Electric vehicle charging station energy efficiency monitoring method and system based on dynamic interaction and visual enhancement

Abstract

This invention relates to a method and system for monitoring the energy efficiency of electric vehicle charging stations based on dynamic interaction and visual enhancement, belonging to the field of geographic information systems and industrial data visualization technology. It addresses the problems of existing technologies, such as lack of interactivity, limited visual representation, overlapping coordinates, and fixed data dimensions. The technical solution includes data acquisition and preprocessing, comprehensive energy efficiency assessment, geocoding and coordinate correction, interactive control and parameter management, and a dynamic visualization rendering module. It uses a hash offset algorithm to prevent coordinate overlap, employs a game theory-based weighted model to calculate energy efficiency scores, and supports dual-mode switching between a standard positioning view and a radial highlight view. This invention improves interactive usability, enhances visual perception, balances micro-level positioning with macro-level situational awareness, and supports dynamic decision support.

Description

Technical Field

[0001] This invention belongs to the field of geographic information systems and industrial data visualization technology, and relates to a method and system for monitoring the energy efficiency of electric vehicle charging stations based on dynamic interaction and visual enhancement. Background Technology

[0002] With the rapid development of the new energy vehicle industry, the construction scale of electric vehicle charging stations is constantly expanding, generating massive amounts of multi-dimensional data from daily operations. Energy efficiency assessment and monitoring of these charging facilities has become a crucial step for operators in refined management and strategic planning. Currently, related technologies in this field mainly focus on constructing mathematical models to assess the energy efficiency of charging stations. For example, mathematical methods such as the Analytic Hierarchy Process (AHP) and the entropy weight method are widely used to construct assessment index systems.

[0003] However, existing technologies have significant shortcomings in visualizing and interactively monitoring assessment results. Firstly, traditional monitoring systems generally lack interactivity and real-time capabilities. Most of these systems use static charts or pre-rendered HTML files as display media, preventing users from adjusting key assessment parameters in real-time on the graphical user interface (GUI), such as subjective and objective weighting preferences and seasonal influencing factors, and from immediately observing the dynamic changes in the assessment results. This severely impacts the decision-making efficiency of managers.

[0004] Secondly, existing technologies suffer from limited visual representation and low information density. Current GIS-based map displays typically distinguish site energy efficiency levels solely through color variations, lacking the ability to perform refined, multi-dimensional visual mapping of energy efficiency scores. Specifically, they cannot simultaneously map core energy efficiency indicators to multiple visual variables such as the geometric size, transparency, and dynamic change frequency of map markers. This simplistic approach makes it difficult for users to quickly perceive the service coverage and real-time operational activity of high-energy-efficiency sites through intuitive visual elements, such as halo size or pulsating breathing effects, thus reducing the efficiency of information transmission.

[0005] Secondly, high-density areas suffer from severe coordinate overlap and unstable display positions. In real-world applications, multiple charging stations from different operators often cluster at the same physical address or within adjacent business districts. Existing geocoding technologies typically resolve the same address of these different stations to identical latitude and longitude coordinates, resulting in severely overlapping and occluding markers on the map interface. Users cannot effectively view or interact with obscured stations. Although coordinate dispersion schemes based on random jitter exist, the offsets generated by this method are random, causing the display position of the same station to change with each page refresh or map redraw. This disrupts the user's spatial coherence and significantly impacts the system's interactive stability.

[0006] Finally, the existing system's data dimensions are relatively fixed, making it difficult to support flexible dynamic comparative analysis. The system typically makes it difficult for users to quickly switch and compare operational data across different time dimensions, such as winter and summer, and cannot meet the need for dynamic monitoring of the impact of environmental factors on charging facility efficiency.

[0007] Therefore, there is an urgent need in this field for a technology solution for monitoring the energy efficiency of electric vehicle charging stations that can solve the above problems, achieve dynamic interaction, multi-dimensional visual enhancement, and stable display. Summary of the Invention

[0008] In view of this, the purpose of the present invention is to provide a method and system for monitoring the energy efficiency of electric vehicle charging stations based on dynamic interaction and visual enhancement.

