CN110311369A - A kind of stabilization of power grids section short term curve prediction method and system - Google Patents
A kind of stabilization of power grids section short term curve prediction method and system Download PDFInfo
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- CN110311369A CN110311369A CN201910473198.8A CN201910473198A CN110311369A CN 110311369 A CN110311369 A CN 110311369A CN 201910473198 A CN201910473198 A CN 201910473198A CN 110311369 A CN110311369 A CN 110311369A
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/003—Load forecast, e.g. methods or systems for forecasting future load demand
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Abstract
The present invention relates to the technical fields of dispatching of power netwoks, more particularly, to a kind of stabilization of power grids section short term curve prediction method and system, comprising the following steps: obtain 220kV main transformer prediction data；Traversal section simultaneously judges whether all sections have stepped through；Predict the load of the component part of section；Section load is predicted according to direction of tide；Generate section prediction curve.Method of the invention is capable of the incidence relation of real-time quick analysis section load and 220kV main transformer load, and according to association main transformer load data, fitting generates section short term curve, and timeliness is strong, and accuracy is high；And above method write-in program module can be placed in computer system by the present invention, realize the high efficiency and automation of forecast analysis.
Description
Technical field
The present invention relates to the technical fields of dispatching of power netwoks, bent more particularly, to a kind of stabilization of power grids section short term
Line prediction technique and system.
Background technique
The entirety that stabilization of power grids section is made of several routes or main transformer switch is powered some load area,
Either switch failure, load will transfer to section residue switch, thus the load prediction of stabilization of power grids section is for promoting power train
System security and stability, promotion demand Side Management level are of great significance.Traditional load prediction is used for the whole city
Electric load is carried out, and total stations are not particularly suited for the load prediction of stable cross section, are primarily due in the whole city
When short term curve prediction, it is believed that load structure is constant, the extraneous factors strong correlation such as load curve and temperature.And section
Load curve depends primarily on the section load structure of current and future, and section load structure due to changes of operating modes, set
Standby maintenance, distribution looped network turn for etc. reasons cannot accurately obtain load structure in real time often in dynamic change, then can not
Its load curve can precisely be predicted.Currently, manual type analysis section load structure situation of change one by one is generally used,
And then load prediction is carried out according to the historical data of each load structure element, it there is no means to implement Computerized intelligent operation.
Summary of the invention
It is an object of the invention to overcome the deficiencies of the prior art and provide a kind of stabilization of power grids section short term curve is pre-
Survey method and system, the incidence relation of real-time quick analysis section load and 220kV main transformer load, according to association main transformer load number
According to fitting generates section short term curve, and timeliness is strong, and accuracy is high.
In order to solve the above technical problems, the technical solution adopted by the present invention is that:
A kind of stabilization of power grids section short term curve prediction method is provided, comprising the following steps:
S1. each 220kV main transformer load prediction data of following 48 hours power grids is obtained；
S2. analysis object is determined, using whole monitoring section existing for current electric grid as analysis object；And judge all prisons
Survey whether section all has stepped through: if so, going to step S6；If it is not, then going to step S3；
S3. judge whether the component part of all monitoring sections has all traversed: if so, going to step S5；If it is not, then
Go to step S4；
S4. for 220kV line switching any in section component, equipment connecting relation, direction of tide, switch are obtained
State and disconnecting link state, and the same station whole 220kV connecting with the 220kV line switching is analyzed according to the information topology of acquisition
Main transformer, by the 220kV line switching and with the ratio of the sum of station whole 220kV main transformer real-time load, in conjunction in step S1
Each 220kV main transformer load prediction data obtained converts to obtain the load prediction data of 220kV line switching；
S5. the whole 220kV line switchings obtained step S4 according to the 220kV positive and negative attribute of line switching real-time load value
Predicted load be set as positive number or negative, addition obtains the prediction data of target section；
S6. same day section prediction curve is generated according to the prediction data of the target section of step S5.
