CN112966358A - Active power distribution network state sensing method based on data patching - Google Patents
Active power distribution network state sensing method based on data patching Download PDFInfo
- Publication number
- CN112966358A CN112966358A CN202110180321.4A CN202110180321A CN112966358A CN 112966358 A CN112966358 A CN 112966358A CN 202110180321 A CN202110180321 A CN 202110180321A CN 112966358 A CN112966358 A CN 112966358A
- Authority
- CN
- China
- Prior art keywords
- real
- data
- time
- measurement
- state
- 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.)
- Granted
Links
- 238000009826 distribution Methods 0.000 title claims abstract description 40
- 238000000034 method Methods 0.000 title claims abstract description 40
- 238000005259 measurement Methods 0.000 claims abstract description 87
- 238000004364 calculation method Methods 0.000 claims abstract description 27
- 230000008447 perception Effects 0.000 claims abstract description 25
- 238000004458 analytical method Methods 0.000 claims abstract description 11
- 230000011664 signaling Effects 0.000 claims abstract description 9
- 230000001502 supplementing effect Effects 0.000 claims abstract description 8
- 238000007781 pre-processing Methods 0.000 claims abstract description 6
- 238000002347 injection Methods 0.000 claims description 6
- 239000007924 injection Substances 0.000 claims description 6
- 230000008569 process Effects 0.000 claims description 5
- 230000008859 change Effects 0.000 claims description 3
- 239000000203 mixture Substances 0.000 claims 1
- 239000002994 raw material Substances 0.000 claims 1
- 239000000243 solution Substances 0.000 description 11
- 238000010586 diagram Methods 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 230000008901 benefit Effects 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 2
- 238000012217 deletion Methods 0.000 description 2
- 230000037430 deletion Effects 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 230000008439 repair process Effects 0.000 description 2
- 230000002411 adverse Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 238000012417 linear regression Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 230000035699 permeability Effects 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/18—Network design, e.g. design based on topological or interconnect aspects of utility systems, piping, heating ventilation air conditioning [HVAC] or cabling
-
- 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
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
-
- 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2113/00—Details relating to the application field
- G06F2113/04—Power grid distribution networks
-
- 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
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
-
- 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
- Y04S10/40—Display of information, e.g. of data or controls
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Power Engineering (AREA)
- General Physics & Mathematics (AREA)
- Geometry (AREA)
- Computer Hardware Design (AREA)
- Mathematical Optimization (AREA)
- Pure & Applied Mathematics (AREA)
- Computational Mathematics (AREA)
- Evolutionary Computation (AREA)
- General Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Mathematical Analysis (AREA)
- Supply And Distribution Of Alternating Current (AREA)
- Remote Monitoring And Control Of Power-Distribution Networks (AREA)
Abstract
The invention discloses an active power distribution network state perception method based on data patching, which comprises the steps of utilizing network topology software to analyze network topology in real time, and establishing a network real-time topology model according to an analysis result; according to the telemetering and remote signaling information of the SCADA system, branch parameters and node parameters are extracted from the real-time acquired measurement information, and data preprocessing is carried out on the branch parameters and the node parameters; detecting and eliminating the preprocessed bad data based on historical measurement in a state perception database, and repairing and supplementing the measurement information acquired in real time; inputting the precision control range of the state sensing calculation parameters and the measurement information to the state sensing calculation module 100 to complete the state sensing calculation; the invention ensures the integrity and correctness of the real-time data acquired by the power grid, realizes the estimation and analysis of the real-time running state of the power grid and improves the observability of the power grid.
Description
Technical Field
The invention relates to the technical field of intelligent power distribution networks, in particular to a state perception method of an active power distribution network based on data patching.
Background
The continuous increase of the permeability of the distributed power supply brings challenges to the safe and stable operation of the active power distribution network; in order to ensure the safety, stability and economy of the operation of the power system, the power system dispatching center needs to quickly, accurately and comprehensively grasp the actual operation state of the power system, so that countermeasures can be timely and accurately provided for solving various problems in the operation.
