A business energy consumption planning method and system based on standardized electrical design drawings

Abstract

This invention belongs to the field of intelligent electrical engineering and building energy management technology, specifically involving a business energy consumption planning method and system based on standardized electrical design drawings. It enables automated construction of energy consumption physical topology, flexible generation of business energy consumption topology, and intelligent recommendation of renovation plans, while also incorporating compliance detection and topology self-calibration mechanisms. This invention achieves fully automated construction of energy consumption physical topology: through standardized drawing specifications and automated parsing algorithms, it completely replaces the manual work of sorting the topology and manually entering hierarchical relationships, shortening the topology construction cycle from several days to minutes, while completely avoiding human error and ensuring the integrity and accuracy of the topology structure.

Description

Technical Field

[0001] This invention belongs to the field of intelligent electrical engineering and building energy management technology, specifically relating to a business energy consumption planning method and system based on standardized electrical design drawings. Background Technology

[0002] Currently, under the policy background of dual-carbon targets, refined energy consumption management of large public buildings such as office buildings and commercial complexes has become an industry necessity. In the current process of building and maintaining energy consumption management systems for existing buildings, existing technologies have the following core shortcomings: Physical topology analysis is inefficient and inaccurate, requiring manual review of drawings to re-analyze the physical topology of on-site meters and manually input the total hierarchical relationship of the meters. This is labor-intensive, time-consuming, and prone to human error or omissions, making it difficult to guarantee the integrity and accuracy of the topology and creating potential data risks for subsequent energy management.

[0003] The business energy consumption topology construction lacks flexibility, requiring manual extraction of electricity meters for each business category and manual construction of the business energy consumption topology. When business needs change (such as adding tenants or adjusting energy consumption allocation rules), manual operations must be repeated, making it impossible to respond quickly to business changes and resulting in extremely low efficiency.

[0004] The decision-making support capability for changes in business needs is weak. When new energy consumption statistics requirements arise, whether to install electricity meters, the number of meters to install, and the line modification plan all rely entirely on the personal experience of professionals. The rationality of the plan is difficult to standardize the review and verification, resulting in low decision-making efficiency and problems such as rework and metering failure caused by unreasonable plans.

[0005] The long-term reliability of topology models is insufficient. Existing technologies can only build topology models based on static drawings and lack verification and calibration mechanisms for on-site electrical modifications. This can easily lead to inconsistencies between digital models and actual on-site wiring, resulting in continuous deviations in subsequent energy consumption analysis and metering, thus weakening the practical value of energy management systems. Summary of the Invention

[0006] In view of this, the present invention provides a business energy consumption planning method and system based on standardized electrical design drawings, which can realize the automated construction of energy consumption physical topology, the flexible generation of business energy consumption topology, and the intelligent recommendation of transformation schemes. At the same time, through compliance detection and topology self-calibration mechanism, it solves the core problems of existing technology such as time-consuming and error-prone manual operation, reliance on expert experience, and disconnect between model and field.

[0007] To achieve the objectives of this invention, the following technical solutions are provided.

[0008] A business energy consumption planning method based on standardized electrical design drawings includes the following steps: S1 acquires standardized electrical design CAD drawings drawn according to preset annotation specifications; S2 parses the CAD drawings and extracts the electrical component objects corresponding to the energy consumption circuit, electricity meter, end load, and distribution box, as well as the attribute information and interconnection relationship of each component; Based on the extracted electrical component objects and their connections, S3 constructs a complete energy consumption physical topology data structure with the main distribution box as the root node through spatial relationship analysis and hierarchical relationship inference algorithms. S4 receives the service category definition input by the user, as well as the matching rules based on the terminal load attribute corresponding to each service category; S5 iterates through all end loads in the energy consumption physical topology data structure and automatically categorizes the loads into the corresponding business categories according to the matching rules; S6 performs reverse aggregation on the end loads of the same service category, locates the upstream electricity meter that supplies it, and automatically generates the service energy consumption topology for the corresponding service category. S7 uses the business energy consumption topology and energy consumption physical topology data structure to conduct business metering missing analysis and identify metering defects corresponding to the current business category. Based on the identified metering defects, S8 automatically generates an energy consumption renovation plan that includes the location of the electricity meter installation, the content of the line modification, the bill of materials, and the construction steps.