Stabilization of power grids section short term curve prediction method of the invention, to automate E file, SCADA web data
Data are data source in library and aid decision-making system database, being capable of quick analysis section in real time using method of the invention
The incidence relation of load and 220kV main transformer load, according to association main transformer load data, fitting generates end face short term curve,
Timeliness is strong, and accuracy is high.
Preferably, in step S1, each 220kV main transformer load prediction data is obtained from aid decision-making system database.
Preferably, in step S3, the component part of monitoring section can be obtained from section composition table, and the section forms table
It is stored in user maintenance table, the user maintenance Biao Niannei is stored with customer substation information.
Preferably, in step S4, switch state and disconnecting link status data are obtained from automation E file, and equipment connection is closed
System and direction of tide are obtained from SCADA Web database.
Preferably, step S4 is sequentially included the following steps:
S401. judge whether target 220kV line switching is listed: if so, judging the target 220kV line switching
Predict that load value is 0, topology terminates；If it is not, then going to step S402；
S402. according to the connection relationship of equipment, the neighbouring device connecting with current device is obtained, and is put into equipment topology table
In screened；
S403. to step S402 obtain armamentarium one by one topology and judge whether all devices in equipment topology table
Through whole traversals: if so, topology terminates, exiting topological process, go to step S410；If it is not, then by step S404~S409's
Judgment rule continues topological judgement；
S404. judge whether current device is listed: if so, topology terminates, exiting topological process, be transferred to step S403；
If it is not, being then transferred to step S405 continues topological judgement；
S405. judge whether current device ownership substation with target 220kV line switching belongs to same substation: if
It is then to be transferred to step S406 to continue topological judgement；If it is not, then terminating the topology judgement of current device, S403 is entered step；
S406. judge whether current device once occurred in father node: if so, topology terminates, exiting topological process, be transferred to
Step S403；If it is not, being then transferred to step S407 continues topological judgement；
S407. judge whether current device belongs to main transformer: if so, stopping topology, the main transformer being included in and target
In the same station 220kV main transformer of 220kV line switching connection, it is transferred to step S403；Continue to open up if it is not, being then transferred to step S408
Flutter judgement；
S408. judge whether current device belongs to switch: if so, being transferred to step S409 continues topological judgement；If
It is no, then stop topology and is transferred to step S402；
S409. judge whether current device is closed: if so, stopping topology being transferred to step S403；If it is not, being then transferred to step
S402；
S410. the currently practical load of target 220kV line switching is obtained as the molecule for calculating proportionate relationship, step
All denominators with the sum of station 220kV main transformer real-time load as proportionate relationship that S407 analysis obtains, are calculated 220kV line
The ratio of way switch and same station 220kV main transformer real-time load；
S411. it takes out from each 220kV main transformer load prediction data of power grid that step S1 is obtained and is analyzed by step S407
Show that 220kV main transformer load prediction data, each 220kV main transformer load prediction data are added the ratio that summation is obtained multiplied by step S410
Example calculates the predicted load of target 220kV line switching；Step S401~S411 is repeated, the whole of composition section is calculated
The predicted load of 220kV line switching.
Preferably, in step S5, the positive and negative attribute of 220kV line switching real-time load value is obtained from SCADA Web database
It takes.
The present invention also provides a kind of stabilization of power grids section short term curve prediction systems, including the power grid is written
The program module of stable cross section short term curve prediction method and be stored with automation E file, SCADA Web database,
The data-storage system of aid decision-making system database, user maintenance table, described program module are embedded in control module, the data
Storage system is connected to control module, and the input terminal of control module is connected with recording module.
Stabilization of power grids section short term curve prediction system of the invention, by each database purchase in computer system
In, by method write-in program module of the invention in computer system, thus analysis section load and 220kV real-time, quickly
The incidence relation of main transformer load, according to association main transformer load data, fitting generates section short term curve, and timeliness is strong, quasi-
Exactness is high, effectively overcome manual work to take time and effort and be unable to satisfy short-term load forecasting in real time, precisely, lacking of efficiently requiring
It falls into.
