New energy engineering cost progress two-dimensional dynamic prediction and risk prevention and control system

Abstract

The invention relates to the technical field of new energy systems, and particularly discloses a new energy engineering cost progress two-dimensional dynamic prediction and risk prevention and control system, which comprises a data processing module, a dynamic prediction module, a risk prevention and control module and a visualization module. Cost and progress linkage prediction is realized based on the coupling relationship between the cost subject tree and the progress node network, the error is reduced by more than 40% compared with the traditional single-dimensional prediction, and the cost hyper-branched and progress lagging risks of the future N cycles can be identified in advance; a multi-level early warning mechanism automatically triggers risk prevention and control suggestions including super-budget attribution analysis, cost compression and progress compression strategies, the response speed is increased, and human decision delay is reduced; supplier full-process management quantifies the performance capability, quality and delivery cycle through a weighted scoring model, an elimination mechanism is automatically triggered based on an accumulated performance problem or a scoring threshold, and the performance risk is reduced.

Description

Technical Field

[0001] This invention relates to the field of new energy system technology, specifically to a dynamic prediction and risk control system for the cost and schedule of new energy projects. Background Technology

[0002] In the current field of new energy project management, traditional cost and schedule control techniques have the following significant shortcomings: 1. Insufficient data integration and dynamic management: The existing system has difficulty integrating multi-source data such as ERP, finance, and IoT. The execution data of cost items (such as investment estimates and execution budgets) lacks a real-time update mechanism, which causes the budget adjustment to lag behind the actual changes in the project and cannot adapt to the dynamic changes in the project. 2. Single-dimensional risk warning: Risk assessment relies solely on cost or schedule, without constructing a dual-dimensional coupled prediction model. This makes it impossible to quantify the linkage risk between cost overruns and schedule delays, often leading to decision-making biases. 3. Low visualization and collaboration efficiency: Lack of integrated display of 3D-BIM model and GIS map, risk distribution and progress status cannot be visualized in real time, serious delay in on-site data synchronization, and insufficient penetrating analysis capability of management dashboard; 4. Inadequate supplier and contract management: The supplier admission and evaluation process lacks quantitative standards, and the linkage control mechanism between contract payment and progress and quality is missing, which can easily lead to waste of funds and performance risks. Summary of the Invention

[0003] To address the shortcomings of existing technologies, this invention provides a dynamic prediction and risk control system for the cost and schedule of new energy projects from two dimensions, thus solving the problems mentioned in the background technology.

[0004] To achieve the above objectives, the present invention provides the following technical solution: a dual-dimensional dynamic prediction and risk control system for the cost and schedule of new energy projects, comprising: The data processing module connects to ERP, OA, financial systems and IoT devices to collect real-time data throughout the entire project lifecycle, including cost item execution data, schedule node data, contract payment data and risk event data. Cost item execution data includes investment estimates, execution budgets and dynamic costs, while schedule node data includes planned progress, actual progress and BIM model timeline. The dynamic forecasting module, based on the coupling relationship between the cost item tree and the schedule node network, constructs a two-dimensional forecasting model and calculates the cost deviation rate on a rolling basis. and schedule deviation rate Output the probability of cost overrun and schedule delay for the next N periods; Risk control module, when or When the preset threshold is exceeded, an early warning will be automatically triggered and risk prevention and control suggestions will be generated, including over-budget attribution analysis, adjustment plan for pending costs, and schedule compression path; The visualization module integrates 3D-BIM models and GIS maps, renders the cost-schedule coupling status in real time, dynamically displays risk distribution in the form of heat maps, and outputs multi-level penetrating analysis reports through the management dashboard.

[0005] Preferably, the cost account tree is constructed according to hierarchical coding rules, with the lowest-level account associated with contract payment terms, material classifications, and budget accounts. Changes in the preliminary estimate are dynamically updated through a version upgrade function, and its version control formula is: ; in, Indicates the first Version execution estimate, For the first Estimated value of the edition, For the first Item change amount, The original value of the corresponding subject. This represents the number of changes; The process for upgrading the execution budget of the cost item tree includes: When the dynamic cost exceeds the total budget, an upgrade command is triggered, and the system automatically copies the previous budget data and fills in the changed amount. The new version title is automatically generated by subtracting "V" from the original title and adding the version number. The release time is synchronized with the document approval time. After the upgrade, an execution budget change table is automatically generated, recording the differences between versions and the change trajectory.

[0006] Preferably, the progress node network maps the physical construction progress to the BIM model timeline, and the actual progress feedback uses a color-coding rule: Green: Actual progress ≥ Planned progress; Yellow: -10%≤ <0; red: <-10%; The formula for calculating the schedule deviation rate is as follows: ; in, This is the actual completion time. This is the planned completion time.

[0007] Preferably, the rolling calculation of the two-dimensional prediction model uses a coupling function: ; ; in, This is the industry adjustment coefficient. , This represents the current total budget estimate.

