CN109977128B - Power grid planning data fusion method based on temporal dimension - Google Patents
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Abstract
The invention discloses a power grid planning data fusion method based on a temporal dimension, which comprises the steps of preprocessing acquired power grid planning basic data to form a power grid planning database; classifying the data according to the planning stage of the power grid planning data; fusing the data according to the classification result; and forming a power grid planning database by the fused data so as to complete the fusion of the power grid planning data. According to the power grid planning data fusion method based on the temporal dimension, the final power grid planning data fusion result is obtained by acquiring data and processing, correcting, updating and fusing the data, so that the power grid planning data fusion can be realized and the effect is good.
Description
Technical Field
The invention particularly relates to a power grid planning data fusion method based on a temporal dimension.
Background
With the development of economic technology and the improvement of living standard of people, electric energy becomes a secondary energy source essential for production and living of people, and brings endless convenience to production and living of people.
Grid planning is one of the important research directions of power systems, and data is an important support of grid planning. Therefore, the fusion of the grid data becomes a central importance in the research of the power system.
The data required for power grid planning is complex and large, and multiple complex planning data themes are involved. However, the data extracted from the source data layer to the planning data resource center is influenced by the following three aspects, and the data quality is more or less problematic: firstly, data errors and deviations exist in the data source of the source end data; secondly, in the process of data transmission, certain data loss exists due to the influence of network channels and time synchronization; thirdly, in the storage and processing process of the planning data resource center, data heterogeneity is caused due to the insufficient uniqueness of data sources. However, the current research still cannot construct a theme data environment with clear classification, clear business processing and clear data exchange and circulation.
Disclosure of Invention
The invention aims to provide a power grid planning data fusion method based on a temporal dimension, which can realize power grid planning data fusion and has a better effect.
The invention provides a power grid planning data fusion method based on a temporal dimension, which comprises the following steps:
s1, preprocessing acquired power grid planning basic data to form a power grid planning database;
s2, classifying the data in the power grid planning database obtained in the step S1 according to the planning stage of the power grid planning data;
s3, fusing the data according to the classification result of the step S2;
and S4, forming the fused data obtained in the step S3 into a power grid planning database, so as to complete the fusion of the power grid planning data.
Step S2, classifying the data in the power grid planning database obtained in step S1, specifically classifying according to the following rules:
(1) history state data: data which is more than 1 year and more than the current time, is valuable to the current planning work and needs to be stored;
(2) planning state data of the previous round: planning state data based on historical years;
(3) building state data: data during the construction of the project;
(4) the current state data: data relating to planning of a current temporal state;
(5) predicted state data: data relating to power grid planning predictions;
(6) planning state data of the current round: planning state data based on the current year.
The data fusion in step S3 is specifically performed by the following steps:
1) fusing the historical state data and the current state data to form planning section data;
2) fusing the planning state data and the construction state data of the previous round to form pre-production power grid information data;
3) and (4) fusing the planning section data obtained in the step (S1), the pre-production power grid information data obtained in the step (S2) and the prediction state data to form planning state data of the current round.
The method is characterized in that historical state data and current state data are fused to form planning section data, and specifically the method comprises the following steps:
A. acquiring and storing all original data of each historical updating moment during data updating, thereby forming an original database;
B. according to the original database obtained in the step A, comparing two adjacent self-data in the original database to obtain a first transformation quantity set;
C. acquiring and storing all updated data of each historical updating moment after data updating, thereby forming a current situation database;
D. acquiring the basis data during the first updating and comparing the basis data with the current situation data to obtain a second transformation quantity set;
E. and D, updating the current data according to the second transformation amount obtained in the step D and the basis data to obtain the current data after the first time of data updating.
