CN108054768A - Transient stability evaluation in power system method based on principal component analysis - Google Patents

Transient stability evaluation in power system method based on principal component analysis Download PDF

Info

Publication number
CN108054768A
CN108054768A CN201711352495.4A CN201711352495A CN108054768A CN 108054768 A CN108054768 A CN 108054768A CN 201711352495 A CN201711352495 A CN 201711352495A CN 108054768 A CN108054768 A CN 108054768A
Authority
CN
China
Prior art keywords
mrow
msub
principal component
mtd
delta
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN201711352495.4A
Other languages
Chinese (zh)
Other versions
CN108054768B (en
Inventor
吴俊勇
张若愚
席雅雯
邵美阳
李宝琴
郝亮亮
刘自程
卢育梓
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Beijing Jiaotong University
Original Assignee
Beijing Jiaotong University
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Beijing Jiaotong University filed Critical Beijing Jiaotong University
Priority to CN201711352495.4A priority Critical patent/CN108054768B/en
Publication of CN108054768A publication Critical patent/CN108054768A/en
Application granted granted Critical
Publication of CN108054768B publication Critical patent/CN108054768B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • 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
    • H02J3/24—Arrangements for preventing or reducing oscillations of power in networks
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]

Landscapes

  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Other Investigation Or Analysis Of Materials By Electrical Means (AREA)
  • Supply And Distribution Of Alternating Current (AREA)

Abstract

The invention discloses a kind of transient stability evaluation in power system method based on principal component analysis, the time-domain traces at all generator amature angles in 25 cycles after failure removal are obtained based on WAMS systems, principal component analysis is carried out after standardization；It is more than 85% example for first principal component variance contribution ratio, builds first principal component virtual synchronous generator；Using the time as parameter, the rotor angle of first principal component virtual synchronous generator and corresponding equivalent output power, equivalent mechanical output are mapped in two-dimensional coordinate to the moment one by one, form the P δ images track of first principal component virtual synchronous generator.The stability margin of first principal component virtual synchronous generator is calculated using law of equal areas, this transient stability margin being calculated is denoted as the transient stability margin of primal system.The present invention is without modeling and simulation, it is only necessary to real-time response information after failure removal, you can judges system stability, realizes the on-line transient stability judgement based entirely on response.

Description

Transient stability evaluation in power system method based on principal component analysis
Technical field
The present invention relates to Power System Stability Assessment, more particularly to a kind of electrical power system transient based on principal component analysis Stability assessment method.
Background technology
With the development of trans-regional interconnected network, the application of various new technologies and the implementation of policy so that electric system Dynamic behaviour is more complicated and changeable, is more easy to trigger Solving Power System Transient Stability Problem.How electric system is rapidly and accurately judged Transient stability is one of major issue of power system security prevention and control.
The method of existing transient stability evaluation in power system mainly has following a few classes：(1) time-domain-simulation method.This method is straight Sight, informative are applicable to various element scales and large-scale electrical power system, but calculating speed it is slow, dependent on system mould Type and parameter, the stability margin value that system cannot be directly given.(2) transient energy function method.This method can quickly be made surely It is fixed to judge, it is not necessary to the running orbit of whole system, but the system that this method only considered naive model are calculated, it can only be steady to head pendulum Qualitative to make assessment, analysis result is easily relatively conservative.(3) to expand law of equal areas (extended equal-area Criterion, EEAC) be representative equivalent method.The estimation of transient stability that this method can quantify, but its assessment is correct Property depend on critical machine correct identification.(4) mixing method.This method combines the advantages of time-domain-simulation method and direct method, together When there is also the shortcomings that the two.(5) artificial intelligence method.This method can carry out the electric power system transient stability differentiation of non-model, Have many advantages, such as that online calculating speed is fast, but cannot function as traditional replacement based on mechanism method, and be only capable of supplementing as it
Recent domestic has started one transient stability analysis of power system and the research boom of control based on response, Research focuses primarily upon phase-swing curves trend prediction and machine learning both direction.It is however whether pre- based on phase-swing curves trend Survey or the research of machine learning, but can not be to electric power system transient stability journey whether they are only capable of judging power system transient stability Degree carries out quantitative evaluation.