[0008] Preferably, the early warning threshold setting of the risk prevention and control module includes: Level 1 Warning: >5% or <-5%; Level 2 warning: >10% or <-10%; The formula for over-probability attribution analysis is: ; in, Estimate costs for contracts to be signed. For estimated change costs; Risk control recommendations are generated based on a dynamic cost table and include: Cost reduction strategies: Freeze payments for non-critical contracts and initiate supplier price comparison programs; Schedule compression strategies: adding resources to the critical path and reorganizing parallel construction processes; Strategy priority is determined by the cost-schedule coupling coefficient: .

[0009] Preferably, the management cockpit of the visualization module integrates the following real-time metrics: Cost dimension: Dynamic cost exceeding the budget ratio Cost per watt ; Progress dimensions: critical path completion rate, BIM model progress color block coverage; Risk dimensions: density of high-risk issues and resolution rate of early warning events; in, For dynamic costs, For the estimated investment amount, The project capacity is MW; Supports offline synchronization on mobile devices. When on-site personnel upload progress photos via the app, the system automatically identifies the completion status of nodes and updates the BIM model. The image recognition confidence formula is: ; when The progress data will be automatically updated when it reaches >90%. To identify the area, This is the standard area.

[0010] Preferably, the dynamic cost management process includes: Cost data has been confirmed to be automatically synchronized: contract amounts and supplementary agreement data are obtained from the procurement platform, and change / approval data are read from the approval process; Manual entry of costs to be incurred: The amount of contracts to be signed is automatically calculated by subtracting the amount of signed contracts from the amount of supplementary agreements. The estimated amount of changes is to be reported monthly by the person in charge of costs. When the total estimated amount exceeds the budget, the corresponding account will be marked with a red warning. The calculation formula is as follows: ; Costs already confirmed.

[0011] Preferably, the entire supplier management process includes: Access review: Enter the supplier's basic information and qualification documents, verify the uniqueness of the supplier's name and unified social credit code, mark the site visit as completed and upload the report after the site visit is passed; Dynamic evaluation: After each department scores offline, the procurement department uploads an evaluation report, and the system calculates the overall competitiveness using a weighted model. ; To score performance, To rate the quality, Scoring based on delivery cycle time, The weighting of enterprise qualification indicators, As the weight of the performance capability indicator, The weights of quality control indicators; Elimination Mechanism: When a supplier accumulates 3 performance issues or an evaluation score below 60, the elimination process is triggered, and the system automatically links all cooperative project data of that supplier as the basis for elimination.

[0012] Preferably, the on-site inspection judgment logic in the supplier access process includes: Inspection document association mechanism: If the on-site inspection audit has been conducted and an inspection report is attached, the system verifies the completeness of the inspection documents using the following formula: ; When file integrity is less than 100%, a pop-up prompt will be made to complete the file; Evaluation conclusions will be quantitatively rated: the evaluation conclusions will generate an initial supplier rating using a weighted scoring model. : ; in As the indicator weight, For individual scores; exemption mechanism: when Furthermore, when the rating is A, the system automatically marks similar projects as exempt from evaluation. The formula for judging similar projects is: .

[0013] Preferred budget dynamic verification model: budget occupancy rate after change The calculation formula is: ; in This is the total amount originally applied for. The original detailed amount, This is the changed amount. This is the estimated value for the corresponding cost item; when When the system automatically triggers an advanced approval process; quantitative control of the contract management closed loop: payment verification logic: system verification during invoice registration. If the amounts differ, write-off will be refused; supplementary agreement amount linkage: total amount of the new contract. Update using the following formula: ; in To change the amount, a dynamic cost adjustment is triggered simultaneously. The adjusted dynamic cost; Payment node trigger condition: The unlocking condition for the payment node is... ,in: .

[0014] This invention provides a dual-dimensional dynamic prediction and risk control system for the cost and schedule of new energy projects, which has the following beneficial effects: 1. Based on the coupling relationship between the cost item tree and the schedule node network, the system enables the linkage prediction of cost and schedule, reducing the error by more than 40% compared with the traditional single-dimensional prediction. It can identify the risk of cost overruns and schedule delays in the next N periods in advance. The multi-level early warning mechanism (level 1 / level 2 early warning) automatically triggers risk prevention and control suggestions, including over-budget attribution analysis, cost reduction and schedule reduction strategies, improving the response speed by 50% and reducing human decision-making delays.

[0015] 2. The cost item tree supports automatic upgrades of the execution budget. When the dynamic cost exceeds the total budget, it automatically copies historical data and updates the changed amount, fully recording the differences between versions and ensuring that the budget data is synchronized with the actual project. Dynamic cost management integrates confirmed costs (automatically synchronized) and costs to be incurred (intelligently calculated). When the cost exceeds the budget, it automatically issues a red alert, improving budget control accuracy by 30% and avoiding the risk of overdraft.

[0016] 3. The management cockpit integrates 12 real-time indicators such as dynamic cost over-budget ratio and cost per watt. It dynamically displays risk distribution through 3D-BIM and GIS map heat map, improving decision-making efficiency by 60%. The mobile terminal supports offline synchronization. On-site personnel can upload progress photos, which can automatically identify node status and update the BIM model. The data synchronization delay is shortened to within 10 minutes, improving on-site collaboration efficiency.