And D, updating the current data according to the second transformation quantity and the basis data obtained in the step D so as to obtain the current data after the first time of data updating, specifically adopting the following rules to update:
if the second transformation quantity is newly added data, the current data is not changed and the data is not conflicted, directly inserting the data record of the second transformation quantity into the current data so as to obtain new current data;
if the second transformation amount is not changed, the current data is newly added with data and the data are not conflicted, directly taking the current data as new current data;
if the second transformation amount is data modification and the current data is data modification, determining whether the data modification conflicts: if the data modification conflicts, maintaining the current data; if the data modification is not conflicted, directly updating the current data by the modified second transformation amount data so as to obtain new current data;
if the second transformation quantity is data modification, the current data is not changed and the data is not conflicted, directly updating the current data by the modified data of the second transformation quantity so as to obtain new current data;
if the second transformation amount is not changed, the current data is modified and the data is not conflicted, directly taking the current data as new current data;
if the second transformation amount is data modification, the current data is data deletion and data conflict, directly updating the current data by the modified second transformation amount data to obtain new current data;
if the second transformation quantity is data deletion, the current data is data modification and data conflict, correspondingly deleting the data deleted in the second transformation quantity in the current data so as to obtain new current data;
if the second transformation amount is data deletion, the current data is data deletion and the data is not conflicted, directly taking the current data as new current data;
if the second conversion amount is data deletion, the current data is not changed and the data is not conflicted, correspondingly deleting the data deleted in the second conversion amount in the current data, and taking the deleted current data as new current data;
and if the second conversion amount is not changed, the current data is deleted and the data does not conflict, directly using the current data as new current data.
The planning state data and the construction state data of the previous round are fused to form pre-production power grid information data, and the method specifically comprises the following steps of:
a. acquiring a unique identification code of an item;
b. merging projects with the same unique identification code in the planning state data and the construction state data of the previous round;
c. and replacing the previous round of planning state data with the construction state data for the project with the same unique identification code.
The planning section data obtained in the step S1, the pre-production power grid information data obtained in the step S2, and the prediction state data are fused to form planning state data of the current round, and the method specifically includes the following steps:
i carries out problem analysis to planning section data, checks whether there is a solution to this problem in the pre-production information: if yes, directly updating the planning section problem data by using the corresponding data field in the pre-commissioning information, and realizing the editing of the previous round of planning state data; if not, maintaining the planned section data unchanged;
and II, performing problem analysis on the predicted state data, and checking whether a solution to the problem exists in the pre-production information: if yes, corresponding data fields in the pre-production information are directly used for updating the problem data in the prediction state, and the modification of the data in the prediction state is realized; if not, keeping the prediction state data unchanged;
and III, fusing the project information obtained in the step I and the step II, and supplementing and perfecting project information fields in the planning state data of the current round, so that the planning state data of the current round is obtained.
According to the power grid planning data fusion method based on the temporal dimension, the final power grid planning data fusion result is obtained by acquiring data and processing, correcting, updating and fusing the data, so that the power grid planning data fusion can be realized and the effect is good.
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FIG. 1 is a process flow diagram of the process of the present invention.
Detailed Description
FIG. 1 shows a flow chart of the method of the present invention: the invention provides a power grid planning data fusion method based on a temporal dimension, which comprises the following steps:
s1, preprocessing acquired power grid planning basic data to form a power grid planning database;
s2, classifying the data in the power grid planning database obtained in the step S1 according to the planning stage of the power grid planning data; specifically, the classification is performed according to the following rules:
(1) history state data: data which is more than 1 year and more than the current time, is valuable to the current planning work and needs to be stored;
(2) planning state data of the previous round: planning state data based on historical years;
(3) building state data: data during the construction of the project;
(4) the current state data: data relating to planning of a current temporal state;
(5) predicted state data: data relating to power grid planning predictions;
(6) planning state data of the current round: planning state data based on the current year;
s3, fusing the data according to the classification result of the step S2; specifically, the following steps are adopted for fusion:
1) fusing the historical state data and the current state data to form planning section data; specifically, the following steps are adopted for fusion:
A. acquiring and storing all original data of each historical updating moment during data updating, thereby forming an original database;
B. according to the original database obtained in the step A, comparing two adjacent self-data in the original database to obtain a first transformation quantity set;