[0009] To achieve the above objectives, the present invention provides the following technical solution:

[0010] A method for monitoring the energy efficiency of electric vehicle charging stations based on dynamic interaction and visual enhancement includes the following steps:

[0011] The data acquisition and preprocessing steps are used to read charging station operation data from external heterogeneous data sources and clean and seasonally segment the data to generate standardized indicator data.

[0012] The comprehensive energy efficiency assessment step is used to calculate the comprehensive score and energy efficiency level of each charging station based on the weight parameters input by the user using a game theory combined weighting model.

[0013] The geocoding and coordinate correction steps are used to convert the address of each charging station into reference geographic coordinates and apply a hash offset algorithm to deterministically offset the coordinates of stations in high-density areas to prevent tag overlap.

[0014] The interactive control and parameter management steps are used to listen for parameter adjustment commands input by the user through the graphical user interface (GUI) and trigger the comprehensive energy efficiency assessment steps to recalculate and generate an updated data stream.

[0015] And a dynamic visualization rendering step, used to perform dynamic visualization rendering based on the updated data stream and the view mode selected by the user, wherein when the radiation highlight view is selected, the comprehensive score is mapped to the spot radius and dynamic lighting effect.

[0016] Furthermore, the calculation of the game-theoretic combinatorial weighting model includes:

[0017] Computational Analytic Hierarchy Process (AHP) Subjective Weight Vector ;

[0018] Calculate the objective weight vector using the entropy weight method ;

[0019] Calculate the grey relational weight vector ;

[0020] And solving for the optimal combination coefficients by minimizing the sum of squared deviations. , , This makes the final weight ,in , , The normalized combination coefficients satisfy... .

[0021] Furthermore, the calculation of the hash offset algorithm includes:

[0022] For each site, the address string and site name string are combined to generate a unique identifier Key;

[0023] Perform an MD5 hash operation on the key to obtain a 128-bit hash value. ;

[0024] According to the formula Calculate the latitude and longitude offset, where This is the offset. N For discrete interval constants, Scale The scaling factor is denoted by mod, and mod is the modulo operator.

[0025] And the offset is superimposed on the reference coordinates to obtain the final coordinates.

[0026] Furthermore, the dynamic visualization rendering step includes: when the standard positioning view is selected, drawing a pin mark at the corrected coordinates with the mark color corresponding to the energy efficiency level; when the radiation highlight view is selected, drawing a light spot with a light spot radius... R According to the formula Calculation, where S For comprehensive scoring, and These are the preset minimum and maximum radii; and a breathing animation effect is applied to sites with a comprehensive score exceeding the threshold.

[0027] Furthermore, the breathing animation effect achieves periodic changes in transparency and scaling through CSS3 keyframe animation.

[0028] An energy efficiency monitoring system for electric vehicle charging stations based on dynamic interaction and visual enhancement includes:

[0029] The data acquisition and preprocessing module is used to read charging station operation data from external heterogeneous data sources and clean and seasonally segment the data to generate standardized indicator data.

[0030] The comprehensive energy efficiency assessment module is used to calculate the comprehensive score and energy efficiency level of each charging station based on the weight parameters input by the user using a game theory combined weighting model.

[0031] The geocoding and coordinate correction module is used to convert the address of each charging station into reference geographic coordinates and apply a hash offset algorithm to deterministically offset the coordinates of stations in high-density areas to prevent tag overlap.

[0032] The interactive control and parameter management module is used to listen for parameter adjustment commands input by the user through the GUI and trigger the comprehensive energy efficiency assessment module to recalculate and generate an updated data stream;

[0033] And a dynamic visualization rendering module, used to perform dynamic visualization rendering based on the updated data stream and the view mode selected by the user, wherein when the radiation highlight view is selected, the comprehensive score is mapped to the spot radius and dynamic light effect.

[0034] Furthermore, the comprehensive energy efficiency assessment module includes:

[0035] Subjective weighting unit, used to calculate AHP subjective weight vector ;

[0036] Objective weighting unit, used to calculate the objective weight vector of the entropy weight method. ;

[0037] Grey relational degree weighting unit, used to calculate the grey relational degree weight vector. ;

[0038] And a weight optimization unit, used to solve for the optimal combination coefficients by minimizing the sum of squared deviations. , , And calculate the final weights .

