flexible resources, obtain the maximum capacity, used capacity, and control characteristic curve.

[0112] (2) The impact of distributed resource output on the resilience of the distribution network;

[0113] A) Analysis of the output law of distributed photovoltaics. By approximating the probability distribution of light intensity with a beta distribution, the photovoltaic output is proportional to the light intensity;

[0114] B) Load characteristic analysis, characterized by a normal distribution. Continuous random variables cannot be directly applied to the study of multi-scenario problems and need to be discretized. However, discretization will inevitably reduce the integrity of the distribution characteristic description, and an appropriate method should be selected to minimize the impact of discretization on the distribution characteristics.

[0115] C) Analysis of the adjustable capacity of flexible loads and energy storage.

[0116] As Figure 6 shown, the power grid fault response process is divided into three stages:

[0117] Pre-fault prevention stage (t0 ≤ t ≤ t1), referring to the stage where the system absorbs faults and ensures normal operation;

[0118] Fault penetration stage (t1 ≤ t ≤ t2), referring to the stage of performance degradation after the power grid fault, also known as the vulnerability stage;

[0119] Fault recovery stage (t2 ≤ t ≤ t3), referring to the stage where the operator organizes the repair of the power grid and gradually restores the power grid to the normal operation level.

[0120] In the embodiments of the present invention, a distribution network resilience model is established for three processes, including: establishing a power grid fault model to simulate power grid fault scenarios; establishing a power grid vulnerability model to simulate the power grid vulnerability process; establishing a power grid restoration process model to simulate the repair process of faulty components. Further, the load of the interactive restoration of resilient resources in the three processes is calculated to achieve quantitative analysis of resilient resources.

[0121] In the embodiments of the present invention, resilience indicators are almost all proposed based on the performance curve PR(t) of the system under normal conditions and the actual performance curve PT(t) under disaster conditions. Resilience is quantified as the ratio of the integral of the actual repair curve PR(t) of the power grid with the time axis to the integral of the expected performance curve PT(t) with the time axis from time 0 to time T, so as to fully reflect the resistance, absorption, and restoration capabilities of the power grid. The formula is as follows:

[0122]

[0123] Step 103, call the microservices of the power grid resource business middle platform to obtain relevant data of the distribution network to achieve macro data monitoring.

[0124] In the embodiments of the present invention, as Figure 7 shown, the micro application APP for the Internet of Things analysis of resilient resources in the distribution substation area calls the microservices of the power grid resource business middle platform to obtain necessary data and support:

[0125] 1) Obtain the information of equipment resources by calling the power grid resource center to establish basic power grid information data;

[0126] 2) Obtain the operating status of the equipment by calling the equipment status center;

[0127] 3) Call the power grid topology center to obtain the current topology, obtain resilient resource information, and obtain the resilient resource evaluation result through calculation;

[0128] Obtain the corresponding electrical diagram by calling the power grid graphics center and display it in the form of an APP. The micro application for the Internet of Things analysis of resilient resources in the distribution substation area realizes macro data monitoring, including platform dashboards, data dashboards, data application dashboards, etc. In addition, key monitoring modules such as access monitoring, data service monitoring, and data quality monitoring of the data platform are monitored. Its overall logic is as shown in the appendix Figure 8 shown.

[0129] Therefore, the present invention takes the transformer substation area as the minimum intelligent management unit to realize the Internet of Things access and rapid modeling of various intelligent distributed resources. Relying on the power grid resource business middle platform, it analyzes the electricity consumption laws of diversified loads and the output capabilities of distributed resources, combines with the dynamic topology of the distribution network, fits the elastic resource map of the transformer substation area, and realizes online analysis. Finally, it provides a micro application for the Internet of Things analysis of the elastic resources of the distribution transformer substation area based on the power grid resource business middle platform. The present invention can realize the lightweight layout of the management and analysis system in the form of service calls. The technology for rapid access and modeling of the elastic resources of the distribution network based on the business middle platform of the present invention can realize the automatic identification, automatic registration, and automatic modeling of elastic resources after they are connected to the power grid. Based on the real-time operation data of the power grid, load data, and the performance of elastic resources, the present invention can analyze the elasticity of the distribution transformer substation area online in real time, providing a scientific means for the real-time operation control of the transformer substation area.

