CN110717725A - 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 regularly acquiring metering data of all power grid equipment in a region based on a wireless meter reading technology; 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; determining metering data corresponding to the type of the auxiliary power grid equipment; and acquiring metering data with the same type as the metering data from the power grid service unified data center, and finishing the selection of the auxiliary power grid equipment type according to the difference value of the metering data and the metering data. The screening of the power grid project is simplified into the screening of the auxiliary power grid equipment, the uniformly collected metering data of the power grid equipment is sorted, the corresponding power grid equipment types are extracted according to different project plans, then the auxiliary power grid equipment is screened, finally the screening of the power grid project is completed based on the screening result, the objectivity of power grid project selection can be improved, and the influence of artificial subjective factors is reduced.
Description
Technical Field
The invention belongs to the field of project management, and particularly relates to a power grid project selection method based on big data analysis.
Background
With a new cycle of power system innovation and new requirements of national enterprise innovation, higher requirements are met for the investment direction, investment efficiency benefit, investment management procedures and the like of a company power grid, work such as investment structure optimization, investment benefit evaluation and the like is needed, and the development quality and the investment benefit of the power grid are continuously improved.
The selection process of the power grid project is usually based on relatively superficial parameters such as project scale, equipment quantity and the like, and the selection mode inevitably has personal subjective tendency and cannot completely and objectively select the power grid equipment.
Disclosure of Invention
In order to solve the defects and shortcomings in the prior art, the invention provides a power grid project selection method based on big data analysis.
Specifically, the method for selecting the power grid device provided by the implementation of the application includes:
acquiring metering data of all power grid equipment in the 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 sending the grouped metering data to a power grid service 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 with the same type as the metering data from the power grid service unified data center, and finishing the selection of the auxiliary power grid equipment type 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 the power grid devices, and sending the grouped metering data to the power grid service unified data center includes:
determining data types corresponding to different types of power grid equipment;
grouping the 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 service unified data center for storage.
Optionally, the extracting the type of the auxiliary power grid device from the project plan to be created, and determining the metering data corresponding to the type of the auxiliary power grid device includes:
the number of the transformer substations to be built in the region and the planning capacity are set in the project planning to be built;
determining the type of the auxiliary power grid equipment according to the number of the transformer substations and the planning capacity;
and determining metering data corresponding to the auxiliary power grid device type based on the obtained auxiliary power grid device type.
Optionally, the number of substations to be built in the area and the planning capacity are set in the project plan to be built, including:
acquiring a construction target in a project plan to be constructed;
and decomposing the construction target based on the standard capacity corresponding to the type of the existing auxiliary power grid equipment, and determining the optimal configuration quantity of the auxiliary power grid equipment and the quantity of the transformer substations to be constructed.
Optionally, the obtaining of the metering data of the type consistent with the metering data from the power grid service unified data center, and completing the selection of the accessory power grid equipment type according to the difference between the two types includes:
acquiring a target attribute field of a metering data type;
acquiring metering data consistent with the target attribute field from a power grid service unified data center;
and calculating the difference value between each item of metering data and the metering data, and selecting the auxiliary power grid equipment type corresponding to the metering data with the minimum difference value as a final result.
Optionally, the method for selecting the power grid device further includes:
and in terms of project construction necessity, project construction benefits and the like, the indexes are subjected to quantitative scoring in sequence, scores in the projects are calculated, and high-quality power grid equipment is selected in a comprehensive evaluation mode.
Optionally, in terms of project construction necessity and project construction benefit, the method includes the steps of sequentially performing quantitative scoring on the indexes, calculating scores in the projects, and selecting high-quality power grid equipment in a comprehensive evaluation mode, where the method includes:
determining the index score according to the formula one,
wherein gamma is index score, alpha is index average value, beta is index strengthening value, and x1To add an initial threshold, x2A point adding termination threshold value;
determining the score of the item according to the formula two,
wherein a iskScoring the item; a isnThe value ranges of k and n are positive integers for the scores of the indexes.