[0009] In step S1, the standardized electrical design CAD drawings include graphic elements of energy consumption circuits, meters, end loads, and distribution boxes, as well as corresponding extended attributes and clear line connection relationships. The preset annotation specifications specifically include: all energy consumption circuits must be drawn as continuous multi-segment lines in a specified layer; meters, end loads, and distribution boxes are all represented by preset blocks and carry extended attributes, respectively recording key information such as component core parameters, type, region, incoming line source, and rated capacity, and the line connection relationships in the drawings are clear and accurate.

[0010] In step S2, the parsing of drawings includes two types: intelligent CAD drawings and dumb CAD drawings. For intelligent CAD drawings, layer elements and block attributes are directly identified to create corresponding electrical component objects. For dumb CAD drawings, component information and connection relationships are extracted through image processing, pattern recognition, text recognition, and connection tracing technologies, while providing a human-interactive correction interface.

[0011] The hierarchical relationship inference algorithm in step S3 adopts the disjoint-set data structure algorithm, which is as follows: starting from the end load and electricity meter without a clear superior, trace back along the energy consumption loop to the corresponding distribution box, and then continue to trace the source of the incoming line of the distribution box, and finally construct a complete tree or mesh energy consumption physical topology data structure from the main distribution box to the end load.

[0012] The service metering deficiency analysis described in step S7 includes the identification of at least two types of metering defects: the first type is that the loads of the target service category have been matched, but are scattered under multiple non-dedicated meters and cannot be metered independently; the second type is that some loads of the target service category are not covered by the existing metering range. In step S8, for the first type of defect, the nearest common upstream meter of the scattered loads is located, and a solution for adding a new meter and reconnecting the line is recommended; for the second type of defect, the uncovered area is located, and a solution for adding a circuit and meter to the corresponding distribution box is recommended.

[0013] The method further includes a design compliance intelligent detection step: based on a preset electrical design specification rule library, a full scan is performed on the completed energy consumption physical topology data structure to identify nodes, lines and loads that violate the specifications, and a compliance detection report is generated that includes the problem level, problem location and rectification suggestions. It supports highlighting the problem location on CAD drawings or topology diagrams.

[0014] The rule base includes at least seven core detection rules: distribution box capacity verification, three-level power distribution and end protection detection, redundant meter detection, load hybridity detection, important load independence detection, primary load power supply path detection, and three-phase load balance detection.

[0015] The method further includes a real-time physical topology self-calibration and deviation detection step: accessing the real-time energy consumption data stream of the smart meter on site, triggering the deviation detection process when a modification event or unexpected energy consumption change is detected, inferring the actual electrical connection relationship through load characteristic matching, power change comparison, and time series synchronization analysis, generating a deviation report and correction suggestions after comparing and identifying topology deviations, and automatically updating the energy consumption physical topology data structure after manual review and confirmation.

[0016] A business energy consumption planning system based on standardized electrical design drawings includes: a drawing input and parsing module for acquiring standardized CAD drawings and extracting electrical component information and connection relationships; a physical topology construction module for constructing an energy consumption physical topology data structure with the main distribution box as the root node; a business classification configuration module for receiving user-defined business classifications and load matching rules; a business topology generation module for completing load classification and automatically generating business energy consumption topologies; and a business analysis and solution recommendation module for identifying metering defects and automatically generating energy consumption renovation solutions.

[0017] The system further includes a design compliance intelligent detection module and a real-time topology self-calibration module. The design compliance intelligent detection module has a built-in electrical design specification rule library for automated compliance scanning and generating detection reports. The real-time topology self-calibration module communicates with the smart meters on site to collect real-time energy consumption data, identify topology deviations, and complete model self-calibration.

[0018] Beneficial effects 1. This invention realizes the fully automated construction of energy consumption physical topology. Through standardized drawing specifications and automated parsing algorithms, it completely replaces the work of manually sorting out the topology and manually entering the hierarchical relationship, shortening the topology construction cycle from several days to minutes, while completely avoiding human error and ensuring the integrity and accuracy of the topology structure.

[0019] 2. This invention enables flexible configuration of business energy consumption topology. Users only need to define business categories through simple rules, and the system can automatically complete load classification and business topology generation without manual matching of electricity meters one by one. It can respond to changes in business needs in real time and greatly improve the flexibility of energy consumption management.

[0020] 3. This invention realizes intelligent decision support for energy consumption transformation. It automatically identifies the core pain points of business metering through metering loss analysis, and automatically generates the optimal transformation plan based on topology data. It does not rely on the experience of professional personnel. The plan is traceable and auditable, which greatly improves decision-making efficiency and the rationality of the plan, and reduces transformation costs and rework risks.