[0130] Exemplary apparatus

[0131] Figure 9 FIG. is a schematic structural diagram of a device for managing elastic resources of a distribution transformer substation area based on a business middle platform provided by an exemplary embodiment of the present invention. As Figure 9 shown, the device 900 includes:

[0132] An elastic resource Internet of Things access module 910, configured to take the transformer substation area as the minimum intelligent management unit and connect various elastic resources to the distribution network through the Internet of Things by determining the interaction format, clarifying the device identifier, and device modeling;

[0133] A transformer substation area elastic resource analysis module 920, configured to obtain power grid data through the power grid resource business middle platform, analyze the impact of the elastic resources of the transformer substation area on the elasticity of the distribution network, analyze the elasticity of the distribution network, and fit the elastic resource map of the transformer substation area in combination with the dynamic topology of the distribution network;

[0134] A micro application module 930, configured to call the microservices of the power grid resource business middle platform to obtain relevant data of the distribution network to realize macro data monitoring.

[0135] Optionally, in the distribution network architecture, the end device and the edge computing node adopt a binary-coded interaction format, and the edge computing node and the distribution network master station adopt a Json data interaction format.

[0136] Optionally, the device identifier of the distribution network is uniformly allocated by the IoT platform, corresponding one-to-one with the unique device identifier, and used as the unique identifier for model generation and data transfer in the interaction process between the end device and the edge computing node, and between the edge computing node and the distribution network master station in the distribution network architecture, and is invisible to the business applications of the end device and the distribution network master station.

[0137] Optionally, the information models of the district intelligent fusion terminal and low-voltage equipment are obtained through device modeling. The information models of the district intelligent fusion terminal and low-voltage equipment take the district intelligent fusion terminal as the core, including the basic information of the district intelligent fusion terminal, the managed equipment and topology, as well as the asset information of the district intelligent fusion terminal.

[0138] Optionally, the district elastic resource analysis module 920 is specifically used for:

[0139] Obtain the basic grid framework information of the target power grid to be analyzed through the power grid resource business platform;

[0140] Obtain the operation information of the distribution network through the power grid resource business platform.

[0141] Optionally, the district elastic resource analysis module 920 is also specifically used for:

[0142] Determine the key analysis equipment, and obtain the equipment ID of the key analysis equipment relying on the power grid resource business platform;

[0143] Starting from the key analysis equipment, obtain the power supply area of the target power grid through the equipment ID and relying on topological analysis, and form an equipment tree or an equipment aggregate;

[0144] Relying on the connection relationship of the equipment, form a target grid aggregate including all equipment and topological relationships.

[0145] Optionally, the district elastic resource analysis module 920 is also specifically used for:

[0146] According to the equipment classification, determine three sub-equipment aggregates of load, new energy power generation, and elastic resources;

[0147] Relying on the ID of the equipment, associate the equipment characteristics and measurement information;

[0148] Obtain the maximum load, minimum load, and typical daily load curve of the load equipment;

[0149] Obtain the installed capacity, output characteristic curve, and typical daily processing curve of new energy power generation;

[0150] Obtain the maximum capacity, used capacity, and control characteristic curve of elastic resources.

[0151] Optionally, the district elastic resource analysis module 920 is used for:

[0152] Analyze the output law of distributed photovoltaics;

[0153] Analyze the load characteristics and represent them through normal distribution;

[0154] Analyze the adjustable capacity of flexible loads and energy storage.

[0155] Optionally, the substation area elastic resource analysis module 920 is configured to:

[0156] Divide the distribution network fault response process into three stages: the pre-fault prevention stage, the fault penetration stage, and the fault recovery stage. The pre-fault prevention stage refers to the stage where the system absorbs faults and ensures normal operation. The fault penetration stage refers to the stage of performance degradation after a power grid fault, also known as the vulnerability stage. The fault recovery stage refers to the stage where the operator organizes the repair of the power grid and gradually restores the power grid to the normal operation level;

[0157] Establish corresponding power grid resilience models for the above three stages;

[0158] Based on the established power grid resilience models, calculate the loads of the elastic resource interaction recovery in the above three stages to achieve quantitative analysis of elastic resources.

