CN110717725B - Power grid project selection method based on big data analysis - Google Patents
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Abstract
The application provides a power grid project selection method based on big data analysis, which comprises the steps of acquiring metering data of all power grid equipment in a region at regular time based on a wireless meter reading technology; grouping the acquired metering data based on different types of power grid equipment, and transmitting the grouped metering data to a power grid business unified data center; determining metering data corresponding to the type of the auxiliary power grid equipment; and acquiring metering data consistent with the metering data type from the power grid business unified data center, and completing the selection of the type of the auxiliary power grid equipment according to the difference value of the metering data and the metering data. The screening of the power grid projects is simplified into the screening of the auxiliary power grid equipment, the metering data of the uniformly collected power grid equipment are arranged, the corresponding power grid equipment types are extracted according to different project plans, the auxiliary power grid equipment is further screened, the screening of the power grid projects is finally completed based on screening results, the objectivity of the power grid project selection can be improved, and the influence of human subjective factors is reduced.
Description
Technical Field
The application belongs to the field of project management, and particularly relates to a power grid project selection method based on big data analysis.
Background
With new power system reform and national enterprise reform new requirements, the investment direction, the investment efficiency benefit, the investment management program and the like of the company power grid face higher requirements, and the work such as investment structure optimization, investment benefit evaluation and the like is required, so that the development quality and the investment benefit of the power grid are continuously improved.
In the process of selecting the power grid project, the selection mode is often based on the scale of the project, the number of equipment and other parameters on the surface, the selection mode inevitably has personal subjective tendency, and the power grid equipment cannot be selected completely and objectively.
Disclosure of Invention
In order to solve the defects and shortcomings in the prior art, the application provides the power grid project selection method based on big data analysis, the metering data of the uniformly collected power grid equipment are arranged, the corresponding power grid equipment types are extracted according to different project plans, the auxiliary power grid equipment is further screened, and finally, the screening of the power grid projects is completed based on the screening result, so that the objectivity of the power grid project selection can be improved, and the influence of human subjective factors is reduced.
Specifically, the method for selecting the power grid equipment provided by the embodiment of the application comprises the following steps:
acquiring metering data of all power grid equipment in the area at regular time based on a wireless meter reading technology;
grouping the acquired metering data based on different types of power grid equipment, and transmitting the grouped metering data to a power grid business unified data center;
extracting the type of the auxiliary power grid equipment from the project plan to be built, and determining metering data corresponding to the type of the auxiliary power grid equipment;
and acquiring metering data consistent with the metering data type from the power grid business unified data center, and completing the selection of the type of the auxiliary power grid equipment according to the difference value of the metering data and the metering data.
Optionally, the grouping the acquired metering data based on different types of power grid equipment, and sending the grouped metering data to a power grid service unified data center includes:
determining the data types corresponding to different types of power grid equipment;
grouping metering data belonging to the same data type power grid equipment, and removing abnormal metering data after grouping;
and sending the processed metering data to a power grid business unified data center for storage.
Optionally, the extracting the auxiliary power grid equipment type from the project plan to be built, and determining the metering data corresponding to the auxiliary power grid equipment type, includes:
setting the number of substations to be built and the planning capacity in the area in the project planning to be built;
determining the type of the auxiliary power grid equipment according to the number of the substations and the planning capacity;
and determining metering data corresponding to the auxiliary power grid equipment type based on the obtained auxiliary power grid equipment type.
Optionally, the step of setting the number of substations to be built and the planned capacity in the area in the project planning to be built includes:
acquiring a construction target in project planning to be constructed;
and decomposing the construction targets based on the standard capacity corresponding to the type of the existing auxiliary power grid equipment, and determining the optimal auxiliary power grid equipment configuration quantity and the quantity of substations to be constructed.
Optionally, the acquiring metering data consistent with the metering data type from the grid business unified data center, and completing the selection of the auxiliary grid equipment type according to the difference value of the metering data and the metering data, includes:
acquiring a target attribute field of the metering data type;
acquiring metering data consistent with a target attribute field from a power grid business unified data center;
and calculating the difference value of each item of metering data and metering data, and selecting the accessory power grid equipment type corresponding to the metering data with the minimum difference value as a final result.