[0017] 4. Supplier end-to-end management uses a weighted scoring model to quantify performance capabilities, quality, and delivery cycle. The elimination mechanism is automatically triggered based on accumulated performance issues or scoring thresholds, reducing performance risk by 25%. Contract payment milestones are forcibly coupled with progress completion rate and quality acceptance score. Payment is only unlocked when the product of the two indicators is ≥0.8, avoiding early payments for non-compliant products and significantly improving the efficiency of capital utilization.

[0018] 5. When the budget utilization rate exceeds 90%, the advanced approval process is automatically triggered, reducing the risk of budget overdraft by 40%; the supplementary agreement amount is linked to update the total contract amount and dynamic cost to ensure 100% data consistency; the invoice reimbursement amount and payment amount are subject to mandatory verification to prevent financial loopholes caused by discrepancies in amounts, and the closed-loop nature of contract management is significantly enhanced. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the principle of a dual-dimensional dynamic prediction and risk control system for cost and schedule of new energy projects as described in this invention. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] like Figure 1 As shown, this invention provides a technical solution: a dual-dimensional dynamic prediction and risk control system for the cost and schedule of new energy projects, comprising: a data processing module, a dynamic prediction module, a risk control module, and a visualization module; the data processing module interfaces with ERP, OA, financial systems, and IoT devices to collect real-time project lifecycle data, including cost item execution data, schedule node data, contract payment data, and risk event data. Cost item execution data includes investment estimates, execution budgets, and dynamic costs; schedule node data includes planned progress, actual progress, and the BIM model timeline; the dynamic prediction module constructs a dual-dimensional prediction model based on the coupling relationship between the cost item tree and the schedule node network, and calculates the cost deviation rate through rolling calculations. and schedule deviation rate Output the probability of cost overrun and schedule delay for the next N periods; the risk control module... or When the preset threshold is exceeded, an early warning is automatically triggered and risk prevention and control suggestions are generated, including over-budget attribution analysis, cost adjustment plan and schedule compression path; the visualization module integrates 3D-BIM model and GIS map, renders the cost-schedule coupling status in real time, dynamically displays the risk distribution in the form of heat map, and outputs multi-level penetrating analysis reports through management dashboard.

[0022] More specifically, the cost account tree is constructed according to hierarchical coding rules. The lowest-level accounts are associated with contract payment terms, material classifications, and budget accounts. Changes in the budget are dynamically updated through the version upgrade function, and its version control formula is: ; in, For the first Estimated value of the edition, For the first Item change amount, The original value of the corresponding subject. This represents the number of changes; The process for upgrading the execution budget of the cost item tree includes: When the dynamic cost exceeds the total budget, an upgrade command is triggered, and the system automatically copies the previous budget data and fills in the changed amount. The new version title is automatically generated by subtracting "V" from the original title and adding the version number. The release time is synchronized with the document approval time. After the upgrade, an execution budget change table is automatically generated, recording the differences between versions and the change trajectory.

[0023] The cost item tree is constructed according to hierarchical coding rules, such as using the coding method "GF.01.02.01", where each level of coding corresponds to the project category, sub-project, cost item, and other levels. The lowest-level item needs to be associated with contract payment terms, material classification codes, and budget accounts to achieve a two-way mapping between cost data and contract management and material procurement. For example, the lowest-level item "GF.01.02.01" can be associated with the payment node of a procurement contract for a certain type of photovoltaic module, the material classification code "WL-001", and the corresponding budget account "YS-003".

[0024] In this embodiment, taking a certain new energy power plant project as an example, when the purchase price of photovoltaic modules increases, causing the dynamic cost to exceed the original estimate by 5%, the system triggers an upgrade: Copy the first version of the preliminary budget data and fill in the component procurement item change amount + 500,000 yuan; The new version automatically generates the title "XX Power Plant Execution Budget - V2", and the release time is recorded as the time of approval. The change statement shows that the "GF.01.02.01" item increased from RMB 3 million to RMB 3.5 million, with the reason for the change being "fluctuations in component market prices".

[0025] More specifically, the progress node network maps physical construction progress to the BIM model timeline, and the actual progress feedback uses a color-coding rule: Green: Actual progress ≥ Planned progress; Yellow: -10%≤ <0; red: <-10%; The formula for calculating the schedule deviation rate is as follows: ; in, This is the actual completion time. This is the planned completion time.

[0026] The construction of the BIM model timeline and progress node network: The progress node network achieves a digital mapping of the physical construction progress through the BIM model timeline. The specific steps are as follows: Import the project BIM model, break the model down into quantifiable progress nodes according to construction procedures, such as "photovoltaic bracket installation" and "cable laying," with each node associated with a planned start / end time; the system automatically generates a timeline, arranging the progress nodes in logical order to form a virtual progress network corresponding to the physical construction; real-time collection of actual on-site progress data (e.g., uploaded via IoT devices or mobile apps), matching it to the corresponding nodes in the BIM model, achieving dynamic updates of the progress status. Color coding feedback rules for actual progress: The system automatically colors-codes progress nodes based on the progress deviation rate (ΔT), with the specific rules as follows: Green indicator: When the actual progress is greater than or equal to the planned progress, the node is displayed in green, indicating that the progress is normal; Yellow indicator: When -10%≤ΔT<0, the node is displayed in yellow, indicating a slight delay in progress; Red indicator: When ΔT < -10%, the node is displayed in red, indicating that the progress is seriously lagging behind.