[0159] Optionally, the substation area elastic resource analysis module 920 is further configured to:

[0160] For the pre-fault prevention stage, establish a power grid fault model to simulate power grid fault scenarios;

[0161] For the fault penetration stage, establish a power grid vulnerability model to simulate the power grid vulnerability process;

[0162] For the fault recovery stage, establish a power grid recovery process model to simulate the repair process of faulty components.

[0163] Optionally, the micro-application module 930 is specifically configured to:

[0164] Obtain information on equipment resources by calling the power grid resource center and establish basic power grid information data;

[0165] Obtain the operating status of equipment by calling the equipment status center;

[0166] Obtain the current topology by calling the power grid topology center, obtain elastic resource information, and obtain an elastic resource evaluation result through calculation;

[0167] Obtain the corresponding electrical diagram by calling the power grid graphics center and display it in the form of an APP.

[0168] The distribution substation area elastic resource management device 900 based on the service middle platform in the embodiment of the present invention corresponds to the distribution substation area elastic resource management method 100 in another embodiment of the present invention, and will not be elaborated here.

[0169] Exemplary electronic device

[0170] Figure 10It is the structure of an electronic device provided by an exemplary embodiment of the present invention. The electronic device can be either the first device or the second device, or both, or a stand-alone device independent of them. The stand-alone device can communicate with the first device and the second device to receive the input signals collected by them. Figure 10 The block diagram of an electronic device according to an embodiment of the present invention is illustrated. As Figure 10 shown, the electronic device 100 includes one or more processors 101 and a memory 102.

[0171] The processor 101 can be a central processing unit (CPU) or other forms of processing units with data processing capabilities and / or instruction execution capabilities, and can control other components in the electronic device to perform desired functions.

[0172] The memory 102 can include one or more computer program products, and the computer program products can include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory can include, for example, random access memory (RAM) and / or cache memory, etc. The non-volatile memory can include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions can be stored on the computer-readable storage medium, and the processor 101 can run the program instructions to implement the method of information mining on historical change records of the software programs of various embodiments of the present invention described above and / or other desired functions. In one example, the electronic device can further include: an input device 103 and an output device 104, and these components are interconnected through a bus system and / or other forms of connection mechanisms (not shown).

[0173] In addition, the input device 103 can further include, for example, a keyboard, a mouse, and so on.

[0174] The output device 104 can output various information to the outside. The output device 104 can include, for example, a display, a speaker, a printer, and a communication network and its connected remote output devices, and so on.

[0175] Of course, for simplicity, Figure 10 only some of the components related to the present invention in the electronic device are shown in, and components such as buses, input / output interfaces, etc. are omitted. In addition, according to specific application scenarios, the electronic device can further include any other appropriate components.

[0176] Exemplary computer program product and computer-readable storage medium

[0177] In addition to the above methods and devices, embodiments of the present invention may also be computer program products, which include computer program instructions that, when run on a processor, cause the processor to execute the steps in the method of information mining on historical change records according to various embodiments of the present invention described in the above "Exemplary Method" section of this specification.

[0178] The computer program product can be written in any combination of one or more programming languages for the program code to perform the operations of the embodiments of the present invention. The programming languages include object-oriented programming languages such as Java, C++, etc., and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computing device, partially on the user's device, executed as an independent software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0179] Furthermore, embodiments of the present invention may also be computer-readable storage media, on which computer program instructions are stored, and the computer program instructions, when run on a processor, cause the processor to execute the steps in the method of information mining on historical change records according to various embodiments of the present invention described in the above "Exemplary Method" section of this specification.

[0180] The computer-readable storage media may adopt any combination of one or more readable media. The readable media may be a readable signal medium or a readable storage medium. The readable storage medium may, for example, include but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination of the above. More specific examples (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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0181] The basic principles of the present invention have been described above in conjunction with specific embodiments. However, it should be noted that the advantages, advantages, effects, etc. mentioned in the present invention are only examples and not limitations. It cannot be considered that these advantages, advantages, effects, etc. are essential for each embodiment of the present invention. In addition, the above-disclosed specific details are only for the purposes of illustration and facilitating understanding, rather than limitations. The above details do not limit the present invention to necessarily adopt the above specific details for implementation.