At present, an SCADA (Supervisory Control And Data Acquisition, Data Acquisition And monitoring system) is widely applied to an electric power system to acquire And transmit Data, wherein errors may be generated in the processes of Data Acquisition, analog-to-digital conversion, transmission And the like, And each process may be interfered or failed sometimes, so that a certain difference is unavoidably generated between Data received by a computer of a dispatching center And real Data, which may affect the judgment result of the dispatching center on the operation state of the electric power system, generate a decision error, And sometimes cause a serious result.
Disclosure of Invention
This section is for the purpose of summarizing some aspects of embodiments of the invention and to briefly introduce some preferred embodiments. In this section, as well as in the abstract and the title of the invention of this application, simplifications or omissions may be made to avoid obscuring the purpose of the section, the abstract and the title, and such simplifications or omissions are not intended to limit the scope of the invention.
The present invention has been made in view of the above-mentioned conventional problems.
Therefore, the invention provides an active power distribution network state sensing method based on data patching, which can avoid the adverse effect of errors generated when the SCADA collects and transmits data.
In order to solve the technical problems, the invention provides the following technical scheme: the method comprises the steps of utilizing network topology software to analyze network topology in real time, and establishing a network real-time topology model according to an analysis result; according to the telemetering and remote signaling information of the SCADA system, branch parameters and node parameters are extracted from the real-time acquired measurement information, and data preprocessing is carried out on the branch parameters and the node parameters; detecting and eliminating the preprocessed bad data based on historical measurement in a state perception database, and repairing and supplementing the measurement information acquired in real time; and inputting the precision control range of the state perception calculation parameters and the measurement information to the state perception calculation module 100 to complete the state perception calculation.
As a preferred solution of the active power distribution network state sensing method based on data patching according to the present invention, wherein: the network real-time topology model comprises a topological graph formed by analyzing the whole active power distribution network into line and point combination according to the topological connection relation of the electrical equipment of the active power distribution network obtained by analysis; and performing network topology connection analysis according to the power supply node, the switch node, the load node and the new energy node, and establishing a topology island structure by taking the power supply node as an initial node.
As a preferred solution of the active power distribution network state sensing method based on data patching according to the present invention, wherein: and the data preprocessing comprises the step of estimating the voltage amplitude and the phase angle on each bus of the SCADA system by utilizing the telemetering and remote signaling information of the SCADA system so as to calculate all line tidal current values and node injection quantities, including active power and reactive power distribution on each line and voltage and injection current of each node.
As a preferred solution of the active power distribution network state sensing method based on data patching according to the present invention, wherein: the bad data comprises an ineffective measurement value collected by the SCADA system, a missing measurement value not collected and unreasonable bad data in real-time measurement data.
As a preferred solution of the active power distribution network state sensing method based on data patching according to the present invention, wherein: detecting the bad data comprises storing the real-time measurement information into a real-time measurement data table through an information recording module 200, traversing the real-time measurement data table, and then recording the equipment numbers and the measurement types corresponding to the invalid measurement values and the missing measurement values in the real-time measurement information; the historical measurements are stored in a historical measurement data table through the information recording module 200, the historical measurement data table is traversed, and the equipment measurements with corresponding numbers are searched and recorded.
As a preferred solution of the active power distribution network state sensing method based on data patching according to the present invention, wherein: repairing and supplementing the measurement information acquired in real time comprises taking a measurement value of a corresponding device measurement type with the latest time scale, and completely supplementing the real-time measurement data table; and setting a limit range of bad data identification, traversing the updated real-time measurement data table, judging the electrical quantity in the updated real-time measurement data table, and repairing data which do not meet the judgment requirement through a load estimation strategy according to the corresponding historical measurement so as to perfect the real-time measurement data table.
As a preferred solution of the active power distribution network state sensing method based on data patching according to the present invention, wherein: the state perception calculation module 100 includes that the state perception calculation module 100 is connected to the information recording module 200, and the state perception calculation module 100 calculates the state perception by using a weighted least square algorithm and then sends a state perception result to the information recording module 200.