[0027] Calculation and application of schedule deviation rate, calculation formula: ; in, The actual completion time of the node. Schedule the completion time for each node; Real-time calculation mechanism: The system automatically captures the actual completion time of each node every minute, compares it with the planned time to calculate ΔT, and updates the color label.

[0028] Case Application: In a photovoltaic power station project, the "inverter installation" milestone was scheduled to be completed on June 10, 2025, but was actually completed on June 15. Therefore: ; Because ΔT>0, the node is displayed in green; if it is actually completed on June 12th, It will remain green; if it is actually completed on June 5th, If it is red, then it will be displayed.

[0029] More specifically, the rolling calculation of the two-dimensional prediction model employs a coupling function: ; ; in, This is the industry adjustment coefficient. It can be adaptively adjusted according to the type of new energy project (such as photovoltaic and wind power). For example, in photovoltaic projects, it can be taken as follows: , The current total estimated cost is based on the latest version of the cost account tree. Sure.

[0030] Rolling calculation mechanism: Data input: The system retrieves the latest data from the data processing module every period (e.g., daily / weekly). and Values; where: ; ; in, For the current execution budget, For dynamic costs, and These are the actual completion time and the planned completion time, respectively. Iterative calculation: Using a sliding window technique, the latest period data is included each time, the earliest period data is removed, and the calculation is recalculated. and Generate the future Risk probability curve for a period of time (e.g., 30 days).

[0031] In this embodiment, a 50MW photovoltaic project is used as an example: Current execution budget 10,000 yuan, dynamic cost Ten thousand yuan, so: ; A key milestone was scheduled to be completed on July 1st, but was actually completed on July 5th. sky, Heaven, therefore: ; Take industry coefficient , , , ,but: ; ; The system according to A level 2 warning is triggered, and a progress compression suggestion is generated (such as adding resources to the bracket installation team).

[0032] More specifically, the early warning threshold settings of the risk control module include: Level 1 Warning: >5% or <-5%; Level 2 warning: >10% or <-10%; The formula for over-probability attribution analysis is: ; in, Estimate costs for contracts to be signed. For estimated change costs; Risk control recommendations are generated based on a dynamic cost table and include: Cost reduction strategies: Freeze payments for non-critical contracts and initiate supplier price comparison programs; Schedule compression strategies: adding resources to the critical path and reorganizing parallel construction processes; Strategy priority is determined by the cost-schedule coupling coefficient: .

[0033] The warning threshold setting and triggering logic system presets two levels of warning thresholds, automatically triggering different levels of warnings based on the degree of deviation of cost deviation rate (ΔC) and schedule deviation rate (ΔT): Level 1 Warning: Triggered when ΔC > 5% or ΔT < -5%, indicating a slight risk of cost overrun or schedule delay in the project. For example, if the dynamic cost of a photovoltaic project exceeds the estimated cost by 6%, or a key milestone is 4% behind schedule, the system will immediately send a warning notification.

[0034] Level 2 Warning: Triggered when ΔC > 10% or ΔT < -10%, indicating a serious risk. If dynamic costs exceed the budget by 12% or the schedule is 15% behind schedule, the system will initiate emergency prevention and control procedures.

[0035] The system quantifies the proportion of reasons for exceeding the budget using the following formula: ; in: The estimated cost for contracts to be signed is derived from the estimated value of contracts to be signed on the procurement platform. The estimated change costs should be submitted monthly by the person responsible for costs. .

[0036] Risk prevention and control suggestion generation mechanism: Cost reduction strategies: 1. Freeze payments for non-critical contracts: The system automatically identifies non-critical path contracts and suspends payments until the risk is mitigated; 2. Initiate supplier comparison scheme: Initiate a new comparison of prices for suppliers associated with high-cost items. For example, when the cost of cable procurement exceeds the budget, a comparison process with more than three suppliers is triggered.

[0037] Schedule compression strategies: 1. Adding resources to the critical path: Analyze critical path nodes, such as when "inverter installation" is delayed, and automatically suggest adding construction teams; 2. Reorganizing parallel construction processes: Adjust serial processes to parallel operations, such as installing brackets and laying cables simultaneously to shorten the construction period.

[0038] Methods for determining strategy priorities: The system automatically prioritizes prevention and control strategies based on the cost-schedule coupling coefficient (K). ; When ΔC = 8% and ΔT = -12%, This indicates that schedule delays are the main risk, and schedule compression strategies should be prioritized. When C=15% and ΔT=-5%, Cost overruns are the primary risk, so cost reduction strategies should be initiated first.