Optionally, the method for selecting power grid equipment is further characterized by comprising:
and in terms of project construction necessity, project construction benefit and the like, the indexes are quantized and scored successively, the scores in the projects are calculated, and high-quality power grid equipment is selected in a comprehensive evaluation mode.
Optionally, the quantitatively scoring the indexes sequentially from the aspect of the project construction necessity and the project construction benefit, calculating the scores in the project, and selecting high-quality power grid equipment in a comprehensive evaluation mode includes:
the index score is determined according to a first formula,
wherein Γ is an index score, α is an index average, β is an index enhancement value, x 1 To add the start threshold, x 2 A score termination threshold;
determining a project score according to a second formula,
wherein a is k Scoring the item; a, a n For each index score, the value range of k and n is a positive integer.
Optionally, the only retaining the grid project corresponding to the auxiliary grid device in the normal working state but the metering data exceeds the preset parameter includes:
extracting metering data corresponding to auxiliary power grid equipment in a normal working state from the acquired metering data;
comparing the extracted metering data with preset parameters to determine auxiliary power grid equipment with the metering data exceeding the preset parameters;
based on the known corresponding relation between the auxiliary power grid metering equipment and the power grid projects, eliminating the power grid projects corresponding to the auxiliary power grid equipment with metering data not exceeding the preset parameters from all current power grid projects, and only reserving the power grid projects corresponding to the auxiliary power grid equipment with metering data exceeding the preset parameters.
The technical scheme provided by the application has the beneficial effects that:
the metering data of the uniformly collected power grid equipment are arranged, the corresponding power grid equipment types are extracted according to different project plans, the auxiliary power grid equipment is further screened, and finally screening of power grid projects is completed based on screening results, so that objectivity of power grid project selection can be improved, and influence of human subjective factors is reduced.
Drawings
In order to more clearly illustrate the technical solutions of the present application, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flow chart of a method for selecting a power grid project based on big data analysis according to the present application.
Detailed Description
In order to make the structure and advantages of the present application more apparent, the structure of the present application will be further described with reference to the accompanying drawings.
Example 1
The application provides a power grid project selection method based on big data analysis, as shown in fig. 1, the power grid equipment selection method comprises the following steps:
11. acquiring metering data of all power grid equipment in the area at regular time based on a wireless meter reading technology;
12. grouping the acquired metering data based on different types of power grid equipment, and transmitting the grouped metering data to a power grid business unified data center;
13. extracting the type of the auxiliary power grid equipment from the project plan to be built, and determining metering data corresponding to the type of the auxiliary power grid equipment;
14. acquiring metering data consistent with the metering data type from a power grid business unified data center, and completing the selection of the type of the auxiliary power grid equipment according to the difference value of the metering data and the metering data;
15. carrying out state parameter verification on the selected auxiliary power grid equipment to determine the auxiliary power grid equipment in a normal working state;
16. and only the power grid projects corresponding to the auxiliary power grid equipment which is in a normal working state and the metering data exceeds the preset parameters are reserved.
In the implementation, in order to accurately complete the selection of the power grid equipment, the metering data of all the power grid equipment in the area needs to be summarized uniformly. And after the summarization is completed, grouping the metering data based on the type of the power grid equipment. And extracting the type of the auxiliary power grid equipment from the project plan to be built, so as to perform corresponding processing on the metering data of the data packet completed in the previous step, and selecting proper auxiliary power grid equipment according to the corresponding data.
The purpose of the auxiliary power grid equipment selection is to select a power grid project meeting the requirements finally, and the corresponding relation exists between the power grid project and the auxiliary power grid equipment, so that the auxiliary power grid equipment is determined to be equivalent to the power grid project, and the specific discussion process for determining the power grid project based on the auxiliary power grid equipment is given hereinafter and is not repeated here.
The specific processing manner proposed in step 12 includes:
121. determining the data types corresponding to different types of power grid equipment;
122. grouping metering data belonging to the same data type power grid equipment, and removing abnormal metering data after grouping;
123. and sending the processed metering data to a power grid business unified data center for storage.
In implementation, the power grid equipment mainly comprises two major types of power generation equipment and power supply equipment, wherein the power generation equipment mainly comprises a power station boiler, a steam turbine, a gas turbine, a water turbine, a generator, a transformer and the like, and the power supply equipment mainly comprises power transmission lines, transformers, contactors and the like with various voltage levels.
