CN109886539A - Based on not knowing multiattribute intelligent distribution network self-healing property evaluation method and system - Google Patents
Based on not knowing multiattribute intelligent distribution network self-healing property evaluation method and system Download PDFInfo
- Publication number
- CN109886539A CN109886539A CN201910026323.0A CN201910026323A CN109886539A CN 109886539 A CN109886539 A CN 109886539A CN 201910026323 A CN201910026323 A CN 201910026323A CN 109886539 A CN109886539 A CN 109886539A
- Authority
- CN
- China
- Prior art keywords
- self
- healing
- index
- statistical data
- level index
- 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
- 238000011156 evaluation Methods 0.000 title claims abstract description 56
- 238000009826 distribution Methods 0.000 title claims abstract description 34
- 238000000034 method Methods 0.000 claims description 29
- 239000011159 matrix material Substances 0.000 claims description 19
- 230000008569 process Effects 0.000 claims description 11
- 238000007781 pre-processing Methods 0.000 claims description 10
- 238000010606 normalization Methods 0.000 claims description 8
- 238000012545 processing Methods 0.000 claims description 6
- 238000011161 development Methods 0.000 abstract description 5
- 230000008901 benefit Effects 0.000 description 7
- 230000018109 developmental process Effects 0.000 description 4
- 238000011084 recovery Methods 0.000 description 4
- 230000009286 beneficial effect Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000009471 action Effects 0.000 description 1
- 230000032683 aging Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 239000002131 composite material Substances 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000009413 insulation Methods 0.000 description 1
- 238000002955 isolation Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Landscapes
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The present invention provides be based on not knowing multiattribute intelligent distribution network self-healing property evaluation method and system, comprising: establishes power grid self-healing assessment indicator system, wherein index system includes first class index, two-level index and three-level index；The objective statistical data during operation of power networks are obtained to calculate the numerical value of three-level index according to index system, and objective statistical data are pre-processed；The weight of each three-level index is calculated according to pretreated objective statistical data；Overall merit is carried out to obtain evaluation result to the self-healing property of smart grid according to weight and numerical value.Evaluation method of the invention is comprehensively objective, and has focused on the Project Realization of power grid self-healing property on this basis, and methodological science is reasonable, meaningful to the exploratory development of power grid self-healing level.
Description
Technical Field
The invention relates to the technical field of power systems, in particular to an uncertain multi-attribute-based self-healing evaluation method and system for an intelligent power distribution network.
Background
Self-healing is an important characteristic of the smart grid, and the content of the self-healing comprises self-regulation optimization in a normal state and fault detection, isolation and self-recovery in a fault state, so that the influence of abnormity or fault on the power grid is reduced to the maximum extent by manual intervention as little as possible. Since a large amount of investment is required for improving the self-healing property, it is necessary to evaluate the economic benefits brought by the self-healing property.
The self-healing evaluation is carried out on the intelligent power distribution network, so that the self-healing of different intelligent power grids can be compared, and the investment decision of the power grids is facilitated; meanwhile, the self-healing performance of different areas of the power grid can be evaluated, and the areas with the self-healing performance needing to be enhanced can be obtained.
In summary, the self-healing evaluation of the intelligent power distribution network at home and abroad is less, the objective and comprehensive evaluation is less, and the method is not beneficial to the current exploration and practice of the benign and healthy development of the intelligent power distribution network in China, so that how to evaluate the self-healing of the intelligent power distribution network is an urgent problem to be solved.
Disclosure of Invention
In view of the above, the invention aims to provide an uncertain multi-attribute-based self-healing evaluation method and system for an intelligent power distribution network.
In a first aspect, an embodiment of the present invention provides a self-healing evaluation method for an intelligent distribution network based on uncertain multiple attributes, including:
establishing an index system for evaluating the self-healing performance of the smart power grid, wherein the index system comprises a first-level index, a second-level index and a third-level index;
acquiring objective statistical data in the power grid operation process according to the index system to calculate the numerical value of the three-level index, and preprocessing the objective statistical data;
calculating the weight of each three-level index according to the preprocessed objective statistical data;
and comprehensively evaluating the self-healing performance of the smart grid according to the weight and the numerical value to obtain an evaluation result.