The present invention overcomes the shortcomings of existing method on existing Research foundation, proposes a kind of electricity based on principal component analysis Force system Transient Stability Evaluation method, this method realize the on-line transient stability based entirely on response without modeling and simulation Property dimensionality reduction assessment and critical machine automatic identification, have a good application prospect.
The content of the invention
The technical problem to be solved in the present invention is to provide a kind of transient stability evaluation in power system based on principal component analysis Method, to overcome problems of the prior art.
In order to solve the above technical problems, the present invention uses following technical proposals：
Based on rotor angle trace information principal component analysis after failure, the appraisal procedure of power system transient stability is carried out. This method comprises the following steps：
Step (1) screens the data message that electric system collects based on WAMS systems, obtains failure removal Afterwards in 25 cycles all generator amature angles time-domain traces, and form raw data set；
Step (2), is standardized the initial data first, then carries out principal component analysis；
Step (3) is more than 85% example for first principal component variance contribution ratio, and first is built using first principal component Principal component virtual synchronous generator；
Step (4), the transient stability margin of first principal component virtual synchronous generator is calculated using law of equal areas, which is For the transient stability margin of raw power system.
2. appraisal procedure according to claim 1, it is characterised in that：In the step (1), define electric system and be used to Property angleWhereinMiInertia time for i-th of generator is normal Number, n be generator number of units, δiFor the rotor angle under original coordinate system.Rotor angle of electric machine is issued in center of inertia system to be denoted asUnder some fault condition, all generator amature angles track of 25 cycles after fault clearance is obtained, in inertia Track matrix is denoted as in center reference coordinate system：[δij]25×n。
3. appraisal procedure according to claim 1, it is characterised in that：In the step (2), to track Ju Zhen ﹛ δij﹜25×nCarry out principal component analysis.
First to matrix [δij]25×nIt is standardized：
In formula, i=1,2 ..., 25, j=1,2 ..., n,sjRespectively each generator observation index δjAverage and side Difference.Standardize later matrix X：
Then, the covariance matrix R=(s of X are calculatedij)n×n：
The eigenvalue λ of R is obtainediAnd corresponding orthogonalization unit character vectorBy characteristic value from big λ is shown to float1≥λ2≥…≥λm, λiCorresponding unit character vector uiIt is exactly principal component FiThe coefficient on former variable, Then i-th of principal component F of former variableiFor：
Fi=ui1δ1+ui2δ2+…+uinδn
The variance contribution ratio of principal component is used for the size for reflecting information content, βiFor：
Finally to select several principal components is determined by accumulative variance contribution ratio G (m), and the expression formula of G (m) is：
When accumulative variance contribution ratio is more than 85%, the letter that these main variables reflect original variable enough is considered as Breath, corresponding m is exactly the preceding m principal component extracted.
4. appraisal procedure according to claim 1, it is characterised in that：In the step (3), for first principal component Variance contribution ratio is more than 85% example, extracts first principal component, builds first principal component virtual synchronous generator.First principal component is empty The equation of rotor motion for sending out motor is expressed as：
In formula：
Wherein, F1For the rotor angle of first principal component virtual synchronous generator；w1For the rotor angle of first principal component virtual synchronous generator Speed；ωnFor synchronous rotor angular speed；Pm、PeRespectively the equivalent mechanical output of first principal component virtual synchronous generator and equivalence are defeated Go out power.
4. appraisal procedure according to claim 1, it is characterised in that：In the step (3), first principal component coefficient To be an advanced group of planes on the occasion of corresponding generator, first principal component coefficient is that the generator corresponding to negative value is a hysteresis group of planes.
5. appraisal procedure according to claim 1, it is characterised in that：Using the time as parameter in the step (4), The rotor angle of first principal component virtual synchronous generator and corresponding equivalent output power, equivalent mechanical output are mapped to the moment one by one Into two-dimensional coordinate, the P- δ images track of first principal component virtual synchronous generator is formed.Using law of equal areas calculate first it is main into Divide the stability margin of virtual synchronous generator, this transient stability margin being calculated is denoted as the transient stability margin of primal system.
