Power transmission and transformation project cost control line measurement and calculation generation method

Abstract

The invention provides a power transmission and transformation project cost control line measurement and calculation generation method, and relates to the technical field of power transmission and transformation project cost control. Step 2, feature extraction and normalization; 3, applying a normal distribution algorithm; 4, applying a normal distribution algorithm; and 5, generating a result. Through a normal distribution algorithm, a big data structured data mode, data cleaning and feature extraction, an efficient and scientific cost control line generation method is effectively provided for the power transmission and transformation project of the Guangzhou bureau, automatic generation, cost management optimization, accuracy and scientificity improvement, manual error reduction and project implementation guarantee are realized, and the method has significant application value.

Description

Technical Field

[0001] The present invention relates to the technical field of power transmission and transformation project cost control, and in particular to a method for calculating and generating a power transmission and transformation project cost control line. Background Art

[0002] In power transmission and transformation projects, cost control is a key step in ensuring the project's economic viability and rationality. Power transmission and transformation projects encompass numerous complex and diverse stages, from early planning and site selection, equipment procurement, mid-term construction and technical installation, to later commissioning and maintenance. Each stage is closely linked to cost. Effective cost control means ensuring project quality and progress through scientific and rational planning, precise cost accounting, and strict expense supervision. This avoids unnecessary waste of resources and capital expenditures, directs limited funds to the most critical project elements, and maximizes project benefits. This ensures the steady progress of power transmission and transformation projects on an economic and rational basis, laying a solid economic foundation for the efficient and stable operation of the entire power system.

[0003] Traditional cost control methods often rely on empirical data from historical data, lacking systematicity and scientificity, making them difficult to adapt to complex and changing engineering environments. Existing technologies rely on manual empirical calculations, requiring manual collection of existing data, removal of interfering data items, and classification before calculating cost control lines. However, existing cost control line results are limited by incomplete data collection and the inability to adequately eliminate erroneous data, resulting in low accuracy and inadequate guidance for current cost analysis. Summary of the Invention

[0004] Technical problems solved In response to the shortcomings of the existing technology, the present invention provides a method for calculating and generating the cost control line of power transmission and transformation projects, which solves the problems that the existing cost control methods of power transmission and transformation projects often rely on manual experience judgment and simple statistical analysis, and are highly subjective, low in precision, low in efficiency, and the cost management is not standardized and has low consistency.

[0005] Technical Solution To achieve the above objectives, the present invention is implemented through the following technical solutions: a method for calculating and generating a cost control line for a power transmission and transformation project, comprising the following implementation steps: Step 1: Data collection and preprocessing; Step 2: Feature extraction and normalization; Step 3: Application of normal distribution algorithm; Step 4: Application of normal distribution algorithm; Step 5: Generate results.

[0006] Preferably, the specific implementation process of step 1 is as follows: S1. Data Acquisition: Collect historical cost data for Guangzhou Bureau's power transmission and transformation projects through circulation and manual entry during the review process; S2. Data cleaning: Remove duplicate, missing, or abnormal data content to ensure data integrity and consistency; S3. Structured processing: Convert the cost documents submitted for review into structured data content based on indicator extraction rules.

[0007] Preferably, the specific implementation process of step 2 is as follows: S1. Feature extraction: Extract key features from the cleaned data and divide the data into new substation construction, substation expansion, overhead line, and cable projects. S2. Normalization: Normalize the extracted features to eliminate dimensional differences and ensure data comparability.

[0008] Preferably, the specific implementation process of step three is as follows: S1. Data distribution analysis: Use the normal distribution algorithm to analyze the distribution pattern of cost data and calculate the mean (μ) and standard deviation (σ); S2. Control line generation: According to the characteristics of normal distribution, set the upper and lower limits of the cost control line.

[0009] Preferably, the specific implementation process of step 4 is as follows: S1. Comparative analysis: Compare the generated control line with the actual cost data to verify its rationality; S2. Dynamic adjustment: Dynamically adjust the control line parameters based on the verification results to ensure their adaptability.

[0010] Preferably, the specific implementation process of step 1 is as follows: S1. The result of obtaining the cost control line; S2. Publish the control line results.

[0011] Beneficial effects The present invention provides a method for calculating and generating a cost control line for a power transmission and transformation project. It has the following beneficial effects: Through the normal distribution algorithm and big data structured data methods, an efficient and scientific cost control line generation method is provided for the Guangzhou Bureau's power transmission and transformation project. It innovates technical means, optimizes the generation process, improves the level of refinement of cost management, and provides strong technical support for precise cost control.