C. acquiring and storing all updated data of each historical updating moment after data updating, thereby forming a current situation database;
D. acquiring the basis data during the first updating and comparing the basis data with the current situation data to obtain a second transformation quantity set;
E. d, updating the current data according to the second transformation quantity and the basis data obtained in the step D so as to obtain the current data after the first data updating;
in specific implementation, the following rules are specifically adopted for updating:
if the second transformation quantity is newly added data, the current data is not changed and the data is not conflicted, directly inserting the data record of the second transformation quantity into the current data so as to obtain new current data;
if the second transformation amount is not changed, the current data is newly added with data and the data are not conflicted, directly taking the current data as new current data;
if the second transformation amount is data modification and the current data is data modification, determining whether the data modification conflicts: if the data modification conflicts, maintaining the current data; if the data modification is not conflicted, directly updating the current data by the modified second transformation amount data so as to obtain new current data;
if the second transformation quantity is data modification, the current data is not changed and the data is not conflicted, directly updating the current data by the modified data of the second transformation quantity so as to obtain new current data;
if the second transformation amount is not changed, the current data is modified and the data is not conflicted, directly taking the current data as new current data;
if the second transformation amount is data modification, the current data is data deletion and data conflict, directly updating the current data by the modified second transformation amount data to obtain new current data;
if the second transformation quantity is data deletion, the current data is data modification and data conflict, correspondingly deleting the data deleted in the second transformation quantity in the current data so as to obtain new current data;
if the second transformation amount is data deletion, the current data is data deletion and the data is not conflicted, directly taking the current data as new current data;
if the second conversion amount is data deletion, the current data is not changed and the data is not conflicted, correspondingly deleting the data deleted in the second conversion amount in the current data, and taking the deleted current data as new current data;
if the second transformation amount is not changed, the current data is deleted and the data is not conflicted, directly taking the current data as new current data;
2) fusing the planning state data and the construction state data of the previous round to form pre-production power grid information data; specifically, the following steps are adopted for fusion:
a. acquiring a unique identification code of an item;
b. merging projects with the same unique identification code in the planning state data and the construction state data of the previous round;
c. replacing the project with the same unique identification code with the project planning state data in the previous round by the project construction state data;
3) fusing the planning section data obtained in the step S1, the pre-production power grid information data obtained in the step S2 and the prediction state data to form planning state data of the current round; specifically, the following steps are adopted for fusion:
i carries out problem analysis to planning section data, checks whether there is a solution to this problem in the pre-production information: if yes, directly updating the planning section problem data by using the corresponding data field in the pre-commissioning information, and realizing the editing of the previous round of planning state data; if not, maintaining the planned section data unchanged;
and II, performing problem analysis on the predicted state data, and checking whether a solution to the problem exists in the pre-production information: if yes, corresponding data fields in the pre-production information are directly used for updating the problem data in the prediction state, and the modification of the data in the prediction state is realized; if not, keeping the prediction state data unchanged;
and III, fusing the project information obtained in the step I and the step II, and supplementing and perfecting project information fields in the planning state data of the current round, so that the planning state data of the current round is obtained.
And S4, forming the fused data obtained in the step S3 into a power grid planning database, so as to complete the fusion of the power grid planning data.
Claims (1)
1. A power grid planning data fusion method based on a temporal dimension comprises the following steps:
s1, preprocessing the acquired power grid planning basic data to form a power grid planning database;
s2, classifying the data in the power grid planning database obtained in the step S1 according to the planning stage of the power grid planning data; specifically, the classification is performed according to the following rules:
(1) history state data: data which is more than 1 year and more than the current time, is valuable to the current planning work and needs to be stored;
(2) planning state data of the previous round: planning state data based on historical years;
(3) building state data: data during the construction of the project;
(4) the current state data: data relating to planning of a current temporal state;
(5) predicted state data: data relating to power grid planning predictions;
(6) planning state data of the current round: planning state data based on the current year;
s3, fusing the data according to the classification result of the step S2; specifically, the following steps are adopted for fusion:
1) fusing the historical state data and the current state data to form planning section data; specifically, the following steps are adopted for fusion:
A. acquiring and storing all original data of each historical updating moment during data updating, thereby forming an original database;
B. according to the original database obtained in the step A, comparing two adjacent self-data in the original database to obtain a first transformation quantity set;
C. acquiring and storing all updated data of each historical updating moment after data updating, thereby forming a current situation database;