[0039] Furthermore, the geocoding and coordinate correction module includes a hash offset anti-overlap unit, used to generate a unique identifier Key for each site and calculate the MD5 hash value. ; and according to the formula Calculate the offset, where This is the offset. N For discrete interval constants, Scale is the scaling factor, and mod is the modulo operator.

[0040] Furthermore, the dynamic visualization rendering module includes:

[0041] The visual mapping unit is used to map the overall score to the spot radius and transparency;

[0042] A dynamic rendering unit is used to load a breathing animation effect when the overall score exceeds a threshold.

[0043] And a multi-dimensional view switching unit for switching between standard positioning view and radial highlight view.

[0044] Furthermore, the dynamic rendering unit uses CSS3 breathing keyframe animation to achieve the breathing effect.

[0045] The beneficial effects of this invention are as follows:

[0046] The main workflow of this invention is as follows:

[0047] The system first uses multi-source charging station operation data and a game theory-based weighting model to perform subjective and objective calculations on the three-dimensional indicators of "economy, service, and scale" to address the one-sidedness of a single evaluation method.

[0048] Subsequently, the system introduced a hash offset anti-overlap algorithm to deterministically discretize the coordinates of multiple sites with the same physical address, thus solving the problem of point occlusion in high-density areas.

[0049] Finally, the dual main view is rendered collaboratively through the front-end engine, seamlessly switching between standard positioning mode and radiation highlight mode, and is supplemented with breathing light effects to intuitively display the strength of energy efficiency.

[0050] The core innovation of this invention lies in: achieving "scientific balance" in the evaluation model, overcoming the problem of unbalanced indicator weighting; achieving "interactive decoupling" of geographic information, eliminating visual blind spots in high-density data; and achieving "dynamic simulation" for decision support, providing a powerful visualization tool for the refined operation of charging facilities through closed-loop parameter feedback.

[0051] (1) Through the innovative hash offset algorithm, the problem of overlapping and occlusion of map markers caused by the same geocoding in high-density areas is effectively solved, ensuring that each charging station can be selected and queried independently and accurately, eliminating information blind spots.

[0052] (2) By constructing a multidimensional visual mapping model, the abstract energy efficiency score data is simultaneously mapped to the geometric size, transparency and dynamic breathing frequency of the light spot, so that users can quickly identify high energy efficiency sites through visual intuition without reading specific values, which greatly reduces the cognitive load.

[0053] (3) The dual-mode real-time switching mechanism of standard location view and radial highlight view enables the same data source to meet the needs of different application scenarios. The standard view focuses on the precise geographical distribution of the site, while the radial view intuitively shows the service radiation capability and business popularity of the site, effectively avoiding the information limitations of the single view mode.

[0054] (4) The system supports users to adjust subjective and objective weight preferences and seasonal data parameters in real time, and can immediately trigger back-end model recalculation and front-end view update, realizing millisecond-level closed-loop interaction from parameter input to visual feedback, helping managers to make rapid and scientific decision analysis under different management strategies and external environments.

[0055] Other advantages, objectives, and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination, or may be learned from practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description

[0056] To make the objectives, technical solutions, and advantages of the present invention clearer, the preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, wherein:

[0057] Figure 1 This is a diagram showing the system module composition.

[0058] Figure 2 A logic diagram for dynamic visualization rendering and dual-mode switching;

[0059] Figure 3This is a flowchart illustrating the data flow and morphological evolution of the core algorithm.

[0060] Figure 4 This is the interactive area of ​​the interactive control panel. Detailed Implementation

[0061] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0062] The accompanying drawings are for illustrative purposes only and are schematic diagrams, not actual pictures. They should not be construed as limiting the invention. To better illustrate the embodiments of the invention, some parts in the drawings may be omitted, enlarged, or reduced, and do not represent the actual product dimensions. It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0063] In the accompanying drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components. In the description of the present invention, it should be understood that if terms such as "upper," "lower," "left," "right," "front," and "rear" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, they are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, the terms used to describe positional relationships in the drawings are only for illustrative purposes and should not be construed as limiting the present invention. For those skilled in the art, the specific meaning of the above terms can be understood according to the specific circumstances.

[0064] like Figure 1 As shown, this system consists of five core modules, each of which achieves a logical closed loop through clearly defined data flow and control flow.

