CN105005946A - Power grid topology error identification method based on branch active power flow - Google Patents
Power grid topology error identification method based on branch active power flow Download PDFInfo
- Publication number
- CN105005946A CN105005946A CN201510424053.0A CN201510424053A CN105005946A CN 105005946 A CN105005946 A CN 105005946A CN 201510424053 A CN201510424053 A CN 201510424053A CN 105005946 A CN105005946 A CN 105005946A
- Authority
- CN
- China
- Prior art keywords
- switch
- power flow
- model
- effective power
- branch
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 16
- 230000015572 biosynthetic process Effects 0.000 claims description 5
- 238000013178 mathematical model Methods 0.000 claims description 3
- 238000005259 measurement Methods 0.000 abstract description 4
- 230000000694 effects Effects 0.000 description 2
- WCUXLLCKKVVCTQ-UHFFFAOYSA-M Potassium chloride Chemical compound [Cl-].[K+] WCUXLLCKKVVCTQ-UHFFFAOYSA-M 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000012850 discrimination method Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000010937 topological data analysis Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Landscapes
- Supply And Distribution Of Alternating Current (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention relates to a power grid topology error identification method based on the branch active power flow. The method includes following steps: reading a power grid model and measuring a section; generating a node branch model; merging a part of switches to a switch group; setting active power flow state quantities of the switches and the switch group; building a branch active power flow estimation model; and performing estimation by employing the weighted least absolute value or solving the estimation value by employing the weighted least squares. By adopting the method, the states of switch-on and switch-off of a switch are respectively estimated by employing the active power flow, the precision is high, and topology errors due to measurement error are effectively avoided.
Description
Technical field
The present invention relates to electrical network field, especially a kind of power network topology misidentification method based on branch road effective power flow.
Background technology
Power network topology mistake directly has influence on various result of calculation, Topology Error and open state closely related, before calculating, carry out on off state identification is the necessary means avoiding Topology Error.
For a long time, owing to being subject to electrical network collecting device, the impact of transmission channel each side, on off state mistake cannot effectively be avoided, and conventional discrimination method actual effect is unsatisfactory.Conventional on off state Identification and estimation Measures compare is simple, some simple Expert Rules are generally adopted to carry out identification, as whether there being the folding condition measuring and judge switch by switch both sides, the impact of collection accuracy is measured by SCADA, on off state is easily caused to judge by accident, cause Topology Error, affect yardman's decision-making.
Summary of the invention
The present invention will solve the shortcoming of above-mentioned prior art, provides a kind of and measures accurately based on the power network topology misidentification method of branch road effective power flow.
The present invention solves the technical scheme that its technical matters adopts: this power network topology misidentification method based on branch road effective power flow, is characterized in that comprising the following steps:
1) electric network model and measuring section is read;
2) electrical network physical model is converted to mathematical model;
3) carry out Network topology, generate node branch model;
4) according to switch or disconnecting link acquisition state, process respectively; For the identical switch of both sides topology point, and the switch that acquisition state is point carries out merging formation switches set;
5) to the branch road effective power flow initialization at switch and switches set place, the switch being point for acquisition state and switches set, its Branch Power Flow measures and is set to zero; Be the switch closed to acquisition state, measure as initial value using the collection of branch road effective power flow;
6) using branch road effective power flow as quantity of state, by electric pressure, plant stand structure switch effective power flow estimation model;
The estimation of weighting least absolute value or weighted least square is adopted to solve.
Inventing useful effect is: adopt method of the present invention, and switch divides the state of closing with switch to utilize effective power flow to estimate respectively, and precision is high, effectively prevent the Topology Error caused because measuring mistake.
Accompanying drawing explanation
Fig. 1 is schematic flow sheet of the present invention;
Embodiment
Below in conjunction with accompanying drawing, the invention will be further described:
As shown in Figure 1, this power network topology misidentification method based on branch road effective power flow, comprises the following steps:
1) electric network model and measuring section is read;
2) electrical network physical model is converted to mathematical model;
3) carry out Network topology, generate node branch model;
4) according to switch or disconnecting link acquisition state, process respectively; For the identical switch of both sides topology point, and the switch that acquisition state is point carries out merging formation switches set;
5) to the branch road effective power flow initialization at switch and switches set place, the switch being point for acquisition state and switches set, its Branch Power Flow measures and is set to zero; Be the switch closed to acquisition state, measure as initial value using the collection of branch road effective power flow;
6) using branch road effective power flow as quantity of state, by electric pressure, plant stand structure switch effective power flow estimation model;
7) estimation of weighting least absolute value or weighted least square is adopted to solve.