With reference to the first aspect, an embodiment of the present invention provides a first possible implementation manner of the first aspect, where the primary index is a self-healing property of a smart grid, and the secondary index includes a user-based index, a grid-based index, and a social-based index.
With reference to the first possible implementation manner of the first aspect, an embodiment of the present invention provides a second possible implementation manner of the first aspect, where the user-based indicator includes a self-healing speed, a self-healing rate, and a self-healing sustainable time coverage rate, the grid-based indicator includes a self-healing control operation complexity and a self-healing investment cost-to-effect ratio, and the social-based indicator includes a distributed power access rate.
With reference to the second possible implementation manner of the first aspect, an embodiment of the present invention provides a third possible implementation manner of the first aspect, where the self-healing speed is based on self-healing speeds of different load categories, where the load categories include a strict load, a sensitive load, and a normal load, the self-healing speed includes a primary speed, a secondary speed, a tertiary speed, and a quaternary speed, and each load category corresponds to four self-healing speeds.
With reference to the first aspect, an embodiment of the present invention provides a fourth possible implementation manner of the first aspect, where the preprocessing the objective statistical data includes:
forming an initial matrix according to the objective statistical data;
carrying out normalization processing on the initial matrix to obtain a normalized matrix;
and carrying out normalization processing on the normalized matrix to obtain a normalized matrix.
With reference to the fourth possible implementation manner of the first aspect, the embodiment of the present invention provides a fifth possible implementation manner of the first aspect, wherein the calculating a weight of each of the three-level indicators according to the preprocessed objective statistical data includes:
and calculating information entropy according to the normalization matrix, and calculating the weight vector of each three-level index according to the information entropy.
With reference to the fifth possible implementation manner of the first aspect, an embodiment of the present invention provides a sixth possible implementation manner of the first aspect, where the comprehensively evaluating the self-healing performance of the smart grid according to the weight and the value to obtain an evaluation result includes:
and comprehensively evaluating the self-healing performance of the smart power grid according to a multi-attribute decision method theory.
In a second aspect, an embodiment of the present invention provides a self-healing evaluation system for an intelligent distribution network based on uncertain multiple attributes, including:
the index system establishing unit is used for establishing an intelligent power grid self-healing evaluation index system, wherein the index system comprises a first-level index, a second-level index and a third-level index;
the first calculation unit is used for acquiring objective statistical data in the power grid operation process according to the index system to calculate the numerical value of the three-level index, and preprocessing the objective statistical data;
the second calculating unit is used for calculating the weight of each three-level index according to the preprocessed objective statistical data;
and the multi-attribute evaluation unit is used for comprehensively evaluating the self-healing performance of the smart grid according to the weight and the value to obtain an evaluation result.
The invention provides an uncertain multi-attribute-based self-healing evaluation method and system for an intelligent power distribution network, which comprises the following steps of: establishing an index system for evaluating the self-healing performance of the smart power grid, wherein the index system comprises a first-level index, a second-level index and a third-level index; acquiring objective statistical data in the power grid operation process according to an index system to calculate the numerical value of a three-level index, and preprocessing the objective statistical data; calculating the weight of each three-level index according to the preprocessed objective statistical data; and comprehensively evaluating the self-healing performance of the smart power grid according to the weight and the value to obtain an evaluation result. The embodiment of the invention respectively considers the self-healing property under the interfered condition and the self-healing property under the fault condition, considers the investment of the power grid on the self-healing property and the social benefit of the self-healing property while considering the self-healing property, and evaluates the engineering realization which comprehensively and simultaneously pays attention to the self-healing property. The SMART principle is followed for each index, and a specific and definite obtaining method is given, so that objective index attributes can be obtained. By adopting the uncertain multi-attribute evaluation method, the evaluation result can be more accurate and reliable.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of a self-healing evaluation method for an intelligent distribution network based on uncertain multiple attributes according to an embodiment of the present invention;
fig. 2 is a schematic diagram of an index system according to an embodiment of the present invention.