[0065] Data Acquisition and Preprocessing Module: As the data source of the system, its input end receives external heterogeneous Excel operation data files, as shown in Table 1; after cleaning and seasonal segmentation, its output end generates a standardized structured data object containing seven-dimensional indicators such as average daily charging volume and station load rate, as shown in Table 2, and transmits it unidirectionally to the comprehensive energy efficiency assessment module.

[0066] Table 1

[0067]

[0068] Table 2

[0069]

[0070] Comprehensive Energy Efficiency Assessment Module: This module adopts a dual-input mechanism, receiving standardized indicator data from upstream on one hand and real-time weight parameter instructions from the interactive control module on the other. After parallel calculation by the game theory model, it outputs complete assessment result data containing "comprehensive score" and "energy efficiency star rating", and then transfers the result to the geocoding and coordinate correction module.

[0071] Geocoding and Coordinate Correction Module: This module takes the site address and name from the evaluation results as input; after parsing and processing by the core hash offset algorithm, it outputs the final geographic coordinates Lat,Lng with a deterministic small offset. Then, it returns the complete site data containing the coordinates and scores to the interactive control module for assembly.

[0072] Interactive control and parameter management module: As the hub connecting backend computing and frontend rendering, its input end listens for user interaction commands in real time (such as seasonal switching and weight adjustment); its output end is divided into two paths: one path sends a recalculation trigger signal to the backend evaluation module, and the other path serializes the finally processed site data into a GeoJSON format data packet and injects it into the dynamic visualization rendering module.

[0073] Dynamic visualization rendering module: As the final display end of the system, its input is the received GeoJSON data packet; after being parsed by the WebGL engine, the output is a visualized map layer, which switches between "standard view" and "radial view" according to the data attributes, realizing a closed loop of the whole link from data access to visual presentation.

[0074] Figure 2 It provides a detailed demonstration of the complete logical process by which the front-end visualization engine processes data and performs dual-mode rendering.

[0075] Initial Judgment Phase: The process begins with receiving the GeoJSON site data packet, followed by a judgment box to "Determine the current visualization mode parameters". Here, the system reads the mode command selected by the user in the control panel. If the command is "Standard Mode", the logic flows to the left branch; if the command is "Radial Mode", the logic flows to the right branch.

[0076] Left branch – Standard positioning view pipeline:

[0077] The process of switching the base map is as follows: The system first performs the base map switching action and loads high-brightness standard map tiles to ensure the clarity of geographic information.

[0078] The process of creating a marker is as follows: The system reads the "Energy Efficiency Star Rating" field from the attributes of each site, and draws the corresponding pin marker at the corrected coordinates according to the preset color mapping table (e.g., five stars correspond to red, three stars correspond to green).

[0079] Labeling steps: Finally, overlay a text label next to the marker to directly display the energy efficiency level and complete the rendering of precise geographic location.

[0080] Right Branch – Radiation Highlight View Pipeline:

[0081] Switching to Dark Background: The system performs a background inversion action, switching the map background to Dark Mode to provide a high-contrast environment for lighting effects rendering.

[0082] The visual mapping calculation steps consist of two core sub-steps. The first is radius mapping, where the system reads the site's "comprehensive score" and calculates the spot radius using a linear interpolation formula; the higher the score, the larger the radius. The second is transparency mapping, which dynamically adjusts the brightness of the spot's center based on the score.

[0083] High energy efficiency threshold judgment box: The process then proceeds to the "Score > Breathing threshold?" judgment box. The system compares the score of each station with a preset threshold (e.g., 80 points):

[0084] Yes (High Efficiency): Executes the "Load CSS3 Breathing Animation" action, injecting periodic scaling and transparency change keyframes into the light spot to create a dynamic breathing effect.

[0085] No (Normal): Performs the "Load Static Styles" action, rendering only fixed radial gradient light spots.

[0086] Interaction and Update Phase: The two branches ultimately converge on the "Bind Click Interaction Event" step. The system registers listeners for all rendered objects, and a details window pops up when the user clicks on a marker or light spot. Finally, the "Update WebGL Map Layer" action is executed, submitting the calculated graphics frame to the graphics card for screen rendering, completing a full view update.

[0087] Figure 3 Using the evolution of data throughout its entire lifecycle as a guide, the text describes how information flows and reorganizes between various modules.

