Encoding method of a full-link device and energy management system

Abstract

This invention discloses a coding method and energy management system for end-to-end devices. A globally unique code is constructed for each device in the chain, with a length of 36 characters, composed of uppercase letters and numbers. Upper-level and lower-level nodes generate high-voltage path codes using prefix matching parent-child binding rules, forming a binding association between lower-level and upper-level nodes. The system of this invention can automatically build charging stations upon device power-on, automatically generate the entire chain power distribution topology, automatically calculate transformer losses, benchmark energy consumption of similar devices, analyze loss rationality, and automatically evaluate equipment energy efficiency. This invention completely solves the pain points of existing coding systems, such as fragmented ownership, inability to automatically build charging stations, and inability to support end-to-end energy analysis, adapting to the needs of large-scale operation and maintenance and refined energy management of charging stations nationwide.

Description

Technical Field

[0001] This invention belongs to the field of new energy power system operation and maintenance and energy management technology, and specifically relates to a coding method covering charging station high and low voltage power distribution, charging piles, photovoltaics, energy storage, metering instruments and other equipment, as well as an energy management system based on the coding that realizes automatic station construction, full-link energy consumption analysis and intelligent equipment energy efficiency analysis. Background Technology

[0002] With the rapid development of the new energy vehicle industry, the construction scale of charging stations across the country has experienced explosive growth. A single charging station often integrates 10kV high-voltage power distribution equipment, transformers, 0.4kV low-voltage power distribution equipment, AC / DC charging piles, distributed photovoltaics, energy storage systems, and various power metering instruments. The diverse equipment types, complex power distribution links, and wide distribution of sites place extremely high demands on the equipment management, energy consumption accounting, and intelligent energy efficiency analysis capabilities of the operation and maintenance system.

[0003] Equipment coding is a core foundation of operation and maintenance systems. Existing equipment coding schemes have the following key flaws: 1. Insufficient coding coverage: Existing codes are mostly only for single charging pile devices or only compatible with traditional power distribution equipment on the grid side. They cannot be compatible with all types of equipment in the charging station scenario, including photovoltaic, energy storage, charging piles, and metering instruments. This results in data isolation between different devices and makes it impossible to achieve full-link energy data linkage.

[0004] 2. Fragmented attribution relationships prevent accurate loss calculation: Existing codes mostly adopt a high-voltage and low-voltage domain isolation design, which can only reflect a single level of equipment. It cannot connect the entire link of "high-voltage incoming line → transformer → low-voltage distribution → terminal equipment", which means that transformer loss and line loss cannot be automatically matched and calculated through codes. The corresponding relationship must be manually configured, which is inefficient, error-prone and cannot meet the operation and maintenance needs of large-scale sites across the country.

[0005] 3. Lack of automatic site building capability: The existing coding can only realize the unique identification of the equipment. It cannot automatically resolve the site ownership, power distribution topology, and upstream and downstream links through the coding. The new site must be manually entered, the power distribution topology must be drawn, and the equipment file must be created. The site building cycle is long and the labor cost is high, which cannot meet the needs of rapid large-scale deployment of charging stations.

[0006] 4. Inability to support end-to-end intelligent energy data analysis: Existing coding cannot simultaneously distinguish between equipment type and energy consumption attribution, and cannot achieve core intelligent energy analysis functions such as energy consumption benchmarking of similar equipment, loss rationality analysis, and equipment energy efficiency assessment based on coding. As a result, the operation and maintenance system can only achieve basic equipment monitoring and cannot achieve refined energy management and energy efficiency optimization. Summary of the Invention

[0007] To address the aforementioned technical problems, this invention provides a coding method for end-to-end devices and an energy management system.

[0008] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: An encoding method for a full-link device includes the following steps: The method is based on an end-to-end system containing several devices, each of which is a first-level node; A globally unique code is constructed for each device, with a length of 36 characters, consisting of uppercase letters and numbers. The encoding structure is SSBBBBBBPPPPPPPPPPPPPPPPTTTCCCNNNNNS, where SS is a 2-bit distinguishing code, BBBBBB is a 6-bit site unique code, PPPPPPPPPPPPPPPP is a 16-bit full-link topology attribution code, TTT is a 3-bit device category code, CCC is a 3-bit device subclass code, NNNNN is a 5-bit device serial number, and S is a 1-bit check code. The 16-bit full-link topology attribution code is structured as GGGGGGGGHHDDDDDD, where GGGGGGGG is an 8-bit high-voltage path code, divided into 4 levels, with 2 bits per level; BB is a 2-bit unique anchor code for relay equipment, and each relay equipment has an immutable unique anchor code; DDDDDD is a 6-bit low-voltage path code, divided into 3 levels, with 2 bits per level. In the end-to-end system, the high-voltage path code of the next-level node is formed by binding the prefix code of the high-voltage path code of the previous-level node; the relay equipment anchor code of the next-level node is bound to the relay equipment anchor code of the previous-level node; the low-voltage path code of the next-level node includes the prefix code of the high-voltage path code of the previous-level node and the relay equipment anchor code.