As a preferred solution of the active power distribution network state sensing method based on data patching according to the present invention, wherein: the method further comprises the step that the information recording module 200 stores the received state sensing result into an operation information table, and the state change process of the active power distribution network is checked in real time through the operation information table.
The invention has the beneficial effects that: according to the invention, error information caused by random interference when the SCADA system collects the power grid measurement information is considered, invalid measurement data and missing measurement data are repaired based on historical measurement data, and the integrity of real-time data collected by the power grid is ensured; bad data are distinguished and repaired, so that the correctness of real-time data collected by a power grid is ensured; meanwhile, according to the repaired complete and correct real-time data, based on the real-time topological model of the power grid, the state sensing calculation is carried out on the power grid by using a weighted least square method, the real-time running state estimation and analysis of the power grid are realized, and the observability of the power grid is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments 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 these drawings without inventive exercise. Wherein:
fig. 1 is a schematic flowchart of a method for sensing a state of an active power distribution network based on data patching according to a first embodiment of the present invention;
fig. 2 is a schematic diagram of a program implementation architecture of a method for sensing a state of an active power distribution network based on data patching according to a first embodiment of the present invention;
fig. 3 is a schematic grid structure diagram of a state sensing method for an active power distribution network based on data patching according to a second embodiment of the present invention;
fig. 4 is a schematic voltage diagram illustrating a real-time operation of an electrical power system of an active power distribution network state sensing method based on data patching according to a second embodiment of the present invention.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, specific embodiments accompanied with figures are described in detail below, and it is apparent that the described embodiments are a part of the embodiments of the present invention, not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making creative efforts based on the embodiments of the present invention, shall fall within the protection scope of the present invention.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways than those specifically described and will be readily apparent to those of ordinary skill in the art without departing from the spirit of the present invention, and therefore the present invention is not limited to the specific embodiments disclosed below.
Furthermore, reference herein to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one implementation of the invention. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments.
The present invention will be described in detail with reference to the drawings, wherein the cross-sectional views illustrating the structure of the device are not enlarged partially in general scale for convenience of illustration, and the drawings are only exemplary and should not be construed as limiting the scope of the present invention. In addition, the three-dimensional dimensions of length, width and depth should be included in the actual fabrication.
Meanwhile, in the description of the present invention, it should be noted that the terms "upper, lower, inner and outer" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of describing the present invention and simplifying the description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation and operate, and thus, cannot be construed as limiting the present invention. Furthermore, the terms first, second, or third are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
The terms "mounted, connected and connected" in the present invention are to be understood broadly, unless otherwise explicitly specified or limited, for example: can be fixedly connected, detachably connected or integrally connected; they may be mechanically, electrically, or directly connected, or indirectly connected through intervening media, or may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
Example 1
Referring to fig. 1 to 2, a first embodiment of the present invention provides an active power distribution network state sensing method based on data patching, including:
s1: and (4) analyzing the network topology in real time by using network topology software, and establishing a network real-time topology model according to an analysis result.
It should be noted that a Network Topology (Network Topology) refers to a physical layout for interconnecting various devices by using a transmission medium, and refers to a specific physical, i.e., real, or logical, i.e., virtual arrangement manner among members constituting a Network; network topology analysis software may employ Visual Route Lite tools.
The network topology is analyzed in real time by using network topology software, the wiring mode and the running state of the power grid are determined, and a network real-time topology model is established based on the wiring mode and the running state.
Specifically, the steps of establishing the network real-time topology model are as follows:
(1) analyzing the whole active power distribution network into a line-point combined topological graph according to the topological connection relation of the electrical equipment of the active power distribution network obtained by analyzing network topology software;
(2) and performing network topology connection analysis according to the power supply node, the switch node, the load node and the new energy node, and establishing a topology island structure taking the power supply node as an initial node.
S2: according to the telemetering and remote signaling information of the SCADA system, branch parameters and node parameters are extracted from the real-time acquired measurement information, and data preprocessing is carried out on the branch parameters and the node parameters.