[0021] 4. This invention realizes fully automated compliance review of electrical design: by standardizing and making industry norms executable through a rule engine, it replaces manual drawing review, can quickly identify safety hazards, energy efficiency defects and non-compliance items in the design, and avoid electrical system operation risks in advance.

[0022] 5. This invention achieves closed-loop self-calibration of the topology model: Through deviation detection and model calibration driven by real-time energy consumption data, a complete closed loop of "planning-implementation-verification-correction" is constructed, which solves the industry pain point of the disconnect between the digital model after the transformation and the actual situation, ensures the long-term accuracy of the topology model, and provides a continuous and reliable data foundation for refined energy consumption management. Attached Figure Description

[0023] Figure 1 This is a schematic diagram of the original CAD drawing obtained in the method of an embodiment of the present invention.

[0024] Figure 2 This is a schematic diagram of the energy consumption topology tree structure extracted in an embodiment of the present invention. Detailed Implementation

[0025] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0026] This invention provides a business energy consumption planning method based on standardized electrical design drawings. By processing standardized input data and employing a series of algorithms and rule engines, it outputs multi-dimensional topology views, inspection reports, and planning suggestions, achieving forward-looking support from "design compliance review" to "operational energy efficiency management." The method includes the following steps: Drawing Input and Parsing: Obtain standardized electrical design CAD drawings that follow preset annotation specifications (such as...) Figure 1 As shown), the paper analyzes and extracts the electrical component objects corresponding to the energy consumption circuit, electricity meter, terminal load, and distribution box in the drawing, as well as the attribute information and interconnection relationship of each component; The goal of this step is to convert graphical CAD data into computer-recognizable and computable topology network data. Standardized electrical design CAD drawings are a fundamental requirement for the input data in this invention. Designers must adhere to a set of annotation standards, such as: all energy consumption circuits (main lines, branch lines) must be drawn as continuous multi-segment lines on a specific layer; each meter is represented by a specific block and includes extended attributes, recording its name, model, rated parameters, and the distribution box it belongs to; each terminal load is represented by a specific block and includes extended attributes, recording its name, type (e.g., "Lighting-Office Area", "Socket-Workstation"), rated power, and the area it belongs to. Simultaneously, a type library must be predefined for types, and the types used must be selected from the type library; the locations of all areas in the project must be predefined for the area, and the area selected for the terminal load must be an area from the area library. Each distribution box is represented by a specific block and includes extended attributes, recording its box number (e.g., "AL-1-1"), model, installation location, rated capacity (total current or power), incoming line source, number and number of outgoing circuits, and main service area or functional description. The distribution box is considered both the physical carrier and the logical aggregation node for electricity meters and wiring. The wiring connections must be clear and accurate on the drawings.

[0027] Automatic physical topology construction: Based on extracted electrical component objects and their connection relationships, a complete energy consumption physical topology data structure is constructed with the main distribution box as the root node (e.g., ...). This is achieved through spatial relationship analysis and hierarchical relationship inference algorithms. Figure 2 (as shown) Automatic business topology generation: Receives user-defined business categories and corresponding load matching rules, traverses the end loads in the physical topology to complete automatic classification, and locates the power supply meters corresponding to the business categories through reverse aggregation to generate business energy consumption topology; Business Analysis and Solution Recommendation: Based on the business energy consumption topology and physical topology, metering deficiency analysis is performed to identify business metering defects and automatically generate executable modification solutions including meter installation, line modification, and bill of materials.

[0028] Furthermore, this method also includes an intelligent design compliance detection step: encoding electrical design industry standards into an executable rule base, performing a full scan of the completed physical topology, automatically identifying design defects, safety hazards and energy efficiency issues, and generating standardized detection reports and rectification suggestions.

[0029] Furthermore, this method also includes a real-time physical topology self-calibration and deviation detection step: accessing the real-time energy consumption data of the smart meters on site, inferring the actual electrical connection relationship through load characteristic matching and time series correlation analysis, identifying the topology deviation between the digital model and the site, and automatically completing the model calibration after manual confirmation to ensure the consistency between the topology model and the actual site.

[0030] The specific steps for implementing this invention are as follows: Step 1, drawing information extraction. During the drawing parsing process, there are two types of drawing parsing: intelligent CAD drawings and "dumb" graphics (CAD drawings without intelligent attributes).