[0009] As a further improvement, in the full-link system, the next-level node and the previous-level node use a prefix matching parent-child binding rule to generate high-voltage path codes. Specifically, the previous-level node is defined as the parent node, and the next-level node is defined as the child node. The 8-bit high-voltage path code of the child node is formed by cyclically constructing the 2-bit prefix code in the 8-bit high-voltage path code of the parent node. If the parent node contains a non-zero code, the child node completely inherits and contains the non-zero code. This is used by the platform to automatically identify the hierarchical relationship and generate a topology tree.

[0010] As a further improvement, the structure of the 6-digit unique station code is 2-digit province code, 2-digit city code, and 2-digit station serial number. The province code and city code adopt the national unified administrative division code, and the station serial number is the self-incrementing number of the station within the corresponding city, with a value range of 01-99.

[0011] As a further improvement, the equipment category code is used to distinguish equipment types, and the equipment sub-category code corresponds one-to-one with the equipment category code to further subdivide equipment models and functions, thereby enabling automatic matching of equipment acquisition protocols and data point tables.

[0012] As a further improvement, the check bit is generated using a modulo-10 check algorithm to prevent encoding errors and dirty data from being entered into the database during the acquisition process.

[0013] An energy management system, comprising: The equipment acquisition module is used to collect 36-bit globally unique codes and equipment operation and energy consumption data reported by field equipment; The encoding parsing module is used to segment and parse the reported globally unique encoding, extract site information, topology attribution information, device type information, and complete the verification of the validity of the check bit. The automatic website building module is used to automatically create website files based on the unique website code obtained from code parsing, and at the same time, automatically match the device model and create the device file based on the device type information; The topology generation module is used to automatically identify the hierarchical relationship of devices based on the full-link topology attribution code obtained by encoding and parsing, and generate a full-link power distribution topology map through prefix matching rules. The energy data analysis module is used to compare key energy consumption indicators, automatically calculate equipment losses, analyze the rationality of losses, and evaluate equipment energy efficiency based on segmented information with globally unique codes.

[0014] As a further improvement, the specific workflow of the automatic site building module is as follows: based on the unique site code obtained from the code parsing, it is determined whether a corresponding site exists. If it does not exist, the site file is automatically created and regional management permissions are assigned based on the province and city codes in the unique site code. At the same time, the device's acquisition protocol, data point table, and alarm threshold are automatically matched based on the device category code and device sub-category code to create a device file.

[0015] As a further improvement, the specific process of automatic equipment loss calculation in the energy data analysis module is as follows: based on the anchor code of the equipment, the signal input metering data and signal output metering data corresponding to the same type of equipment are automatically matched, and the total equipment loss, load loss and loss rate are automatically calculated.

[0016] As a further improvement, the specific process for comparing key energy consumption indicators in the energy data analysis module is as follows: based on the equipment category code and equipment sub-category code, filter equipment of the same type and specifications, automatically compare the core indicators of unit energy consumption, load rate, and utilization rate, and generate a cross-site benchmarking analysis report.

[0017] As a further improvement, the specific process of equipment energy efficiency assessment in the energy data analysis module is as follows: based on the equipment's full-link affiliation, combined with equipment operation data and energy consumption data, the core energy efficiency indicators of the equipment are automatically calculated, and combined with benchmarking data of similar equipment, the equipment is rated for energy efficiency and energy efficiency optimization suggestions are generated.

[0018] The present invention has the following beneficial technical effects: 1. One code with multiple functions, simultaneously realizing device type differentiation and full-link attribution binding: The globally unique code integrates four core pieces of information: site identifier, full-link topology attribution, device type, and device unique identifier. It can accurately distinguish device types through device category code and device sub-category code, and can also connect the high- and low-voltage full-link attribution relationship through the 16-bit full-link topology attribution code, completely solving the core pain point of the fragmented attribution of existing codes.

[0019] 2. Automatic and accurate calculation of transformer losses with zero manual configuration: By binding all data of high voltage input, transformer body and low voltage output through a 2-digit unique anchor code of the transformer, the platform can automatically match and calculate transformer losses through coding, without the need for manual configuration of corresponding relationships, and adapt to the operation and maintenance needs of large-scale sites across the country.

[0020] 3. Truly achieve automatic site creation upon device power-on: After the device reports the site code, topology ownership code, and device type code in the code, the platform can automatically complete site creation, topology generation, device file establishment, and data collection protocol matching after the device is powered on and reports the code. The entire process requires no manual intervention, which greatly shortens the new site launch cycle and reduces labor costs.

[0021] 4. Automated implementation of end-to-end energy data analysis: Based on coded segmented information, it can automatically achieve cross-site energy consumption benchmarking of similar equipment, end-to-end loss rationality analysis, and automated equipment energy efficiency assessment, which completely solves the problem of insufficient energy analysis capabilities of existing operation and maintenance systems, and realizes refined energy management and energy efficiency optimization of charging stations.

[0022] 5. Industrial-grade compatibility and scalability: 36-bit fixed-length encoding with no special characters, compatible with all industrial acquisition protocols and hardware terminals, supports complex power distribution scenarios such as unlimited cascading of high-voltage ring networks and multi-level branches of low-voltage networks, and can adapt to large-scale management needs. Detailed Implementation

[0023] The embodiments of the present invention are described in detail below.

[0024] An encoding method for a full-link device includes the following steps: The method is based on a full-link system comprising several devices, each device being a primary node. The full-link system can be a power distribution network for a charging station or an energy management network for an industrial park. In this system, each device is considered a node; for example, a transformer or a charging pile can be a node. These sub-nodes form a complete link through physical connections or logical relationships.