[0182] In the embodiments described in this specification, a progressive approach is adopted. Each embodiment focuses on the differences from other embodiments. For the same or similar parts among the embodiments, reference can be made to each other. For system embodiments, since they basically correspond to method embodiments, the description is relatively simple. For relevant parts, reference can be made to the corresponding parts of the method embodiments.

[0183] The block diagrams of the devices, systems, equipment, and systems involved in the present invention are only illustrative examples and are not intended to require or imply that they must be connected, arranged, and configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, systems, equipment, and systems can be connected, arranged, and configured in any manner. Words such as "including", "comprising", "having", etc. are open-ended terms, meaning "including but not limited to", and can be used interchangeably with each other. The words "or" and "and" used herein refer to the phrase "and / or", and can be used interchangeably with it, unless the context clearly indicates otherwise. The word "such as" used herein refers to the phrase "such as but not limited to", and can be used interchangeably with it.

[0184] The methods and systems of the present invention can be implemented in many ways. For example, the methods and systems of the present invention can be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above order of the steps for the method is only for illustration. The steps of the method of the present invention are not limited to the specific order described above, unless otherwise specifically stated. In addition, in some embodiments, the present invention can also be implemented as a program recorded in a recording medium, and these programs include machine-readable instructions for implementing the method according to the present invention. Therefore, the present invention also covers a recording medium storing a program for executing the method according to the present invention.

[0185] It should also be noted that in the systems, equipment, and methods of the present invention, each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent solutions of the present invention. The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these aspects are very obvious to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of the present invention. Therefore, the present invention is not intended to be limited to the aspects shown herein, but rather to the broadest scope consistent with the principles and novel features disclosed herein.

[0186] The above description has been given for purposes of illustration and description. In addition, this description is not intended to limit the embodiments of the present invention to the forms disclosed herein. Although multiple example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, changes, additions, and sub-combinations thereof.

Claims

1. A method for managing elastic resources in a distribution substation area based on a business middle platform, characterized in that, Including: Taking the power distribution area as the minimum intelligent management unit, various elastic resources are connected to the power distribution network through determining the interaction format, clarifying the device identification, and device modeling; Obtaining power grid data through the power grid resource service center, analyzing the impact of the elastic resources in the power distribution area on the power grid elasticity, analyzing the power grid elasticity, and combining with the dynamic topology of the power distribution network to fit the elastic resource map of the power distribution area; Invoking the microservices of the power grid resource service center to obtain relevant data of the power distribution network to achieve macro data monitoring, including: obtaining the information of device resources through the power grid resource center to establish basic power grid information data; obtaining the operating status of the device through the device status center; obtaining the current topology through the power grid topology center to obtain elastic resource information and calculating the elastic resource evaluation result through calculation; obtaining the corresponding electrical diagram through the power grid graphic center and displaying it through the APP; Analyzing the impact of the elastic resources in the power distribution area on the power grid elasticity, including: analyzing the output law of distributed photovoltaic; analyzing the load characteristics and representing them through normal distribution; analyzing the adjustable capacity of flexible loads and energy storage; Analyzing the power grid elasticity, including: dividing the power grid fault response process into three stages: pre-fault prevention stage, fault penetration stage, and fault recovery stage. The pre-fault prevention stage refers to the stage when the system absorbs faults and ensures normal operation. The fault penetration stage refers to the stage of performance degradation after the power grid fault, also known as the vulnerability stage. The fault recovery stage refers to the stage when the operator organizes the repair of the power grid and gradually restores the power grid to the normal operation level; establishing corresponding power grid elasticity models for the above three stages; based on the established power grid elasticity models, calculating the loads restored by the interaction of elastic resources in the above three stages to achieve quantitative analysis of elastic resources.

2. The method according to claim 1, characterized in that, In the power distribution network architecture, the end device and the edge computing node adopt a binary encoding interaction format, and the edge computing node and the power distribution network master station adopt a Json data interaction format.

3. The method according to claim 1, characterized in that, The device identification of the power distribution network is uniformly assigned by the IoT platform and corresponds one-to-one with the unique device identification. It is used as the unique identification for model generation and data flow in the interaction process between the end device and the edge computing node, and between the edge computing node and the power distribution network master station in the power distribution network architecture, and is invisible to the business applications of the end device and the power distribution network master station.