[0031] Among these, intelligent CAD drawing parsing refers to drawings created using professional electrical design software (such as AutoCAD Electrical, EPLAN, SEEE Electrical) according to annotation standards, where components (meters, distribution boxes, loads, etc.) have intelligent "block" attributes or database links. This includes: Identify lines: Identify continuous polylines in a specific layer, abstract them into Circuit objects, and record their path coordinates.

[0032] Identify the electricity meter: Traverse the specific blocks in the drawing, extract their location coordinates, ID, rated current, etc., and create a Meter object.

[0033] Identify load: Traverse the tiles representing the load, extract their location, ID, name, type, power, business area and other attributes, and create a Load object.

[0034] Identify the distribution box: Traverse the tiles representing the distribution box, extract its number, location, capacity, incoming line source, outgoing line list, and other attributes, and create a Panel object. This object will become the key node connecting the upstream power supply and the downstream meter / load.

[0035] Analysis of "dumb" graphic drawings, including: It employs image processing-based connected component analysis and pattern recognition technology, combined with a pre-set symbol template library, to identify symbols for electricity meters, loads, and distribution boxes.

[0036] Layer and Block Recognition: A script is written to traverse the drawings and identify the layer and block name of the meter block. For elements that cannot be automatically recognized, the system provides a graphical interface that allows users to manually select, specify the type, and input attributes.

[0037] Attribute extraction: Read the text next to the tile (using text recognition or reading attribute text) to obtain the meter number, model, etc.

[0038] Wiring tracing: Tracing the wires (multiple wires) originating from the meter to find the symbol of the upstream distribution box to which it connects. This requires complex graphics algorithms and is a technical challenge.

[0039] Relationship establishment: Associations are established through "loop number" text (such as WL1), or the attribution relationship is inferred through spatial location and connection logic.

[0040] Load identification: The system identifies text by recognizing the ends of line segments. For content that cannot be clearly identified, the system will provide a prompt after reading the text, allowing for manual input.

[0041] Step 2, connection inference and topology generation, includes: Spatial Relationship Analysis: Establish the hierarchy and connections between Panel, Meter, Load, and Circuit objects. The core logic is: Circuit connects two nodes (e.g., Panel to Meter, Meter to Load, or Panel to Panel).

[0042] Hierarchical relationship inference (optimization algorithm): Starting from all Loads and Meters without clearly defined superiors, trace backwards along the Circuit until the Panel is found. Then trace the incoming lines of the Panel to construct a complete tree or mesh topology starting from the main distribution room Panel (root node). Use the Union-Find algorithm to efficiently handle potentially complex connection relationships and ensure topology consistency.

[0043] Generate a topology tree: This ultimately forms a complete data structure with the main distribution box as the root and containing multiple layers of nodes such as Panel, Meter, and Load.

[0044] Step 3: Design a compliance intelligent detection module (rule engine) to encode industry standards into executable detection rules and scan the generated physical topology tree.

[0045] Here is an example of a rule base: R0: Distribution Box Capacity Verification: For each Panel object, calculate the sum of the rated current or power of all its subordinate outgoing circuits (Meter or Direct Load) and compare it with the Panel's rated capacity attribute. If the sum exceeds 80% of the capacity (configurable threshold), a warning "Distribution box capacity is close to saturation" is issued; if it exceeds 100%, a warning "Distribution box overload" is issued.

[0046] R1: Three-level power distribution and end-point protection detection: Check the panel and meter levels in the path from the main distribution box (level 1) to the end load. Ensure that the power distribution does not exceed level 3. Simultaneously, check if the end circuit has corresponding protective devices (which can be inferred from the meter or load attributes) and verify that their settings match the load.

[0047] R2: Redundant meter detection: Compare adjacent nodes at the same level. If two meters (A, B) have completely identical load types, power, and service areas, and are physically close, it indicates a possible redundant design, and it is recommended to merge the circuits.

[0048] R3: Load Mixing Detection: For a single end loop node, check the "Type" attribute of all its subordinate Loads. If it contains "Lighting", "Socket" and "High-Power Air Conditioner" at the same time, trigger an alarm, indicating "Different types of loads are mixed, posing a risk of interference or overload".

[0049] R4: Critical Load Independence Detection: Establish a "Critical Load Type List" (e.g., "Fire Protection", "Security", "Computer Room"). Traverse all end loops. If a loop is found to contain both critical and non-critical loads, trigger an alarm and display the message "Critical load does not have an independent dedicated loop".