[0025] A globally unique code is constructed for each device, with a length of 36 characters, consisting of uppercase letters and numbers. The encoding structure is SSBBBBBBPPPPPPPPPPPPPPPPTTTCCCNNNNNS, where SS is a 2-bit distinguishing code, BBBBBB is a 6-bit site unique code, PPPPPPPPPPPPPPPP is a 16-bit full-link topology attribution code, TTT is a 3-bit device category code, CCC is a 3-bit device subclass code, NNNNN is a 5-bit device serial number, and S is a 1-bit check code. The 16-bit full-link topology attribution code is structured as GGGGGGGGHHDDDDDD, where GGGGGGGG is an 8-bit high-voltage path code, divided into 4 levels, with 2 bits per level; BB is a 2-bit unique anchor code for relay equipment, and each relay equipment has an immutable unique anchor code; DDDDDD is a 6-bit low-voltage path code, divided into 3 levels, with 2 bits per level. In the end-to-end system, the high-voltage path code of the next-level node is formed by binding the prefix code of the high-voltage path code of the previous-level node; the relay equipment anchor code of the next-level node is bound to the relay equipment anchor code of the previous-level node; the low-voltage path code of the next-level node includes the prefix code of the high-voltage path code of the previous-level node and the relay equipment anchor code.

[0026] A full-link system consists of multiple devices connected via wired or wireless signals, arranged sequentially from the signal input to the user end according to their beginning and end relationships.

[0027] SS Distinguishing Code, which can be fixed to CN to represent sites within China, is used for site expansion and to identify country / region. It is set according to the common codes of different countries.

[0028] The structure of the 6-digit unique station code consists of a 2-digit province code, a 2-digit city code, and a 2-digit station serial number. The province code and city code adopt the national unified administrative division code, and the station serial number is an auto-incrementing number of the station within the corresponding city, with a value range of 01-99.

[0029] Equipment Category Code (TTT): This refers to a 3-character field in the globally unique code used to identify the general category of the equipment. For example, it can be used to distinguish between transformers, charging piles, and photovoltaic inverters. The value range is 001-999, and can be flexibly defined, such as: 001=Charging pile equipment, 002=Photovoltaic equipment, 003=Energy storage equipment, 004=Power distribution equipment, 005=Power metering instruments, 006=Environmental monitoring equipment, 999=Other auxiliary equipment.

[0030] Equipment subclass code CCC: refers to a 3-character field in the globally unique code, which corresponds one-to-one with the equipment major class code, realizing automatic matching of equipment model, acquisition protocol, and data point table. For example: under the major class of power distribution equipment, 001=high voltage main incoming line cabinet, 002=high voltage outgoing line cabinet, 005=power transformer, 006=low voltage main incoming line cabinet, 007=low voltage feeder cabinet; under the major class of metering instruments, 001=high voltage side metering meter, 002=low voltage side main metering meter, 003=feeder circuit metering meter.

[0031] Device Serial Number NNNNN: This refers to a 5-character field in the globally unique code, used to uniquely identify devices within the same site and of the same type. For example, it can be used to distinguish multiple charging piles of the same model. It is a unique, auto-incrementing number for devices of the same type within the site, ranging from 00001 to 99999, automatically assigned by the platform without manual intervention.

[0032] Checksum S: Refers to a 1-bit character segment in the globally unique code, used to verify the legality of the entire code to prevent errors that may occur during data transmission or data entry. It is generated using a modulo-10 checksum algorithm to prevent encoding errors and dirty data from being entered into the database during the data acquisition process. The hardware terminal can pre-program the checksum, and the platform can automatically verify the code's legality.

[0033] In a full-link system, to establish topological affiliation between devices, the high-voltage path code of a lower-level sub-node is bound by the prefix code of the high-voltage path code of the upper-level sub-node. For example, if the code of a high-voltage distribution cabinet contains a high-voltage path code, then the prefix part of the high-voltage path code in the code of the next-level device (e.g., a transformer) connected to that distribution cabinet will match the high-voltage path code of that distribution cabinet. Simultaneously, the relay device anchor code of a lower-level sub-node is bound to the relay device anchor code of the upper-level sub-node. For example, if a transformer is identified as a relay device, then the anchor code in the code of the low-voltage distribution cabinet connected to that transformer will be consistent with the anchor code of that transformer. Furthermore, the low-voltage path code binding of a lower-level sub-node includes the prefix code of the high-voltage path code of the upper-level sub-node and the relay device anchor code. For example, the low-voltage path code of a charging pile not only reflects its hierarchy on the low-voltage side but also includes the prefix information of its upstream high-voltage path code and the anchor code of the relay transformer, thus achieving the connection between high and low voltage links.

[0034] By constructing a structured, globally unique code and utilizing the full-link topology attribution code in the code to achieve hierarchical binding between devices, the problem of insufficient device coding coverage, fragmented attribution relationships, lack of automatic station building capabilities, and difficulty in supporting full-link intelligent energy analysis in complex scenarios such as charging stations is effectively solved, providing basic support for realizing full-link device management, accurate energy consumption accounting, and intelligent energy efficiency assessment.