Optionally, the only remaining power grid items corresponding to the auxiliary power grid devices in the normal operating state but with the metering data exceeding the preset parameters includes:
extracting metering data corresponding to the auxiliary power grid equipment in the normal working state from the acquired metering data;
comparing the extracted metering data with preset parameters, and determining the 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, the power grid projects corresponding to the auxiliary power grid equipment of which the metering data do not exceed the preset parameters are removed from all the current power grid projects, and only the power grid projects corresponding to the auxiliary power grid equipment of which the metering data exceed the preset parameters are reserved.
The technical scheme provided by the invention has the beneficial effects that:
the uniformly collected metering data of the power grid equipment are sorted, the corresponding power grid equipment types are extracted according to different project plans, then the auxiliary power grid equipment is screened, finally, the screening of the power grid project is completed based on the screening result, the objectivity of power grid project selection can be improved, and the influence of artificial subjective factors is reduced.
Drawings
In order to more clearly illustrate the technical solution of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on the drawings without creative efforts.
Fig. 1 is a schematic flow chart of a power grid project selection method based on big data analysis according to the present application.
Detailed Description
To make the structure and advantages of the present invention clearer, the structure of the present invention will be further described with reference to the accompanying drawings.
Example one
The application provides a power grid project selection method based on big data analysis, and 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 region 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 sending the grouped metering data to a power grid service 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 with the same type as the metering data from the power grid service unified data center, and finishing the selection of the auxiliary power grid equipment type according to the difference value of the metering data and the metering data;
15. performing 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 reserving the power grid items corresponding to the auxiliary power grid equipment which is in the normal working state and the metering data of which exceeds the preset parameters.
In implementation, in order to accurately complete the selection of the power grid devices, the metering data of all the power grid devices in the area needs to be collected uniformly. And grouping the metering data based on the type of the power grid equipment after the summary is finished. And then extracting the type of the auxiliary power grid equipment from the project plan to be established, correspondingly processing the auxiliary power grid equipment with the metering data of the data packet completed in the step, and selecting proper auxiliary power grid equipment according to the corresponding data.
The auxiliary power grid equipment is selected to finally select a power grid project meeting the requirement, and because the power grid project and the auxiliary power grid equipment have a corresponding relationship, the determination of the auxiliary power grid equipment is equivalent to the determination of the power grid project, and a specific discussion process for determining the power grid project based on the auxiliary power grid equipment is given in the following text and is not repeated here.
The specific processing method proposed in step 12 includes:
121. determining data types corresponding to different types of power grid equipment;
122. grouping the 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 service unified data center for storage.
In implementation, the power grid equipment mainly comprises two 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, mutual inductors, contactors and the like with various voltage levels.
Based on a full-service unified data center, key indexes such as power grid regional electricity sales amount, regional load, equipment load rate, equipment age, insulation rate, cabling rate, voltage qualification rate and the like are accessed and analyzed, according to objective facts, different-end data is treated, a data analysis model is formulated, the rationality of index data is analyzed from the aspects of index current situation, index acceleration 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 needs to be processed by exception. The criterion for determining an abnormality lies in the working experience of a front-line worker.
The decision step for determining the metering data set forth in step 13 includes:
131. the number of the transformer substations to be built in the region and the planning capacity are set in the project planning to be built;
132. determining the type of the auxiliary power grid equipment according to the number of the transformer substations and the planning capacity;
133. and determining metering data corresponding to the auxiliary power grid device type based on the obtained auxiliary power grid device type.
The method comprises the steps that the project plan to be built of an area contains information in many aspects, power grid equipment information is also contained, the number of substations to be built and the planning capacity in the area can be determined through extraction of the project plan to be built, and then the specific number and the power consumption capacity of auxiliary power grid equipment such as power plants, substations, power transmission towers and transformer rooms to be built in the area can be determined according to the number and the planning capacity, so that the metering data such as the power consumption and the length of power transmission lines 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 a single target to correspond to a multi-index condition; according to the importance and relevance of each index, setting the weight influence factor of each index to be 1-5 points, according to the current situation and weak point of each regional power grid, setting the basic score of each index, and determining the weight of each index by performing superposition calculation on the basic score and the influence factor, thereby constructing a project optimization evaluation index system integrating a construction target, the power grid index and the index weight.