Detailed Description
To make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
At present, the self-healing evaluation of the intelligent power distribution network at home and abroad is less, the objective and comprehensive evaluation is less, and the method is not beneficial to the current exploration and practice of the benign and healthy development of the intelligent power distribution network in China, so that the problem to be solved urgently is how to evaluate the self-healing of the intelligent power distribution network. Based on the method and the system for evaluating the self-healing performance of the intelligent power distribution network based on the uncertain multiple attributes, provided by the embodiment of the invention, the evaluation method is comprehensive and objective, the engineering realization of the self-healing performance of the power grid is emphasized on the basis, the method is scientific and reasonable, and the method and the system have significance for exploratory development of the self-healing level of the intelligent power grid.
The technical background of the self-healing of the intelligent power distribution network is further explained here.
Distribution automation detects fault information through an intelligent distribution terminal on the basis of communication, and positions, isolates and eliminates faults. By remote control of the intelligent switch, several seconds to tens of seconds are generally needed for isolating faults, and several tens of seconds to several minutes are generally needed for recovering power supply. The method and the device provide technical support for self-healing of the smart power grid and provide a data source for evaluation indexes of the self-healing.
The fault can be obtained through a substation protection and fault recording device, and the load power failure condition can be obtained through a power distribution terminal and an intelligent electric meter. The SCADA system can collect alarm information such as voltage out-of-limit when the power grid normally operates, and alarm information such as action protection and switch tripping caused by power grid faults. Therefore, the objective data acquisition of the embodiment of the invention has certain availability.
Faults such as short circuit, disconnection and the like can occur to all primary equipment of the power system due to external force, insulation aging, overvoltage, misoperation, design and manufacture defects and the like in the operation process. Since the self-healing evaluation is performed in the fault state, if the fault never occurs in the area, the self-healing evaluation is not performed, and therefore, before the self-healing evaluation is performed, it is necessary to evaluate the fault condition of each part of the smart grid. In a series of fault indexes of the smart power grid, the fault rate has the greatest influence on self-healing evaluation, and is most direct. The self-healing requirement on the power grid is higher at places with higher fault rates, and the self-healing requirement on the power grid is lower at places with lower fault rates. The embodiments of the present invention will be specifically explained below.
The first embodiment is as follows:
referring to fig. 1, the method for evaluating the self-healing performance of the intelligent power distribution network based on uncertain multiple attributes comprises the following steps:
step S101, establishing an index system for evaluating the self-healing performance of the smart power grid, wherein the index system comprises a first-level index, a second-level index and a third-level index;
step S102, objective statistical data in the power grid operation process are obtained according to an index system to calculate the numerical value of a three-level index, and the objective statistical data are preprocessed;
step S103, calculating the weight of each three-level index according to the preprocessed objective statistical data;
and S104, comprehensively evaluating the self-healing performance of the smart grid according to the weight and the value to obtain an evaluation result.
Specifically, referring to fig. 2, the primary index is self-healing of the smart grid, and the secondary indexes include user-based indexes, grid-based indexes, and social-based indexes. The user-based indexes comprise self-healing speed, self-healing rate and self-healing sustainable time coverage rate, the grid-based indexes comprise self-healing control operation complexity and self-healing input cost-effect ratio, and the social-based indexes comprise distributed power supply access rate. Here, the stability is improved for society due to self-healing, and the internet access (microgrid) of the distributed power supply is improved. Meanwhile, the more distributed power sources the smart power grid accommodates, the higher the self-healing capability requirement of the power grid is, and the self-healing performance of the power grid can be reflected to a certain extent.
It should be noted that the self-healing speed is based on self-healing speeds of different load categories, the load categories include strict load, sensitive load and ordinary load, the self-healing speed includes a primary speed, a secondary speed, a tertiary speed and a quaternary speed, and each load category corresponds to four self-healing speeds.
Self-healing speed (speech type): considering that the influence degrees of the fault time on different loads are different, the loads are divided into ordinary loads, sensitive loads and strict loads. The common load refers to a load with less loss and social influence caused by power interruption, such as common lighting, household appliances and the like; the sensitive load refers to a load which is influenced by several cycles of power supply interruption, such as a variable frequency speed regulation device and the like. The strict load means a load which has a particularly high power supply requirement and is seriously affected by a cycle power interruption, such as a computer system of a bank and a security center.