The SCADA system is a computer-based automation system for controlling and scheduling production processes that can monitor and control the on-site operating equipment.
Collecting and updating the remote measuring and remote signaling information of the SCADA system once in each scanning period, and storing the information into a database, wherein the scanning period is 2 seconds; and according to the telemetering and remote signaling information acquired by the SCADA system, the branch parameters and the node parameters are extracted from the measurement information of nearby power equipment.
Further, the extracted parameters are preprocessed, specifically, voltage amplitude values and phase angles on all buses of the system are estimated by utilizing telemetering and remote signaling information of the SCADA system, and therefore all line tidal current values and node injection quantities including active power and reactive power distribution on all lines and voltage and injection current of all nodes are calculated.
S3: and detecting and eliminating bad data based on historical measurement in the state perception database, and repairing and supplementing the measurement information acquired in real time.
It should be noted that the objects for detecting and repairing bad data mainly include invalid measurement values collected by the SCADA system, missing measurement values that are not collected, and unreasonable bad data in real-time measurement data.
Storing the historical measurement into a historical measurement data table through the information recording module 200, traversing the historical measurement data table, and searching and recording the equipment measurement with the corresponding number;
the real-time measurement information is stored in the real-time measurement data table through the information recording module 200, the real-time measurement data table is traversed, then the equipment numbers and the measurement types corresponding to invalid measurement and non-collected missing measurement in the real-time measurement information are recorded, the measurement value corresponding to the equipment measurement type with the latest time scale is obtained, and the real-time measurement data table is completely supplemented.
Setting a limit range for identifying bad data, judging the data to be bad data when an outline Coefficient (Silhouette coeffient) is more than 0.7, and judging the data to be good data if the outline Coefficient (Silhouette coeffient) is not more than 0.7; traversing the updated real-time measurement data table, judging the electric quantities such as voltage, current, active power, reactive power and the like in the real-time measurement table, and repairing data which do not meet the judgment requirement by a load estimation method according to corresponding historical measurement, wherein the formula is as follows:
wherein S (t) is data after repair, C (t) is data before repair, t0、t1Are data points.
And recording the repaired data into a real-time measurement data table.
S4: the accuracy control range and the measurement information of the state sensing calculation parameters are input to the state sensing calculation module 100, and the state sensing calculation is completed.
The state perception calculation module 100 is connected to the information recording module 200, and the state perception calculation module 100 calculates state perception by using an optimized weighted least square algorithm, which has an advantage that any statistical characteristic of a random variable is not required, and is an estimation method using the minimum sum of squares of differences between a measured value and an estimated value as a target criterion.
Specifically, the optimized weighted least squares algorithm comprises the following steps:
(1) the weights W of all sample points are calculated using a gaussian kernel:
wherein, wnThe weight in the regression for the nth sample.
(2) Performing weighted linear regression on the ith sample according to the weight W to obtain a fitted linear equation:
Y＝Kα+c
wherein,
c＝0.77W
ynis the nth estimated value, Y is the observation vector, alpha is the unknown parameter vector, c is the constant, xnIs the nth sample point.
(3) Setting an objective function to obtain an estimated value of alpha:
(4) an estimate is obtained for each sample.
Further, the state sensing calculation module 100 stores the state sensing result in a database and sends the state sensing result to the information recording module 200, the information recording module 200 stores the received state sensing result in an operation information table, and a worker can check the state change process of the active power distribution network in real time through the operation information table.
Referring to fig. 2, in order to achieve the purpose of decoupling the database from the algorithm code of the state sensing calculation module 100 and the information recording module 200 of this embodiment, the present invention adopts a Bridge design mode (Bridge Pattern) when the code is implemented, and the CAlgoDb is used as an interface class to call the service provided by the CAlgoLite interface; wherein the CAlgOLITE is focused on the algorithm and decoupled from the database objects; the CAlgoDb also provides an interface responsible for providing data preparation for the CAlgoLite.