Wherein step 131 specifically comprises:
1311. acquiring a construction target in a project plan to be constructed;
1312. and decomposing the construction target based on the standard capacity corresponding to the type of the existing auxiliary power grid equipment, and determining the optimal configuration quantity of the auxiliary power grid equipment and the quantity of the transformer substations to be constructed.
And microcosmically analyzing indexes of each power grid project construction equipment, equipment age, equipment load and the like which influence the equipment, opening a data link from the power grid project to the power grid equipment and then to the operation index by combining the results of the power grid current situation analysis library to form a strong mapping association relation, and tracing the detailed operation data of the specific equipment and equipment corresponding to the project in real time by taking the project as a visual angle.
The step of completing the selection of the auxiliary grid device type set forth in step 14 includes:
141. acquiring a target attribute field of a metering data type;
142. acquiring metering data consistent with the target attribute field from a power grid service unified data center;
143. and calculating the difference value between each item of metering data and the metering data, and selecting the auxiliary power grid equipment type corresponding to the metering data with the minimum difference value as a final result.
The specific choice is based on choosing the same type of target attribute field from the metering data.
For example, the target attribute fields to be referred to for the substation include no-load reactive loss, no-load loss, rated capacity of the transformer, no-load current percentage of the transformer, short-circuit voltage percentage, average load factor, load fluctuation loss factor, and the like.
After the same-target attribute field is obtained, the difference value between each item of metering data and the metering data needs to be calculated, and if the difference value is small, the selected auxiliary power grid equipment can be used as a final result; and if the difference is too large, the auxiliary power grid equipment selection needs to be carried out again.
The foregoing steps have already completed the selection of the auxiliary grid devices, and in order to complete the validation of the final grid project, the selected auxiliary grid devices in step 14 need to be subjected to the verification of the state parameters as shown in step 15. The purpose of verification is to verify and analyze the state parameters of the auxiliary power grid equipment during working, determine whether the equipment in a poor working state exists, and the power grid project containing the auxiliary power grid equipment is easy to go out of line and has a fault in the later period and cannot be used as a final reserved project.
After the auxiliary power grid equipment in the normal working state is acquired, the step of determining the final power grid project, namely step 16, includes:
161. and extracting the metering data corresponding to the auxiliary power grid equipment in the normal working state from the acquired metering data. The purpose of acquiring the corresponding metering data of the auxiliary power grid device is to prepare for secondary selection of the auxiliary power grid device in the next step.
162. And comparing the extracted metering data with preset parameters, and determining the auxiliary power grid equipment with the metering data exceeding the preset parameters. The preset parameters are used as threshold values for screening of the auxiliary power grid equipment, the aim is to select the auxiliary power grid equipment in the optimal working state, and the auxiliary power grid equipment in the optimal working state can also exert the optimal production efficiency to a certain extent, so that the finally obtained power grid project is also the optimal power grid project.
163. Based on the known corresponding relation between the auxiliary power grid metering equipment and the power grid projects, the power grid projects corresponding to the auxiliary power grid equipment of which the metering data do not exceed the preset parameters are removed from all the current power grid projects, and only the power grid projects corresponding to the auxiliary power grid equipment of which the metering data exceed the preset parameters are reserved.
The power grid project comprises a plurality of auxiliary power grid devices, one-to-one correspondence exists between the auxiliary power grid devices, and 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, so that the power grid projects are screened based on the characteristic of the auxiliary power grid devices.
Example two
For the above power grid project selection method, as for the auxiliary power grid device selection mode therein, the embodiment of the present application further provides another power grid device selection method, further including:
and in terms of project construction necessity, project construction benefits and the like, the indexes are subjected to quantitative scoring in sequence, scores in the projects are calculated, and high-quality power grid equipment is selected in a comprehensive evaluation mode.
Specifically referring to the calculation modes of the formula one and the formula two, 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, specifically comprising:
determining the index score according to the formula one,
wherein gamma is index score, alpha is index average value, beta is index strengthening value, and x1To add an initial threshold, x2A point adding termination threshold value;
determining the score of the item according to the formula two,
wherein a iskScoring the item; a isnThe value ranges of k and n are positive integers for the scores of the indexes.