[0035] In the full-link system, the next-level child node and the previous-level child node generate high-voltage path codes using a prefix matching parent-child binding rule. Specifically, the 8-bit high-voltage path code of the next-level child node is formed by cyclically constructing the 2-bit prefix code of the 8-bit high-voltage path code of the previous-level child node. If the previous-level child node contains a non-zero code, then the next-level child node completely inherits and includes that non-zero code. This is used by the platform to automatically identify the hierarchical relationship and generate a topology tree.

[0036] This prefix matching parent-child binding rule is the core mechanism for ensuring the accurate establishment of device hierarchy relationships in the end-to-end system. Through specific structured processing of the high-voltage path code, the system can automatically identify the parent-child relationship between devices. The introduction of this rule transforms the high-voltage path code from merely an identifier into a code containing topological information, providing a foundation for automated topology construction. Specifically, the 8-bit high-voltage path code GGGGGGGG in the 16-bit end-to-end topology attribution code is divided into four levels, with two bits per level. When generating the high-voltage path code for the next-level child node, a specific 2-bit prefix code is extracted from the high-voltage path code of its parent node and incorporated as part of its own high-voltage path code. This cyclical construction method ensures that the high-voltage path code can extend downwards level by level, clearly reflecting the device's hierarchical position in the topology. For example, if the parent high-voltage path code is G1+G2+G3+G4, then the high-voltage path code of the next-level child node inherits G1 as its prefix, forming a high-voltage path code of G1+G1+G1+G1. The ultimate goal of the aforementioned prefix matching parent-child binding rules is to enable the energy management platform to efficiently and accurately identify the hierarchical relationships between devices in the entire power distribution system. By parsing the high-voltage path code in the device encoding, the platform can automatically construct a complete power distribution topology tree without manual intervention, based on preset rules. This greatly simplifies system configuration and maintenance, and provides an accurate structural foundation for subsequent energy data analysis.

[0037] Transformer end-to-end inheritance rule: All devices on the low-voltage side of the same relay equipment must inherit 100% of the 8-bit high-voltage path code + 2-bit relay equipment anchor code corresponding to that relay equipment, achieving seamless end-to-end attribution across high voltage, relay equipment, and low voltage. 00 Termination Rule: In the full-link topology attribution code, a node at a certain level is 00, which means that the node is the termination node of the current link and has no subordinate attribution.

[0038] In addition, this invention also discloses an energy management system, comprising: an equipment acquisition module for acquiring 36-bit globally unique codes and equipment operation and energy consumption data reported by field equipment; an encoding parsing module for segmenting and parsing the reported globally unique codes to extract site information, topology attribution information, and equipment type information, and completing the verification of check bit validity; an automatic site building module for automatically creating site files based on the site unique codes obtained from encoding parsing, and automatically matching equipment models and creating equipment files based on equipment type information; a topology generation module for automatically identifying the hierarchical attribution relationship of equipment and generating a full-link power distribution topology map based on the full-link topology attribution code obtained from encoding parsing and using prefix matching rules; and an energy data analysis module for comparing key energy consumption indicators, automatically calculating equipment losses, analyzing the rationality of losses, and evaluating equipment energy efficiency based on the segmented information of the globally unique codes.

[0039] By systematically integrating the encoding parsing module with the automatic site building module, topology generation module, and energy data analysis module, this invention automatically extracts site information, topology attribution, and equipment type information based on a 36-bit globally unique code. This enables automatic creation of site profiles, automatic generation of distribution topologies, and intelligent analysis of key energy consumption indicators. Specifically, the automatic site building module automatically creates site profiles and matches equipment models based on the unique site code, significantly shortening the new site deployment cycle. The topology generation module automatically identifies the hierarchical attribution of equipment using prefix matching rules, generating a full-link distribution topology map, resolving the problem of fragmented attribution relationships, and enabling automatic calculation of transformer and line losses. The energy data analysis module filters similar equipment based on the equipment category code and sub-category code for energy consumption benchmarking, and calculates energy efficiency indicators based on the full-link attribution relationship, generating optimization suggestions. Through the above technical solutions, this application effectively overcomes the shortcomings of existing technologies, providing efficient and accurate energy management capabilities for the large-scale operation and maintenance of charging stations.

[0040] The specific workflow of the automatic website building module is as follows: Based on the unique code of the site obtained by code parsing, it determines whether a corresponding site exists. If it does not exist, it automatically creates a site file and assigns regional management permissions based on the province and city codes in the site's unique code. At the same time, it automatically matches the device's acquisition protocol, data point table, and alarm thresholds based on the device's major category code and sub-category code to create a device file.

[0041] Specifically, this workflow first determines whether a corresponding site exists based on the site's unique code obtained through encoding parsing. This step aims to ensure that upon receiving a new device code, the system first parses the 36-bit globally unique code using the encoding parsing module, extracting the 6-bit site-unique code. Subsequently, the automatic site creation module uses this site-unique code to query the system's existing database to determine if the site has already been registered or a file has been created. This determination process can be implemented through database index queries, ensuring a fast response. Its purpose is to avoid duplicate creation of existing site files, ensuring data consistency and system efficiency.

