CN112711905A - Wind power plant current collection line protection method based on clustering algorithm - Google Patents
Wind power plant current collection line protection method based on clustering algorithm Download PDFInfo
- Publication number
- CN112711905A CN112711905A CN202011537549.6A CN202011537549A CN112711905A CN 112711905 A CN112711905 A CN 112711905A CN 202011537549 A CN202011537549 A CN 202011537549A CN 112711905 A CN112711905 A CN 112711905A
- Authority
- CN
- China
- Prior art keywords
- fault
- clustering algorithm
- data
- power plant
- clustering
- 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
- 238000004422 calculation algorithm Methods 0.000 title claims abstract description 54
- 238000000034 method Methods 0.000 title claims abstract description 43
- 230000002238 attenuated effect Effects 0.000 claims description 10
- 230000000295 complement effect Effects 0.000 claims description 3
- 238000007499 fusion processing Methods 0.000 claims description 3
- 238000002759 z-score normalization Methods 0.000 claims 1
- 238000004458 analytical method Methods 0.000 abstract description 4
- 230000001012 protector Effects 0.000 abstract 2
- 238000004088 simulation Methods 0.000 description 5
- 238000010586 diagram Methods 0.000 description 4
- 238000004364 calculation method Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000007621 cluster analysis Methods 0.000 description 1
- 239000002131 composite material Substances 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000010606 normalization Methods 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/27—Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
-
- 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2113/00—Details relating to the application field
- G06F2113/06—Wind turbines or wind farms
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Evolutionary Computation (AREA)
- Health & Medical Sciences (AREA)
- Economics (AREA)
- Tourism & Hospitality (AREA)
- General Health & Medical Sciences (AREA)
- Geometry (AREA)
- Supply And Distribution Of Alternating Current (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Public Health (AREA)
- Computer Hardware Design (AREA)
- Software Systems (AREA)
- Water Supply & Treatment (AREA)
- General Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Marketing (AREA)
- Primary Health Care (AREA)
- Strategic Management (AREA)
- Artificial Intelligence (AREA)
- General Business, Economics & Management (AREA)
- Medical Informatics (AREA)
Abstract
A method for protecting current collecting line of wind power plant based on clustering algorithm includes setting up model of wind power plant according to actual wind power plant, setting short circuit fault at different position in model, inputting fault information to fault protector of clustering algorithm for standardization and clustering analysis to obtain fault clustering center and non-fault clustering center, utilizing protector of clustering algorithm to carry out standardization and judgment on fault information when actual wind power plant is fault so as to realize protection of current collecting line The method is simple and high in feasibility degree, and is suitable for large-scale popularization and application.
Description
Technical Field
The invention relates to the technical field of electric power, in particular to a method for protecting a current collecting line of a wind power plant based on a clustering algorithm.
Background
The known collecting line is one of the main devices for wind power plant and power grid interconnection, and the wiring form of the collecting line adopts a traditional radial wiring form and adopts a conventional three-section type current protection. When a fault occurs, the fault current of a current collection line is influenced by various factors such as the type of a fan, the running state of the fan and the like, the traditional relay protection is not applicable to configuration and setting, when a short circuit or disconnection fault occurs, if a protection device cannot timely and accurately act, the stable running of the whole wind power plant can be influenced, the power grid is greatly influenced, the wind power plant equipment can be damaged in serious conditions, large-scale off-grid accidents are caused, the wind power plant and even the power grid are greatly lost, and the requirement on the stability of electric energy cannot be met. For example, in some wind power bases in the middle and western parts of China, too-large-area off-grid accidents occur for many times, so that the generated power is lost, wherein the power is lost for many times because the relay protection cannot act in time. For example, an accident happens once in a wind farm with a spring, and the root cause is that the current collecting line of the wind farm cannot be rapidly tripped due to the fault. Therefore, the construction of relay protection inside the wind power plant must be strengthened.