[0050] R5: Primary Load Power Supply Path Detection: Identifies all loads classified as "Primary Load" or "Specially Important Load," traces their power supply path in reverse, and checks whether they share meters or upstream lines with other non-Primary Loads. If they do, the "Separate Radial Power Supply" requirement is not met.

[0051] R6: Load balance detection in the distribution box: For a three-phase distribution box, analyze the total power of the single-phase loads connected to each phase and calculate the three-phase imbalance. If it exceeds the standard (e.g., 15%), the system will indicate "A certain phase is overloaded, resulting in reduced efficiency and equipment risk".

[0052] Execution and output: The rule engine executes the above rules in sequence, records the nodes, lines, and load information that violate the rules, and can highlight the problem locations on the original CAD drawings or topology tree diagram.

[0053] Step 4 involves automatic business topology planning and reverse recommendation, mapping from the "physical world" to the "business world" and providing decision support. Specifically, this includes: Step 41, Business Category Definition Users define business categories through the UI interface, such as: "Office lighting", "Office sockets", "Public area air conditioning", "Data center IT load", "Emergency support system", and "Smart devices in conference rooms".

[0054] Each business category is associated with a set of matching rules. The rules are defined based on the Load property.

[0055] Example rule: "Office Zone Lighting" = Load.Type contains "Lighting" AND Load.BusinessZone contains "Office Zone".

[0056] Example rule: "Data Center IT Load" = Load.Type equals "IT-Server" or "Network Device".

[0057] Step 42, Automatic Generation of Business Topology The system traverses all Load objects in the entire physical topology tree and, based on the business matching rules defined in step 1, categorizes each load into one or more business categories.

[0058] Then, reverse aggregation is performed: all upstream meters supplying power to these loads are identified. These meters constitute the "business topology" serving this business category.

[0059] Visualization: Generates a new tree diagram with the business category as the root node, where the leaf nodes are the specific electricity meters supplying that business, and allows drill-down to view the specific loads under each meter. Step 43, Business Analysis and Reverse Recommendation (Core Algorithm) 4.3.1 Missing Item Analysis: For example, matching rules for "intelligent conference room devices" (e.g., Load.Type contains "projector" and "video conferencing" AND Load.BusinessZone contains "conference room"). The system performs matching and finds: Scenario A: There is load matching, but these loads are distributed across multiple existing meters that power the "office area sockets" and cannot be metered independently.

[0060] Scenario B: Some loads are matched, but some equipment in the conference room is not covered by the existing electricity meter (no corresponding load record).

[0061] 4.3.2 Recommended Solution: For scenario A (independent metering not possible): The system locates the nearest common upstream meter for these loads. It is recommended to add a new meter after this common upstream meter and before these loads, and reconnect the relevant load lines to this new meter. The system can automatically mark the optimal location (line node) for installing the meter on the topology map.

[0062] For scenario B (incomplete coverage): The system, in conjunction with the building floor plan (if associated), locates the uncovered meeting room and prompts the installation of a new circuit and meter in the corresponding distribution box.

[0063] Output recommendation: Automatically generate a text report containing: "To meet the independent metering requirements of the new business 'intelligent meeting room devices,' we recommend: 1. Add a meter M-new1 at the outgoing terminal of the AL3-2 distribution box on the 3F floor and reconnect the relevant loads of meeting rooms 301 and 302 to this terminal; 2. It is estimated that one new meter will be needed and three wiring modifications will be required." Output proposal: Automatically generates a detailed proposal including schematic diagrams, locations for power distribution box modifications, required materials (meter model, cable specifications and length estimates), and a summary of construction steps.

[0064] Finally, when users raise new business statistics requirements, they only need to edit the content in section 3.1, and the system can automatically generate business topology, perform business analysis, and make reverse recommendations.

[0065] On the other hand, the present invention provides a business energy consumption planning system based on standardized electrical design drawings, including: a drawing input and parsing module, a physical topology construction module, a business classification configuration module, a business topology generation module, and a business analysis and solution recommendation module; preferably, the system can also be expanded to include a design compliance intelligent detection module and a real-time topology self-calibration module.

[0066] Example 1: Recommendation for Independent Metering and Retrofitting of Smart Meeting Room Equipment. This example addresses the requirement for "independent metering of energy consumption for smart meeting room equipment" in an office building that is already in use, and details the specific implementation process of the present invention.