[0042] If the system determines that the site file corresponding to the site's unique code does not yet exist, it will automatically create the site file and assign regional management permissions based on the province and city codes in the site's unique code. When the system determines that the site file corresponding to the site's unique code does not yet exist, the automatic site creation module will trigger the automatic creation process. According to the above method, the 6-digit site unique code contains 2 digits of province code and 2 digits of city code. The system will extract these province and city codes and automatically generate the basic file information of the site, such as the site name and the administrative region to which it belongs, based on the preset administrative division information or mapping table. At the same time, the system will automatically assign the corresponding regional management permissions to the newly created site based on the site's geographical affiliation (province, city), such as assigning the site to a specific regional administrator or management team, thereby realizing automated permission configuration and simplifying the system deployment and management process.

[0043] The system automatically matches the device's acquisition protocol, data point table, and alarm thresholds based on the device's major category code and sub-category code to create a device profile. Simultaneously or subsequently, the automatic site creation module further utilizes the 3-digit major category code and 3-digit sub-category code obtained through code parsing. According to this method, the major category code distinguishes device types, while the sub-category code further subdivides device models and functions. The system has a pre-stored device model library, which contains acquisition protocols, data point tables (defining the data items that can be collected and their formats), and alarm thresholds (defining the normal range and abnormal alarm conditions for device operating parameters) corresponding to different device types and models. The automatic site creation module performs precise matching within this device model library based on the parsed major and sub-category codes, automatically acquiring and loading the corresponding acquisition protocol, data point table, and alarm thresholds, thereby creating a detailed device profile for the device. This process automates device configuration, significantly improving the efficiency and accuracy of device access.

[0044] When the energy management system receives a new device code, it can intelligently determine whether the site exists based on the unique site code obtained through code parsing. If the site does not exist, the system can automatically create a site profile and assign regional management permissions based on the province and city codes in the site's unique code. This avoids the tedious process of manually creating sites and potential permission configuration errors, ensuring the accuracy of site information and the rationality of management permissions. Simultaneously, the system can automatically match the device's data acquisition protocol, data point table, and alarm thresholds based on the device's major category code and subcategory code, and create a device profile. This highly automates the process of adding new devices, completing device model matching and configuration without manual intervention. This significantly improves the efficiency and accuracy of device deployment, reduces operation and maintenance costs, and lays a solid foundation for subsequent device data collection, monitoring, and analysis. This automated and intelligent site creation and device profile creation mechanism effectively solves the efficiency bottlenecks and data consistency issues in large-scale device access and management.

[0045] In the energy data analysis module, the specific process of automatic equipment loss calculation is as follows: based on the anchor code of the equipment, the signal input metering data and signal output metering data corresponding to the same type of equipment are automatically matched, and the total equipment loss, load loss and loss rate are automatically calculated.

[0046] The device's anchor code (HH) is part of the 16-bit end-to-end topology attribution code in the globally unique coding system, specifically a 2-bit unique anchor code for relay devices. It identifies a fixed, immutable reference point for the device within the end-to-end topology, especially useful for relay devices. During device coding, a relay device is assigned a unique anchor code, which is unique and unchanging throughout the entire end-to-end system. Non-relay devices may inherit the anchor code from their parent relay device or generate one based on their position in the topology. In device loss accounting scenarios, the anchor code, as a unique identifier for the device within the end-to-end topology, is a crucial basis for associating its input and output data.

[0047] Automatic matching of signal input and output metering data for the same type of equipment refers to the energy management system's ability to intelligently identify and associate input and output power, energy, or other signal data belonging to the same physical equipment but collected from different locations or through different sensors, based on the equipment's anchor code, equipment category code (TTT), and equipment sub-category code (CCC). Specifically, after the equipment acquisition module collects the globally unique code and equipment operation and energy consumption data reported by the field equipment, the code parsing module extracts the equipment's anchor code, equipment category code, and equipment sub-category code. The energy data analysis module then uses this information to accurately find all signal input and output metering data associated with the equipment's anchor code and equipment type by querying a pre-defined database of equipment-metering point mapping relationships or based on predefined rules. For example, for a transformer, its input and output terminals may be connected to electricity meters. The data from these electricity meters is identified and matched through their associated equipment anchor codes and equipment types, ensuring the accuracy of the data source, avoiding data confusion between different devices, and thus improving the automation of loss calculation.

[0048] Automatic calculation of total equipment losses, load losses, and loss rates refers to the energy management system's ability to automatically derive various loss indicators of equipment based on preset calculation models and formulas after successfully matching the signal input and output metering data. Total equipment losses are typically obtained as the difference between input and output metering data; for example, for electrical equipment, total losses equal input power minus output power. Load losses refer to the losses generated when equipment operates under load, and their calculation may require combining real-time data such as operating current and voltage with the equipment's inherent parameters. The loss rate is usually expressed as the percentage of total losses relative to input or output. These calculations are all automated by the energy data analysis module without manual intervention, thereby quantifying the equipment's operating efficiency and providing direct and accurate data support for subsequent energy efficiency assessments and optimizations.

[0049] The energy management system utilizes anchor codes within the globally unique identifiers of each device as key markers. Combined with device type information, this allows for precise identification and automatic matching of signal input and output metering data for the same type of device at different measurement points. This anchor code- and device type-based matching mechanism effectively solves the technical challenges of difficult data correlation and automated loss calculation in complex end-to-end systems, significantly improving the automation and accuracy of equipment loss calculation. Based on this, the system can automatically and efficiently calculate various loss indicators for the equipment, such as total loss, load loss, and loss rate. This provides accurate data support for equipment operation status assessment, energy efficiency optimization, and fault early warning, thereby enhancing the intelligence level and decision support capabilities of the energy management system.