The self-healing speed required by different loads is different, and the evaluation indexes of the self-healing speed for different loads are also different. The self-healing speed index is divided into four grades: first-order speed (millisecond-order, self-healing within one cycle), second-order speed (cycle-order, more than one cycle, within tens of milliseconds), third-order speed (second-order, self-healing within several seconds), and fourth-order speed (minute-order, self-healing within 3 minutes). It can be seen that the recovery within the first-level speed has little influence on the strict load; the speed is recovered in the second-level speed, the strict load is influenced, and the influence on the sensitive load is small; the sensitive load is influenced by recovery within three-level speed; the recovery within the four-stage speed influences the normal operation of the sensitive load. If the self-healing is not performed within the four-level speed, the self-healing is not performed. The self-healing time can be obtained through the fault recording device. Table 1 shows the load types and corresponding self-healing speed evaluation comparison tables.
TABLE 1 load class and corresponding self-healing speed evaluation comparison table
The calculation of the self-healing rate (benefit type) needs to consider the importance level of the load and the size of the load. The self-healing sustainable time coverage rate (profitability) is that when a fault occurs, the microgrid may still be connected to the grid or may be operated off the grid. In off-grid operation, the sustainable operation time of the microgrid needs to be considered. The complexity (cost type) of the self-healing control operation is measured by the switching times, and the more the switching times are, the more the self-healing operation is complex, and the longer the service life of the equipment is. The self-healing investment cost to effect ratio (cost type) is the loss of self-healing reduction/self-healing equipment investment cost. The distributed power access rate (profitability) is then the maximum load in the microgrid/system maximum load in a given period.
Specifically, the self-healing rate is calculated by the following formula:
（1）
wherein,、、the weight coefficients representing the loads at each stage,、、representing the actual recovered loads at each level,、、representing the loads at all stagesThe original load demand at the moment.Representing the allowed self-healing time, set to 3 min.
Further, preprocessing the objective statistical data comprises:
forming an initial matrix according to the objective statistical data;
carrying out normalization processing on the initial matrix to obtain a normalized matrix;
and carrying out normalization processing on the normalized matrix to obtain a normalized matrix.
Further, step S103 includes:
and calculating the information entropy according to the normalized matrix, and calculating the weight vector of each three-level index according to the information entropy.
It should be noted that, in the embodiment of the present invention, based on an uncertain multi-attribute evaluation method, a multi-attribute evaluation method based on an improved entropy weight method is adopted for an index whose weight and attribute value are both real numbers.
Although the entropy weight method is objective and highly applicable, when all entropy values are close to 1, even a slight difference causes the entropy weight to be changed by multiples, so that the weight of the embodiment of the invention deviates from the meaning of the entropy weight method, and therefore the weight of the embodiment of the inventionThe calculation of (c) is improved as follows.
（2）
Wherein,is shown asThe entropy value of each of the indicators,is the average of all entropy values that are not 1.
（3）
（4）
For the index (self-healing speed index) with the weight and the attribute value both being languages, a multi-attribute evaluation method based on an LWM operator is adopted.
Is provided withAnda scheme set and an attribute set, respectively. The evaluator gives the protocolIn attributeLanguage assessment valueAnd obtaining a language assessment matrixThe weight vector of the attribute is。
Evaluating matrices using LWM operator pairsTo middleAggregating the line language evaluation information to obtain a decision schemeComposite attributeEvaluation value：。
The invention provides an uncertain multi-attribute-based self-healing evaluation method for an intelligent power distribution network, which comprises the following steps of: establishing an index system for evaluating the self-healing performance of the smart power grid, wherein the index system comprises a first-level index, a second-level index and a third-level index; acquiring objective statistical data in the power grid operation process according to an index system to calculate the numerical value of a three-level index, and preprocessing the objective statistical data; calculating the weight of each three-level index according to the preprocessed objective statistical data; and comprehensively evaluating the self-healing performance of the smart power grid according to the weight and the value to obtain an evaluation result. The evaluation method is comprehensive and objective, pays attention to the engineering realization of the self-healing performance of the power grid on the basis, is scientific and reasonable, and has significance for exploratory development of the self-healing level of the intelligent power grid.
