CN112232625A - Power transmission and transformation project cost evaluation method based on space-time big data - Google Patents
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Abstract
The invention provides a power transmission and transformation project cost evaluation method based on space-time big data, which comprises the following steps: the data collection module is connected with the data classification storage module, the data classification storage module is connected with the data verification module, the data verification module is connected with the auditing evaluation module, and the auditing evaluation module simulates the representative attribute of a project through the clustering analysis of samples and the combing of the cost influence factors to determine the classification principle of the samples, namely determining the influence factors according to the voltage grade and the single-double circuit line; constructing a multiple regression model according to the determined sample classification principle, and distinguishing the influence of a single factor, namely an independent variable, from the total construction cost, namely a dependent variable, of the project; the invention considers the independence among all factors, namely all factors do not influence each other, and can be applied to planning scheme investment frame calculation, pre-researched investment estimation and technical scheme selection.
Description
Technical Field
The invention relates to the technical field of engineering cost analysis, in particular to a power transmission and transformation engineering cost evaluation method based on space-time big data.
Background
The construction and the transformation of the power grid in China have gained brilliant achievements, but with the increase of investment scale, the influence of the engineering price level on the development of the power grid becomes more obvious, and the construction cost of the power grid is also concerned. The investment of each power grid enterprise is continuously increased for power grid construction, enterprise operation and sustainable development face greater challenges, the theoretical research and application practice work of a power transmission and transformation project cost basic data centralized management, resource sharing and cost statistical analysis system is well done, and great promotion effects are achieved for revealing cost level change rules, making cost control of power grid project construction projects, reasonably utilizing limited construction funds and the like.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a power transmission and transformation project cost evaluation method based on space-time big data so as to solve the problems in the background technology.
The technical problem solved by the invention is realized by adopting the following technical scheme: the power transmission and transformation project cost evaluation method based on the space-time big data comprises the following steps: the data collection module is connected with the data classification storage module, the data classification storage module is connected with the data verification module, the data verification module is connected with the auditing evaluation module, and the auditing evaluation module simulates the representative attribute of a project through the cluster analysis of samples and the combing of the cost influence factors to determine the classification principle of the samples, namely determining the influence factors according to the voltage grade and single and double circuit lines; constructing a multiple regression model according to the determined sample classification principle, and distinguishing the influence of a single factor, namely an independent variable, from the total construction cost, namely a dependent variable, of the project; introducing virtual variables into the multiple regression model to form a virtual variable leading multiple regression model, and quantifying qualitative variables to simultaneously analyze the influence of the qualitative variables and the quantitative factors on the construction cost in the multiple regression model for the same construction cost sensitivity analysis; the data classification storage module comprises a server online initialization module, a server state maintenance module, a server type selection module, a synchronous request generation module, a synchronous request sending module, a serialization scheduling module, a decision regulation module, a synchronous update receiving module, a synchronous update retransmission module and a synchronous update execution module.
The data collection module is mainly used for realizing automatic auxiliary report of the cost analysis basic data of the power transmission and transformation project, and realizing the collection of the cost analysis basic data of the national grid company and the energy bureau total project in the system according to the requirements of the cost analysis of the power transmission and transformation project of the Guilin power grid responsion national grid company and the cost analysis work of the energy bureau on the cost analysis of the power transmission and transformation project and the 35kV rural grid project; the collected data comprises engineering basic information, main technical and economic indexes, approximate calculation indexes and settlement indexes; extracting cost analysis basic data from the engineering files by establishing a power transmission and transformation engineering cost analysis basic data and engineering file data extraction rule, and completing the collection work of the cost analysis basic data by manual reporting and importing; the raw data collected by the cost analysis data collection module is directly stored in a database and is also transmitted to a data verification module for data verification.