A typical database, when describing a record, contains the following two-dimensional information:
{ belonged table identification, table record subscript }
According to this, a data structure is established:
struct OID
{
int m _ Id; // affiliated table identification ID
int m _ Sub; // record subscript
}；
In this embodiment, based on the program implementation framework, the power system state sensing algorithm based on the least square method is encapsulated, and the real-time operating electrical quantity of the power system can be calculated and obtained by manually setting the precision control range of the state sensing calculation parameter and inputting the repaired real-time measurement data, so as to analyze and evaluate the real-time operating state of the power system.
Example 2
In order to verify and explain the technical effect adopted in the method, the embodiment selects the circuit breaker power data of a certain distribution network to perform statistical calculation so as to verify the real effect of the method.
The related statistical information of the power data of partial time interval before data arrangement is shown in table 1, and the related information of the data optimized by the method is shown in table 2.
Table 1: and the statistical information table related to the power data of the partial time period before data arrangement.
| 7 | 8 | 9 | 10 | 11 | |
| Bad data (a) | 1657 | 1652 | 1712 | 1639 | 1593 |
| Effective rate (%) | 81.96％ | 82.36％ | 82.41％ | 82.71％ | 81..32％ |
| Missing data (person) | 2436 | 3542 | 2110 | 2430 | 1631 |
| Deletion Rate (%) | 27.50％ | 39.99％ | 23.82％ | 27.96％ | 18.21％ |
Table 2: and the statistical information table is related to the power data of the partial time interval after data sorting.
| 7 | 8 | 9 | 10 | 11 | |
| Bad data (a) | 1721 | 1413 | 1294 | 1934 | 1694 |
| Effective rate (%) | 85.34％ | 87.21％ | 86.26％ | 89.51％ | 84.58％ |
| Missing data (person) | 1254 | 2103 | 1963 | 2137 | 1862 |
| Deletion Rate (%) | 12.93％ | 31.69％ | 19.52％ | 24.96％ | 11.30％ |
As can be seen from tables 1 and 2, after the bad data is repaired by the method, the effective rate of the data is improved, the missing rate of the data is reduced, and the correctness of the real-time data acquired by the power grid is ensured.
Selecting a 20kV TC # 1 feeder line of a certain transformer substation for state sensing calculation, wherein the area comprises 5 load points and 1 rooftop photovoltaic, and a grid structure is shown in FIG. 3; the precision control range of the state perception calculation parameters is set to be 0.95, the repaired real-time measurement data is input, the voltage of the real-time operation of the net rack is obtained through calculation, and the real-time operation state of the power system is observed in real time as shown in fig. 4.
It should be noted that the above-mentioned embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, which should be covered by the claims of the present invention.
Claims (8)
1. A method for sensing the state of an active power distribution network based on data patching is characterized in that: comprises the steps of (a) preparing a mixture of a plurality of raw materials,
utilizing network topology software to analyze the network topology in real time, and establishing a network real-time topology model according to the analysis result;
according to the telemetering and remote signaling information of the SCADA system, branch parameters and node parameters are extracted from the real-time acquired measurement information, and data preprocessing is carried out on the branch parameters and the node parameters;
detecting and eliminating the preprocessed bad data based on historical measurement in a state perception database, and repairing and supplementing the measurement information acquired in real time;
and inputting the precision control range of the state perception calculation parameters and the measurement information to the state perception calculation module 100 to complete the state perception calculation.
2. The active power distribution network state awareness method based on data patching of claim 1, wherein: the real-time topology model of the network comprises,
analyzing the whole active power distribution network into a line-point combined topological graph according to the topological connection relation of the electrical equipment of the active power distribution network obtained by analysis;
and performing network topology connection analysis according to the power supply node, the switch node, the load node and the new energy node, and establishing a topology island structure by taking the power supply node as an initial node.
3. The active power distribution network state awareness method based on data patching according to claim 1 or 2, characterized by: the pre-processing of the data includes,
and estimating the voltage amplitude and the phase angle on each bus of the SCADA system by utilizing the telemetering and remote signaling information of the SCADA system, thereby calculating all line tidal current values and node injection quantities, including active power and reactive power distribution on each line and voltage and injection current of each node.