Example two:
the self-healing evaluation system of the intelligent power distribution network based on uncertain multiple attributes comprises:
the index system establishing unit is used for establishing an intelligent power grid self-healing evaluation index system, wherein the index system comprises a first-level index, a second-level index and a third-level index;
the first calculation unit is used for acquiring objective statistical data in the power grid operation process according to an index system to calculate the numerical value of a three-level index and preprocessing the objective statistical data;
the second calculating unit is used for calculating the weight of each three-level index according to the preprocessed objective statistical data;
and the multi-attribute evaluation unit is used for comprehensively evaluating the self-healing performance of the smart grid according to the weight and the value to obtain an evaluation result.
The self-healing evaluation system of the intelligent distribution network based on the uncertain multiple attributes, provided by the embodiment of the invention, has the same technical characteristics as the self-healing evaluation method of the intelligent distribution network based on the uncertain multiple attributes, so that the same technical problems can be solved, and the same technical effects can be achieved.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the system and the apparatus described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present invention, which are used for illustrating the technical solutions of the present invention and not for limiting the same, and the protection scope of the present invention is not limited thereto, although the present invention is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the embodiments of the present invention, and they should be construed as being included therein. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (8)
1. An uncertain multi-attribute-based self-healing evaluation method for an intelligent power distribution network is characterized by comprising the following steps:
establishing an index system for evaluating the self-healing performance of the smart power grid, wherein the index system comprises a first-level index, a second-level index and a third-level index;
acquiring objective statistical data in the power grid operation process according to the index system to calculate the numerical value of the three-level index, and preprocessing the objective statistical data;
calculating the weight of each three-level index according to the preprocessed objective statistical data;
and comprehensively evaluating the self-healing performance of the smart grid according to the weight and the numerical value to obtain an evaluation result.
2. The self-healing evaluation method for the intelligent distribution network based on the uncertain multiple attributes as claimed in claim 1, wherein the primary indexes are self-healing of the intelligent distribution network, and the secondary indexes comprise user-based indexes, grid-based indexes and social-based indexes.
3. The self-healing evaluation method for the intelligent power distribution network based on the uncertain multiple attributes as claimed in claim 2, wherein the user-based indexes comprise self-healing speed, self-healing rate and self-healing duration coverage rate, the grid-based indexes comprise self-healing control operation complexity and self-healing input cost-to-effect ratio, and the social-based indexes comprise distributed power access rate.
4. The method according to claim 3, wherein the self-healing speed is based on different load categories, the load categories include severe load, sensitive load and normal load, and the self-healing speed includes a primary speed, a secondary speed, a tertiary speed and a quaternary speed.
5. The method for evaluating the self-healing performance of the intelligent distribution network based on the uncertain multiple attributes as recited in claim 1, wherein the preprocessing the objective statistical data comprises:
forming an initial matrix according to the objective statistical data;
carrying out normalization processing on the initial matrix to obtain a normalized matrix;
and carrying out normalization processing on the normalized matrix to obtain a normalized matrix.
6. The method according to claim 5, wherein the calculating the weight of each of the three-level indexes according to the preprocessed objective statistical data comprises:
and calculating information entropy according to the normalization matrix, and calculating the weight vector of each three-level index according to the information entropy.
7. The method for evaluating the self-healing performance of the intelligent power distribution network based on the uncertain multiple attributes as claimed in claim 6, wherein the comprehensively evaluating the self-healing performance of the intelligent power distribution network according to the weight and the value to obtain an evaluation result comprises:
and comprehensively evaluating the self-healing performance of the smart power grid according to a multi-attribute decision method theory.