Specifically: carry out in two steps detecting Topology Error, the first step detects the switch that acquisition state is point, and second step is that the switch closed detects to acquisition state.
First from SCADA, electric network model and measuring section is obtained.
Secondly according to switch/disconnecting link acquisition state, carry out primary network topological analysis, generate topology point branch model.For acquisition state be point and the both sides switch that belongs to different topology point, then carry out the whether suspicious detection of state.Due to may exist multiple be in point state and the switch that both sides topology point is identical, therefore mergings formation switches set is carried out to these switches.Switches set is treated to the branch road that trend measurement is zero.Ignore the active loss of branch road, using branch road effective power flow as quantity of state, measure according to branch road effective power flow and each topological Kirchhoff's current law (KCL) constraint structure branch road effective power flow estimation model put.Branch road effective power flow estimation model is Linear Estimation model, can adopt weighting least absolute value estimate or weighted least square solve.Least absolute value estimates to have stronger Robustness least squares, and weighted least square then needs to carry out corresponding bad data recognition.No matter be based on weighted least-squares principle, or based on weighting least absolute value estimation principle, or based on information loss minimum principle, topology error identification problem mathematically all can be described as linear or Nonlinear Mixed Integer Programming Problem.Weighting least absolute value estimation model has stronger Robustness least squares, automatically the impact of bad data can be got rid of, and topology error identification problem can be described as Mixed integer linear programming, and ripe business Optimization Software (as CPLEX) can be utilized to solve.
For the switches set that acquisition state is point, if the absolute value of effective power flow estimated value is greater than certain amplitude, then think that the state of each switch is all suspicious in this switches set.
For the switch that acquisition state is conjunction, using branch road effective power flow estimated result as measurement, using switch effective power flow as quantity of state, by plant stand by electric pressure structure switch effective power flow estimation model.In this step, switch trend measures to be estimated participation, for the situation that switch is surveyed without tide flow, adds the puppet measurement that effective power flow value is 0, and participates in estimating with less weight, the observability of switch effective power flow during to ensure to occur switch ring.Weighting least absolute value method of estimation is adopted to estimate switch effective power flow.If switch trend estimated value is enough large, then think that acquisition state is credible, otherwise add the suspicious switch collection of candidate and detect further.
Above-mentioned branch road effective power flow estimation model is owing to have ignored Kirchhoff's second law constraint, and trend estimated result is approximately to the switch of zero, its deciliter state does not almost affect estimated result in the model.Consider Kirchhoff's second law constraint, namely adopt DC power flow estimation model to carry out a state estimation, and adopt method similar to the above, estimate switch effective power flow by plant stand by electric pressure.For the suspicious switch of candidate, if estimated result is approximately zero, illustrate that switch deciliter state does not almost affect the distribution of the trend of electrical network, on off state can not identification, thinks that acquisition state is correct; On the contrary, if estimated result exceedes certain value, illustrate that on off state is close to cause larger estimation residual error, think that on off state is suspicious.
In addition to the implementation, the present invention can also have other embodiments.All employings are equal to the technical scheme of replacement or equivalent transformation formation, all drop on the protection domain of application claims.