[0012] Through data cleaning, feature extraction and normal distribution analysis, the cost control line can be automatically generated, which improves the scientificity and accuracy of cost management, reduces errors caused by manual intervention, provides a quantitative basis for all aspects of project cost, ensures the smooth implementation of the project, and has significant practical application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 The present invention provides a flow chart of an implementation plan for a method for calculating and generating a cost control line for a power transmission and transformation project. DETAILED DESCRIPTION

[0014] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0015] Example 1: like Figure 1 As shown, an embodiment of the present invention provides a method for calculating and generating a cost control line for a power transmission and transformation project, including the following implementation steps: Step 1: Data collection and preprocessing; Step 2: Feature extraction and normalization; Step 3: Application of normal distribution algorithm; Step 4: Application of normal distribution algorithm; Step 5: Generate results.

[0016] The specific implementation process of step one is as follows: S1. Data Acquisition: Collect historical cost data for Guangzhou Bureau's power transmission and transformation projects through circulation and manual entry during the review process; S2. Data cleaning: Remove duplicate, missing, or abnormal data content to ensure data integrity and consistency; S3. Structured processing: Convert the cost documents submitted for review into structured data content based on indicator extraction rules.

[0017] Data Acquisition: Data collection is a fundamental and critical step in the power transmission and transformation project review process. Through both data transfer and manual data entry during the review process, we comprehensively collected and acquired historical cost data for the Guangzhou Bureau's power transmission and transformation projects. This historical data covers detailed cost information for numerous completed projects, including cost breakdowns for various project types, material costs, labor costs, and equipment expenses, providing a rich data resource for subsequent analysis and calculations.

[0018] Data cleaning: Because collected data may contain issues, data cleaning is necessary. Duplicate, missing, or abnormal data content is removed to ensure data integrity and consistency. For example, obvious errors can be corrected or deleted, and missing key data fields can be supplemented to ensure data quality and accurately reflect the actual project cost.

[0019] Structural processing: Convert submitted cost documents into structured data based on index extraction rules. This process aims to organize and standardize the information in the disorganized cost documents, presenting them in a format that is easy to process and analyze. By defining clear index extraction rules, each data point in the cost document is mapped to corresponding structured fields. For example, information such as the main transformer capacity of the substation project and the conductor specifications of the overhead line can be stored in corresponding database tables or data structures, facilitating subsequent feature extraction and analysis.

[0020] The specific implementation process of step 2 is as follows: S1. Feature extraction: Extract key features from the cleaned data and divide the data into new substation construction, substation expansion, overhead line, and cable projects. S2. Normalization: Normalize the extracted features to eliminate dimensional differences and ensure data comparability.

[0021] The characteristics of the substation project are stage, voltage level, distribution device, number of units in this phase, and main transformer capacity in this phase; Overhead line project characteristics include stage, voltage level, number of circuits, and conductor specifications and models; Cable line engineering is divided into stages, voltage levels, number of loops and cable cross-sections.

[0022] Feature Extraction: Key features are extracted from the cleaned data, and the data is divided and processed according to new substation construction, substation expansion, overhead line, and cable projects. Different project types have different cost-influencing factors, so their respective features need to be extracted. Substation project features include stage, voltage level, distribution device, number of units in this phase, and main transformer capacity in this phase; overhead line project features include stage, voltage level, number of circuits, and conductor specifications; and cable line project features include stage, voltage level, number of circuits, and cable cross-section. These features effectively characterize the cost characteristics of each project and serve as a crucial basis for subsequent cost control line calculations.

[0023] Normalization: Extracted features are normalized to eliminate dimensional differences and ensure data comparability. Because the dimensions and value ranges of different features can vary significantly—for example, voltage levels are measured in kilovolts, while transformer capacity is measured in megavolt-amperes—direct analysis can lead to bias. Normalization maps these feature data to the same scale, giving each feature equal importance in subsequent algorithm applications, thereby improving the accuracy and reliability of the analysis.

[0024] The specific implementation process of step three is as follows: S1. Data distribution analysis: Use the normal distribution algorithm to analyze the distribution pattern of cost data and calculate the mean (μ) and standard deviation (σ); S2. Control line generation: According to the characteristics of normal distribution, set the upper and lower limits of the cost control line.

[0025] The upper and lower limits of the cost control line are set as follows: Lower limit: μ-3σ Upper limit: μ+3σ Data Distribution Analysis: Analyze the distribution patterns of construction cost data using the normal distribution algorithm, calculating the mean (μ) and standard deviation (σ). Normal distribution is a common continuous probability distribution that is observed in many natural and social phenomena. By performing normal distribution analysis on construction cost data, we can gain a deeper understanding of the data's central tendency and dispersion. The mean reflects the average level of the data, while the standard deviation measures the fluctuation range and dispersion of the data, providing key parameters for subsequently setting cost control lines.