Wherein law of equal areas calculation formula is as follows：
For unstability example, stability margin ηunIt is expressed as：
In formula：
Wherein AincThe kinetic energy of moment to excision time instant τ occurs for failure increases area；AdecIt it is the failure removal moment to not The kinetic energy of stable equilibrium point UEP reduces area；δoFor before failure at system operating point first principal component virtual synchronous generator rotor Angle；δτFor the rotor angle of failure removal moment first principal component virtual synchronous generator；δUEPFor first at unstable equilibrium point UEP Principal component virtual synchronous generator rotor angle；PeFor the equivalent output power of first principal component virtual synchronous generator；PmIt is empty for first principal component Send out the equivalent mechanical output of motor.
For stablizing example, the quadratic function that the preceding several points for first passing through first pendulum solstics FEP use redundancy higher is most Small square law predicts the virtual power-angle curve of first pendulum solstics FEP to unstable equilibrium point UEP.If virtual Pe(δ) curve is：
Pe(δ)=a0+a1δ+a2δ2,a0≠0
A in formula0, a1, a2For unknown variable.
Stability margin η is expressed as：
In formula：
Wherein Adec.potRepresenting, which makes the image reach Instability state, also wants increased Implantation Energy, it can be With by fabricating path P in P- δ planese(δ)、Pm(δ), δ axis and straight line δ=δFEPThe area that is enclosed is measured.A* decIt is cut for failure Except the kinetic energy of time instant τ system at the FEP of solstics reduces area；δτFor failure removal moment first principal component virtual synchronous generator Rotor angle；δFEPHeaded by put FEP at first principal component virtual synchronous generator rotor angle；δUEPHeaded by put UEP at first principal component Virtual synchronous generator rotor angle；PeFor the equivalent output power of first principal component virtual synchronous generator；PmIt virtually generates electricity for first principal component The equivalent mechanical output of machine.ηunValue range [- 1,0], ηunValue is smaller, and the unstable degree of system is bigger；The value model of η It encloses [0,1], η values are bigger, and system stability margin is bigger.
Description of the drawings
The specific embodiment of the present invention is described in further detail below in conjunction with the accompanying drawings：
Fig. 1 shows a kind of signal of transient stability evaluation in power system method based on principal component analysis of the present invention Figure；
Fig. 2 shows the topology diagram of 10 machine of New England, 39 node system in the present embodiment；
Fig. 3 shows 10 machine of New England, 39 node system example first principal component variance contribution ratio in the present embodiment；
Fig. 4 shows the first principal component virtual synchronous generator P- δ curves of 10 machine of the present embodiment, 39 node system example 1；
Fig. 5 shows the first principal component virtual synchronous generator P- δ curves of 10 machine of the present embodiment, 39 node system example 2.
Specific embodiment
The invention discloses one kind based on rotor angle trace information principal component analysis after failure, it is steady to carry out electrical power system transient Qualitatively appraisal procedure.This method comprises the following steps：
Step (1) screens the data message that electric system collects based on WAMS systems, obtains failure removal Afterwards in 25 cycles all generator amature angles time-domain traces, and form raw data set；
Step (2), is standardized the initial data first, then carries out principal component analysis；
Step (3) is more than 85% example for first principal component variance contribution ratio, and first is built using first principal component Principal component virtual synchronous generator；
Step (4), the transient stability margin of first principal component virtual synchronous generator is calculated using law of equal areas, which is For the transient stability margin of raw power system.
2. appraisal procedure according to claim 1, it is characterised in that：In the step (1), define electric system and be used to Property angleWhereinMiInertia time for i-th of generator is normal Number, n be generator number of units, δiFor the rotor angle under original coordinate system.Rotor angle of electric machine is issued in center of inertia system to be denoted asUnder some fault condition, all generator amature angles track of 25 cycles after fault clearance is obtained, in inertia Track matrix is denoted as in center reference coordinate system：[δij]25×n。
3. appraisal procedure according to claim 1, it is characterised in that：In the step (2), to track Ju Zhen ﹛ δij﹜25×nCarry out principal component analysis.