Compared with prior art, the beneficial effects of the present invention are:
Stabilization of power grids section short term curve prediction method and system of the invention, being capable of quick analysis section in real time
The incidence relation of load and 220kV main transformer load, according to association main transformer load data, fitting generates end face short term curve,
Timeliness is strong, and accuracy is high.
Detailed description of the invention
Fig. 1 is stabilization of power grids section short term curve prediction method flow diagram of the invention；
Fig. 2 is the schematic diagram of stabilization of power grids section short term curve prediction method data source；
Fig. 3 is the analytic process flow chart of step S4.
Specific embodiment
The present invention is further illustrated With reference to embodiment.
Embodiment one
It is as shown in Figure 1 to Figure 3 the embodiment of stabilization of power grids section short term curve prediction method of the invention, including
Following steps:
S1. each 220kV main transformer load prediction data of following 48 hours power grids is obtained；
S2. analysis object is determined, using whole monitoring section existing for current electric grid as analysis object；And judge all prisons
Survey whether section all has stepped through: if so, going to step S6；If it is not, then going to step S3；
S3. judge whether the component part of all monitoring sections has all traversed: if so, going to step S5；If it is not, then
Go to step S4；
S4. for 220kV line switching any in section component, equipment connecting relation, direction of tide, switch are obtained
State and disconnecting link state, and the same station whole 220kV master connecting with 220kV line switching is analyzed according to the information topology of acquisition
Become, by 220kV line switching and with the ratio of the sum of station whole 220kV main transformer real-time load, in conjunction with what is obtained in step S1
Each 220kV main transformer load prediction data converts to obtain the load prediction data of 220kV line switching；
S5. the whole 220kV line switchings obtained step S4 according to the 220kV positive and negative attribute of line switching real-time load value
Predicted load be set as positive number or negative, addition obtains the prediction data of target section；
S6. same day section prediction curve is generated according to the prediction data of the target section of step S5.
In the present embodiment, short-term load forecasting is to predict that precision of prediction is to the following 48 hours load curves of equipment
Every 15 minutes points.
In step S1, each 220kV main transformer load prediction data is obtained from aid decision-making system database.
In step S3, the component part of monitoring section can be obtained from section composition table, and section composition table is stored in user
In Maintenance Table, user maintenance Biao Niannei is stored with customer substation information.
In step S4, switch state and disconnecting link status data are obtained from automation E file, equipment connecting relation and trend
Direction is obtained from SCADA Web database.
Step S4 is sequentially included the following steps:
S401. judge whether target 220kV line switching is listed: if so, judging the prediction of target 220kV line switching
Load value is 0, and topology terminates；If it is not, then going to step S402；
S402. according to the connection relationship of equipment, the neighbouring device connecting with current device is obtained, and is put into equipment topology table
In screened；
S403. to step S402 obtain armamentarium one by one topology and judge whether all devices in equipment topology table
Through whole traversals: if so, topology terminates, exiting topological process, go to step S410；If it is not, then by step S404~S409's
Judgment rule continues topological judgement；
S404. judge whether current device is listed: if so, topology terminates, exiting topological process, be transferred to step S403；
If it is not, being then transferred to step S405 continues topological judgement；
S405. judge whether current device ownership substation with target 220kV line switching belongs to same substation: if
It is then to be transferred to step S406 to continue topological judgement；If it is not, then terminating the topology judgement of current device, S403 is entered step；
S406. judge whether current device once occurred in father node: if so, topology terminates, exiting topological process, be transferred to
Step S403；If it is not, being then transferred to step S407 continues topological judgement；
S407. judge whether current device belongs to main transformer: if so, stopping topology, main transformer being included in and target 220kV line
In the same station 220kV main transformer of way switch connection, it is transferred to step S403；If it is not, being then transferred to step S408 continues topological judgement；
S408. judge whether current device belongs to switch: if so, being transferred to step S409 continues topological judgement；If
It is no, then stop topology and is transferred to step S402；
S409. judge whether current device is closed: if so, stopping topology being transferred to step S403；If it is not, being then transferred to step
S402；
S410. the currently practical load of target 220kV line switching is obtained as the molecule for calculating proportionate relationship, step
All denominators with the sum of station 220kV main transformer real-time load as proportionate relationship that S407 analysis obtains, are calculated 220kV line
The ratio of way switch and same station 220kV main transformer real-time load；
S411. it takes out from each 220kV main transformer load prediction data of power grid that step S1 is obtained and is analyzed by step S407
Show that 220kV main transformer load prediction data, each 220kV main transformer load prediction data are added the ratio that summation is obtained multiplied by step S410
Example calculates the predicted load of target 220kV line switching；Step S401~S411 is repeated, the whole of composition section is calculated
The predicted load of 220kV line switching.