The data checking module is used for automatically checking the correctness and the logic rule of the basic data of the cost analysis for the related data transmitted by the cost analysis data collecting module; if the problem occurs, prompting a user to adjust, and finally automatically summarizing cost analysis basic data reported by all local companies; the module formulates project screening conditions according to indexes commonly used by different project types, lists corresponding projects according to the screening conditions, and can look up index data corresponding to the projects;
the server online initialization module is responsible for determining the type of a new online server through the server type selection module when the server is newly online, and then sending online messages to other servers in the network, wherein the online messages comprise the IP address, the highest version number and the server type of the server; the server information is added to the server state table.
And the server state maintenance module is responsible for receiving online messages of other servers in the network, modifying the server state table and broadcasting the IP address, the highest version number and the server type of the server in the network at regular intervals.
The synchronous request generating module generates a data synchronous operation sequence when the server has a data synchronous request; the synchronous request sending module is responsible for sending the data synchronous operation sequence of the server to other online servers in the network; and the serialization scheduling module is responsible for receiving data synchronization operation sequences of all servers in the network and serializing the operation sequences to form a serialization operation sequence, wherein each operation in the sequence corresponds to a version number.
If the server is a decision server, when a new on-line server exists and the highest version number of the server is inconsistent with that of the decision server, a serialization operation sequence enabling the highest version number of the server to be consistent with that of the decision server is sent to the server; and when a data synchronization request exists in the network, sending the serialization operation sequence after the highest version number of the decision server to other servers in the network.
Compared with the prior art, the invention has the beneficial effects that: the invention considers the independence among all factors, namely all factors are not mutually influenced, all virtual variables and quantitative variables are independent and have no interaction influence, so that the virtual variables and the quantitative variables are combined by adopting a simple addition form and the method can be applied to investment calculation of a planning scheme, pre-researched investment estimation and technical scheme selection.
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FIG. 1 is a schematic diagram of the method of the present invention.
Detailed Description
In the description of the present invention, it should be noted that unless otherwise specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning fixedly connected, detachably connected, or integrally connected, mechanically or electrically connected; the two elements can be directly connected or indirectly connected through an intermediate medium, and the two elements can be communicated with each other.
Example 1
As shown in fig. 1, the method for estimating the construction cost of power transmission and transformation project based on space-time big data includes: the data collection module is connected with the data classification storage module, the data classification storage module is connected with the data verification module, the data verification module is connected with the auditing and evaluation module, and the auditing and evaluation module simulates the representative attribute of a project through the cluster analysis of samples and the combing of the cost influence factors to determine the classification principle of the samples, namely determining the influence factors according to the voltage grade and the single-double circuit line; constructing a multiple regression model according to the determined sample classification principle, and distinguishing the influence of a single factor, namely an independent variable, from the total construction cost, namely a dependent variable, of the project; virtual variables are introduced into the multiple regression model to form a virtual variable leading multiple regression model, qualitative variables are quantified, and the influence of the qualitative variables and the quantitative factors on the engineering cost is simultaneously analyzed in the multiple regression model for the same engineering cost sensitivity analysis. The data collection module is mainly used for realizing automatic auxiliary report of the construction cost analysis basic data of the power transmission and transformation project, and realizing the collection of the construction cost analysis basic data of the national grid company and the energy source bureau in the system according to the requirements of the construction cost analysis of the power transmission and transformation project of the national grid company and the energy source bureau for responding to the construction cost analysis work of the national grid company and the energy source bureau for the construction cost analysis of the power transmission and transformation project and the construction cost analysis of the 35kV rural power grid project; the collected data comprises engineering basic information, main technical and economic indexes, a summary index and a settlement index; extracting cost analysis basic data from the engineering files by establishing a power transmission and transformation engineering cost analysis basic data and engineering file data extraction rule, and completing the collection work of the cost analysis basic data by manual reporting and importing; the raw data collected by the cost analysis data collection module is directly stored in the database and is also transmitted to the data verification module for data verification. The data checking module is used for automatically checking the correctness and the logic rule of the cost analysis basic data for the related data transmitted by the cost analysis data collecting module; if the problem occurs, prompting a user to adjust, and finally automatically summarizing cost analysis basic data reported by all local companies; the module formulates project screening conditions according to indexes commonly used by different project types, lists corresponding projects according to the screening conditions, and can look up index data corresponding to the projects; the data classification storage module comprises a server online initialization module, a server state maintenance module, a server type selection module, a synchronous request generation module, a synchronous request sending module, a serialization scheduling module, a decision regulation module, a synchronous update receiving module, a synchronous update retransmission module and a synchronous update execution module