[0088] Raw Data Access and Structuring Phase: The process begins with the "raw operational data stream," which is in the form of an unstructured Excel file (.xlsx). After cleaning and seasonal slicing (Summer / Winter), the data is transformed into a structured PandasDataFrame data object in memory. At this point, the data stream carries basic operational indicators such as "average daily charging volume A4" and "station load rate A5," but does not yet include evaluation and coordinate information.

[0089] Multi-dimensional attribute expansion stage: The data stream enters the core computing domain and interacts with the floating-point weight parameters input by the user. Integration. Through matrix operations using a game theory-based weighted model, the data object's attributes were expanded, adding two key fields: "Comprehensive Score (floating-point)" and "Energy Efficiency Level (enumerated type)".

[0090] Spatial geographic mapping stage: To achieve map visualization, the data stream needs to be processed by a hash offset algorithm. The system determines whether the reference coordinates overlap and transforms the text-type address field into a deterministic geographic coordinate tuple (Lat, Lng). At this point, the data format changes from two-dimensional table rows to a list of Python dictionaries (ListofDicts) containing "geometric information + attribute information," completing the transformation from pure data to spatial entities.

[0091] Standardized encapsulation and rendering injection phase: In the final output stage, the dictionary list is serialized into a standard GeoJSON format data packet String. This data packet, as a universal exchange format, encapsulates the coordinates, ratings, colors, and animation states of all sites and is directly injected into the front-end WebGL engine through the script interface. This process marks the final evolution of the data stream into a "dynamic visual object" that can be parsed by the browser, completing the full-link evolution from static recording to interactive layers.

[0092] like Figure 4 As shown, Figure 4 This is the interactive area of ​​the interactive control panel.

[0093] The system supports two visualization rendering modes in the map rendering area, specifically including:

[0094] (1) Standard view mode: This mode is configured to display the precise geographical distribution of the site.

[0095] Base map configuration: The system loads a high-brightness standard road network map as the background layer to provide clear geographic reference.

[0096] Symbolic representation: The system draws thumbtack-shaped entity markers on the map based on the coordinates after latitude and longitude correction.

[0097] Color coding: The fill color of the marker directly corresponds to the energy efficiency level of the site (e.g., red corresponds to five-star, green corresponds to three-star, etc.), and the energy efficiency level is intuitively distinguished by the difference in hue.

[0098] Information interaction: When a click event is detected on the marker, the system pops up an information window containing indicators such as average daily charging volume and station load rate.

[0099] (2) High-brightness radiation mode: This mode is configured to display the macro-level situation of energy efficiency and the service radiation range.

[0100] Base map configuration: The system automatically switches to a dark background map to enhance the contrast of the light effect rendering.

[0101] Visual mapping: The system hides entity markers and instead renders an energy-efficient light spot with a radial gradient effect at the coordinate points. The coverage radius and center transparency of the light spot are calculated by a mapping function based on the site's overall score. The higher the score, the larger the light spot size and the higher the center brightness.

[0102] Dynamic enhancement: For sites whose comprehensive score exceeds the preset threshold, the system loads keyframe animations, driving the light spot to perform periodic scaling and transparency changes, forming a breathing and flashing effect, and visually highlighting the core high-quality sites.

[0103] (3) Control and Interaction Area: The control and interaction area located on the right side of the interface is the input interface for realizing human-machine collaborative decision-making, and mainly includes the following functional modules:

[0104] ①Data Source and Mode Switching Module: This module displays the currently loaded operational data attributes (such as summer or winter data) and provides a selection control to switch between standard view mode and radial highlight mode.

[0105] ② Multi-dimensional filtering module: contains checkboxes for site type and energy efficiency level, used to filter and display charging sites with specific attributes according to user instructions.

[0106] ③ Strategy Preset Module: Provides several predefined weight configuration buttons (such as economy priority strategy, efficiency priority strategy), which can quickly apply a set of weight parameters in response to click commands.

[0107] ④Weight dynamic adjustment module:

[0108] Subjective / Objective Weight Scale Adjuster: This slider control receives user-inputted coefficient values ​​and dynamically adjusts the fusion ratio of subjective and objective weights in the game theory model.

[0109] Indicator Fine-tuning Slider Group: Provides independent adjustment sliders for individual indicators such as DC pile inventory, station load rate, and price economy, allowing users to fine-tune the importance of specific indicators.