First to matrix [δij]25×nIt is standardized：
In formula, i=1,2 ..., 25, j=1,2 ..., n,sjRespectively each generator observation index δjAverage and side Difference.Standardize later matrix X：
Then, the covariance matrix R=(s of X are calculatedij)n×n：
The eigenvalue λ of R is obtainediAnd corresponding orthogonalization unit character vectorBy characteristic value from big λ is shown to float1≥λ2≥…≥λm, λiCorresponding unit character vector uiIt is exactly principal component FiThe coefficient on former variable, Then i-th of principal component F of former variableiFor：
Fi=ui1δ1+ui2δ2+…+uinδn
The variance contribution ratio of principal component is used for the size for reflecting information content, βiFor：
Finally to select several principal components is determined by accumulative variance contribution ratio G (m), and the expression formula of G (m) is：
When accumulative variance contribution ratio is more than 85%, the letter that these main variables reflect original variable enough is considered as Breath, corresponding m is exactly the preceding m principal component extracted.
4. appraisal procedure according to claim 1, it is characterised in that：In the step (3), for first principal component Variance contribution ratio is more than 85% example, extracts first principal component, builds first principal component virtual synchronous generator.First principal component is empty The equation of rotor motion for sending out motor is expressed as：
In formula：
Wherein, F1For the rotor angle of first principal component virtual synchronous generator；w1For the rotor angle of first principal component virtual synchronous generator Speed；ωnFor synchronous rotor angular speed；Pm、PeRespectively the equivalent mechanical output of first principal component virtual synchronous generator and equivalence are defeated Go out power.
4. appraisal procedure according to claim 1, it is characterised in that：In the step (3), first principal component coefficient To be an advanced group of planes on the occasion of corresponding generator, first principal component coefficient is that the generator corresponding to negative value is a hysteresis group of planes.
5. appraisal procedure according to claim 1, it is characterised in that：Using the time as parameter in the step (4), The rotor angle of first principal component virtual synchronous generator and corresponding equivalent output power, equivalent mechanical output are mapped to the moment one by one Into two-dimensional coordinate, the P- δ images track of first principal component virtual synchronous generator is formed.Using law of equal areas calculate first it is main into Divide the stability margin of virtual synchronous generator, this transient stability margin being calculated is denoted as the transient stability margin of primal system.
Wherein law of equal areas calculation formula is as follows：
For unstability example, stability margin ηunIt is expressed as：
In formula：
Wherein AincThe kinetic energy of moment to excision time instant τ occurs for failure increases area；AdecIt it is the failure removal moment to not The kinetic energy of stable equilibrium point UEP reduces area；δoFor before failure at system operating point first principal component virtual synchronous generator rotor Angle；δτFor the rotor angle of failure removal moment first principal component virtual synchronous generator；δUEPFor first at unstable equilibrium point UEP Principal component virtual synchronous generator rotor angle；PeFor the equivalent output power of first principal component virtual synchronous generator；PmIt is empty for first principal component Send out the equivalent mechanical output of motor.
For stablizing example, the quadratic function that the preceding several points for first passing through first pendulum solstics FEP use redundancy higher is most Small square law predicts the virtual power-angle curve of first pendulum solstics FEP to unstable equilibrium point UEP.If virtual Pe(δ) curve is：
Pe(δ)=a0+a1δ+a2δ2,a0≠0
A in formula0, a1, a2For unknown variable.
Stability margin η is expressed as：
In formula：
Wherein Adec.potRepresenting, which makes the image reach Instability state, also wants increased Implantation Energy, it can be With by fabricating path P in P- δ planese(δ)、Pm(δ), δ axis and straight line δ=δFEPThe area that is enclosed is measured.A* decIt is cut for failure Except the kinetic energy of time instant τ system at the FEP of solstics reduces area；δτFor failure removal moment first principal component virtual synchronous generator Rotor angle；δFEPHeaded by put FEP at first principal component virtual synchronous generator rotor angle；δUEPHeaded by put UEP at first principal component Virtual synchronous generator rotor angle；PeFor the equivalent output power of first principal component virtual synchronous generator；PmIt virtually generates electricity for first principal component The equivalent mechanical output of machine.ηunValue range [- 1,0], ηunValue is smaller, and the unstable degree of system is bigger；The value model of η It encloses [0,1], η values are bigger, and system stability margin is bigger.