In step S5, the positive and negative attribute of 220kV line switching real-time load value is obtained from SCADA Web database.
By above step, it is capable of the incidence relation of real-time quick analysis section load and 220kV main transformer load, according to pass
Join main transformer load data, fitting generates section short term curve, and timeliness is strong, and accuracy is high.
Embodiment two
The present embodiment is the embodiment of stabilization of power grids section short term curve prediction system, the stabilization of power grids including write-in
The program module of section short term curve prediction method and be stored with automation E file, SCADA Web database, auxiliary
The data-storage system of decision system database, user maintenance table, program module are embedded in control module, data-storage system connection
Recording module is connected in the input terminal of control module, control module.
The present embodiment utilizes computer system, analysis section load and 220kV main transformer load can be associated with real-time, quickly
Relationship, according to association main transformer load data, fitting generates section short term curve, and timeliness is strong, and accuracy is high, effectively overcomes
Manual work take time and effort and be unable to satisfy short-term load forecasting in real time, precisely, the defect that efficiently requires.
Obviously, the above embodiment of the present invention be only to clearly illustrate example of the present invention, and not be pair
The restriction of embodiments of the present invention.For those of ordinary skill in the art, may be used also on the basis of the above description
To make other variations or changes in different ways.There is no necessity and possibility to exhaust all the enbodiments.It is all this
Made any modifications, equivalent replacements, and improvements etc., should be included in the claims in the present invention within the spirit and principle of invention
Protection scope within.
Claims (7)
1. a kind of stabilization of power grids section short term curve prediction method, which comprises the following steps:
S1. each 220kV main transformer load prediction data of following 48 hours power grids is obtained；
S2. analysis object is determined, using whole monitoring section existing for current electric grid as analysis object；And judge that all monitorings are disconnected
Whether face all has stepped through: if so, going to step S6；If it is not, then going to step S3；
S3. judge whether the component part of all monitoring sections has all traversed: if so, going to step S5；If it is not, then turning to walk
Rapid S4；
S4. for 220kV line switching any in section component, equipment connecting relation, direction of tide, switch state are obtained
And disconnecting link state, and the same station whole 220kV master connecting with the 220kV line switching is analyzed according to the information topology of acquisition
Become, by the 220kV line switching and with the ratio of station the sum of whole 220kV main transformer real-time load, in conjunction with being obtained in step S1
Each 220kV main transformer load prediction data taken converts to obtain the load prediction data of 220kV line switching；
S5. the bearing the step S4 whole 220kV line switchings obtained according to the 220kV positive and negative attribute of line switching real-time load value
Lotus predicted value is set as positive number or negative, and addition obtains the prediction data of target section；
S6. same day section prediction curve is generated according to the prediction data of the target section of step S5.