[0110] When the system detects that a user has entered a parameter adjustment command in the control interaction area, the system backend immediately triggers the recalculation process of the game theory combination weighting model, generates an updated score data stream, and drives the map rendering area to refresh the display effect in real time, realizing a closed-loop interaction from parameter input to visual feedback.

[0111] This area serves as the core interface for human-computer interaction and includes the following key UI elements and functional logic:

[0112] Multi-dimensional parameter configuration component functions: Seasonal data selection control: The drop-down selection box at the top of the panel allows users to switch between "Summer (June data)" and "Winter (January data)". This control is used to define the data baseline for the evaluation model to meet the energy efficiency analysis needs under different climate scenarios. Visualization mode switcher: The tab control in the middle allows users to switch between "Standard View Mode" and "Radiation Highlight Mode (Dark)" in real time, used to change the map base map style (light / dark) and the site rendering form (pins / spots). Energy efficiency level filter checkbox: Provides checkboxes from "One Star" to "Five Stars", allowing users to quickly filter the display status of specific level sites on the map by checking or dechecking. Weight adjustment and preset area: The lower half of the panel contains the core parameter adjustment tools. The "One-click parameter setting" button group (such as "Economy Priority", "Efficiency Priority") allows users to quickly apply predefined expert strategies; "Subjective and objective weight ratio" The slider is used to dynamically adjust the proportion of subjective and objective weights in the game theory model; the "AHP Subjective Weight Configuration" slider group corresponds to seven specific indicators from A1 to B1, allowing users to fine-tune the importance of a single indicator.

[0113] Interaction-triggered system response chain: This system implements a millisecond-level closed-loop response mechanism. When the user interacts with any of the UI elements mentioned above, such as dragging the weight slider to change... Upon receiving the change, the system will immediately trigger the following chain reaction: Command capture and parameter injection: The interaction layer first captures the user's change event, obtains the latest weight coefficients or filtering conditions, and injects them into the backend calculation module. Real-time model recalculation: The calculation core immediately executes the game theory combined weighting algorithm based on the new parameters to recalculate the comprehensive energy efficiency score and star level for all sites. Visual variable mapping update: The recalculation results are mapped in real time to new visual variables (such as spot radius size and color encoding), and an updated graphic data package is generated. View redraw feedback: After receiving the data, the front-end rendering engine smoothly transitions and redraws the map layer without refreshing the page, realizing real-time dynamic decision support for "parameter adjustment - model recalculation - visual feedback".

[0114] I. System Module Composition and Data Flow

[0115] As attached Figure 1 As shown, the system is logically divided into five core functional modules:

[0116] 1. Data Acquisition and Preprocessing Module: As the system's data entry point, this module is responsible for reading external heterogeneous data sources, such as Excel files, and performing data cleaning, field mapping, and outlier handling. This module includes a built-in seasonal data sharding unit, which can load summer or winter operational datasets based on user instructions. Simultaneously, its derived indicator calculation unit automatically calculates secondary indicators such as station load rate and average daily charging volume based on the original fields. The specific formula for calculating the station load rate is:

[0117]

[0118] After processing, a structured standard data table is generated and temporarily stored in memory.

[0119] 2. Comprehensive Energy Efficiency Assessment Module: As the core of the system's calculations, this module is responsible for the dynamic calculation of weights and site scoring. It employs a game-theoretic combinatorial weighting model, comprising a subjective weighting unit, an objective weighting unit, and a weight optimization unit. The subjective weighting unit receives parameters from the analytic hierarchy process (AHP), while the objective weighting unit calculates entropy weights and grey relational degrees. The weight optimization unit solves for the optimal combination coefficients by minimizing the sum of squared deviations. Let there be a total... L Various empowerment methods, recorded For the first k The weight vector of the method, the optimal coefficients The following optimization problem was solved to obtain the following:

[0120]

[0121] right Normalize: The final combined weights are obtained. Overall rating for each site From the formula The calculation shows that, among which For the first j The combined weights of the indicators For the first i The first site j The normalized values ​​of each indicator.