[0067] Implementation Scenario: An office building has been completed and put into use. The property management company needs to independently meter the energy consumption of smart devices (projectors, video conferencing systems, smart sockets, etc.) in all meeting rooms throughout the building for cost allocation and refined management. The electrical design drawings of this office building are smart CAD drawings that follow the preset annotation specifications of this invention.

[0068] Specific implementation steps: Standardized CAD drawing input and parsing The standardized electrical design CAD drawings for the office building were input into the system. All energy consumption circuits in the drawings were drawn on continuous polylines in a designated layer. Electricity meters, end loads, and distribution boxes were all drawn using preset blocks and carried complete extended attributes. Among them, the loads such as projectors and video conferencing equipment in the conference rooms were clearly marked in their block attributes as "projector" and "video conferencing", and belonged to areas such as "3F Conference Room 301" and "3F Conference Room 302".

[0069] The system automatically parses the drawings, identifies and extracts all energy consumption circuits, meters, end loads, and electrical component objects corresponding to distribution boxes, and records the attribute information and connection relationships of each component, including the power supply lines, upstream meters, and distribution box information of each smart device in the conference room.

[0070] Automatic construction of energy consumption physical topology Based on the electrical component objects obtained through parsing, the system establishes the connection relationships between distribution boxes, meters, end loads, and energy consumption circuits through spatial relationship analysis. Using a disjoint-set data structure algorithm, starting from the end loads and meters, the system traces back along the energy consumption circuits to the upstream distribution boxes, all the way to the main incoming distribution box in the main distribution room. Finally, it constructs a complete tree-like physical topology data structure for energy consumption, with the main distribution box as the root node, including the distribution layer, metering layer, and power consumption layer, thus fully reconstructing the power supply path from the main incoming line to each end load.

[0071] Business category definition and matching rule configuration Users can add a new business category, "Conference Room Smart Device Energy Consumption," through the system's UI interface and configure the corresponding matching rules: Load.Type includes "Projector" OR "Video Conferencing" OR "Smart Socket" AND Load.BusinessZone includes "Conference Room."

[0072] Automatic generation of business energy consumption topology The system traverses all end loads in the constructed energy consumption physical topology. Based on the matching rules mentioned above, it automatically identifies and categorizes all eligible smart conference room device loads throughout the building. The system then performs reverse aggregation on the categorized loads, tracing the upstream power supply meter of each load. It discovers that all smart conference room device loads are distributed across "office area socket" meters on each floor. These meters also supply power to ordinary office area socket loads, making independent metering of the smart conference room devices impossible. Based on the aggregation results, the system automatically generates a business energy consumption topology view corresponding to "Conference Room Smart Device Energy Consumption," clearly displaying all loads, power supply meters, and power supply paths corresponding to this business category.

[0073] Recommended solutions for missing business measurement analysis and improvement Based on the business energy consumption topology and physical topology, the system identified the current metering defect as follows: the load of the target business category has been matched, but it is scattered under multiple non-dedicated meters and cannot be metered independently.

[0074] To address this deficiency, the system automatically locates the nearest common upstream power distribution box for all smart devices in the conference rooms—the 3F floor power distribution box AL3-2—and generates a corresponding renovation plan: Recommended Installation Location: Add one smart meter M-new1 to the outgoing line of the AL3-2 distribution box on the 3F floor to independently measure the total energy consumption of the smart devices in the conference rooms; Wiring Modification Plan: Reconnect all load lines corresponding to the smart devices in conference rooms 301, 302, and 303 from the original "office area socket" branch meter to the outgoing line of the new meter M-new1; Bill of Materials: Automatically matches recommended meter models, cable specifications and estimated lengths, and a list of supporting auxiliary materials; Construction Steps Summary: Clearly outlines the entire process of power outage operation, meter installation, wiring modification, power-on testing, and system integration; Visual Annotation: Highlights the installation location of the new meter and the wiring nodes requiring modification in the physical topology diagram and original CAD drawings. Finally, the system automatically generates a standardized modification plan proposal, which is delivered to the user for review and implementation.