[0026] Control Line Generation: The upper and lower limits of the cost control line are set based on the characteristics of a normal distribution. In a normal distribution, data is symmetrically distributed around the mean, with the majority of data concentrated near the mean. Based on this characteristic, the upper and lower limits of the cost control line are set as follows: lower limit: μ - 3σ, upper limit: μ + 3σ. This setting, based on statistical principles, considers cost data outside this range as abnormal, thereby achieving effective cost control and ensuring that project costs fluctuate within a reasonable range.

[0027] The specific implementation process of step 4 is as follows: S1. Comparative analysis: Compare the generated control line with the actual cost data to verify its rationality; S2. Dynamic adjustment: Dynamically adjust the control line parameters based on the verification results to ensure their adaptability.

[0028] Comparative Analysis: Compare the generated control line with actual cost data to verify its rationality. By comparing actual project cost data with the set control line, you can intuitively identify which projects' costs exceed the control line range and analyze the reasons. This step helps evaluate whether the generated control line accurately reflects the actual project cost and is sufficiently reasonable and applicable. If a large number of projects are found to exceed the control line, the control line parameters may need to be adjusted.

[0029] Dynamic Adjustment: Based on verification results, control line parameters are dynamically adjusted to ensure adaptability. Because the cost of power transmission projects is influenced by a variety of factors, such as market price fluctuations, technological advancements, and policy changes, control lines require dynamic adjustment capabilities. Based on comparative analysis results and actual conditions, appropriate adjustments are made to control line parameters such as the mean and standard deviation to adapt to the ever-changing project cost environment and maintain effective control over project costs.

[0030] The specific implementation process of step one is as follows: S1. The result of obtaining the cost control line; S2. Publish the control line results.

[0031] Obtaining the cost control line: After completing the above steps, the final result of the transmission and transformation project cost control line is obtained. This result is presented in the form of clear upper and lower limits, providing a specific quantitative standard for project cost management and control.

[0032] Publishing control line results: The generated cost control line results are published so that they can be widely used during the construction of power transmission and transformation projects. This can be done by notifying relevant parties, such as project management departments, construction companies, and design companies, and incorporating them into project cost management systems and processes. This serves as an important basis for project budget preparation, bid price setting, and cost review, thereby achieving refined control and management of power transmission and transformation project costs.

[0033] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A method for calculating and generating a cost control line for a power transmission and transformation project, characterized by: The implementation steps include the following: Step 1: Data collection and preprocessing; Step 2: Feature extraction and normalization; Step 3: Application of normal distribution algorithm; Step 4: Application of normal distribution algorithm; Step 5: Generate results.

2. The method for calculating and generating a cost control line for a power transmission and transformation project according to claim 1, characterized in that: The specific implementation process of step one is as follows: S1. Data Acquisition: Collect historical cost data for Guangzhou Bureau's power transmission and transformation projects through circulation and manual entry during the review process; S2. Data cleaning: Remove duplicate, missing, or abnormal data content to ensure data integrity and consistency; S3. Structured processing: Convert the cost documents submitted for review into structured data content based on indicator extraction rules.

3. The method for calculating and generating a cost control line for a power transmission and transformation project according to claim 1, characterized in that: The specific implementation process of step 2 is as follows: S1. Feature extraction: Extract key features from the cleaned data and divide the data into new substation construction, substation expansion, overhead line, and cable projects. S2. Normalization: Normalize the extracted features to eliminate dimensional differences and ensure data comparability.

4. The method for calculating and generating a cost control line for a power transmission and transformation project according to claim 1, characterized in that: The specific implementation process of step three is as follows: S1. Data distribution analysis: Use the normal distribution algorithm to analyze the distribution pattern of cost data and calculate the mean (μ) and standard deviation (σ); S2. Control line generation: According to the characteristics of normal distribution, set the upper and lower limits of the cost control line.

5. The method for calculating and generating a cost control line for a power transmission and transformation project according to claim 1, characterized in that: The specific implementation process of step 4 is as follows: S1. Comparative analysis: Compare the generated control line with the actual cost data to verify its rationality; S2. Dynamic adjustment: Dynamically adjust the control line parameters based on the verification results to ensure their adaptability.

6. The method for calculating and generating a cost control line for a power transmission and transformation project according to claim 1, characterized in that: The specific implementation process of step one is as follows: S1. The result of obtaining the cost control line; S2. Publish the control line results.

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