4. The active power distribution network state awareness method based on data patching of claim 2, wherein: the bad data includes at least one of,
the system comprises an invalid measurement value collected by the SCADA system, an unrecovered missing measurement value and unreasonable bad data in real-time measurement data.
5. The active power distribution network state sensing method based on data patching according to claim 2 or 4, wherein: the detecting the bad data includes detecting that the bad data includes,
storing the real-time measurement information into a real-time measurement data table through an information recording module 200, traversing the real-time measurement data table, and then recording the equipment numbers and the measurement types corresponding to the invalid measurement values and the missing measurement values in the real-time measurement information;
the historical measurements are stored in a historical measurement data table through the information recording module 200, the historical measurement data table is traversed, and the equipment measurements with corresponding numbers are searched and recorded.
6. The active power distribution network state awareness method based on data patching of claim 5, wherein: repairing and supplementing the real-time acquired metrology information includes,
taking a measurement value corresponding to the measurement type of the equipment with the latest time mark, and completely supplementing the real-time measurement data table;
and setting a limit range of bad data identification, traversing the updated real-time measurement data table, judging the electrical quantity in the updated real-time measurement data table, and repairing data which do not meet the judgment requirement through a load estimation strategy according to the corresponding historical measurement so as to perfect the real-time measurement data table.
7. The active power distribution network state awareness method based on data patching according to claim 1 or 6, wherein: the state-aware computing module 100 includes,
the state perception calculation module 100 is connected to the information recording module 200, and the state perception calculation module 100 calculates the state perception by using a weighted least square algorithm and then sends a state perception result to the information recording module 200.
8. The active power distribution network state awareness method based on data patching of claim 7, wherein: also comprises the following steps of (1) preparing,
the information recording module 200 stores the received state sensing result into an operation information table, and checks the state change process of the active power distribution network in real time through the operation information table.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110180321.4A CN112966358B (en) | 2021-02-08 | 2021-02-08 | Active power distribution network state sensing method based on data patching |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110180321.4A CN112966358B (en) | 2021-02-08 | 2021-02-08 | Active power distribution network state sensing method based on data patching |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112966358A true CN112966358A (en) | 2021-06-15 |
| CN112966358B CN112966358B (en) | 2024-07-12 |
Family
ID=76284618
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110180321.4A Active CN112966358B (en) | 2021-02-08 | 2021-02-08 | Active power distribution network state sensing method based on data patching |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112966358B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116979532A (en) * | 2023-09-25 | 2023-10-31 | 国网江苏省电力有限公司苏州供电分公司 | Power system dynamic state estimation observability evaluation method and system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103413044A (en) * | 2013-08-13 | 2013-11-27 | 东北电网有限公司 | Substation measurement information based method for estimating local topology of electric power system |
| CN103745109A (en) * | 2014-01-10 | 2014-04-23 | 国家电网公司 | Bad data detection and identification method based on measurement of PMU (Phasor Measurement Unit) and measurement of SCADA (Supervisory Control and Data Acquisition) |
| CN104134999A (en) * | 2014-08-06 | 2014-11-05 | 国家电网公司 | Power-distribution-network measurement effectiveness analysis practical calculation method based on multiple data sources |
| WO2016078477A1 (en) * | 2014-11-18 | 2016-05-26 | 国电南瑞科技股份有限公司 | Transformer substation three-phase linear generalized state estimation method |
| CN106845845A (en) * | 2017-01-23 | 2017-06-13 | 中国电力科学研究院 | A kind of photovoltaic generation multi-stage combination status assessing system and appraisal procedure |