8. The utility model provides an intelligent power distribution network self-healing evaluation system based on uncertain multiattribute which characterized in that includes:
the index system establishing unit is used for establishing an intelligent power grid self-healing evaluation index system, wherein the index system comprises a first-level index, a second-level index and a third-level index;
the first calculation unit is used for acquiring objective statistical data in the power grid operation process according to the index system to calculate the numerical value of the three-level index, and preprocessing the objective statistical data;
the second calculating unit is used for calculating the weight of each three-level index according to the preprocessed objective statistical data;
and the multi-attribute evaluation unit is used for comprehensively evaluating the self-healing performance of the smart grid according to the weight and the value to obtain an evaluation result.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910026323.0A CN109886539A (en) | 2019-01-11 | 2019-01-11 | Based on not knowing multiattribute intelligent distribution network self-healing property evaluation method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910026323.0A CN109886539A (en) | 2019-01-11 | 2019-01-11 | Based on not knowing multiattribute intelligent distribution network self-healing property evaluation method and system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109886539A true CN109886539A (en) | 2019-06-14 |
Family
ID=66925957
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910026323.0A Pending CN109886539A (en) | 2019-01-11 | 2019-01-11 | Based on not knowing multiattribute intelligent distribution network self-healing property evaluation method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109886539A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112016838A (en) * | 2020-08-31 | 2020-12-01 | 广东电网有限责任公司 | Method and system for calculating contribution rate of power distribution network energy efficiency index system and terminal equipment |
| CN113055237A (en) * | 2021-05-12 | 2021-06-29 | 广东电网有限责任公司 | Distribution network main station cooperative self-healing reliability determination method and device and storage medium |
| CN113131615A (en) * | 2021-04-20 | 2021-07-16 | 广东电网有限责任公司 | Self-healing technology evaluation method and system for distribution network master station |
-
2019
- 2019-01-11 CN CN201910026323.0A patent/CN109886539A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112016838A (en) * | 2020-08-31 | 2020-12-01 | 广东电网有限责任公司 | Method and system for calculating contribution rate of power distribution network energy efficiency index system and terminal equipment |
| CN113131615A (en) * | 2021-04-20 | 2021-07-16 | 广东电网有限责任公司 | Self-healing technology evaluation method and system for distribution network master station |
| CN113055237A (en) * | 2021-05-12 | 2021-06-29 | 广东电网有限责任公司 | Distribution network main station cooperative self-healing reliability determination method and device and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110346717B (en) | Artificial intelligent on-line monitoring system and method for high-voltage circuit breaker | |
| JP5452613B2 (en) | Power grid supply interruption and failure status management | |
| CN106570784B (en) | Voltage monitoring integrated model | |
| US20150002186A1 (en) | Power grid outage and fault condition management | |
| CN110429714B (en) | Cloud platform intelligent power distribution system based on big data | |
| CN104701831A (en) | Power distribution network self-healing control method | |
| CN109886539A (en) | Based on not knowing multiattribute intelligent distribution network self-healing property evaluation method and system | |
| US10310495B2 (en) | Systems and methods for monitoring automation systems | |
| CN111049266B (en) | Intelligent second-level power restoration method and system for regulation and control service | |
| CN107871202A (en) | A kind of system adequacy evaluation method of meter and multi-voltage grade | |
| CN110493031A (en) | A kind of substation control system network device state on-line monitoring method | |
| WO2020171814A1 (en) | Event selection for power grid disturbance | |
| CN111582838B (en) | Substation typical information table extraction method based on SCD file | |
| Islam et al. | A review on adaptive power system protection schemes for future smart and micro grids, challenges and opportunities | |
| CN113376553A (en) | Intelligent discrimination method and system for three-phase four-wire metering string current loop wiring | |
| CN107732902A (en) | Power distribution network economical operation monitoring and evaluation method | |
| CN111598377A (en) | Method and system for acquiring regional power grid reference risk on line | |
| Cai et al. | Study on reliability assessment of distribution networks containing distributed power supplies | |
| CN106022950B (en) | Power distribution network secondary equipment type identification method and system | |
| Rao et al. | Online monitoring of power grid intelligent voltage stability considering potential factors | |
| CN113011047A (en) | Reliability analysis method based on secondary system of intelligent substation of 220kV or below | |
| Abanihi et al. | Modeling and evaluation of system reliability for auchi distribution network | |
| Pashaei et al. | Adaptive Centralized Protection Scheme Using Clustering Algorithms for Offline Settings Calculations | |
| Ruiz Flores | ADMS technology: The challenges of modeling to operating electrical systems with digital twins | |
| Jadhav et al. | Review on Data Compression Methods of Smart Grid Power System Using Wavelet Transform |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| WD01 | Invention patent application deemed withdrawn after publication | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20190614 |