[0075] Example 2: Intelligent Design Compliance Detection. This example is based on the energy consumption physical topology data structure constructed in Example 1, and performs intelligent design compliance detection. The specific process is as follows: The system activates the rule engine, loads the built-in electrical design specification rule library, and performs a full scan of the building's energy consumption physical topology. Distribution box capacity verification: The system scans and finds that the rated capacity of distribution box AL3-2 on the 3F floor is 100A, and the total rated current of all its outgoing circuits is 95A, exceeding the preset 80% warning threshold. The system automatically generates a warning message: "Distribution box AL3-2's capacity is nearing saturation (load rate 95%), it is recommended to evaluate capacity expansion or load adjustment," and highlights the distribution box.

[0076] Independence detection of critical loads: The system identified "fire emergency lighting" as a critical load. The scan revealed that a fire emergency lighting circuit on the first basement level was also connected to the ordinary lighting load in the underground parking garage. The system immediately triggered a critical alarm: "Fire emergency lighting does not have an independent dedicated circuit and shares a circuit with non-critical loads, posing a safety hazard." The system also highlighted the non-compliant circuit on the drawings and simultaneously pushed rectification suggestions.

[0077] Three-phase load balance detection: The system performs three-phase load analysis on the 1F main distribution box and calculates that the total power of phase A load is 82kW, phase B is 55kW, and phase C is 60kW. The three-phase imbalance exceeds the national standard of 15%, and the system triggers an alarm, indicating that "phase A load is too heavy, which may lead to reduced energy efficiency and equipment overheating risk. It is recommended to adjust the three-phase load distribution."

[0078] After the scan is completed, the system automatically generates a compliance inspection report, listing all issues categorized by severity level, including the location of the issue, the non-compliant clauses, risk descriptions, and rectification suggestions. It also supports exporting and linking with drawings for location information.

[0079] Example 3: Real-time Physical Topology Self-calibration and Deviation Detection. This example focuses on the scenario after the modification scheme in Example 1 is implemented, and realizes the self-calibration of the topology model. The specific process is as follows: After the system completes the push of the renovation plan, it automatically marks the 3F distribution box AL3-2 and related circuits as the area affected by the renovation, and starts enhanced real-time data monitoring of the area. It accesses the real-time current, power and voltage data of all smart meters in the area through the MQTT protocol, with a collection frequency of 1 minute / time.

[0080] After the renovation is completed, the system will continuously collect real-time operating data of the electricity meters in the renovated area to establish an energy consumption baseline before and after the renovation. The system expects that after the renovation, the newly added electricity meter M-new1 should show the load corresponding to the smart devices in the conference room, and the basic load of the electricity meters in the original office area sockets should show a corresponding decrease.

[0081] Through time series synchronization analysis, the system found that the power on / off events of the projector in conference room 302 were not correlated with the power changes of meter M-new1, but were highly synchronized with the power changes of meter M-old3 in the 3F office area socket that had not been modified, with a Pearson correlation coefficient of 0.98. Therefore, it was inferred that the projector's wiring in conference room 302 was not reconnected to meter M-new1 as planned, but was still connected to the original meter M-old3.

[0082] The system automatically generates a topology deviation report, detailing the deviation location, the basis for inference (including real-time power change curves and correlation coefficients), and providing model correction suggestions: change the upstream power supply meter of the projector load in conference room 302 from M-new1 to M-old3.

[0083] After receiving the report, the property management personnel conducted an on-site inspection and confirmed the oversight during construction. After completing the rewiring, they confirmed the correction suggestions in the system. The system automatically updated the energy consumption physical topology data structure, completed the model self-calibration, and ensured that the digital model was completely consistent with the actual wiring on site.

[0084] This invention includes, but is not limited to, the above embodiments. Any equivalent substitutions or partial improvements made under the spirit and principles of this invention shall be considered within the scope of protection of this invention.

Claims

1. A business energy consumption planning method based on standardized electrical design drawings, characterized in that, Includes the following steps: S1 acquires standardized electrical design CAD drawings drawn according to preset annotation specifications; S2 parses the CAD drawings and extracts the electrical component objects corresponding to the energy consumption circuit, electricity meter, end load, and distribution box, as well as the attribute information and interconnection relationship of each component; Based on the extracted electrical component objects and their connections, S3 constructs a complete energy consumption physical topology data structure with the main distribution box as the root node through spatial relationship analysis and hierarchical relationship inference algorithms. S4 receives the service category definition input by the user, as well as the matching rules based on the terminal load attribute corresponding to each service category; S5 iterates through all end loads in the energy consumption physical topology data structure and automatically categorizes the loads into the corresponding business categories according to the matching rules; S6 performs reverse aggregation on the end loads of the same service category, locates the upstream electricity meter that supplies it, and automatically generates the service energy consumption topology for the corresponding service category. S7 uses the business energy consumption topology and energy consumption physical topology data structure to conduct business metering missing analysis and identify metering defects corresponding to the current business category. Based on the identified metering defects, S8 automatically generates an energy consumption renovation plan that includes the location of the electricity meter installation, the content of the line modification, the bill of materials, and the construction steps.