[0039] In this embodiment: During the construction phase of a wind power project, the dynamic cost exceeded the budget by 12% (ΔC=12%), and the progress of a key milestone was delayed by 8% (ΔT=-8%). The system triggers a level-two warning (ΔC>10%), and the calculation is as follows: This is attributed to the pending tower contract and design changes; The following prevention and control recommendations were generated: freeze payments for non-critical cable contracts, initiate price comparisons with tower suppliers, and add two construction teams to the critical path of "wind turbine hoisting". calculate Prioritize cost reduction strategies and simultaneously advance progress measures.

[0040] More specifically, the management cockpit of the visualization module integrates the following real-time metrics: Cost dimension: Dynamic cost exceeding the budget ratio Cost per watt ; Progress dimensions: critical path completion rate, BIM model progress color block coverage; Risk dimensions: density of high-risk issues and resolution rate of early warning events; in, Indicates the first Version execution estimate, For dynamic costs, For the estimated investment amount, The project capacity is MW; Supports offline synchronization on mobile devices. When on-site personnel upload progress photos via the app, the system automatically identifies the completion status of nodes and updates the BIM model. The image recognition confidence formula is: ; when The progress data will be automatically updated when it reaches >90%. To identify the area, This is the standard area.

[0041] The multi-dimensional real-time indicator integrated management dashboard is based on 3D-BIM models and GIS maps, and renders the cost-schedule coupling status in real time, integrating three core indicators: Cost dimension: Dynamic cost over budget ratio The calculation formula is: ; in, For dynamic costs (real-time synchronization with the procurement platform and approval process). This is the current estimated value. For example, a photovoltaic project. Ten thousand yuan, When it reaches 10,000 yuan, The cockpit displays the overspending percentage in the form of a progress bar.

[0042] Cost per watt The calculation formula is: ; in, The estimated investment amount is in yuan. Project capacity (unit: MW). For example... Ten thousand yuan, ,but The cost per watt is displayed in the form of a heat map, showing the differences in cost per watt by region.

[0043] Progress dimension: Critical path completion rate = number of completed nodes on the critical path / total number of nodes on the critical path, calculated in real time and marked with a Gantt chart to indicate lagging nodes; BIM model progress color block coverage: The model is rendered using green (normal progress), yellow (slightly behind schedule), and red (severely behind schedule) color blocks. Coverage = area of ​​updated color blocks / total area of ​​the model × 100%.

[0044] Risk dimensions: High-risk issue distribution density = number of high-risk issues / project area, displayed as red dot density on the GIS map; The early warning event resolution rate = number of resolved early warnings / total number of early warnings, which is updated in real time via the dashboard.

[0045] Mobile offline synchronization and image recognition mechanism: Data synchronization process: 1. On-site personnel take photos of construction nodes through the APP and select the corresponding BIM model node to upload; 2. The system stores the photos and node association information when offline, and automatically synchronizes them to the server when connected to the network.

[0046] Image recognition and progress updates: Confidence level calculation formula: ; in, The completed construction area is determined by image recognition. This refers to the standard construction area. For example, a bracket installation node. Recognition area ,but ; when When the system automatically updates the BIM model node status to "Completed", it will mark it as "Pending Confirmation" and send a manual review notification.

[0047] In this embodiment, the application scenario is a 50MW wind power project: Real-time display of the management cockpit (Exceeding the initial estimate by 3 million yuan), cost per watt Yuan / watt, the cost heat map highlights the overspending on tower procurement items; In the BIM model, the "Wind Turbine Installation" node is displayed as a red block, with a progress coverage rate of only 60% and a critical path completion rate of 75%, triggering a level 2 warning; On-site personnel uploaded photos of the cabin installation, and the system calculated... The node status is automatically updated, and the risk dimension warning event resolution rate is simultaneously refreshed to 80%.

[0048] This mechanism improves project management efficiency by more than 50% and reduces risk identification delay to within 1 hour by visualizing multi-dimensional indicators and synchronizing them with mobile devices.

[0049] More specifically, the dynamic cost management process includes: Cost data has been confirmed to be automatically synchronized: contract amounts and supplementary agreement data are obtained from the procurement platform, and change / approval data are read from the approval process; Manual entry of costs to be incurred: The amount of contracts to be signed is automatically calculated by subtracting the amount of signed contracts from the amount of supplementary agreements. The estimated amount of changes is to be reported monthly by the person in charge of costs. When the total estimated amount exceeds the budget, the corresponding account will be marked with a red warning. The calculation formula is as follows: ; Confirmed costs (contract amount + supplementary agreements + change orders); Estimate costs for contracts to be signed; For estimated change costs; This represents the current total budget estimate.

[0050] Visualized early warning display: When When the cost item name is displayed in bold red font, it will be pinned to the top of the "Risk Items" list in the management dashboard. For example, if the total amount of the "Photovoltaic Bracket Procurement" item exceeds the budget by 1 million yuan, the system will automatically mark it in red and pop up a message saying "Over-budget risk: +5%".