Based on the all-service unified data center, key indexes such as regional sales power, regional load, equipment load rate, equipment age, insulation rate, cabling rate and voltage qualification rate of a power grid are accessed and analyzed, abnormal end data are treated according to objective facts, a data analysis model is formulated, the rationality of index data is analyzed from the aspects of index current situation, index speed increase and the like, and data guarantee is provided for project optimization.
In order to make the process of finally selecting the type of the power grid equipment as accurate as possible, the grouped data also needs to be processed by exception proposal. The criterion for determining abnormality is the working experience of the first line worker.
The step of determining the measurement data set forth in the step 13 includes:
131. setting the number of substations to be built and the planning capacity in the area in the project planning to be built;
132. determining the type of the auxiliary power grid equipment according to the number of the substations and the planning capacity;
133. and determining metering data corresponding to the auxiliary power grid equipment type based on the obtained auxiliary power grid equipment type.
The project plan to be built for a region contains information of various aspects, the power grid equipment information is also contained, the number of substations to be built and the planned capacity in the region can be determined through extraction of the project plan to be built, and further the specific number and the electricity consumption capacity of auxiliary power grid equipment such as power plants, substations, power transmission towers, power transformation rooms and the like which need to be built in the region can be determined according to the number and the planned capacity, so that metering data such as electricity consumption and power transmission line length and the like can be determined according to the obtained number of the auxiliary power grid equipment.
Macroscopically analyzing a construction target of a power grid project, mapping the construction target to a power grid index according to a strong coupling relation between the construction target and the power grid index, and supporting the condition that a single target corresponds to multiple indexes; according to the importance and relevance of each index, setting the weight influence factor of each index to be 1-5 minutes, setting the index basic score according to the current situation and weak point of each regional power grid, performing superposition calculation on the basic score and the influence factor, and determining each index weight, thereby constructing an item optimal evaluation index system integrating the construction target, the power grid index and the index weight.
The step 131 specifically includes:
1311. acquiring a construction target in project planning to be constructed;
1312. and decomposing the construction targets based on the standard capacity corresponding to the type of the existing auxiliary power grid equipment, and determining the optimal auxiliary power grid equipment configuration quantity and the quantity of substations to be constructed.
And (3) microscopically analyzing indexes such as equipment years, equipment loads and the like of each power grid project construction equipment and influence equipment, and combining with the current situation analysis library results, opening up a data link from the power grid project to the power grid equipment and then to the operation indexes to form a strong mapping association relation, so that detailed operation data of specific equipment and equipment corresponding to the project can be traced in real time by taking the project as a view angle.
The step of completing the selection of the auxiliary power grid equipment type set forth in the step 14 includes:
141. acquiring a target attribute field of the metering data type;
142. acquiring metering data consistent with a target attribute field from a power grid business unified data center;
143. and calculating the difference value of each item of metering data and metering data, and selecting the accessory power grid equipment type corresponding to the metering data with the minimum difference value as a final result.
The specific selection is based on selecting the same type of target attribute field from the metering data.
The target attribute fields that need to be referenced for a substation include, for example, no-load reactive losses, no-load losses, rated load losses, transformer rated capacity, transformer no-load current percentage, short circuit voltage percentage, average load factor, load fluctuation loss factor, etc.
After the acquisition of the same target attribute field is completed, calculating the difference value of each item of metering data and metering data, and if the difference value is small, taking the selected auxiliary power grid equipment as a final result; if the difference is too large, the auxiliary power grid equipment selection needs to be carried out again.
The foregoing steps have completed the selection of the auxiliary power grid equipment, and in order to complete the confirmation of the final power grid project, the auxiliary power grid equipment selected in step 14 needs to be subjected to the verification of the state parameters as shown in step 15. The verification aims at verifying and analyzing the state parameters of the auxiliary power grid equipment during working to determine whether the equipment in a poor working state exists or not, and a power grid project containing the auxiliary power grid equipment is easy to be out of line fault in the later period and cannot be used as a final reserved project.
After the auxiliary grid device is obtained in the normal operation state, the step of determining the final grid project, that is, step 16, includes:
161. and extracting metering data corresponding to the auxiliary power grid equipment in a normal working state from the acquired metering data. The purpose of the acquisition of the corresponding metering data of the auxiliary network device is to prepare the secondary selection of the auxiliary network device for the next step.