[0050] In the energy data analysis module, the specific process for comparing key energy consumption indicators is as follows: based on the equipment category code and equipment sub-category code, filter equipment of the same type and specifications, automatically compare the core indicators of unit energy consumption, load rate, and utilization rate, and generate a cross-site benchmarking analysis report.

[0051] After selecting comparable equipment, the energy data analysis module automatically compares key indicators such as unit energy consumption, load rate, and utilization rate. Unit energy consumption refers to the energy consumed by the equipment to complete a unit of work or produce a unit of energy, directly reflecting the equipment's energy efficiency level. Load rate is the ratio of the equipment's actual operating load to its rated load. Utilization rate is the ratio of the equipment's actual operating time to its total available time within a certain period, or the ratio of actual output to maximum possible output. The energy data analysis module automatically extracts and calculates these key indicators from the operating and energy consumption data acquired by the equipment acquisition module using preset calculation models and algorithms. For example, by monitoring the equipment's input power, output power, and operating time in real time, and combining this with the equipment's rated parameters, the module automatically calculates the aforementioned indicators.

[0052] Finally, the energy data analysis module will generate a cross-site benchmarking analysis report. This report presents the comparison results, visually displaying and summarizing similar indicators from different sites and equipment, such as through charts and tables. The report typically includes the indicator values ​​for each device, their ranking, deviations from the average, historical trends, and may provide preliminary analytical conclusions or anomaly warnings.

[0053] The energy data analysis module describes the specific process of equipment energy efficiency assessment. This process first automatically calculates the core energy efficiency indicators of the equipment based on its end-to-end ownership structure, combined with equipment operating data and energy consumption data. Then, by combining benchmarking data from similar equipment, the energy efficiency of the equipment is rated, and finally, energy efficiency optimization suggestions are generated.

[0054] Specifically, when conducting equipment energy efficiency assessments, the system first utilizes the equipment's end-to-end attribution relationship. This attribution relationship is obtained by parsing the 16-bit end-to-end topology attribution code (PPPPPPPPPPPPPPPPPP) from the equipment's globally unique code. This attribution code includes an 8-bit high-voltage path code (GGGGGGGG), a 2-bit unique anchor code (HH) for intermediate equipment, and a 6-bit low-voltage path code (DDDDDD). With this information, the system can accurately identify the equipment's hierarchy, location, and upstream and downstream relationships within the entire energy network. For example, it can determine which substation or distribution cabinet the equipment belongs to, and its specific role in the energy transmission and distribution chain. This precise understanding of the equipment's topological location forms the basis for subsequent energy efficiency assessments, ensuring the contextual accuracy of the assessment.

[0055] Based on this, the system combines equipment operation data and energy consumption data. Equipment operation data can include parameters such as real-time or historical voltage, current, power factor, operating time, load rate, and temperature obtained from the equipment's acquisition module, while energy consumption data refers to the electricity, heat, or other forms of energy consumed by the equipment within a specific time period. For example, for an industrial motor, its operation data may include speed and torque, while its energy consumption data is the amount of electricity consumed. The comprehensive analysis of this data can fully reflect the equipment's performance under actual operating conditions.

[0056] The system will then automatically calculate the core energy efficiency indicators of the equipment. These indicators are extracted and calculated from the aforementioned operating and energy consumption data based on preset algorithms and models, and are key parameters that directly reflect the energy utilization efficiency of the equipment. For example, for transformers, core energy efficiency indicators may include no-load loss, load loss, and efficiency; for refrigeration equipment, they may be the Energy Efficiency Ratio (EER) or Seasonal Energy Efficiency Ratio (SEER). The calculation process will fully consider the type of equipment, rated parameters, and actual operating conditions to ensure the accuracy and representativeness of the indicators.

[0057] It can be modularized. The energy data analysis model block includes the following sub-modules, all of which are based on coding to achieve automated analysis: Key Energy Consumption Indicator Comparison Submodule: Used to filter equipment of the same type and specifications nationwide based on equipment category code and sub-category code, automatically compare core indicators such as unit energy consumption, load rate, and utilization rate, and generate cross-site benchmarking analysis reports; Transformer Loss Analysis Submodule: Based on the transformer anchor point code, it automatically matches the high-voltage side input metering data, low-voltage side output metering data, and transformer body operation data corresponding to the same transformer, and automatically calculates the total transformer loss, load loss, and loss rate, realizing automated loss accounting. The Loss Rationality Analysis Submodule is used to determine whether the transformer loss is within a reasonable range by combining the transformer's nominal parameters, operating ambient temperature, and load rate; at the same time, it automatically calculates the line loss of each feeder and each distribution box according to the affiliation of the low-voltage link, analyzes the rationality of the line loss, and locates problems such as leakage and metering abnormalities. Equipment Energy Efficiency Assessment Sub-model Module: Based on the equipment's full-link affiliation, combined with equipment operation data and energy consumption data, it automatically calculates core energy efficiency indicators such as charging pile charging efficiency, photovoltaic inverter conversion efficiency, and energy storage system charging and discharging efficiency. Combined with benchmarking data of similar equipment, it performs energy efficiency rating on the equipment and generates energy efficiency optimization suggestions. Alarm and Optimization Module: Based on energy consumption analysis results, this module automatically issues alarms for equipment with excessive energy loss or abnormal energy efficiency, and pushes corresponding maintenance and optimization suggestions.