Regarding the relay protection of the collecting line of the wind power plant, the following problems mainly exist at present:
(1) when short-circuit current calculation and relay protection setting calculation are carried out on a power system comprising a wind power plant, a fan is regarded as a common load, and the common load is directly cut off when a fault occurs, which is obviously incorrect because the short-circuit current generated by the fan is obviously not negligible when the fault occurs in the wind power plant;
(2) the wind power plant has the characteristics of randomness and volatility, and the fault current of the wind power plant is different from that of a thermal power plant, so that the wind power plant cannot be adjusted according to a traditional method.
Therefore, how to provide a method for protecting a collecting line of a wind power plant based on a clustering algorithm becomes a long-term technical appeal for the technical personnel in the field.
Disclosure of Invention
In order to overcome the defects in the background technology, the invention provides a method for protecting the current collecting line of the wind power plant based on a clustering algorithm.
In order to achieve the above purpose, the invention adopts the following technical scheme:
a method for protecting a collecting line of a wind power plant based on a clustering algorithm specifically comprises the following steps:
firstly, establishing a wind power plant model according to an actual wind power plant structure;
secondly, setting faults at different positions in the model to obtain a historical fault data set, and transmitting the historical fault data set to a clustering algorithm fault protection device;
thirdly, standardizing fault data through a clustering algorithm line protection device, and calculating by using a clustering algorithm to obtain a fault clustering center and a non-fault clustering center;
and fourthly, inputting the real-time fault data into a clustering algorithm fault protection device, standardizing, and performing protection judgment to realize line protection.
According to the wind power plant collector line protection method based on the clustering algorithm, fault data in the second step and the fourth step are composed of sub collector bus voltage, fault current power frequency components, attenuated fault current direct current components and rotating speed frequency components.
According to the method for protecting the current collecting line of the wind power plant based on the clustering algorithm, the fault data is selected by the following method:
after the fault occurs, the stator current of the doubly-fed wind turbine is as follows:
Id＝a1cos(w1t+f)+a2e-atcosf+a3e-atcos(wr+f)
wherein f is the initial phase angle;
a1，a2，a3is constant and is related to terminal drop voltage;
w1is the grid angular frequency;
wris the rotor angular frequency;
according to the formula, the stator fault current mainly comprises a power frequency component, an attenuated direct current component and a rotating speed frequency component, and the fact that complementary information on protection possibly exists among different fault characteristic quantities is considered, so that a steady-state component and a transient-state component of the short-circuit current of the fan are subjected to fusion processing, meanwhile, the offspring collector bus voltages of different dimensions are taken as discrimination factors for fault and non-fault identification to be comprehensively considered, the influence of interference signals on protection criteria is reduced, and therefore, the offspring collector bus voltages, the fault current power frequency component, the attenuated fault current direct current component and the rotating speed frequency component are selected as fault data.
According to the wind power plant collecting line protection method based on the clustering algorithm, fault data in the third step are standardized through a Z-score method.
According to the wind power plant collecting line protection method based on the clustering algorithm, the Z-score standardization is realized through the following formula:
the 3-dimensional data for n groups is as follows:
taking the first row of data as an example, first row average is found:
the standard deviation was then found:
finally, the normalized values are obtained:
the method for protecting the current collecting line of the wind power plant based on the clustering algorithm is implemented by the following steps in the third step:
A. randomly initializing 2 clustering center points, and defining the clustering center points as a fault center and a non-fault center;
B. traversing all the data, and dividing the data into clusters corresponding to the cluster centers with the closest distance by measuring the distance between the data and 2 cluster centers;
C. calculating the average value of each cluster as a new cluster center point;
D. repeating steps (B) and (C) until a preset standard is reached.
In the method for protecting the current collecting line of the wind power plant based on the clustering algorithm, in the fourth step, the protection judgment is that the distance between the standardized real-time fault data and the two clustering centers is judged according to the Manhattan distance, if the distance is close to the fault clustering center, the fault is in-line, and the protection action is performed, if the distance is close to the non-fault clustering center, the fault is out-line, and the protection is not performed.
The wind power plant current collection line protection method based on the clustering algorithm comprises the following steps: the system comprises at least one processor and a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors respectively realize the wind farm collecting line protection method based on the clustering algorithm.