162. And comparing the extracted metering data with preset parameters to determine auxiliary power grid equipment with the metering data exceeding the preset parameters. The preset parameters are used as threshold values for screening auxiliary power grid equipment, and the purpose is to select auxiliary power grid equipment in an optimal working state, so that the auxiliary power grid equipment in the optimal working state can also exert optimal production efficiency to a certain extent, and the finally obtained power grid project can be ensured to be the optimal power grid project.
163. Based on the known corresponding relation between the auxiliary power grid metering equipment and the power grid projects, eliminating the power grid projects corresponding to the auxiliary power grid equipment with metering data not exceeding the preset parameters from all current power grid projects, and only reserving the power grid projects corresponding to the auxiliary power grid equipment with metering data exceeding the preset parameters.
The power grid project comprises a plurality of auxiliary power grid devices, wherein a one-to-one correspondence exists between the auxiliary power grid devices, after the auxiliary power grid devices in the optimal working state are selected based on the step 162, the power grid projects which do not meet the preset parameter comparison process are removed from all the power grid projects according to the existing correspondence, and therefore screening of the power grid projects is completed based on the characteristic of the auxiliary power grid devices.
Example two
Aiming at the power grid project selection method, the embodiment of the application also provides another power grid equipment selection method regarding the auxiliary power grid equipment selection mode, and the method further comprises the following steps:
and in terms of project construction necessity, project construction benefit and the like, the indexes are quantized and scored successively, the scores in the projects are calculated, and high-quality power grid equipment is selected in a comprehensive evaluation mode.
Specifically referring to a calculation mode of a formula I and a formula II, determining a plurality of index types and scores under each index, and judging whether the selected auxiliary power grid equipment has high-quality power grid equipment or not based on the scores, wherein the method specifically comprises the following steps of:
the index score is determined according to a first formula,
wherein Γ is an index score, α is an index average, β is an index enhancement value, x 1 To add the start threshold, x 2 A score termination threshold;
determining a project score according to a second formula,
wherein a is k Scoring the item; a, a n For each index score, the value range of k and n is a positive integer.
The various numbers in the above embodiments are for illustration only and do not represent the order of assembly or use of the various components.
The foregoing is illustrative of the present application and is not to be construed as limiting thereof, but rather, the present application is to be construed as limited to the appended claims.
Claims (4)
1. The power grid project selection method based on big data analysis is characterized by comprising the following steps of:
acquiring metering data of all power grid equipment in the area at regular time based on a wireless meter reading technology;
grouping the acquired metering data based on different types of power grid equipment, and transmitting the grouped metering data to a power grid business unified data center;
extracting the type of the auxiliary power grid equipment from the project plan to be built, and determining metering data corresponding to the type of the auxiliary power grid equipment; the method comprises the steps of obtaining metering data consistent with the metering data type from a power grid business unified data center, and completing the selection of the auxiliary power grid equipment type according to the difference value of the metering data and the metering data, wherein the obtaining of the metering data consistent with the metering data type from the power grid business unified data center comprises the following steps:
acquiring a target attribute field of the metering data type;
acquiring metering data consistent with a target attribute field from a power grid business unified data center;
calculating the difference value of each item of metering data and metering data, and selecting the accessory power grid equipment type corresponding to the metering data with the minimum difference value as a final result;
carrying out state parameter verification on the selected auxiliary power grid equipment to determine the auxiliary power grid equipment in a normal working state;
only the power grid project corresponding to the auxiliary power grid equipment which is in a normal working state but the metering data exceeds the preset parameters is reserved, and the method comprises the following steps:
extracting metering data corresponding to auxiliary power grid equipment in a normal working state from the acquired metering data, comparing the extracted metering data with preset parameters, determining auxiliary power grid equipment with metering data exceeding the preset parameters, removing power grid items corresponding to the auxiliary power grid equipment with metering data not exceeding the preset parameters from all current power grid items based on the corresponding relation between the known auxiliary power grid metering equipment and the power grid items, and only reserving the power grid items corresponding to the auxiliary power grid equipment with metering data exceeding the preset parameters;
the power grid equipment selecting method further comprises the following steps:
from aspects of project construction necessity, project construction benefit and the like, the indexes are quantized and scored successively, scores in the projects are calculated, and high-quality power grid equipment is selected in a comprehensive evaluation mode;
the method comprises the steps of quantitatively scoring indexes in sequence from the aspects of project construction necessity and project construction benefit, calculating scores in projects, and selecting high-quality power grid equipment in a comprehensive evaluation mode, wherein the method comprises the following steps:
the index score is determined according to a first formula,
wherein Γ is an index score, α is an index average, β is an index enhancement value, x 1 To add the start threshold, x 2 A score termination threshold;
determining a project score according to a second formula,
wherein a is k Scoring the item; a, a n For each index score, the value range of k and n is a positive integer.