Beneficial effects of the present invention are as follows：
Technical solution this method present invention of the present invention need not establish Power System Analysis model and emulation, according only to The rotor angle of generator, mechanical output, output power information after the failure removal that WAMS systems obtain, directly to electric system Transient stability is assessed, and realizes the on-line transient stability judgement based entirely on response.This method need not be to power train System carries out snock swarming, has the ability of automatic identification criticality benchmark and Failure Model.With the expansion of system scale, this method Only need to judge the stability characteristic (quality) of first principal component virtual synchronous generator, calculation amount is not significantly increased, the advantage compared with conventional method It is more obvious.
Below by one group of embodiment, the invention will be further described：
The present embodiment is illustrated by taking 10 machine of New England, 39 node system as an example.System uses constant impedance load, bears Lotus level sets 5 kinds of different generated outputs, three-phase shortcircuit is set among 34 circuits under 100% gauge load level Failure, 5 cycle excision near terminal faults after failure occurs, 6 cycle excision far-end faults or 9 cycle excision near terminal faults, 10 cycles excision far-end faults or 19 cycles excision near terminal faults, 20 cycles cut off far-end faults, and symbiosis is into 5 × 34 × 3=510 example.Rotor angle trace information is by simulation software Power System Tool after the generator failure of PMU actual measurements (PST) 3.0 obtained data of emulation are simulated, simulation frequency 60Hz.
The rotor angle trace information of 25 cycles, obtains after inertia central transformation at inertia center after extraction failure removal Rotor angle trace information under coordinate system.Then principal component analysis is carried out to it, calculates the first principal component variance of each example Contribution rate, as shown in Figure 3.
510 examples of 10 machine, 39 node system emulation generation as shown in Figure 3,100% example first principal component variance Contribution rate is all higher than 85%, therefore according to the principle of Principle component extraction in multivariate statistics principal component analysis, first it is main into Divide and contain most original generator amature angles trace information.Therefore the first principal component virtual synchronous generator of this method structure Contain most information of primal system each unit rotor angle track.
Using the time as parameter, by the rotor angle of first principal component virtual synchronous generator and corresponding equivalent output power, etc. Value mechanical output is mapped in two-dimensional coordinate to the moment one by one, forms the P- δ images track of first principal component virtual synchronous generator.
When disturbed track δ (t) unstability of first principal component virtual synchronous generator rotor angle, corresponding P- δ image curves must Run into unstable equilibrium point (unstable equilibrium point, UEP).Unstability image stablizing before standardization is abundant Spend ηunIt is expressed as：
ηun=Adec-Ainc (1)
The value can be turned to perunit：
In formula：
When first principal component virtual synchronous generator P- δ image curves run into first pendulum solstics (furthest equilibrium Point, FEP) when, which can be judged to stablize, and there are A at this timedecWith AincIt is equal.Imagination is injected at FEP to the image Additional kinetic energy, and assume that imaginary path of the image track after FEP has preferable autonomy, therefore this imaginary road Footpath can be predicted by several points before FEP with the higher quadratic function least square method of redundancy.If virtual Pe(δ) is bent Line is：
Pe=a0+a1δ+a2δ2,a0≠0 (5)
A in formula0, a1, a2For unknown variable.
Potential kinetic energy reduces area Adec.potRepresenting, which makes the image reach Instability state, also wants increased note Enter energy, it can be in P- δ planes with by fabricating path Pe(δ)、Pm(δ), δ axis and straight line δ=δFEPThe area enclosed carrys out amount Degree.Area (A can be reduced with total kinetic energy* dec+Adec.pot) and actual kinetic energy increase area AincDifference, i.e. Adec.potTo make For the stability margin before standardization.And the stability margin η after standardization is：
In formula：
A* decArea, δ are reduced for the kinetic energy of failure removal time instant τ system at the FEP of solsticsoIt works for system before failure The rotor angle of first principal component virtual synchronous generator, δ at pointτFor the rotor of failure removal moment first principal component virtual synchronous generator Angle, δFEPHeaded by put FEP at first principal component virtual synchronous generator rotor angle, δUEPHeaded by put UEP at first principal component it is virtual Generator amature angle.From formula (2), (6), ηunValue range [- 1,0], ηunValue is smaller, the unstable degree of system It is bigger；The value range [0,1] of η, η values are bigger, and system stability margin is bigger.