Claims (1)
1., based on a power network topology misidentification method for branch road effective power flow, it is characterized in that comprising the following steps:
1) electric network model and measuring section is read;
2) electrical network physical model is converted to mathematical model;
3) carry out Network topology, generate node branch model;
4) according to switch or disconnecting link acquisition state, process respectively; For the identical switch of both sides topology point, and the switch that acquisition state is point carries out merging formation switches set;
5) to the branch road effective power flow initialization at switch and switches set place, the switch being point for acquisition state and switches set, its Branch Power Flow measures and is set to zero; Be the switch closed to acquisition state, measure as initial value using the collection of branch road effective power flow;
6) using branch road effective power flow as quantity of state, by electric pressure, plant stand structure switch effective power flow estimation model;
7) estimation of weighting least absolute value or weighted least square is adopted to solve.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510424053.0A CN105005946A (en) | 2015-07-17 | 2015-07-17 | Power grid topology error identification method based on branch active power flow |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510424053.0A CN105005946A (en) | 2015-07-17 | 2015-07-17 | Power grid topology error identification method based on branch active power flow |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN105005946A true CN105005946A (en) | 2015-10-28 |
Family
ID=54378605
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510424053.0A Pending CN105005946A (en) | 2015-07-17 | 2015-07-17 | Power grid topology error identification method based on branch active power flow |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105005946A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107317394A (en) * | 2017-07-05 | 2017-11-03 | 广西电网有限责任公司玉林供电局 | Dispatching anti-misoperation method, device and system |
| CN108710036A (en) * | 2018-04-13 | 2018-10-26 | 广州穗华能源科技有限公司 | A kind of sampling element state evaluating method based on intelligent substation state estimation |
| CN110751423A (en) * | 2019-11-18 | 2020-02-04 | 广东电网有限责任公司 | State estimation service system, micro-service architecture and state estimation method |
-
2015
- 2015-07-17 CN CN201510424053.0A patent/CN105005946A/en active Pending
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107317394A (en) * | 2017-07-05 | 2017-11-03 | 广西电网有限责任公司玉林供电局 | Dispatching anti-misoperation method, device and system |
| CN107317394B (en) * | 2017-07-05 | 2019-12-27 | 广西电网有限责任公司玉林供电局 | Anti-misoperation method, device and system for scheduling operation ticket |
| CN108710036A (en) * | 2018-04-13 | 2018-10-26 | 广州穗华能源科技有限公司 | A kind of sampling element state evaluating method based on intelligent substation state estimation |
| CN108710036B (en) * | 2018-04-13 | 2021-05-25 | 广州穗华能源科技有限公司 | Sampling link state evaluation method based on intelligent substation state estimation |
| CN110751423A (en) * | 2019-11-18 | 2020-02-04 | 广东电网有限责任公司 | State estimation service system, micro-service architecture and state estimation method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Farshad et al. | A novel fault-location method for HVDC transmission lines based on similarity measure of voltage signals | |
| US10288667B2 (en) | Method and system for fault detection and faulted line identification in power systems using synchrophasors-based real-time state estimation | |
| CN103324847B (en) | Electrical Power System Dynamic bad data detection and identification method | |
| CN106646140B (en) | HVDC transmission line internal fault external fault recognition methods based on measurement wave impedance | |
| CN107453484B (en) | SCADA data calibration method based on WAMS information | |
| CN103838959A (en) | Method for applying partial least squares regression to power distribution network harmonic source positioning and detecting | |
| CN108562821B (en) | Method and system for determining single-phase earth fault line selection of power distribution network based on Softmax | |
| CN103197111B (en) | The comprehensive detection method of quantity of electricity of three-phase alternating current and testing circuit | |
| CN110289613A (en) | The identification of distribution net topology and line parameter circuit value discrimination method based on sensitivity matrix | |
| CN103941149B (en) | Electrified railway traction networks localization of fault method | |
| CN104836223A (en) | Power grid parameter error and bad data coordinated identification and estimation method | |
| CN111064180B (en) | Medium-voltage distribution network topology detection and identification method based on AMI (advanced mechanical arm) power flow matching | |
| CN102005757A (en) | Method for recognizing grid topology based on measurement spanning tree | |
| Azizi et al. | From available synchrophasor data to short-circuit fault identity: Formulation and feasibility analysis | |
| CN105005946A (en) | Power grid topology error identification method based on branch active power flow | |
| CN104297628A (en) | Method for detecting and positioning section faults of power distribution network containing DGs (distributed generators) | |
| CN105552887A (en) | Branch active power flow-based power network topology error identification method | |
| CN104316841A (en) | Method for identifying all line parameters by means of fault recording data | |
| Paladhi et al. | Accurate superimposed component estimation for improved relay performance during power swing | |
| Goh et al. | Dynamic estimation of power system stability in different Kalman filter implementations | |
| Ghaedi et al. | Modified WLS three-phase state estimation formulation for fault analysis considering measurement and parameter errors | |
| CN106646106B (en) | Electric network fault detection method based on outlier's detection technology | |
| CN107565549A (en) | A kind of Power System Network Topology Analysis Using method measured based on synchronized phasor | |
| Ccahuana et al. | Analysis of bad data detection in power system state estimators considering PMUs | |
| CN110780129A (en) | Electricity stealing and leakage positioning method based on current deviation analysis technology |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20151028 |
|
| WD01 | Invention patent application deemed withdrawn after publication |