Example 2
As shown in fig. 1, the method for estimating the construction cost of power transmission and transformation project based on space-time big data includes: the data collection module is connected with the data classification storage module, the data classification storage module is connected with the data verification module, the data verification module is connected with the auditing and evaluation module, and the auditing and evaluation module simulates the representative attribute of a project through the cluster analysis of samples and the combing of the cost influence factors to determine the classification principle of the samples, namely determining the influence factors according to the voltage grade and the single-double circuit line; constructing a multiple regression model according to the determined sample classification principle, and distinguishing the influence of a single factor, namely an independent variable, from the total construction cost, namely a dependent variable, of the project; virtual variables are introduced into the multiple regression model to form a virtual variable leading multiple regression model, qualitative variables are quantified, and the influence of the qualitative variables and the quantitative factors on the engineering cost is simultaneously analyzed in the multiple regression model for the same engineering cost sensitivity analysis. (ii) a The data classification storage module comprises a server online initialization module, a server state maintenance module, a server type selection module, a synchronous request generation module, a synchronous request sending module, a serialization scheduling module, a decision-making scheduling module, a synchronous update receiving module, a synchronous update retransmission module and a synchronous update execution module; the server online initialization module is responsible for determining the type of a new online server through the server type selection module when the server is newly online, and then sending online information to other servers in the network, wherein the online information comprises the IP address, the highest version number and the server type of the server; and adding the server information in the server state table. And the server state maintenance module is responsible for receiving online messages of other servers in the network, modifying the server state table and broadcasting the IP address, the highest version number and the server type of the server in the network at regular intervals. The synchronous request generating module generates a data synchronous operation sequence when the server has a data synchronous request; the synchronous request sending module is responsible for sending the data synchronous operation sequence of the server to other online servers in the network; and the serialization scheduling module is responsible for receiving data synchronization operation sequences of all servers in the network and serializing the operation sequences to form a serialization operation sequence, wherein each operation in the sequence corresponds to a version number. If the server is a decision server, when a new on-line server exists and the highest version number of the server is inconsistent with that of the decision server, a serialization operation sequence enabling the highest version number of the server to be consistent with that of the decision server is sent to the server; and when a data synchronization request exists in the network, sending the serialization operation sequence after the highest version number of the decision server to other servers in the network.
The invention analyzes a large amount of power transmission and transformation project cost data excessively, excavates the internal rules of cost level change, uses the cost data as a research object, seeks characteristics such as periodicity and trend of data change through time series analysis, and establishes an effective prediction model by combining methods such as a neural network prediction technology, a time series prediction technology, a regression prediction technology and the like.
The foregoing shows and describes the general principles and broad features of the present invention and advantages thereof. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (7)
1. The power transmission and transformation project cost evaluation method based on the space-time big data comprises the following steps: the data collection module, the data collection module is connected in data classification storage module, its characterized in that: the data classification storage module is connected with the data verification module, the data verification module is connected with the auditing and evaluating module, and the auditing and evaluating module simulates the representative attribute of a project through the clustering analysis of samples and the combing of the cost influence factors to determine the classification principle of the samples, namely determining the influence factors according to the voltage grade and single and double circuit lines; constructing a multiple regression model according to the determined sample classification principle, and distinguishing the influence of a single factor, namely an independent variable, from the total construction cost, namely a dependent variable, of the project; introducing virtual variables into the multiple regression model to form a virtual variable leading multiple regression model, quantifying qualitative variables, and analyzing the influence of the qualitative variables and the quantitative factors on the construction cost in the same multiple regression model for the sensitivity analysis of the construction cost; the data classification storage module comprises a server online initialization module, a server state maintenance module, a server type selection module, a synchronous request generation module, a synchronous request sending module, a serialization scheduling module, a decision regulation and control module, a synchronous update receiving module, a synchronous update retransmission module and a synchronous update execution module.