In order to verify the correctness of the obtained stability of context of methods and degree of stability, introduce based on critical clearing time (CCT) index M quantifies the degree of stability of primal system, and M index definitions are as follows：
M ∈ [- 1,1], M are more than zero, and system is stable state, more stable closer to 1 system；When M is equal to zero, system is to face Boundary's state；M is less than zero, and system is instability status, and closer -1 system gets over unstability.tCCTValue can be by time-domain-simulation method repeatedly Exploration obtains, tclFor the failure actual mute time.
Three phase short circuit fault occurs for 0s at the 50% of 1, No. 24 circuits of example, 9 cycles excisions are near after failure occurs Failure is held, 10 cycles cut off far-end fault.To the generator of 25 cycles after the failure removal under 1 center of inertia system of example Rotor angle information carries out principal component analysis, and it is as shown in table 1 to obtain first principal component coefficient.
1 10 machine of table, 39 node system example, 1 first principal component coefficient
It observes first principal component coefficient to find, the weight coefficient absolute value of each generator is close to equal, and busbar volume Numbers 30~38 generator weight coefficient is positive value, and the generator weight coefficient of busbar number 39 is negative value.Busbar number 30~ 38 generator weight coefficient is with the generator weight coefficient of busbar number 39 on the contrary, being walked with time-domain-simulation generator rocking curve Gesture reverse phenomenon is consistent.Existing EEAC methods are that the generator of busbar number 30~38 is merged into unit before neck, weight Equal is 1.0, and for the generator of busbar number 39 as hysteresis unit, equal weight is also 1.0.Subtract each other conjunction in two machine rotor angles And into one machine infinity bus system, judge power system transient stability using law of equal areas.Compare both approaches, it is known that the first master Ingredient coefficient is similar to the weight coefficient of each generator in EEAC methods, and more more objective than EEAC method.Because principal component point Analysis method is the correlation between each generator obtained according to the real-time response data characteristics of system, and not artificially setting is each The weight coefficient of a generator.As it can be seen that the weight that EEAC methods assign every generator is only the virtual synchronous generator method based on PCA One limit special case.The weight coefficient that virtual synchronous generator method based on PCA provides realizes automatic identification Failure Model and critical The function of unit.
According to the corresponding principal component coefficient structure first principal component virtual synchronous generator of first principal component.First principal component is virtual Generator amature angle δ is：
The output power P of first principal component virtual synchronous generatoreFor：
The mechanical output P of first principal component virtual synchronous generatormFor：
MT=M30+M31+…+M39 (14)
The first principal component virtual synchronous generator P- δ curves of example 1 are as shown in figure 4, five jiaos of hearts of wherein first hollow out represent The FEP of head pendulum, second hollow out, five jiaos of hearts represent virtual UEP, and horizontal linear represents first principal component virtual synchronous generator machinery Power P m (δ), solid-line curve represent the output power Pe (δ) of first principal component virtual synchronous generator, and dotted line represents that FEP to UEP is empty Pe (δ) track of structure.1 stability analysis data of example are as shown in table 2.
The stability analysis data of 2 10 machine of table, 39 node system example 1
As shown in Table 2, when the first pendulum of first principal component virtual synchronous generator rotor angle meets FEP, there is A* dec=Ainc.It utilizes First principal component virtual synchronous generator stability margin η=0.4546 is calculated in formula (6), based on critical clearing time tCCTIt calculates Obtained primal system stability indicator M=0.4706, it is seen that η is all positive number with M and numerical values recited is suitable, i.e. first principal component The stability of virtual synchronous generator is consistent with the stability of primal system, is stable state.
Three phase short circuit fault occurs for 0s at the 50% of 2, No. 6 circuits of example, 19 cycles excisions are near after failure occurs Failure is held, 20 cycles cut off far-end fault.The first principal component virtual synchronous generator equivalence power-angle curve of example 2 is as shown in Figure 5. Curve represents the output power Pe (δ) of first principal component virtual synchronous generator in figure, and horizontal linear represents that first principal component is virtually sent out Electromechanics power P m (δ), five jiaos of hearts of hollow out represent UEP.2 stability analysis data of example are as shown in table 3.