[0122] 3. Geocoding and Coordinate Correction Module: This module is responsible for converting site addresses into geographic coordinates and resolving display conflicts in high-density areas. Its core is the hash offset anti-overlap unit. This unit first calls the map application programming interface to obtain the baseline coordinates; for multiple sites with the same address, it extracts the address and name to form a unique identifier string (Key); and then performs an MD5 hash operation on the Key to obtain a 128-bit hash value. ; Calculate the latitude and longitude offset using the formula:

[0123]

[0124] in N For discrete interval constants, Scale This is the scaling factor (e.g., set to 0.0001 degrees). The calculated deterministic offset... Overlaying onto the baseline coordinates ensures that sites with the same address are discretely distributed on the map and have fixed locations.

[0125] 4. Interactive Control and Parameter Management Module: As the system's main control center, this module connects the user interface and the backend logic. It monitors user interactions on the graphical user interface in real time, such as sliding the weight slider, switching seasons, and changing display modes. Once parameters change, the evaluation module is immediately triggered to recalculate, and the latest results are serialized into a JSON data stream.

[0126] 5. Dynamic Visualization Rendering Module: Residing in the front-end web engine, this module is responsible for the final rendering and visual mapping of the map. It consists of three sub-units:

[0127] Visual mapping unit: Establishing a comprehensive score S The functional relationship between light spot radius and visual variables. In a radiometric highlight view, the light spot radius... R From the formula Decision, among which and These are the preset minimum and maximum radii, respectively.

[0128] Dynamic rendering unit: When the site's overall score exceeds a preset threshold (such as 80 points), CSS3 frame animation is automatically loaded, causing the light spot to produce periodic changes in transparency and scaling, creating a breathing effect.

[0129] Multi-dimensional view switching unit: Supports real-time switching between standard location view and radial highlight view. The standard view uses pin markers to accurately display the geographical location; the radial view hides the markers and draws dynamic halos to represent the radiating influence of the site.

[0130] II. Dual-mode dynamic visualization rendering logic

[0131] like Figure 2 As shown, the workflow of the front-end rendering engine is as follows:

[0132] The process begins with receiving a data packet from the GeoJSON site. The system first determines the current visualization mode parameters. If the user selects the standard positioning view, a light-colored background map is loaded, and pin markers are drawn at the corrected coordinates. The marker colors directly correspond to the energy efficiency star rating, and text labels are overlaid.

[0133] If the user selects the radiation highlight view, the map background is first switched to a darker color. Then, a visual mapping calculation is performed, determining the radius and center brightness of the light spot based on the site's overall rating. Next, it's determined whether the rating is higher than the breathing effect threshold. If it is higher, a CSS3 breathing animation is loaded; if it's lower, only a static light spot is rendered. Finally, click events are bound to all graphic elements, and the map layer is updated to complete the rendering.

[0134] Users can access the information provided in the attached document. Figure 4 The interactive control panel shown adjusts parameters in real time. The panel includes a seasonal data selection control, a visualization mode switcher, energy efficiency level filter checkboxes, a weight adjustment slider group, and preset strategy buttons. Any operation triggers a command capture from the parameter management module, which then initiates backend recalculation and frontend redrawing, forming a millisecond-level real-time closed-loop interaction.

[0135] Example

[0136] Taking two charging stations, A and B, located at the same address "No. 88, a certain avenue" in a certain city as an example, their reference coordinates are both (29.600000, 106.500000).

[0137] The data acquisition and preprocessing module reads its summer operation data and calculates that the load rate of site A is 50% and the load rate of site B is 2%.

[0138] The geocoding and coordinate correction module performs a hash operation on the address identifiers of the two sites to generate different tiny offsets, causing their final displayed coordinates to differ and avoiding overlap.

[0139] The integrated energy efficiency assessment module runs a game theory combinatorial weighting model to calculate the integrated score for site A. Site B's overall rating .

[0140] The dynamic visualization rendering module performs mapping under the radiation highlight view. Let... =20px, =100px, then the radius of the light spot at site A =92.32px, and because its score is higher than 80, the breathing light effect is triggered; the light spot radius of site B. =25.36px, displayed only as a static dark spot. Users can intuitively and clearly identify high-efficiency sites.