2. The power transmission and transformation project cost evaluation method based on space-time big data according to claim 1, characterized in that: the data collection module is mainly used for realizing automatic auxiliary report of the power transmission and transformation project cost analysis basic data, and realizing the collection of the national grid company and the energy bureau total project cost analysis basic data in the system according to the requirements of the power transmission and transformation project cost analysis of the Guilin power grid response national grid company and the energy bureau cost analysis work on the power transmission and transformation project and the 35kV rural power grid project cost analysis; the collected data comprises engineering basic information, main technical and economic indexes, approximate calculation indexes and settlement indexes; extracting cost analysis basic data from the engineering files by establishing a power transmission and transformation engineering cost analysis basic data and engineering file data extraction rule, and completing the collection work of the cost analysis basic data by manual reporting and importing; the raw data collected by the cost analysis data collection module is directly stored in a database and is also transmitted to a data verification module for data verification.
3. The power transmission and transformation project cost evaluation method based on space-time big data according to claim 1, characterized in that: the data checking module is used for automatically checking the correctness and the logic rule of the cost analysis basic data for the related data transmitted by the cost analysis data collecting module; if the problem occurs, prompting a user to adjust, and finally automatically summarizing cost analysis basic data reported by all local companies; the module formulates project screening conditions according to indexes commonly used by different project types, lists corresponding projects according to the screening conditions, and can look up index data corresponding to the projects.
4. The power transmission and transformation project cost evaluation method based on space-time big data according to any one of claims 1 to 3, characterized in that: the server online initialization module is responsible for determining the type of a new online server through the server type selection module when the server is newly online, and then sending online information to other servers in the network, wherein the online information comprises the IP address, the highest version number and the server type of the server; the server information is added to the server state table.
5. The power transmission and transformation project cost evaluation method based on space-time big data according to claim 4, characterized in that: and the server state maintenance module is responsible for receiving online messages of other servers in the network, modifying the server state table and broadcasting the IP address, the highest version number and the server type of the server in the network at regular intervals.
6. The power transmission and transformation project cost evaluation method based on space-time big data according to claim 5, characterized in that: the synchronous request generating module generates a data synchronous operation sequence when the server has a data synchronous request; the synchronous request sending module is responsible for sending the data synchronous operation sequence of the server to other online servers in the network; and the serialization scheduling module is responsible for receiving data synchronization operation sequences of all servers in the network and serializing the operation sequences to form a serialization operation sequence, wherein each operation in the sequence corresponds to a version number.
7. The power transmission and transformation project cost evaluation method based on space-time big data according to claim 6, characterized in that: if the server is a decision server, when a new on-line server exists and the highest version number of the server is inconsistent with that of the decision server, a serialization operation sequence enabling the highest version number of the server to be consistent with that of the decision server is sent to the server; and when a data synchronization request exists in the network, sending the serialization operation sequence after the highest version number of the decision server to other servers in the network.
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| CN113095565A (en) * | 2021-04-07 | 2021-07-09 | 国家电网有限公司 | Transformer substation production technical improvement project engineering cost prediction model |
| CN115511462A (en) * | 2022-09-29 | 2022-12-23 | 国网宁夏电力有限公司经济技术研究院 | Overhead line engineering cost level evaluation method, medium and system |
| CN117236988A (en) * | 2023-10-11 | 2023-12-15 | 国网宁夏电力有限公司经济技术研究院 | Power transmission and transformation project cost calculation system and cost calculation method |
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Application publication date: 20210115 |