The sequence numbers in the above embodiments are merely for description, and do not represent the sequence of the assembly or the use of the components.
The above description is only exemplary of the present invention and should not be taken as limiting the invention, as any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. The power grid project selection method based on big data analysis is characterized by comprising the following steps:
acquiring metering data of all power grid equipment in the 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 sending the grouped metering data to a power grid service 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;
acquiring metering data with the same type as the metering data from the power grid service unified data center, and finishing the selection of the auxiliary power grid equipment type according to the difference value of the metering data and the metering data;
performing state parameter verification on the selected auxiliary power grid equipment to determine the auxiliary power grid equipment in a normal working state;
and only reserving the power grid items corresponding to the auxiliary power grid equipment which is in the normal working state and the metering data of which exceeds the preset parameters.
2. The method for selecting a power grid project based on big data analysis according to claim 1, wherein the obtained metering data is grouped based on different types of power grid devices, and the grouped metering data is sent to a power grid service unified data center, including:
determining data types corresponding to different types of power grid equipment;
grouping the 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 service unified data center for storage.
3. The method for selecting the power grid project based on the big data analysis according to claim 1, wherein the extracting of the type of the auxiliary power grid device from the project plan to be built and the determining of the metering data corresponding to the type of the auxiliary power grid device comprise:
the number of the transformer substations to be built in the region and the planning capacity are set in the project planning to be built;
determining the type of the auxiliary power grid equipment according to the number of the transformer substations and the planning capacity;
and determining metering data corresponding to the auxiliary power grid device type based on the obtained auxiliary power grid device type.
4. The power grid project selection method based on big data analysis according to claim 3, wherein the setting of 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 a project plan to be constructed;
and decomposing the construction target based on the standard capacity corresponding to the type of the existing auxiliary power grid equipment, and determining the optimal configuration quantity of the auxiliary power grid equipment and the quantity of the transformer substations to be constructed.
5. The method for selecting a power grid project based on big data analysis according to claim 1, wherein the step of obtaining metering data with the same type as the metering data from the power grid service unified data center and completing the selection of the auxiliary power grid equipment type according to the difference between the metering data and the metering data comprises the steps of:
acquiring a target attribute field of a metering data type;
acquiring metering data consistent with the target attribute field from a power grid service unified data center;
and calculating the difference value between each item of metering data and the metering data, and selecting the auxiliary power grid equipment type corresponding to the metering data with the minimum difference value as a final result.
6. The big data analysis-based power grid project selection method according to claim 1, wherein the power grid equipment selection method further comprises:
and in terms of project construction necessity, project construction benefits and the like, the indexes are subjected to quantitative scoring in sequence, scores in the projects are calculated, and high-quality power grid equipment is selected in a comprehensive evaluation mode.
7. The power grid project selection method based on big data analysis according to claim 6, wherein the step of quantifying scores of the indexes in sequence from the aspects of project construction necessity and project construction benefit, calculating scores in the projects, and selecting high-quality power grid equipment in a comprehensive evaluation mode comprises the steps of:
determining the index score according to the formula one,
wherein gamma is index score, alpha is index average value, beta is index strengthening value, and x1To add an initial threshold, x2A point adding termination threshold value;
determining the score of the item according to the formula two,
wherein a iskScoring the item; a isnScore each indexAnd the value ranges of k and n are positive integers.
8. The method for selecting power grid projects based on big data analysis according to claim 1, wherein the step of only reserving the power grid projects corresponding to the auxiliary power grid devices which are in the normal working state and the metering data of which exceeds the preset parameters comprises the following steps:
extracting metering data corresponding to the auxiliary power grid equipment in the normal working state from the acquired metering data;
comparing the extracted metering data with preset parameters, and determining the 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, the power grid projects corresponding to the auxiliary power grid equipment of which the metering data do not exceed the preset parameters are removed from all the current power grid projects, and only the power grid projects corresponding to the auxiliary power grid equipment of which the metering data exceed the preset parameters are reserved.
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| 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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| CN111461582A (en) * | 2020-05-15 | 2020-07-28 | 广东电网有限责任公司湛江供电局 | Power grid construction project scheme selection method, system and storage medium |
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