[0051] In this embodiment, dynamic cost management of a 50MW photovoltaic project is implemented: Confirmed costs: 30 million RMB for the component procurement contract synchronized with the procurement platform, and 2 million RMB for the supplementary agreement; 1.5 million RMB for the cable change approval process, totaling [amount missing]. Ten thousand yuan; Costs to be incurred: The estimated execution cost is 50 million yuan, while the total cost of signed contracts and supplementary agreements is 32 million yuan. The cost of contracts to be signed is automatically calculated. The estimated change amount was RMB 3 million; the person responsible for the cost reported an estimated change amount of RMB 3 million. Ten thousand yuan; Warning trigger judgment: The system triggered an over-budget warning, and items such as "photovoltaic bracket procurement" and "cable laying" were displayed in red. At the same time, a risk report was generated, suggesting that supplier price comparison be initiated to reduce the cost of pending contracts.

[0052] More specifically, the entire supplier management process includes: Access review: Enter the supplier's basic information and qualification documents, verify the uniqueness of the supplier's name and unified social credit code, mark the site visit as completed and upload the report after the site visit is passed; Dynamic evaluation: After each department scores offline, the procurement department uploads an evaluation report, and the system calculates the overall competitiveness using a weighted model. ; To score performance, To rate the quality, Scoring based on delivery cycle time, The weighting of enterprise qualification indicators, As the weight of the performance capability indicator, The weights of quality control indicators; Elimination Mechanism: When a supplier accumulates 3 performance issues or an evaluation score below 60, the elimination process is triggered, and the system automatically links all cooperative project data of that supplier as the basis for elimination.

[0053] Data collection for the weighted calculation model of dynamic evaluation scoring: Performance rating ( The score is based on the completion of contract payment milestones. 10 points will be deducted for each instance of late delivery, with a maximum score of 100 points. Quality rating ( The quality inspection department scores the goods based on the acceptance rate upon arrival; a pass rate of ≥95% receives 90 points or higher. Delivery cycle score ( ): The deviation rate between the actual delivery period and the contractually agreed period. A deviation of ≤0% earns 100 points, and 5 points are deducted for each day exceeding the deviation.

[0054] Overall competitiveness calculation: The system automatically calculates scores according to preset weights: ; The default value for the weight is: (Performance) (quality), (Delivery) can be adjusted according to project type (e.g., photovoltaic project design). ).

[0055] Data update mechanism: The procurement department uploads evaluation reports for each supplier by the 5th of each month. The system automatically overwrites historical scores and generates trend charts, such as the score of a cable supplier in June. The score improved by 13 points compared to May (72 points).

[0056] The automated triggering process of the elimination mechanism determines the triggering conditions: The system monitors the following indicators in real time: Cumulative count of performance issues: Each instance of late delivery / quality non-compliance is counted as 1, and when it reaches 3 times, it is automatically marked as "high risk"; Evaluation score threshold: when When the time is set, an alert is triggered and the supplier's name is highlighted.

[0057] Data correlation for elimination: When elimination is triggered, the system automatically retrieves all cooperative project data by supplier ID and generates an "Elimination Basis Report", which includes: historical contract amount (e.g., cumulative contract amount of 5 million yuan); details of performance issues (e.g., one late delivery in March 2025); and impact analysis (e.g., causing a 2-day delay in project progress).

[0058] Approval process: The elimination report is automatically pushed to the procurement director for approval. Once approved, the system executes the following: Mark the supplier's status as "obsolete" to prevent them from creating new contracts; Synchronize with the supplier blacklist database and connect to the industry credit platform.

[0059] In this embodiment: a case of supplier elimination for a photovoltaic project: Access Phase: A support supplier entered the name "XX Metal Products Co., Ltd.", passed the unified social credit code verification, and the on-site inspection report showed that the production capacity met the standards, so it was marked as "inspected". Dynamic evaluation: Performance score within 3 months of cooperation. (Due to two delivery delays), quality rating (Acceptance pass rate 92%), delivery cycle score (Average delay of 5 days), weighting , , The calculation yields: ; Elimination Trigger: Delivery delays occurred again in the 4th month, and the cumulative number of performance issues reached 3. The system automatically generated an elimination report, showing that the supplier caused the project schedule to be delayed by 5 days. After approval, it was marked as "eliminated" and linked to all 3 of its contract data (total amount of 2 million yuan) as the basis.

[0060] More specifically, the on-site inspection judgment logic in the supplier access process includes: Inspection document association mechanism: If the on-site inspection audit has been conducted and an inspection report is attached, the system verifies the completeness of the inspection documents using the following formula: ; When file integrity is less than 100%, a pop-up prompt will be made to complete the file; Evaluation conclusions will be quantitatively rated: the evaluation conclusions will generate an initial supplier rating using a weighted scoring model. : ; in Weighting of indicators (such as enterprise qualifications) Capability to fulfill obligations ), Individual score (0-100 points); Exemption mechanism: when Furthermore, when the rating is A, the system automatically marks similar projects as exempt from evaluation. The formula for judging similar projects is: .

[0061] As the indicator weight, the preset value is, for example, enterprise qualification. Capability to fulfill obligations Quality control ; Each item is scored individually (0-100 points), and the score is given by the examiners based on the on-site situation, such as: Company Qualifications: 90 points for companies with valid business licenses, ISO certifications, etc. Performance capability: 85 points for on-time delivery rate of similar projects in the past 3 years ≥ 90%; Rating generation example: Evaluation and assessment of a photovoltaic module supplier: Company qualifications Score, weight Capability to fulfill obligations Score, weight Quality control Score, weight ; The calculation yields: ; The system automatically rated it as "Grade B".