By adopting the technical scheme, the invention has the following advantages:
the method can meet the selectivity requirement of current collection line protection, is beneficial to realizing low voltage ride through, ensures the stability of a power grid, and simultaneously can simply obtain the historical fault data again even if the structure of the wind power plant changes because the historical fault data is obtained by a model, so the method is high in visibility, simple and high in feasibility degree, and is suitable for large-scale popularization and application.
Drawings
FIG. 1 is a flow chart of the present invention;
FIG. 2 is a diagram of a simulation model of a wind power field in simulation analysis according to the present invention;
FIG. 3 is a diagram of a clustering algorithm in simulation analysis according to the present invention.
Detailed Description
The present invention will be explained in more detail by the following examples, which are not intended to limit the invention;
the invention relates to a method for protecting a current collecting line of a wind power plant based on a clustering algorithm, which specifically comprises the following steps:
firstly, establishing a wind power plant model according to an actual wind power plant structure;
secondly, setting faults at different positions in the model to obtain a historical fault data set, and transmitting the historical fault data set to a clustering algorithm fault protection device;
thirdly, standardizing fault data through a clustering algorithm line protection device, and calculating by using a clustering algorithm to obtain a fault clustering center and a non-fault clustering center; the fault data is normalized by the Z-score method, which is achieved by the following formula:
the 3-dimensional data for n groups is as follows:
taking the first row of data as an example, first row average is found:
the standard deviation was then found:
finally, the normalized values are obtained:
further, the clustering algorithm is realized by the following steps:
A. randomly initializing 2 clustering center points, and defining the clustering center points as a fault center and a non-fault center;
B. traversing all the data, and dividing the data into clusters corresponding to the cluster centers with the closest distance by measuring the distance between the data and 2 cluster centers;
C. calculating the average value of each cluster as a new cluster center point;
D. repeating steps (B) and (C) until a preset standard is reached.
Fourthly, inputting the real-time fault data into a clustering algorithm fault protection device, standardizing, and performing protection judgment to realize line protection; the protection judgment is to judge the distance between the standardized real-time fault data and two types of class centers through the Manhattan distance, if the distance is close to the fault class center, the fault is in-line fault, and the protection action is performed, if the distance is close to the non-fault class center, the fault is out-line fault, and the protection action is not performed.
In the second step and the fourth step, the fault data are composed of sub-generation collector bus voltage, fault current power frequency component, attenuated fault current direct current component and rotating speed frequency component, and the fault data are selected by the following method:
after the fault occurs, the stator current of the doubly-fed wind turbine is as follows:
Id＝a1cos(w1t+f)+a2e-atcosf+a3e-atcos(wr+f)
wherein f is the initial phase angle;
a1，a2，a3is constant and is related to terminal drop voltage;
w1is the grid angular frequency;
wris the rotor angular frequency;
according to the formula, the stator fault current mainly comprises a power frequency component, an attenuated direct current component and a rotating speed frequency component, and the fact that complementary information on protection possibly exists among different fault characteristic quantities is considered, so that a steady-state component and a transient-state component of the short-circuit current of the fan are subjected to fusion processing, meanwhile, the offspring collector bus voltages of different dimensions are taken as discrimination factors for fault and non-fault identification to be comprehensively considered, the influence of interference signals on protection criteria is reduced, and therefore, the offspring collector bus voltages, the fault current power frequency component, the attenuated fault current direct current component and the rotating speed frequency component are selected as fault data.
Further, the clustering algorithm line protection device comprises: the system comprises at least one processor and a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors respectively realize the wind farm collecting line protection method based on the clustering algorithm.
The basic working principle of the invention is as follows: aiming at the problem that the traditional protection can not meet the requirement of collection line selectivity, the invention provides a method for protecting collection lines of a wind power plant based on a clustering algorithm, and firstly, a wind power plant model is established according to the actual structure of the wind power plant by combining with attached figures 1, 2 and 3; then setting faults at different positions in the model to obtain a historical fault data set, and transmitting the historical fault data set to a clustering algorithm fault protection device; then, standardizing the data through a clustering algorithm line protection device, and calculating by using a clustering algorithm to obtain a fault clustering center and a non-fault clustering center; and finally, inputting the real-time fault data into a clustering algorithm fault protection device, standardizing, and performing protection judgment to realize line protection.