[0058] The following example uses the various devices involved in a new energy vehicle charging station as a whole-chain system for illustration.

[0059] Example 1 This embodiment takes the No. 5 charging station in Shenzhen, Guangdong as an example. The station code is 440305 (44 = Guangdong Province, 03 = Shenzhen City, 05 = No. 5 station in Shenzhen City). The anchor point code of the No. 1 transformer in the station is 01. The power distribution link is as follows: main station high voltage main incoming line → No. 1 high voltage outgoing line cabinet → substation No. 1 high voltage incoming line cabinet → substation No. 1 high voltage outgoing line cabinet → No. 1 transformer → low voltage main incoming line cabinet → No. 1 low voltage feeder cabinet → No. 3 feeder circuit → No. 2 secondary distribution box → No. 5 tertiary distribution box → No. 1 DC charging pile.

[0060] The complete 36-bit encoding and parsing for each device are as follows: 1. Main high-voltage incoming line cabinet: CN440305010000000100000004001000016 Analysis: Country code CN, site code 440305, topology code 01000000 01 000000 (high voltage primary node, bound to transformer No. 1), equipment category 004 = power distribution equipment, subcategory 001 = high voltage main incoming line cabinet, serial number 00001, check digit 6.

[0061] 2. Input meter on the high-voltage side of transformer No. 1: CN4403050101010101000000005001000017 Analysis: The topology code 01010101 01 000000 fully inherits the high-voltage link and is bound to the anchor code 01 of transformer No. 1. The equipment category 005 = metering instruments and the subcategory 001 = high-voltage side metering meter are the input data sources for transformer loss calculation.

[0062] 3. Transformer body No. 1: CN4403050101010101000000004005000013 Analysis: The topology code is completely consistent with the high-voltage side meter and is bound to the anchor code 01 of transformer No. 1, realizing a strong correlation between the main data and energy consumption data.

[0063] 4. Low-voltage side output summary meter for transformer No. 1: CN4403050101010101010000005002000014 Analysis: The topology code 01010101 01 010000 inherits 100% of the high-voltage link code and transformer anchor code 01. The equipment subclass 002 = low-voltage side master table, which is the output data source for transformer loss calculation.

[0064] 5. DC charging station No. 1: CN4403050101010101010103001001000017 Analysis: The topology code fully inherits the upstream high-voltage link and transformer anchor code. The equipment category 001 = charging pile, the subcategory 001 = DC charging pile, and it is automatically assigned to feeder circuit 3 of transformer 1.

[0065] Example 2: Coding-Based Automated Website Building Process This embodiment is based on the coding of Embodiment 1, and realizes automatic site creation upon device power-on. The specific process is as follows: 1. When the equipment is powered on, it reports a 36-bit unique code and basic equipment data to the platform through the data acquisition terminal.

[0066] 2. The platform's encoding parsing module verifies and segments the encoding, extracts site code 440305, and determines that there is no such site file in the system.

[0067] 3. The automatic website building module automatically creates website files based on 44 (Guangdong Province) and 03 (Shenzhen City) in the site code, matches the corresponding geographical information, and assigns management permissions for the Guangdong Province region.

[0068] 4. The encoding and parsing module extracts the device category code and sub-category code, automatically matches the corresponding device's acquisition protocol, data point table, and alarm threshold, and creates device files in batches.

[0069] 5. The topology generation module automatically identifies the hierarchical relationship of each device based on the 16-bit full-link topology attribution code and uses prefix matching rules to generate a full-link power distribution topology diagram, completing the automatic construction of the entire station without the need for manual data entry.

[0070] Example 3: Encoding-Based Energy Data Analysis Process 1. Automatic calculation and rationality analysis of transformer losses: The platform automatically filters all devices at the same site, on the same high-voltage link, and with the same anchor code using transformer anchor code 01. It extracts the input power of the high-voltage side meter, the output power of the low-voltage side main meter, and the load rate and temperature data of the transformer body, and automatically calculates: Total transformer losses = High-voltage side input power - Low-voltage side output power. Transformer loss rate = Total loss / High-voltage side input power × 100% Based on the transformer's nominal no-load loss and load loss parameters, determine whether the current loss rate is within a reasonable range. If it exceeds the threshold, an alarm will be automatically issued and maintenance suggestions will be pushed.

[0071] 2. Energy consumption benchmarking analysis of similar equipment: The platform uses the equipment category code 001 and sub-category code 001 to filter all DC charging pile equipment nationwide, automatically compares key indicators such as average daily charging volume per pile, energy consumption per unit charging volume, and charging efficiency, generates cross-site benchmarking reports, and identifies low-energy-efficiency equipment.

[0072] 3. Equipment energy efficiency assessment: The platform automatically matches the upstream and downstream link data of the device through the topology attribution code, and calculates the conversion efficiency of the photovoltaic inverter, the charging and discharging efficiency of the energy storage system, and the charging efficiency of the charging pile by combining the device's operating data. Based on the industry benchmark values ​​of similar devices, the platform performs an AE level 5 energy efficiency rating for the device and generates energy efficiency optimization suggestions.