[0062] Exemption mechanism for similar projects that do not require on-site inspection: Exemption conditions determination: when Furthermore, when the rating is A, the system automatically activates the exemption mechanism. The judgment logic for similar projects is as follows: If the first three digits of the material classification code are the same, then they are considered to be the same type of item; otherwise, they are not.

[0063] For example, the material classification code for photovoltaic brackets is "WL-001-01", with the first three digits being "WL-0". If the material code of a new supplier is "WL-002-01", with the first three digits being the same, it is determined to be a similar project.

[0064] Exemption marking process: The system generates a "Same type of project exempt from inspection" label on the supplier profile page and associates it with the material classification code; when similar projects are approved for access in the future, the on-site inspection step for this supplier will be automatically skipped and a "Exempted" prompt will be displayed.

[0065] In this embodiment: a supplier access scenario for a wind power project: Document upload: The user selected "Examined" and uploaded 7 documents, for a total of 8 documents examined. Document integrity = The system pop-up window displayed "Warehouse capacity report not uploaded". After completing the report, the verification was successful. Rating Calculation: Inspector's Score: Enterprise Qualification 95 points ( ); Performance capability score: 92 ( Quality control 90 points ( );have to: Rated as Grade A; Exemption Application: When the supplier subsequently participates in the "WL-003-01" (first 3 characters "WL-0") wind power tower project, the system will automatically mark it as "exempt from inspection" and it will directly enter the qualification review stage.

[0066] More specifically, the budget dynamic verification model: budget occupancy rate after changes. The calculation formula is: ; in This is the total amount originally applied for. The original detailed amount, This is the changed amount. This is the estimated value for the corresponding cost item; when When the system automatically triggers an advanced approval process; quantitative control of the contract management closed loop: payment verification logic: system verification during invoice registration. If the amounts differ, write-off will be refused; supplementary agreement amount linkage: total amount of the new contract. Update using the following formula: ; in To change the amount, a dynamic cost adjustment is triggered simultaneously. , The adjusted dynamic cost; Payment node trigger condition: The unlocking condition for the payment node is... ,in: .

[0067] Advanced approval trigger logic: When At that time, the system will automatically trigger the advanced approval process; For example: ; Calculated No advanced approval is required; like =500,000 yuan, then It still triggers a regular approval process; like =700,000 yuan, then It will be automatically pushed to the CFO for approval.

[0068] In this embodiment: a contract management scenario for a new energy project: Budget change verification: The original application for the purchase of photovoltaic modules was 5 million yuan (

[0069] : ; : ; ; calculate This triggers advanced approval and requires the general manager's signature for confirmation.

[0070] Contract payment control: The payment amount for a certain inverter purchase contract is 1 million yuan, the progress completion rate is 90% (planned installation of 100 units, actual installation of 90 units), and the quality acceptance score is 75 points; calculate The payment node has not been unlocked, and the system prompts "Progress or quality does not meet the standards, payment refused"; The quality score after rectification was 85 points. Still not satisfied; Until progress reaches 100% and quality score reaches 80 points, Only after this can a payment request be submitted.

[0071] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A dual-dimensional dynamic prediction and risk control system for the cost and schedule of new energy projects, characterized in that, include: The data processing module connects to ERP, OA, financial systems and IoT devices to collect real-time data throughout the entire project lifecycle, including cost item execution data, schedule node data, contract payment data and risk event data. Cost item execution data includes investment estimates, execution budgets and dynamic costs, while schedule node data includes planned progress, actual progress and BIM model timeline. The dynamic forecasting module, based on the coupling relationship between the cost item tree and the schedule node network, constructs a two-dimensional forecasting model and calculates the cost deviation rate on a rolling basis. and schedule deviation rate Output the probability of cost overrun and schedule delay for the next N periods; Risk control module, when or When the preset threshold is exceeded, an early warning will be automatically triggered and risk prevention and control suggestions will be generated, including over-budget attribution analysis, adjustment plan for pending costs, and schedule compression path; The visualization module integrates 3D-BIM models and GIS maps, renders the cost-schedule coupling status in real time, dynamically displays risk distribution in the form of heat maps, and outputs multi-level penetrating analysis reports through the management dashboard. The cost account tree is constructed according to hierarchical coding rules. The lowest-level accounts are associated with contract payment terms, material categories, and budget accounts. Changes in the budget are dynamically updated through the version upgrade function. Its version control formula is: ； in, For the first Estimated value of the edition, For the first Item change amount, The original value of the corresponding subject. This represents the number of changes; The process for upgrading the execution budget of the cost item tree includes: When the dynamic cost exceeds the total budget, an upgrade command is triggered, and the system automatically copies the previous budget data and fills in the changed amount. The new version title is automatically generated by subtracting "V" from the original title and adding the version number. The release time is synchronized with the document approval time. After the upgrade, an execution budget change table is automatically generated, recording the differences between versions and the change trajectory.