2. The method according to claim 1, characterized in that, In step S1, the standardized electrical design CAD drawings include graphic elements of energy consumption circuits, electricity meters, end loads, distribution boxes, corresponding extended attributes, and clear line connection relationships. The preset labeling specifications specifically include: all energy consumption loops must be drawn as continuous polylines in the specified layer; Electricity meters, end loads, and distribution boxes are all represented by preset blocks and carry extended attributes, recording key information such as core component parameters, type, region, incoming line source, and rated capacity. The wiring connections in the drawings are clear and accurate.

3. The method according to claim 1, characterized in that, Step S2 involves parsing two types of drawings: intelligent CAD drawings and dumb CAD drawings. For intelligent CAD drawings, layer elements and block attributes are directly identified to create corresponding electrical component objects. For dumb CAD drawings, component information and connection relationships are extracted through image processing, pattern recognition, text recognition, and connection tracing technologies, while providing a human-interactive correction interface.

4. The method according to claim 1, characterized in that, The hierarchical relationship inference algorithm described in step S3 adopts the disjoint-set data structure algorithm, which is as follows: starting from the end load and electricity meter without a clear superior, trace back along the energy consumption loop to the corresponding distribution box, and then continue to trace the source of the incoming line of the distribution box, and finally construct a complete tree or mesh energy consumption physical topology data structure from the main distribution box to the end load.

5. The method according to claim 1, characterized in that, The service metering gap analysis described in step S7 includes the identification of at least two types of metering defects: the first type is that the loads of the target service category have been matched, but are scattered under multiple non-dedicated meters and cannot be metered independently; the second type is that some loads of the target service category are not covered by the existing metering range. In step S8, for the first type of defect, the nearest common upstream meter of the scattered loads is located, and a solution to add a new meter and modify the line is recommended; for the second type of defect, the uncovered area is located, and a solution to add a circuit and meter to the corresponding distribution box is recommended.

6. The method according to claim 1, characterized in that, The method also includes a design compliance intelligent detection step: based on a preset electrical design specification rule library, a full scan is performed on the completed energy consumption physical topology data structure to identify nodes, lines and loads that violate the specifications, and a compliance detection report is generated that includes the problem level, problem location and rectification suggestions. It supports highlighting the problem location on CAD drawings or topology diagrams.

7. The method according to claim 6, characterized in that, The rule base includes at least seven core detection rules: distribution box capacity verification, three-level power distribution and end protection detection, redundant meter detection, load hybridity detection, important load independence detection, primary load power supply path detection, and three-phase load balance detection.

8. The method according to any one of claims 1-7, characterized in that, The method also includes a real-time physical topology self-calibration and deviation detection step: access the real-time energy consumption data stream of the smart meter on site, trigger the deviation detection process when a modification event or unexpected energy consumption change is detected, infer the actual electrical connection relationship through load characteristic matching, power change comparison, and time series synchronization analysis, generate a deviation report and correction suggestions after comparing and identifying topology deviations, and automatically update the energy consumption physical topology data structure after manual review and confirmation.

9. A business energy consumption planning system based on standardized electrical design drawings, characterized in that, include: The drawing input and parsing module is used to acquire standardized CAD drawings and extract electrical component information and connection relationships; The physical topology construction module is used to construct the energy consumption physical topology data structure with the main distribution box as the root node; the service classification configuration module is used to receive user-defined service classification and load matching rules; the service topology generation module is used to complete load classification and automatically generate service energy consumption topology; and the service analysis and solution recommendation module is used to identify metering defects and automatically generate energy consumption transformation solutions.

10. The system according to claim 9, characterized in that, The system also includes a design compliance intelligent detection module and a real-time topology self-calibration module; the design compliance intelligent detection module has a built-in electrical design specification rule library for automated compliance scanning and generating detection reports; the real-time topology self-calibration module is connected to the field smart meter for collecting real-time energy consumption data, identifying topology deviations and completing model self-calibration.

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