-
2021
- 2021-02-08 CN CN202110180321.4A patent/CN112966358B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103413044A (en) * | 2013-08-13 | 2013-11-27 | 东北电网有限公司 | Substation measurement information based method for estimating local topology of electric power system |
| CN103745109A (en) * | 2014-01-10 | 2014-04-23 | 国家电网公司 | Bad data detection and identification method based on measurement of PMU (Phasor Measurement Unit) and measurement of SCADA (Supervisory Control and Data Acquisition) |
| CN104134999A (en) * | 2014-08-06 | 2014-11-05 | 国家电网公司 | Power-distribution-network measurement effectiveness analysis practical calculation method based on multiple data sources |
| WO2016078477A1 (en) * | 2014-11-18 | 2016-05-26 | 国电南瑞科技股份有限公司 | Transformer substation three-phase linear generalized state estimation method |
| CN106845845A (en) * | 2017-01-23 | 2017-06-13 | 中国电力科学研究院 | A kind of photovoltaic generation multi-stage combination status assessing system and appraisal procedure |
Non-Patent Citations (3)
| Title |
|---|
| 刘峰;: "EMS中状态估计模块生产运行及实用化问题分析", 电力自动化设备, no. 04, pages 122 - 127 * |
| 刘成君;马山牧;翁嘉明;柴铁洪;: "一种实用的配电网状态估计方法", 供用电, no. 12, pages 46 - 49 * |
| 孙谦等: "基于特性矩阵分层分析的短期母线负荷预测坏数据处理策略", 《电工技术学报》, vol. 28, no. 7, pages 228 - 230 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116979532A (en) * | 2023-09-25 | 2023-10-31 | 国网江苏省电力有限公司苏州供电分公司 | Power system dynamic state estimation observability evaluation method and system |
| CN116979532B (en) * | 2023-09-25 | 2024-01-23 | 国网江苏省电力有限公司苏州供电分公司 | Power system dynamic state estimation observability evaluation method and system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112966358B (en) | 2024-07-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN114640173B (en) | Early warning model of transformer and generator based on many characteristic quantities | |
| CN104134999B (en) | Distribution network based on multi-data source measures the practical method of calculation of efficiency analysis | |
| CN103413044B (en) | A kind of electric system local topology method of estimation based on transformer station's measurement information | |
| CN105976257A (en) | Power grid vulnerability evaluation method based on membership function fuzzy comprehensive evaluation method | |
| CN109752629B (en) | Intelligent diagnosis method and system for power grid measurement problems | |
| CN108199891B (en) | Cps network attack identification method based on artificial neural network multi-angle comprehensive decision | |
| CN109034461A (en) | A kind of voltage dip Stochastic prediction method based on actual electric network monitoring information | |
| CN110348114B (en) | Non-precise fault identification method for power grid completeness state information reconstruction | |
| CN113985339B (en) | Error diagnosis method and system for intelligent ammeter, equipment and storage medium | |
| CN113239132A (en) | Online out-of-tolerance identification method for voltage transformer | |
| CN118378545B (en) | Metering topology simulation method and system under complex operation mode of power grid | |
| CN114089262B (en) | Intelligent error analysis model construction method for small-power intelligent ammeter | |
| CN111881124A (en) | Data processing method and system based on state estimation of improved algorithm | |
| CN113904322A (en) | Low-voltage distribution network topology generation method based on current and voltage | |
| CN111999692A (en) | Multi-table error calibration method and device | |
| CN113376476A (en) | PHM-based operation and maintenance system and method for medium and low voltage power distribution network | |
| CN110412417B (en) | Micro-grid data fault diagnosis method based on intelligent power monitoring instrument | |
| CN118330505B (en) | Line leakage current monitoring and leakage protection method based on wireless communication | |
| CN106443253A (en) | Power transmission line parameter identification method based on PMU (phasor measurement unit) data | |
| CN109829246B (en) | Line parameter identification method based on parameter comprehensive suspicion | |
| CN112966358A (en) | Active power distribution network state sensing method based on data patching | |
| CN114442543A (en) | Computer monitoring method suitable for early warning of hydropower station fault | |
| CN111999691A (en) | Error calibration method and error calibration device for metering sensor device | |
| CN112446801B (en) | System and method for improving data quality of power system | |
| CN108092272A (en) | A kind of voltage stabilization on-line monitoring method based on the Kalman filtering that fades |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |