CN110535144A - The intelligent distribution network toughness quantitative analysis method of the load containing polymorphic type under dusty wind weather - Google Patents
The intelligent distribution network toughness quantitative analysis method of the load containing polymorphic type under dusty wind weather Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/12—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load
- H02J3/14—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load by switching loads on to, or off from, network, e.g. progressively balanced loading
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- 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
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B70/00—Technologies for an efficient end-user side electric power management and consumption
- Y02B70/30—Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as climate change mitigation technology in the buildings sector, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
- Y02B70/3225—Demand response systems, e.g. load shedding, peak shaving
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- 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
- Y04S20/00—Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
- Y04S20/20—End-user application control systems
- Y04S20/222—Demand response systems, e.g. load shedding, peak shaving
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Abstract
The present invention relates to the intelligent distribution network toughness quantitative analysis methods of the load containing polymorphic type under dusty wind weather, include the following steps: to simulate dust storm wind field and obtain each point wind speed, the load effect of power distribution network is calculated according to wind speed and direction, respectively obtain distribution network line fault rate and shaft tower failure rate, the failure rate for calculating electric distribution network overhead wire, obtains the scene that power distribution network under extreme weather at a time breaks down；Assign each stage load different weights according to load importance；Whether the system line after judgement is broken down overloads, and implements off-load measure to existing load when circuit overload；Day part load loss is sequentially completed calculating by the load reduction for going out current scene according to weight calculation, and then the average aggregate load of calculated load is cut down, and calculates the toughness index of power distribution network.The present invention preferably solves the problems, such as that electric energy supply pressure is big under dusty wind weather, effectively improves the anti-disaster ability of power distribution network.
Description
Technical field
The invention belongs to negative containing polymorphic type under intelligent distribution network toughness quantitative analysis tech field more particularly to dusty wind weather
The intelligent distribution network toughness quantitative analysis method of lotus.
Background technique
In recent years, many natural calamities and unreasonable manual operation result in extensive continuous power failure, give electric system
Unprecedented challenge is brought, wherein influence of the extreme weather to electric system is generally difficult to resist.South China in 2008
Snow disaster destroys the electric power facility of 13 provinces and cities, and more than 129 routes are impaired, and 14,660,000 family families have a power failure；2016, river
Su Sheng is attacked by cyclone, and 13.5 ten thousand family families have a power failure.Although the occurrence frequency of extreme weather is lower, to electric system
Caused by destroy it is often bigger, therefore, in order to analyze influence of the extreme weather to electric system, and to the effective of disaster countermeasure
Property evaluated and tested, " toughness " concept be introduced into electric system to assess electric system reply extreme weather ability.Power distribution network
Toughness is mainly reflected in support and recovery capability of the system to important load under extreme weather, deeply probes into it, is conducive to protect
Hinder power generation, improves the ability that disaster is resisted in electric system.How to realize and intelligent distribution network toughness under extreme weather is determined
Amount analysis is one difficult point urgently to be resolved of current power industry.
Currently, expert is mainly unfolded in terms of three for the research of power distribution network toughness both at home and abroad.Some scholars focus on
The research that extreme weather influences distribution network carries out frequency analysis to various extreme weather conditions, and is based on various extreme days
Gas situation constructs the Temporal And Spatial Distribution Model between meteorological condition and electric network fault to the extent of the destruction of electric system；Some scholars are special
It infuses in the building of electric system toughness evaluation system, their some are based on wind and loading condiction to transmission line malfunction probability to electricity
The toughness of Force system is assessed, and some, which evaluates different electric power toughness based on load frequency loss and expected loss, to be enhanced
The validity of measure；Furthermore the scholar having is dedicated to improving the project study of electric system toughness, and someone constructs three perfecting by stage
Model simultaneously proposes the method for determining optimal enhancing position and enhancing strategy, it is thus proposed that for battery energy storage and photovoltaic power generation
Optimum position method improves electric system toughness by improving extreme weather come the accessibility of temporary electrical power and power capacity,
Somebody proposes micro-capacitance sensor optimal location models, which has determined the best size and location of micro-capacitance sensor in power grid, with maximum
The toughness of change system.
At present for the anti-disaster ability that the tough Journal of Sex Research of power distribution network is to assess all loads under extreme weather mostly.
As long as however, there is a certain proportion of important load of enough power supply in power distribution network, it is not necessary to guarantee extreme weather conditions
Under power supply at full capacity.For this problem, the invention proposes the power distribution networks based on load importance under a kind of extreme weather
Toughness evaluation method.
Summary of the invention
It is an object of the invention to overcome the deficiencies of the prior art and provide guarantee certain proportion under the conditions of a kind of dusty wind weather
The power distribution network toughness quantitative analysis method of important load power supply, it is big preferably to solve electric energy supply pressure under dusty wind weather
The problem of, effectively improve the anti-disaster ability of power distribution network.
The present invention solves its technical problem and adopts the following technical solutions to achieve:
The intelligent distribution network toughness quantitative analysis method of the load containing polymorphic type, includes the following steps: under dusty wind weather
S1, the meteorological data according to dusty wind weather simulate dust storm wind field using Batts wind-field model and are obtained each
Point wind speed, using following formula:
Wherein: V is dust storm wind speed, and wind direction is the upper tangential direction counterclockwise of simulation circle, RmaxFor maximum wind speed radius,
For the wind speed of maximum wind speed radius, R is distance of the point to be studied to dust bowl point；
S2, the load effect P that power distribution network is calculated according to wind speed and direction, using following formula:
Wherein, D is the outer diameter of distribution wire, and α is wind evil attacking lung, μscIt is wire shaped coefficient, μzIt is that wind pressure height becomes
Change coefficient, θ is the angle of wind direction and route；
S3, assume power distribution network in distribution network line tensile strength and shaft tower bending strength Normal Distribution, base
In the normpdf f of the bending strength of the tensile strength and shaft tower of distribution network lineR(x) and power distribution network facility
Load effect P, distribution network line fault rate P can be respectively obtainedlWith shaft tower failure rate Pp, following formula:
Wherein, the value of μ and δ can be obtained by material strength test, μ, μ1、μpFor mathematic expectaion, δ, δ1、δpFor standard deviation；
X is the tensile strength of distribution network line or the bending strength of shaft tower；σ1For the tensile strength of route, MpThe bending strength of shaft tower；σg
Be distribution network line highest hitch point by big wind-induced pressure, the value be highest hitch point tension and wire sectional area it
Than directly proportional to the vector sum of wind-force and gravity；MTFor shaft tower root bending moment caused by route stress, which is the wind lotus of route
Carry with bending moment vector caused by the wind load of shaft tower and；
Under S4, route normal operating condition, route and shaft tower are worked normally, and can be equivalent to series model, in turn
Calculate the failure rate P of electric distribution network overhead wirek(V), using following formula:
Wherein, Pk(V) be overhead transmission line k failure rate, n is the shaft tower quantity on overhead transmission line k, and m is on overhead transmission line k
Route number of segment, ppik(V) be upper i-th shaft tower of route k failure rate, pljk(V) be jth section route on route k failure rate；
S5, the failure rate of overhead transmission line is added to the failure field that day part under dusty wind weather is simulated in monte carlo method
Scape obtains the scene that power distribution network under extreme weather at a time breaks down；
S6, load in power distribution network is divided into several grades, assigns each stage load different weights according to load importance；Sentence
It is disconnected break down after system line whether overload, when circuit overload, implements off-load measure to existing load；According to weight calculation
The load reduction of current scene out:
Wherein,For i-th of load reduction of t moment under j scene；For the corresponding weight of i-th of load；For the j scene of the corresponding t moment of i-th of load；Indicate i-th of load under j scene t moment cut down state two into
Variable processed,Value is that 0 or 1,0 expression load is not cut down, and 1 indicates that load is cut down；It is i-th of load of t moment in j scene
Under corresponding power；
S7, day part load loss is sequentially completed calculating, then the average aggregate load of calculated load is cut down, using such as
Lower formula:
Wherein: Δ PjIt (X) is the synthetic load reduction of t moment under j scene, m is hits, and M is total sampling of t moment
Number, T are a sampling period, and τ is time variable；P0Total load is initially weighted for power distribution network；
The toughness index R expression of S8, power distribution network are as follows:
Further, fault scenes analogy method is as follows in the step S5:
S501, the overhead transmission line quantity for assuming power distribution network are N, then the operating status of power distribution network can be indicated by N-dimensional vector, i.e.,
X=[x1,x2,…,xN]；
S502, the operating status for calculating kth section overhead transmission line in power distribution network are xk, using following formula:
Wherein, the random number that r is generated between [0,1]；K=1,2 ..., N；PkIt (V) is the failure rate of overhead transmission line；
S503, M sampling, the available one group vector S=(X comprising M distribution network system state sample are repeated1,
X2.…,XM), the scene that power distribution network at a time breaks down under set S, that is, extreme weather.
Further, the load criteria for classifying is " Code for design of electric power supply systems GB50052-2009 " in the step S6,
Load is divided into n grades by importance.
Further, the step of implementing off-load measure to existing load when circuit overload in the step S6 is as follows:
S601, the power distribution network topological structure after breaking down is layered, according to level of hierarchy search topology, when certain
When route overloads, pass through the calculating overload power compared with the design maximum of route receiving power；
S602, selection unloaded loads, first unload rudimentary load, are greater than or equal to overload output in the load for ensuring removal
Meanwhile making the minimum loads of removal, if all unloading cannot still be met the requirements rudimentary load, upper level load is unloaded, according to
Secondary unloading is until meeting the requirements；
S603, it is continued searching according to hierarchical structure, until there is no overload situations in topology.
The advantages and positive effects of the present invention are:
The present invention proposes the intelligent distribution network toughness quantitative analysis method of the load containing polymorphic type under dusty wind weather, fixed by this
Analysis method obtains power distribution network toughness, so as to carry out reparation reinforcement to power distribution network according to power distribution network toughness, in dusty wind weather
Under the conditions of ensure that the power supply of certain proportion important load, it is big preferably to solve electric energy supply pressure under dusty wind weather
Problem effectively improves the anti-disaster ability of power distribution network.
Detailed description of the invention
Technical solution of the present invention is described in further detail below with reference to drawings and examples, but should
Know, these attached drawings are designed for task of explanation, therefore not as the restriction of the scope of the invention.In addition, except non-specifically
It points out, these attached drawings are meant only to conceptually illustrate structure construction described herein, without to be drawn to scale.
Fig. 1 is power distribution network toughness evaluation method flow diagram under dusty wind weather provided in an embodiment of the present invention；
Fig. 2 is the improved IEEE-33 meshed network frame construction drawing of combination actual conditions provided in an embodiment of the present invention；
Fig. 3 is power distribution network facility vulnerability curve provided in an embodiment of the present invention；
Fig. 4 is system loading loss late under dusty wind weather provided in an embodiment of the present invention；
Fig. 5 is the different tactful effects of enhancing under dusty wind weather provided in an embodiment of the present invention；
Wherein,
In Fig. 3: number 1 is line failure rate, and number 2 is shaft tower failure rate；
In Fig. 4: number 1 is the first order load for being distributed formula plant-grid connection, and number 2 is to be distributed the second level of formula plant-grid connection
Load, number 3 are three stage loads for being distributed formula plant-grid connection, and number 4 is the first order load of distribution-free formula plant-grid connection, number
5 be two stage loads of distribution-free formula plant-grid connection；Number 6 is three stage loads of distribution-free formula plant-grid connection；
In Fig. 5: number 1 is strategy 1, and number 2 is strategy 2, and number 3 is strategy 3.
Specific embodiment
Firstly, it is necessary to which explanation, illustrates specific structure of the invention, feature and excellent for by way of example below
Point etc., however what all descriptions were intended merely to be illustrated, and should not be construed as to present invention formation any restrictions.This
Outside, any single technical characteristic for being described by or implying in each embodiment mentioned by this paper, still can be in these technologies spy
Continue any combination between sign (or its equivalent) or delete, to obtain this hair that may do not referred to directly herein
Bright more other embodiments.
It should be noted that in the absence of conflict, the features in the embodiments and the embodiments of the present application can phase
Mutually combination.
The present invention just is illustrated in conjunction with Fig. 1-5 below.
Embodiment 1
Using the toughness for combining power distribution network under the improved IEEE-33 nodal system analysis extreme weather of actual conditions, Fig. 2
For modified IEEE-33 node system network architecture figure.It is that origin establishes coordinate system with node 1, every route is long
5km, average span 50m.Distribution network line uses LGJ-240/30 steel strand wires；Shaft tower is made of 12m concrete frame, strength grade
For G；Landed Typhoon coordinate is (- 125km, -40km), and typhoon is moved with the speed of 25km/h along positive direction of the x-axis；When Landed Typhoon
Between for simulation starting the time.Due to overhead transmission line after route disconnects or shaft tower collapses can not automatic reclosing, therefore route is flat
Equal repair time is assumed to be 5 hours；The power distribution network toughness evaluation process proposed according to the present invention, evaluation cycle are set to 1 hour.
When the power supply line of important load is cut off by dusty wind weather, adding distributed generation resource in its vicinity can be formed
Independent supply network, i.e. island mode.Assuming that there is 4 distributed generation resource access power distribution networks, specific installation site and capacity are shown in
Table 1.
1 distributed power supply location of table and capacity
| Distributed generation resource | Position | Capacity/kW |
| 1 | 7 | 400 |
| 2 | 14 | 300 |
| 3 | 25 | 400 |
| 4 | 32 | 200 |
The vulnerability curve of the route and shaft tower that are obtained according to power distribution network facility failure rate model is shown in Fig. 3.
From the figure 3, it may be seen that with the increase of typhoon wind speed, the failure rate of each facility of power distribution network is gradually increased, when hanging down for route
When straight wind speed is greater than 20m/s, the failure rate of route increases sharply.As typhoon approaches distribution network line, wind speed constantly increases, when
When route and center of typhoon distance are less than maximum wind speed radius, wind speed reduces at route.When route is close to maximum wind speed radius,
Route is easiest to break down.
Each node load importance divides as shown in table 2 in IEEE-33 node system.
2 IEEE-33 node system load importance of table divides
Using the access of distributed generation resource, it is ensured that power supply of the power distribution network to important load during extreme weather continues mentions
The high ability of system reply disaster.By example, after accessing distributed generation resource, the toughness value of system never accesses distributed electrical
0.0893 when source is increased to 0.1738, and the synthetic load loss late of system is as shown in Figure 4.
Moving emergency generator is the important flexible apparatus of power distribution network reply natural calamity, it is assumed that No. 4 distributed generation resource quilts
Moving emergency generator with capacity substitutes, and when No. 32 nodes operate normally, moving emergency generator can be moved into neighbouring
Node power supply.By example, it can be seen that, compared with the previous case, the toughness value of distribution system is increased to from 0.1738
0.1764, the access of moving emergency generator enhances power distribution network in disaster to the power supply capacity of important load, improves and is
It unites and carrys out interim flexibility in disaster.
For the accuracy for examining this method to judge system toughness, strategy is enhanced by common power distribution network toughness to test
The validity of the mentioned evaluation method of card this paper.
Strategy 1: the normal operation of any measure is not taken, as a control group；
Strategy 2: by the physical strength of the modes enhancement line L1 such as reinforcing, so that it will not break down, but it is actual
Effect is only reduction of the failure rate of route；
Strategy 3: fault restoration speed is improved by intelligent power grid technologies such as fault detection positioning, IT communications, when by repairing
Between shorten 20%.
It the results are shown in Table 3 and Fig. 5.
The common power distribution network toughness enhancement measures of table 3 and its effect
| Strategy | Enhancement measures | System toughness value |
| 1 | Nothing | 0.1738 |
| 2 | Enhancement line L1 | 0.199 |
| 3 | Improve fault restoration speed | 0.1988 |
It is found by table 3 and Fig. 4-Fig. 5:
(1) for firsts and seconds load in the case where being distributed formula plant-grid connection, load comprehensive loss rate is significantly lower than nothing
The case where distributed generation resource accesses.
System toughness value under (2) two kinds of enhancing strategies is above the system toughness value of original system, and two kinds of enhancing strategies
Under synthetic load lost area be respectively less than original system.
The reason of system above toughness enhances is respectively:
(1) access of distributed generation resource makes part power grid form island mode, remains to maximum probability under extreme weather conditions
The power supply for guaranteeing important load nearby, improves toughness of the system under extreme weather.
(2) it ensure that the normal power supply of node 2 in strategy 2 to the reinforcement of route 1, the power supply for also improving route 1 is reliable
Property, and then the power supply capacity of whole system is improved, reduce the load loss in typhoon impact process.
(3) strategy 3 shortens the repair time after line fault, makes the load loss curve integral forward lead of system, reduces
The probability of secondary and multiple failure occurs for system, improves the toughness of system.
The above sample calculation analysis shows that evaluation method proposed by the invention meets reality, rationally effectively.
Above embodiments describe the invention in detail, but content is only the preferred embodiment of the present invention, no
It can be believed to be used to limit the scope of the invention.Any changes and modifications in accordance with the scope of the present application,
It should still fall within the scope of the patent of the present invention.
Claims (4)
1. the intelligent distribution network toughness quantitative analysis method of the load containing polymorphic type under dusty wind weather, it is characterised in that: including as follows
Step:
S1, the meteorological data according to dusty wind weather simulate dust storm wind field using Batts wind-field model and obtain each point wind
Speed, using following formula:
Wherein: V is dust storm wind speed, and wind direction is the upper tangential direction counterclockwise of simulation circle, RmaxFor maximum wind speed radius,For maximum
The wind speed of wind speed radius, R are distance of the point to be studied to dust bowl point；
S2, the load effect P that power distribution network is calculated according to wind speed and direction, using following formula:
Wherein, D is the outer diameter of distribution wire, and α is wind evil attacking lung, μscIt is wire shaped coefficient, μzIt is wind pressure height change system
Number, θ is the angle of wind direction and route；
The bending strength Normal Distribution of S3, the tensile strength for assuming distribution network line in power distribution network and shaft tower, based on matching
The normpdf f of the bending strength of the tensile strength and shaft tower of power network lineR(x) and the lotus of power distribution network facility
Effect P is carried, distribution network line fault rate P can be respectively obtainedlWith shaft tower failure rate Pp, following formula:
Wherein, the value of μ and δ can be obtained by material strength test, μ, μ1、μpFor mathematic expectaion, δ, δ1、δpFor standard deviation；X be with
The tensile strength of power network line or the bending strength of shaft tower；σ1For the tensile strength of route, MpThe bending strength of shaft tower；σgFor with
For power network line highest hitch point by big wind-induced pressure, which is the ratio between highest hitch point tension and wire sectional area, with
The vector sum of wind-force and gravity is directly proportional；MTFor shaft tower root bending moment caused by route stress, the value be route wind load with
Bending moment vector caused by the wind load of shaft tower and；
Under S4, route normal operating condition, route and shaft tower are worked normally, and can be equivalent to series model, and then calculate
The failure rate P of electric distribution network overhead wirek(V), using following formula:
Wherein, Pk(V) be overhead transmission line k failure rate, n is the shaft tower quantity on overhead transmission line k, and m is route on overhead transmission line k
Number of segment, ppik(V) be upper i-th shaft tower of route k failure rate, pljk(V) be jth section route on route k failure rate；
S5, the failure rate of overhead transmission line is added to the fault scenes that day part under dusty wind weather is simulated in monte carlo method,
Obtain the scene that power distribution network under extreme weather at a time breaks down；
S6, load in power distribution network is divided into several grades, assigns each stage load different weights according to load importance；Judgement hair
Whether the system line after raw failure overloads, and when circuit overload implements off-load measure to existing load；Go out to work as according to weight calculation
The load reduction of preceding scene:
Wherein,For i-th of load reduction of t moment under j scene；For the corresponding weight of i-th of load；For
The j scene of the corresponding t moment of i-th of load；Indicate that i-th of load t moment under j scene cuts down the binary system change of state
Amount,Value is that 0 or 1,0 expression load is not cut down, and 1 indicates that load is cut down；It is right under j scene for i-th of load of t moment
The power answered；
S7, day part load loss is sequentially completed calculating, then the average aggregate load of calculated load is cut down, using following public affairs
Formula:
Wherein: Δ PjIt (X) is the synthetic load reduction of t moment under j scene, m is hits, and M is total hits of t moment, T
For a sampling period, τ is time variable；P0Total load is initially weighted for power distribution network；
The toughness index R expression of S8, power distribution network are as follows:
2. the intelligent distribution network toughness quantitative analysis method of the load containing polymorphic type under dusty wind weather according to claim 1,
It is characterized by: fault scenes analogy method is as follows in the step S5:
S501, the overhead transmission line quantity for assuming power distribution network are N, then the operating status of power distribution network can be indicated by N-dimensional vector, i.e. X=
[x1,x2,…,xN]；
S502, the operating status for calculating kth section overhead transmission line in power distribution network are xk, using following formula:
Wherein, the random number that r is generated between [0,1]；K=1,2 ..., N；PkIt (V) is the failure rate of overhead transmission line；
S503, M sampling, the available one group vector S=(X comprising M distribution network system state sample are repeated1,X2.…,
XM), the scene that power distribution network at a time breaks down under set S, that is, extreme weather.
3. the intelligent distribution network toughness quantitative analysis side of the load containing polymorphic type under dusty wind weather according to claim 1 or 2
Method, it is characterised in that: the load criteria for classifying is " Code for design of electric power supply systems GB 50052-2009 " in the step S6, will
Load is divided into n grades by importance.
4. the intelligent distribution network toughness quantitative analysis method of the load containing polymorphic type under dusty wind weather according to claim 3,
It is characterized by: the step of implementing off-load measure to existing load when circuit overload in the step S6 is as follows:
S601, the power distribution network topological structure after breaking down is layered, according to level of hierarchy search topology, when certain route
When overloading, pass through the calculating overload power compared with the design maximum of route receiving power；
S602, selection unloaded loads, first unload rudimentary load, are greater than or equal to the same of overload output in the load for ensuring removal
When, make the minimum loads of removal, if all unloading cannot still be met the requirements rudimentary load, unloads upper level load, successively
Unloading is until meeting the requirements；
S603, it is continued searching according to hierarchical structure, until there is no overload situations in topology.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111682539A (en) * | 2020-06-30 | 2020-09-18 | 国网山东省电力公司威海供电公司 | Partitioning method and system for power grid with distributed power supply based on simplified comprehensive scene |
| CN112288326A (en) * | 2020-11-23 | 2021-01-29 | 天津大学 | Fault scene set reduction method suitable for toughness evaluation of power transmission system |
| CN113505967A (en) * | 2021-06-04 | 2021-10-15 | 上海电力大学 | Power distribution network toughness improving method based on real-time fault rate |
| CN113541211A (en) * | 2021-06-11 | 2021-10-22 | 国网上海市电力公司 | Method and system for determining toughness of alternating current-direct current power distribution network |
| CN114662350A (en) * | 2022-05-26 | 2022-06-24 | 国网山东省电力公司泰安供电公司 | Wind-sand coupling load simulation method, system and terminal |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20170040839A1 (en) * | 2014-04-22 | 2017-02-09 | Siemens Aktiengesellschaft | Flexible control architecture for microgrid resiliency |
| CN108537413A (en) * | 2018-03-19 | 2018-09-14 | 国网天津市电力公司 | Based on the considerations of the power grid toughness appraisal procedure of Markov Chain typhoon space-time characterisation |
-
2019
- 2019-09-27 CN CN201910925193.4A patent/CN110535144A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20170040839A1 (en) * | 2014-04-22 | 2017-02-09 | Siemens Aktiengesellschaft | Flexible control architecture for microgrid resiliency |
| CN108537413A (en) * | 2018-03-19 | 2018-09-14 | 国网天津市电力公司 | Based on the considerations of the power grid toughness appraisal procedure of Markov Chain typhoon space-time characterisation |
Non-Patent Citations (4)
| Title |
|---|
| LUO D S等: "Evaluation Method of Distribution Network Resilience Focusing on Critical Loads", 《IEEE ACCESS》 * |
| 周晓敏等: "极端天气条件下的配电网韧性分析方法及提升措施研究", 《中国电机工程学报》 * |
| 杜雅昕等: "极端天气下计及电-气互联影响的配电网弹性评估", 《供用电》 * |
| 陈碧云等: "考虑网架重构和灾区复电过程的配电网抗台风韧性评估", 《电力系统自动化》 * |
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| CN111682539A (en) * | 2020-06-30 | 2020-09-18 | 国网山东省电力公司威海供电公司 | Partitioning method and system for power grid with distributed power supply based on simplified comprehensive scene |
| CN111682539B (en) * | 2020-06-30 | 2024-01-19 | 国网山东省电力公司威海供电公司 | Partitioning method and system for power grid containing distributed power source based on simplified comprehensive scene |
| CN112288326A (en) * | 2020-11-23 | 2021-01-29 | 天津大学 | Fault scene set reduction method suitable for toughness evaluation of power transmission system |
| CN113505967A (en) * | 2021-06-04 | 2021-10-15 | 上海电力大学 | Power distribution network toughness improving method based on real-time fault rate |
| CN113505967B (en) * | 2021-06-04 | 2022-05-20 | 上海电力大学 | Power distribution network toughness improving method based on real-time fault rate |
| CN113541211A (en) * | 2021-06-11 | 2021-10-22 | 国网上海市电力公司 | Method and system for determining toughness of alternating current-direct current power distribution network |
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