The wind power plant model established in the invention is shown in fig. 2, and is composed of 12 doubly-fed wind turbines, taking the protection of a current collection line L1 as an example, and the parameters of the wind turbines are shown in the following table:
setting short-circuit faults at intervals of 10% in different current collecting lines, selecting offspring current collecting bus voltage, fault current power frequency components, attenuated fault current direct current components and rotating speed frequency components under different fault working conditions as fault data to obtain a historical fault data set, sending the historical fault data set into a clustering algorithm fault protection device for standardization, and then performing clustering analysis to obtain a clustering algorithm diagram as shown in the second drawing, wherein the clustering centers of the clustering algorithm diagram are shown as follows (three fault data in small brackets corresponding to F and N are respectively the offspring current collecting bus voltage, the fault current power frequency components, the fault current direct current components and the rotating speed frequency components after standardization according to the sequence):
fault cluster center F (-1.2909, -1.2754, 1.2788);
non-failure class-based center N (0.6454, 0.6377, -0.6394);
carrying out simulation verification:
a set of real-time fault data is obtained, and after normalization, the values are as follows:
actual failure class: f. of1(-0.53，-0.47，0.74)f2(-1.81, -1.76, 1.55) actual non-failing class: n is1(0.36，0.34，-0.2)n2(0.84，0.86.-0.91)
n3(0.36，0.33.-0.186)n4(0.84，0.84，-0.89)
As can be seen from the manhattan criterion,
because of the fact that
Hence the real-time data point f1Judging the fault in the area by a cluster analysis method, and conforming to the reality;
in the same way, the method for preparing the composite material,
judging that the fault is in accordance with the actual condition;
According to the simulation, even if the data volume is not large, the fault information can be accurately judged, the selectivity requirement of current collection line protection is met, low voltage ride through is facilitated, and the stability of a power grid is guaranteed. The method realizes the protection of the current collecting line of the wind power plant by using the clustering algorithm, and is a method with high visibility, simplicity and high feasibility.
According to an embodiment of the present invention, there is also provided an electronic device including:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the aforementioned methods.
The present invention is not described in detail in the prior art.
The embodiments selected for the purpose of disclosing the invention, are presently considered to be suitable, it being understood, however, that the invention is intended to cover all variations and modifications of the embodiments which fall within the spirit and scope of the invention.
Claims (8)
1. A wind power plant current collection line protection method based on a clustering algorithm is characterized by comprising the following steps: the method specifically comprises the following steps: firstly, establishing a wind power plant model according to an actual wind power plant structure;
secondly, setting faults at different positions in the model to obtain a historical fault data set, and transmitting the historical fault data set to a clustering algorithm fault protection device;
thirdly, standardizing fault data through a clustering algorithm line protection device, and calculating by using a clustering algorithm to obtain a fault clustering center and a non-fault clustering center;
and fourthly, inputting the real-time fault data into a clustering algorithm fault protection device, standardizing, and performing protection judgment to realize line protection.
2. A wind farm collection line protection method based on clustering algorithm according to claim 1, characterized by: and the fault data in the second step and the fourth step consists of sub-generation collector bus voltage, fault current power frequency component, attenuated fault current direct current component and rotating speed frequency component.