[0141] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for monitoring the energy efficiency of electric vehicle charging stations based on dynamic interaction and visual enhancement, characterized in that: Includes the following steps: The data acquisition and preprocessing steps are used to read charging station operation data from external heterogeneous data sources and clean and seasonally segment the data to generate standardized indicator data. The comprehensive energy efficiency assessment step is used to calculate the comprehensive score and energy efficiency level of each charging station based on the weight parameters input by the user using a game theory combined weighting model. The geocoding and coordinate correction steps are used to convert the address of each charging station into reference geographic coordinates and apply a hash offset algorithm to deterministically offset the coordinates of stations in high-density areas to prevent tag overlap. The interactive control and parameter management steps are used to listen for parameter adjustment commands input by the user through the graphical user interface (GUI) and trigger the comprehensive energy efficiency assessment steps to recalculate and generate an updated data stream. And a dynamic visualization rendering step, used to perform dynamic visualization rendering based on the updated data stream and the view mode selected by the user, wherein when the radiation highlight view is selected, the comprehensive score is mapped to the spot radius and dynamic light effect; The calculation of the game theory combinatorial weighting model includes: Calculating the subjective weight vector of the Analytic Hierarchy Process (AHP) ; Calculate the objective weight vector using the entropy weight method ; Calculate the grey relational weight vector ; And solving for the optimal combination coefficients by minimizing the sum of squared deviations. , , This makes the final weight ,in , , The normalized combination coefficients satisfy... ; The calculation of the hash offset algorithm includes: For each site, the address string and site name string are combined to generate a unique identifier Key; Perform an MD5 hash operation on the key to obtain a 128-bit hash value. ; According to the formula Calculate the latitude and longitude offset, where This is the offset. N For discrete interval constants, Scale The scaling factor is denoted by mod, and mod is the modulo operator. And the offset is superimposed on the reference coordinates to obtain the final coordinates; The dynamic visualization rendering steps include: when the standard positioning view is selected, drawing a pin mark at the corrected coordinates with the mark color corresponding to the energy efficiency level; when the radiation highlight view is selected, drawing a light spot with a light spot radius... R According to the formula Calculation, where S For comprehensive scoring, and These are the preset minimum and maximum radii; and a breathing animation effect is added for sites whose overall score exceeds the threshold. The breathing animation effect uses CSS3 keyframe animation to achieve periodic changes in transparency and scaling.

2. An energy efficiency monitoring system for electric vehicle charging stations based on dynamic interaction and visual enhancement, characterized in that: include: The data acquisition and preprocessing module is used to read charging station operation data from external heterogeneous data sources and clean and seasonally segment the data to generate standardized indicator data. The comprehensive energy efficiency assessment module is used to calculate the comprehensive score and energy efficiency level of each charging station based on the weight parameters input by the user using a game theory combined weighting model. The geocoding and coordinate correction module is used to convert the address of each charging station into reference geographic coordinates and apply a hash offset algorithm to deterministically offset the coordinates of stations in high-density areas to prevent tag overlap. The interactive control and parameter management module is used to listen for parameter adjustment commands input by the user through the GUI and trigger the comprehensive energy efficiency assessment module to recalculate and generate an updated data stream; And a dynamic visualization rendering module, used to perform dynamic visualization rendering based on the updated data stream and the view mode selected by the user, wherein when the radiation highlight view is selected, the comprehensive score is mapped to the spot radius and dynamic light effect; The comprehensive energy efficiency assessment module includes: Subjective weighting unit, used to calculate AHP subjective weight vector ; Objective weighting unit, used to calculate the objective weight vector of the entropy weight method. ; Grey relational degree weighting unit, used to calculate the grey relational degree weight vector. ; And a weight optimization unit, used to solve for the optimal combination coefficients by minimizing the sum of squared deviations. , , And calculate the final weights ; The geocoding and coordinate correction module includes a hash offset anti-overlap unit, used to generate a unique identifier key for each site and calculate the MD5 hash value. ; and according to the formula Calculate the offset, where This is the offset. N For discrete interval constants, Scale The scaling factor is denoted by mod, and mod is the modulo operator. The dynamic visualization rendering module includes: The visual mapping unit is used to map the overall score to the spot radius and transparency; A dynamic rendering unit is used to load a breathing animation effect when the overall score exceeds a threshold. And a multi-dimensional view switching unit for switching between standard positioning view and radial highlight view; The dynamic rendering unit uses CSS3 breathing keyframe animation to achieve the breathing effect.

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