D. acquiring the basis data during the first updating and comparing the basis data with the current situation data to obtain a second transformation quantity set;
E. d, updating the current data according to the second transformation quantity and the basis data obtained in the step D so as to obtain the current data after the first data updating; specifically, the following rules are adopted for updating:
if the second transformation quantity is newly added data, the current data is not changed and the data is not conflicted, directly inserting the data record of the second transformation quantity into the current data so as to obtain new current data;
if the second transformation amount is not changed, the current data is newly added with data and the data are not conflicted, directly taking the current data as new current data;
if the second transformation amount is data modification and the current data is data modification, determining whether the data modification conflicts: if the data modification conflicts, maintaining the current data; if the data modification is not conflicted, directly updating the current data by the modified second transformation amount data so as to obtain new current data;
if the second transformation quantity is data modification, the current data is not changed and the data is not conflicted, directly updating the current data by the modified data of the second transformation quantity so as to obtain new current data;
if the second transformation amount is not changed, the current data is modified and the data is not conflicted, directly taking the current data as new current data;
if the second transformation amount is data modification, the current data is data deletion and data conflict, directly updating the current data by the modified second transformation amount data to obtain new current data;
if the second transformation quantity is data deletion, the current data is data modification and data conflict, correspondingly deleting the data deleted in the second transformation quantity in the current data so as to obtain new current data;
if the second transformation amount is data deletion, the current data is data deletion and the data is not conflicted, directly taking the current data as new current data;
if the second conversion amount is data deletion, the current data is not changed and the data is not conflicted, correspondingly deleting the data deleted in the second conversion amount in the current data, and taking the deleted current data as new current data;
if the second transformation amount is not changed, the current data is deleted and the data is not conflicted, directly taking the current data as new current data;
2) fusing the planning state data and the construction state data of the previous round to form pre-production power grid information data; specifically, the following steps are adopted for fusion:
a. acquiring a unique identification code of an item;
b. merging projects with the same unique identification code in the planning state data and the construction state data of the previous round;
c. replacing the project with the same unique identification code with the project planning state data in the previous round by the project construction state data;
3) fusing the planning section data obtained in the step 1), the pre-production power grid information data obtained in the step 2) and the prediction state data to form planning state data of the current round; specifically, the following steps are adopted for fusion:
i carries out problem analysis to planning section data, checks whether there is a solution to this problem in the pre-production information: if yes, directly updating the planning section problem data by using the corresponding data field in the pre-commissioning information, and realizing the editing of the previous round of planning state data; if not, maintaining the planned section data unchanged;
and II, performing problem analysis on the predicted state data, and checking whether a solution to the problem exists in the pre-production information: if yes, corresponding data fields in the pre-production information are directly used for updating the problem data in the prediction state, and the modification of the data in the prediction state is realized; if not, keeping the prediction state data unchanged;
III, fusing the project information obtained in the step I and the step II, and supplementing and perfecting project information fields in the planning state data of the current round, so as to obtain the planning state data of the current round;
and S4, forming a power grid planning mature database by the fused data obtained in the step S3, and completing fusion of the power grid planning data.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105160593A (en) * | 2015-08-18 | 2015-12-16 | 国家电网公司 | Power transmission and transformation equipment multidimensional heterogeneous data fusion method and system facing big data |
| CN105389367A (en) * | 2015-11-12 | 2016-03-09 | 江苏省电力公司扬州供电公司 | Power network graphic multi-tense and multi-level distributed storage method based on Mongo database |
| CN105631597A (en) * | 2015-12-31 | 2016-06-01 | 中国南方电网有限责任公司 | Construction method for transformer substation three-dimensional visual platform |
| WO2018101722A2 (en) * | 2016-11-30 | 2018-06-07 | 에스케이 주식회사 | Machine learning-based semiconductor manufacturing yield prediction system and method |
| CN108647268A (en) * | 2018-04-28 | 2018-10-12 | 国网湖南省电力有限公司 | Increment updating method for distribution network planning data integration |
Family Cites Families (1)
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105160593A (en) * | 2015-08-18 | 2015-12-16 | 国家电网公司 | Power transmission and transformation equipment multidimensional heterogeneous data fusion method and system facing big data |
| CN105389367A (en) * | 2015-11-12 | 2016-03-09 | 江苏省电力公司扬州供电公司 | Power network graphic multi-tense and multi-level distributed storage method based on Mongo database |
| CN105631597A (en) * | 2015-12-31 | 2016-06-01 | 中国南方电网有限责任公司 | Construction method for transformer substation three-dimensional visual platform |
| WO2018101722A2 (en) * | 2016-11-30 | 2018-06-07 | 에스케이 주식회사 | Machine learning-based semiconductor manufacturing yield prediction system and method |
| CN108647268A (en) * | 2018-04-28 | 2018-10-12 | 国网湖南省电力有限公司 | Increment updating method for distribution network planning data integration |
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