2. The method for selecting a grid project based on big data analysis according to claim 1, wherein the grouping the acquired metering data based on different types of grid equipment, and transmitting the grouped metering data to a grid business unified data center, comprises:
determining the data types corresponding to different types of power grid equipment;
grouping metering data belonging to the same data type power grid equipment, and removing abnormal metering data after grouping;
and sending the processed metering data to a power grid business unified data center for storage.
3. The method for selecting a grid project based on big data analysis according to claim 1, wherein the extracting the type of the auxiliary grid equipment from the project plan to be built, determining the metering data corresponding to the type of the auxiliary grid equipment, comprises:
setting the number of substations to be built and the planning capacity in the area in the project planning to be built;
determining the type of the auxiliary power grid equipment according to the number of the substations and the planning capacity;
and determining metering data corresponding to the auxiliary power grid equipment type based on the obtained auxiliary power grid equipment type.
4. The method for selecting a power grid project based on big data analysis according to claim 3, wherein the step of setting the number of substations to be built and the planned capacity in the area in the project plan to be built comprises:
acquiring a construction target in project planning to be constructed;
and decomposing the construction targets based on the standard capacity corresponding to the type of the existing auxiliary power grid equipment, and determining the optimal auxiliary power grid equipment configuration quantity and the quantity of substations to be constructed.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105205573A (en) * | 2015-10-27 | 2015-12-30 | 国网福建省电力有限公司 | Planned project selecting and sequencing method comprehensively taking basic power supply responsibility of power network enterprise into consideration for low and medium voltage distribution network |
| CN107256441A (en) * | 2017-06-02 | 2017-10-17 | 广东电网有限责任公司电网规划研究中心 | Distribution network planning tentative plan of construction program method based on non-dominated sorted genetic algorithm |
| TWI642022B (en) * | 2017-11-24 | 2018-11-21 | 財團法人工業技術研究院 | Device and method for selecting building products |
| CN109325296A (en) * | 2018-09-26 | 2019-02-12 | 国网电子商务有限公司 | Photovoltaic plant establishes recommended method, device and the electronic equipment of scheme |
| CN109558897A (en) * | 2018-11-08 | 2019-04-02 | 华北电力大学 | A kind of more situation extracting methods of Electric Power Network Planning based on data mining |
| CN109657959A (en) * | 2018-12-12 | 2019-04-19 | 国家电网有限公司 | A kind of distribution network planning calculation and analysis methods containing multivariate data |
-
2019
- 2019-08-30 CN CN201910816376.2A patent/CN110717725B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105205573A (en) * | 2015-10-27 | 2015-12-30 | 国网福建省电力有限公司 | Planned project selecting and sequencing method comprehensively taking basic power supply responsibility of power network enterprise into consideration for low and medium voltage distribution network |
| CN107256441A (en) * | 2017-06-02 | 2017-10-17 | 广东电网有限责任公司电网规划研究中心 | Distribution network planning tentative plan of construction program method based on non-dominated sorted genetic algorithm |
| TWI642022B (en) * | 2017-11-24 | 2018-11-21 | 財團法人工業技術研究院 | Device and method for selecting building products |
| CN109325296A (en) * | 2018-09-26 | 2019-02-12 | 国网电子商务有限公司 | Photovoltaic plant establishes recommended method, device and the electronic equipment of scheme |
| CN109558897A (en) * | 2018-11-08 | 2019-04-02 | 华北电力大学 | A kind of more situation extracting methods of Electric Power Network Planning based on data mining |
| CN109657959A (en) * | 2018-12-12 | 2019-04-19 | 国家电网有限公司 | A kind of distribution network planning calculation and analysis methods containing multivariate data |
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