2. The dual-dimensional dynamic prediction and risk control system for cost and schedule of new energy projects according to claim 1, characterized in that, The progress node network maps physical construction progress to the BIM model timeline, and the actual progress feedback uses a color-coding rule: Green: Actual progress ≥ Planned progress; Yellow: -10%≤ <0; red: <-10%; The formula for calculating the schedule deviation rate is as follows: ； in, This is the actual completion time. This is the planned completion time.

3. The dual-dimensional dynamic prediction and risk control system for cost and schedule of new energy projects according to claim 2, characterized in that, The rolling calculation of the two-dimensional prediction model uses a coupling function: ； ； in, This is the industry adjustment coefficient. , This represents the current total budget estimate.

4. The dual-dimensional dynamic prediction and risk control system for cost and schedule of new energy projects according to claim 3, characterized in that, The early warning threshold settings of the risk control module include: Level 1 Warning: >5% or <-5%; Level 2 warning: >10% or <-10%; The formula for over-probability attribution analysis is: ； in, Estimate costs for contracts to be signed. For estimated change costs; Risk control recommendations are generated based on a dynamic cost table and include: Cost reduction strategies: Freeze payments for non-critical contracts and initiate supplier price comparison programs; Schedule compression strategies: adding resources to the critical path and reorganizing concurrent construction processes; Strategy priority is determined by the cost-schedule coupling coefficient: .

5. The dual-dimensional dynamic prediction and risk control system for cost and schedule of new energy projects according to claim 4, characterized in that, The management cockpit of the visualization module integrates the following real-time metrics: Cost dimension: Dynamic cost exceeding the budget ratio Cost per watt ; Progress dimensions: critical path completion rate, BIM model progress color block coverage; Risk dimensions: density of high-risk issues and resolution rate of early warning events; in, Indicates the first Version execution estimate, For dynamic costs, For the estimated investment amount, The project capacity is MW; Supports offline synchronization on mobile devices. When on-site personnel upload progress photos via the app, the system automatically identifies the completion status of nodes and updates the BIM model. The image recognition confidence formula is: ； when The progress data will be automatically updated when it reaches >90%. To identify the area, This is the standard area.

6. The dual-dimensional dynamic prediction and risk control system for cost and schedule of new energy projects according to claim 5, characterized in that, The dynamic cost management process includes: Cost data has been confirmed to be automatically synchronized: contract amounts and supplementary agreement data are obtained from the procurement platform, and change / approval data are read from the approval process; Manual entry of costs to be incurred: The amount of contracts to be signed is automatically calculated by subtracting the amount of signed contracts from the amount of supplementary agreements. The estimated amount of changes is to be reported monthly by the person in charge of costs. When the total estimated amount exceeds the budget, the corresponding account will be marked with a red warning. The calculation formula is as follows: ； Costs already confirmed.

7. The dual-dimensional dynamic prediction and risk control system for cost and schedule of new energy projects according to claim 6, characterized in that, The entire supplier management process includes: Access review: Enter the supplier's basic information and qualification documents, verify the uniqueness of the supplier's name and unified social credit code, mark the site visit as completed and upload the report after the site visit is passed; Dynamic evaluation: After each department scores offline, the procurement department uploads an evaluation report, and the system calculates the overall competitiveness using a weighted model. ; To score performance, To rate the quality, Scoring based on delivery cycle time, The weighting of enterprise qualification indicators, As the weight of the performance capability indicator, The weights of quality control indicators; Elimination Mechanism: When a supplier accumulates 3 performance issues or an evaluation score below 60, the elimination process is triggered, and the system automatically links all cooperative project data of that supplier as the basis for elimination.

8. The dual-dimensional dynamic prediction and risk control system for cost and schedule of new energy projects according to claim 7, characterized in that, The on-site inspection judgment logic in the supplier access process includes: Inspection document association mechanism: If the on-site inspection audit has been conducted and an inspection report is attached, the system verifies the completeness of the inspection documents using the following formula: ； When file integrity is less than 100%, a pop-up prompt will be made to complete the file; Quantitative rating of evaluation conclusions: The evaluation conclusions will generate an initial supplier rating using a weighted scoring model. : ； in As the indicator weight, For individual scores; exemption mechanism: when Furthermore, when the rating is A, the system automatically marks similar projects as exempt from evaluation. The formula for judging similar projects is: 。 9. The dual-dimensional dynamic prediction and risk control system for cost and schedule of new energy projects according to claim 8, characterized in that, Budget dynamic verification model: budget occupancy rate after change The calculation formula is: ； in This is the total amount originally applied for. The original detailed amount, This is the changed amount. This is the estimated value for the corresponding cost item; when When the system automatically triggers an advanced approval process; quantitative control of the contract management closed loop: payment verification logic: system verification during invoice registration. If the amounts differ, write-off will be refused; supplementary agreement amount linkage: total amount of the new contract. Update using the following formula: ； in To change the amount, a dynamic cost adjustment is triggered simultaneously. The adjusted dynamic cost; Payment node trigger condition: The unlocking condition for the payment node is... ,in: 。

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