3. A wind farm collection line protection method based on clustering algorithm according to claim 2, characterized by: the fault data is selected by the following method:
after the fault occurs, the stator current of the doubly-fed wind turbine is as follows:
Id＝a1cos(w1t+f)+a2e-atcos f+a3e-atcos(wr+f)
wherein f is the initial phase angle;
a1，a2，a3is constant and is related to terminal drop voltage;
w1is the grid angular frequency;
wris the rotor angular frequency;
according to the formula, the stator fault current mainly comprises a power frequency component, an attenuated direct current component and a rotating speed frequency component, and the fact that complementary information on protection possibly exists among different fault characteristic quantities is considered, so that a steady-state component and a transient-state component of the short-circuit current of the fan are subjected to fusion processing, meanwhile, the offspring collector bus voltages of different dimensions are taken as discrimination factors for fault and non-fault identification to be comprehensively considered, the influence of interference signals on protection criteria is reduced, and therefore, the offspring collector bus voltages, the fault current power frequency component, the attenuated fault current direct current component and the rotating speed frequency component are selected as fault data.
4. A wind farm collection line protection method based on clustering algorithm according to claim 1, characterized by: the fault data in the third step is normalized by the Z-score method.
5. A wind farm collection line protection method based on clustering algorithm according to claim 4, characterized by: the Z-score normalization is achieved by the following equation:
the 3-dimensional data for n groups is as follows:
taking the first row of data as an example, first row average is found:
the standard deviation was then found:
finally, the normalized values are obtained:
6. a wind farm collection line protection method based on clustering algorithm according to claim 1, characterized by: the clustering algorithm in the third step is realized by the following steps:
A. randomly initializing 2 clustering center points, and defining the clustering center points as a fault center and a non-fault center;
B. traversing all the data, and dividing the data into clusters corresponding to the cluster centers with the closest distance by measuring the distance between the data and 2 cluster centers;
C. calculating the average value of each cluster as a new cluster center point;
D. repeating steps (B) and (C) until a preset standard is reached.
7. A wind farm collection line protection method based on clustering algorithm according to claim 1, characterized by: and in the fourth step, the protection judgment is to judge the distance between the standardized real-time fault data and the two cluster centers through the Manhattan distance, if the distance is close to the fault cluster center, the fault is an in-line fault, and the protection action is performed, if the distance is close to the non-fault cluster center, the fault is an out-of-line fault, and the protection action is not performed.
8. A wind farm collection line protection method based on clustering algorithm according to claim 1, characterized by: the clustering algorithm line protection device comprises: the system comprises at least one processor and a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors respectively realize the wind farm collecting line protection method based on the clustering algorithm.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011537549.6A CN112711905A (en) | 2020-12-23 | 2020-12-23 | Wind power plant current collection line protection method based on clustering algorithm |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011537549.6A CN112711905A (en) | 2020-12-23 | 2020-12-23 | Wind power plant current collection line protection method based on clustering algorithm |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112711905A true CN112711905A (en) | 2021-04-27 |
Family
ID=75545391
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011537549.6A Pending CN112711905A (en) | 2020-12-23 | 2020-12-23 | Wind power plant current collection line protection method based on clustering algorithm |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112711905A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114221301A (en) * | 2021-12-03 | 2022-03-22 | 北方工业大学 | Alternating current micro-grid protection method and device considering photovoltaic low-voltage ride through characteristics |
| CN115021228A (en) * | 2022-07-19 | 2022-09-06 | 华北电力大学 | Wind field collection station interactive protection method and system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105846459A (en) * | 2016-04-12 | 2016-08-10 | 南京国电南自电网自动化有限公司 | Natural frequency and characteristic frequency combination based self-adaptive distance protection method |
| CN106786677A (en) * | 2017-03-29 | 2017-05-31 | 温州大学 | A kind of interconnected electric power system distributed dynamic matrix frequency control method of meter and wind-powered electricity generation |