2. stabilization of power grids section short term curve prediction method according to claim 1, which is characterized in that step S1
In, each 220kV main transformer load prediction data is obtained from aid decision-making system database.
3. stabilization of power grids section short term curve prediction method according to claim 1, which is characterized in that step S3
In, the component part of monitoring section can be obtained from section composition table, and the section composition table is stored in user maintenance table, institute
It states user maintenance Biao Niannei and is stored with customer substation information.
4. stabilization of power grids section short term curve prediction method according to claim 1, which is characterized in that step S4
In, switch state and disconnecting link status data are obtained from automation E file, and equipment connecting relation and direction of tide are from SCADA
It is obtained in Web database.
5. stabilization of power grids section short term curve prediction method according to claim 1, which is characterized in that step S4 is pressed
Following steps carry out:
S401. judge whether target 220kV line switching is listed: if so, judging the prediction of the target 220kV line switching
Load value is 0, and topology terminates；If it is not, then going to step S402；
S402. according to the connection relationship of equipment, obtain the neighbouring device connecting with current device, and be put into equipment topology table into
Row screening；
Entirely whether the armamentarium S403. obtained to step S402 topology and judge in equipment topology table all devices one by one
Portion's traversal: if so, topology terminates, topological process is exited, S410 is gone to step；If it is not, then pressing the judgement of step S404~S409
Rule continues topological judgement；
S404. judge whether current device is listed: if so, topology terminates, exiting topological process, be transferred to step S403；If it is not,
It is then transferred to step S405 and continues topological judgement；
S405. judge whether current device ownership substation with target 220kV line switching belongs to same substation: if so,
It is transferred to step S406 and continues topological judgement；If it is not, then terminating the topology judgement of current device, S403 is entered step；
S406. judge whether current device once occurred in father node: if so, topology terminates, exiting topological process, be transferred to step
S403；If it is not, being then transferred to step S407 continues topological judgement；
S407. judge whether current device belongs to main transformer: if so, stopping topology, the main transformer being included in and target 220kV line
In the same station 220kV main transformer of way switch connection, it is transferred to step S403；If it is not, being then transferred to step S408 continues topological judgement；
S408. judge whether current device belongs to switch: if so, being transferred to step S409 continues topological judgement；If it is not, then
Stop topology and is transferred to step S402；
S409. judge whether current device is closed: if so, stopping topology being transferred to step S403；If it is not, being then transferred to step
S402；
S410. the currently practical load of target 220kV line switching is obtained as the molecule for calculating proportionate relationship, and step S407 divides
The all denominators with the sum of station 220kV main transformer real-time load as proportionate relationship obtained are analysed, 220kV line switching is calculated
With the ratio of same station 220kV main transformer real-time load；
S411. it takes out from each 220kV main transformer load prediction data of power grid that step S1 is obtained and is obtained by step S407 analysis
220kV main transformer load prediction data, each 220kV main transformer load prediction data are added the ratio that summation is obtained multiplied by step S410,
Calculate the predicted load of target 220kV line switching；Step S401~S411 is repeated, the whole of composition section is calculated
The predicted load of 220kV line switching.
6. stabilization of power grids section short term curve prediction method according to any one of claims 1 to 5, feature exist
In in step S5, the positive and negative attribute of 220kV line switching real-time load value is obtained from SCADA Web database.
7. a kind of stabilization of power grids section short term curve prediction system, which is characterized in that including being written with claim 1 to 6
The program module of described in any item stabilization of power grids section short term curve prediction methods and be stored with automation E file,
SCADA Web database, aid decision-making system database, user maintenance table data-storage system, described program module is embedded in
Control module, the data-storage system are connected to control module, and the input terminal of control module is connected with recording module.
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| CN113972664A (en) * | 2021-10-29 | 2022-01-25 | 国网上海市电力公司 | Electric power data complement method and system |
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| CN110311369B (en) | 2020-09-25 |
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