[0073] It should be noted that the above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. However, any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A coding method for a full-link device, characterized in that, Includes the following steps: The method is based on an end-to-end system containing several devices, each of which is a first-level node; A globally unique code is constructed for each device, with a length of 36 characters, consisting of uppercase letters and numbers. The encoding structure is SSBBBBBBPPPPPPPPPPPPPPPPTTTCCCNNNNNS, where SS is a 2-bit distinguishing code, BBBBBB is a 6-bit site unique code, PPPPPPPPPPPPPPPP is a 16-bit full-link topology attribution code, TTT is a 3-bit device category code, CCC is a 3-bit device subclass code, NNNNN is a 5-bit device serial number, and S is a 1-bit check code. The 16-bit full-link topology attribution code is structured as GGGGGGGGHHDDDDDD, where GGGGGGGG is an 8-bit high-voltage path code, divided into 4 levels, with 2 bits per level; BB is a 2-bit unique anchor code for relay equipment, and each relay equipment has an immutable unique anchor code; DDDDDD is a 6-bit low-voltage path code, divided into 3 levels, with 2 bits per level. In the end-to-end system, the high-voltage path code of the next-level node is formed by binding the prefix code of the high-voltage path code of the previous-level node; the relay equipment anchor code of the next-level node is bound to the relay equipment anchor code of the previous-level node; the low-voltage path code of the next-level node includes the prefix code of the high-voltage path code of the previous-level node and the relay equipment anchor code.

2. The encoding method for end-to-end devices according to claim 1, characterized in that, In the full-link system, the next-level node and the previous-level node generate high-voltage path codes using a prefix matching parent-child binding rule. Specifically, the previous-level node is defined as the parent node, and the next-level node is defined as the child node. The 8-bit high-voltage path code of the child node is formed by cyclically constructing the 2-bit prefix code of the 8-bit high-voltage path code of the parent node. If the parent node contains a non-zero code, the child node completely inherits and contains that non-zero code. This is used by the platform to automatically identify the hierarchical relationship and generate a topology tree.

3. The coding method for the end-to-end device according to claim 1, characterized in that, The structure of the 6-digit unique station code consists of a 2-digit province code, a 2-digit city code, and a 2-digit station serial number. The province code and city code adopt the national unified administrative division code, and the station serial number is an auto-incrementing number of the station within the corresponding city, with a value range of 01-99.

4. The coding method for a full-link device according to claim 1, characterized in that, The equipment category code is used to distinguish equipment types. The equipment sub-category code corresponds one-to-one with the equipment category code and is used to further subdivide equipment models and functions, enabling automatic matching of equipment acquisition protocols and data point tables.

5. The coding method for a full-link device according to claim 1, characterized in that, The check bit is generated using a modulo-10 check algorithm to prevent encoding errors and dirty data from being entered into the database during the data acquisition process.

6. An energy management system applying the method according to any one of claims 1-5, characterized in that, include: The equipment acquisition module is used to collect 36-bit globally unique codes and equipment operation and energy consumption data reported by field equipment; The encoding parsing module is used to segment and parse the reported globally unique encoding, extract site information, topology attribution information, device type information, and complete the verification of the validity of the check bit. The automatic website building module is used to automatically create website files based on the unique website code obtained from code parsing, and at the same time, automatically match the device model and create the device file based on the device type information; The topology generation module is used to automatically identify the hierarchical relationship of devices based on the full-link topology attribution code obtained by encoding and parsing, and generate a full-link power distribution topology map through prefix matching rules. The energy data analysis module is used to compare key energy consumption indicators, automatically calculate equipment losses, analyze the rationality of losses, and evaluate equipment energy efficiency based on segmented information with globally unique codes.

7. The energy management system according to claim 6, characterized in that, The specific workflow of the automatic website building module is as follows: Based on the unique code of the site obtained by code parsing, determine whether there is a corresponding site. If not, automatically create a site file and assign regional management permissions according to the province and city codes in the unique code of the site. Simultaneously, based on the device category code and device sub-category code, the device's acquisition protocol, data point table, and alarm threshold are automatically matched to create a device profile.

8. The energy management system according to claim 6, characterized in that, In the energy data analysis module, the specific process of automatic equipment loss calculation is as follows: based on the anchor code of the equipment, the signal input metering data and signal output metering data corresponding to the same type of equipment are automatically matched, and the total equipment loss, load loss and loss rate are automatically calculated.

9. The energy management system according to claim 6, characterized in that, In the energy data analysis module, the specific process for comparing key energy consumption indicators is as follows: based on the equipment category code and equipment sub-category code, filter equipment of the same type and specifications, automatically compare the core indicators of unit energy consumption, load rate, and utilization rate, and generate a cross-site benchmarking analysis report.

10. The energy management system according to claim 6, characterized in that, In the energy data analysis module, the specific process of equipment energy efficiency assessment is as follows: based on the equipment's full-link affiliation, combined with equipment operation data and energy consumption data, the core energy efficiency indicators of the equipment are automatically calculated. Combined with benchmarking data of similar equipment, the equipment is rated for energy efficiency and energy efficiency optimization suggestions are generated.