| CN110609200A (en) * | 2019-09-20 | 2019-12-24 | 长沙理工大学 | Power distribution network earth fault protection method based on fuzzy metric fusion criterion |
| CN111564828A (en) * | 2020-06-11 | 2020-08-21 | 国网江西省电力有限公司电力科学研究院 | Distance pilot protection method suitable for double-fed fan output line |
| CN111769529A (en) * | 2020-07-28 | 2020-10-13 | 广东电网有限责任公司 | Grounding protection method |
-
2020
- 2020-12-23 CN CN202011537549.6A patent/CN112711905A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105846459A (en) * | 2016-04-12 | 2016-08-10 | 南京国电南自电网自动化有限公司 | Natural frequency and characteristic frequency combination based self-adaptive distance protection method |
| CN106786677A (en) * | 2017-03-29 | 2017-05-31 | 温州大学 | A kind of interconnected electric power system distributed dynamic matrix frequency control method of meter and wind-powered electricity generation |
| CN110609200A (en) * | 2019-09-20 | 2019-12-24 | 长沙理工大学 | Power distribution network earth fault protection method based on fuzzy metric fusion criterion |
| CN111564828A (en) * | 2020-06-11 | 2020-08-21 | 国网江西省电力有限公司电力科学研究院 | Distance pilot protection method suitable for double-fed fan output line |
| CN111769529A (en) * | 2020-07-28 | 2020-10-13 | 广东电网有限责任公司 | Grounding protection method |
Non-Patent Citations (1)
| Title |
|---|
| 赵国炫等: "基于K-means聚类分析的风电场集电线路保护方法", 《电力系统及其自动化学报》, no. 07, 30 July 2020 (2020-07-30), pages 1 - 8 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114221301A (en) * | 2021-12-03 | 2022-03-22 | 北方工业大学 | Alternating current micro-grid protection method and device considering photovoltaic low-voltage ride through characteristics |
| CN114221301B (en) * | 2021-12-03 | 2023-11-14 | 北方工业大学 | Alternating-current micro-grid protection method and device considering photovoltaic low-voltage ride through characteristics |
| CN115021228A (en) * | 2022-07-19 | 2022-09-06 | 华北电力大学 | Wind field collection station interactive protection method and system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107453401B (en) | Doubly-fed wind generator parameter identification method | |
| CN102799722B (en) | A kind of wind power plant low voltage ride-through capability emulation verification method | |
| CN112711905A (en) | Wind power plant current collection line protection method based on clustering algorithm | |
| CN104459540B (en) | Power-grid-impact-free detection method for low voltage ride through function of doubly-fed wind turbine generator system | |
| Jin et al. | Modeling of wind speeds inside a wind farm with application to wind farm aggregate modeling considering LVRT characteristic | |
| CN108667005B (en) | Power grid static and dynamic combination vulnerability assessment method considering new energy influence | |
| CN109901013B (en) | Method for judging fault direction of power distribution network by using polarity of current and voltage sudden change | |
| CN106651128A (en) | Power transmission and transformation system risk early warning method | |
| CN109301814B (en) | Method and system for analyzing wind power capacity of access power grid | |
| CN110880743A (en) | Kendel rank correlation-based pilot protection method for outgoing line of wind power plant | |
| CN111082749B (en) | Photovoltaic string running state identification method, device and storage medium | |
| Elizondo et al. | Model reduction, validation, and calibration of wind power plants for dynamic studies | |
| CN106410862B (en) | Based on the active wind power plant single machine equivalence method for restoring slope correction | |
| CN110165644B (en) | New energy station pilot protection method based on transient current time-frequency characteristics | |
| CN114201483A (en) | Photovoltaic array fault diagnosis method based on statistical modeling | |
| CN111080169B (en) | Active power distribution network risk assessment method under extreme weather | |
| CN107886227B (en) | Method for evaluating disaster resistance improvement degree of power distribution network | |
| Qi et al. | Dynamic equivalent modeling of direct-drive PMSG wind farms based on the transient active power response characteristics | |
| CN115563876A (en) | Wind power plant dynamic equivalent modeling method based on step-by-step parameter identification | |
| CN113848347A (en) | Health state detection method for wind meter of wind driven generator | |
| CN112345880A (en) | Double-fed wind power plant outgoing line fault phase selection method | |
| Khalel et al. | Dynamic security assessment for the power system in the presence of wind turbines | |
| Gupta et al. | Apparent power loss based equivalent model of wind farm collector system | |
| CN115932477B (en) | Multi-source information fusion overhead transmission line fault cause diagnosis method and system | |
| CN113949343B (en) | Method and device for detecting photovoltaic power generation equipment, electronic equipment and storage medium |
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 | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20210427 |