4. The method according to claim 1, characterized in that, Obtaining the information models of the intelligent fusion terminal and low-voltage devices in the power distribution area through device modeling. The information models of the intelligent fusion terminal and low-voltage devices in the power distribution area take the intelligent fusion terminal in the power distribution area as the core, including the basic information of the intelligent fusion terminal in the power distribution area, the managed devices and topology, and the asset information of the intelligent fusion terminal in the power distribution area.

5. The method according to claim 1, characterized in that, Obtaining power grid data through the power grid resource service center, including: Obtaining the basic grid framework information of the target power grid to be analyzed through the power grid resource service center; Obtaining the operation information of the power distribution network through the power grid resource service center.

6. The method according to claim 5, characterized in that, Obtaining the basic grid framework information of the target power grid to be analyzed through the power grid resource service center, including: Determining the key analysis devices and relying on the power grid resource service center to obtain the device IDs of the key analysis devices; Starting from the key analysis devices, obtaining the power supply area of the target power grid through the device IDs and relying on topology analysis to form a device tree or a device aggregate; Based on the connection relationships of the devices, a target grid framework set including all devices and topological relationships is formed.

7. The method according to claim 5, characterized in that, Obtain the operation information of the distribution network through the power grid resource business middle platform, including: Determine three types of sub-device aggregates of load, new energy power generation, and flexible resources according to device classification; Based on the IDs of the devices, associate device characteristics and measurement information; Obtain the maximum load, minimum load, and typical daily load curve of load devices; Obtain the installed capacity, output characteristic curve, and typical daily processing curve of new energy power generation; Obtain the maximum capacity, used capacity, and control characteristic curve of flexible resources.

8. The method according to claim 1, characterized in that, Establish corresponding power grid elasticity models for the above three stages, including: For the pre-fault prevention stage, establish a power grid fault model to simulate power grid fault scenarios; For the fault penetration stage, establish a power grid vulnerability model to simulate the power grid vulnerability process; For the fault recovery stage, establish a power grid recovery process model to simulate the repair process of faulty components.

9. A device for managing elastic resources in a distribution substation area based on a business middle platform, characterized in that, Including: The flexible resource Internet of Things access module is used to connect various flexible resources to the distribution network through the Internet of Things with the substation area as the smallest intelligent management unit by determining the interaction format, clarifying the device identification, and device modeling; The substation area flexible resource analysis module is used to obtain power grid data through the power grid resource business middle platform, analyze the impact of substation area flexible resources on the power grid elasticity, analyze the power grid elasticity, and combine the power grid dynamic topology to fit the substation area flexible resource map; The micro-application module is used to call the microservices of the power grid resource business middle platform to obtain relevant data of the distribution network to achieve macro data monitoring, including: obtaining the information of device resources through the power grid resource center to establish basic power grid information data; obtaining the operation status of devices through the device status center; obtaining the current topology through the power grid topology center, obtaining flexible resource information, and obtaining the flexible resource evaluation result through calculation; obtaining the corresponding electrical diagram through the power grid graphics center and displaying it through the APP; Analyze the impact of substation area flexible resources on the power grid elasticity, including: analyzing the output law of distributed photovoltaics; analyzing load characteristics and representing them through normal distribution; analyzing the adjustable capacity of flexible loads and energy storage; Analyze the power grid elasticity, including: dividing the power grid fault response process into three stages: the pre-fault prevention stage, the fault penetration stage, and the fault recovery stage. The pre-fault prevention stage refers to the stage where the system absorbs faults and ensures normal operation. The fault penetration stage refers to the stage of performance degradation after the power grid fault, also known as the vulnerability stage. The fault recovery stage refers to the stage where the operator organizes the repair of the power grid and gradually restores the power grid to the normal operation level; establish corresponding power grid elasticity models for the above three stages; based on the established power grid elasticity models, calculate the load restored by the interaction of flexible resources in the above three stages to achieve quantitative analysis of flexible resources.

10. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, and the computer program is used to execute the method according to any one of claims 1-8 above.

11. An electronic device, characterized in that, The electronic device includes: A processor; A memory for storing executable instructions of the processor; The processor is configured to read the executable instructions from the memory and execute the instructions to implement the method according to any one of claims 1-8 above.

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