The stability analysis data of 3 10 machine of table, 39 node system example 2
As shown in Table 3, first principal component virtual synchronous generator stability margin ηun=-0.9087, based on critical clearing time tCCT The primal system stability indicator M=-0.8947 being calculated.It can be seen that ηunWith M be all negative and numerical values recited is suitable, i.e., The stability of first principal component virtual synchronous generator and primal system are instability status.
10 machine, 39 node system part sample calculation analysis the results are shown in Table 4.Through simulating, verifying, when first principal component is virtual in table 4 When the first pendulum in generator amature angle meets FEP, there is A* dec=Ainc, therefore stable example can be calculated using formula (6) Stability margin η；When first principal component virtual synchronous generator rotor angle has passed through UEP, η is calculated using formula (2)un, so as to obtain The stability margin η of unstability exampleun。
4 10 machine of table, 39 node system stability analysis result
As can be seen from Table 4：The two kinds of stability margin index numerical value calculated herein based on PCA methods and time-domain-simulation method Sign is identical, and order of magnitude is suitable.The transient stability of first principal component virtual synchronous generator has with primal system stability There is uniformity, the first principal component virtual synchronous generator based on Principal Component Analysis structure can be used for the transient stability of multi-computer system Assessment.
Obviously, the above embodiment of the present invention is just for the sake of removing the citing for illustrating that the present invention carries out, and it is pair to be not The restriction of embodiments of the present invention, for those of ordinary skill in the art, on the basis of above description can be with Other various forms of variations or variation are made, can not give exhaustion to all way of example here, it is every to belong to this hair The obvious changes or variations that bright technical solution is extended out is still in the row of protection scope of the present invention.

Claims (6)

1. the transient stability evaluation in power system method based on principal component analysis, which is characterized in that the step of the method includes：
Step (1) is screened the data message that electric system collects based on WAMS systems, is obtained 25 after failure removal The time-domain traces at all generator amature angles in cycle, and form raw data set；
Step (2), is standardized the initial data first, then carries out principal component analysis；
Step (3), for first principal component variance contribution ratio be more than 85% example, using first principal component structure first it is main into Divide virtual synchronous generator；
Step (4), the transient stability margin of first principal component virtual synchronous generator is calculated using law of equal areas, which is original The transient stability margin of beginning electric system.
2. appraisal procedure according to claim 1, it is characterised in that：In the step (1), define in electric system inertia Heart angleWhereinMiFor the inertia time constant of i-th of generator, n For generator number of units, δiFor the rotor angle under original coordinate system.Rotor angle of electric machine is issued in center of inertia system to be denoted asUnder some fault condition, all generator amature angles track of 25 cycles after fault clearance is obtained, in inertia Track matrix is denoted as in center reference coordinate system：[δij]25×n。
3. appraisal procedure according to claim 1, it is characterised in that：In the step (2), to track Ju Zhen ﹛ δij﹜25×n Carry out principal component analysis.
First to matrix [δij]25×nIt is standardized：
<mrow> <msup> <msub> <mi>&amp;delta;</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <mo>*</mo> </msup> <mo>=</mo> <mfrac> <mrow> <msub> <mi>&amp;delta;</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <mo>-</mo> <msub> <mover> <mi>&amp;delta;</mi> <mo>&amp;OverBar;</mo> </mover> <mi>j</mi> </msub> </mrow> <msub> <mi>s</mi> <mi>j</mi> </msub> </mfrac> </mrow>
In formula, i=1,2 ..., 25, j=1,2 ..., n,sjRespectively each generator observation index δjAverage and variance. Standardize later matrix X：
<mrow> <mi>X</mi> <mo>=</mo> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <mrow> <msup> <msub> <mi>&amp;delta;</mi> <mn>11</mn> </msub> <mo>*</mo> </msup> </mrow> </mtd> <mtd> <mrow> <msup> <msub> <mi>&amp;delta;</mi> <mn>12</mn> </msub> <mo>*</mo> </msup> </mrow> </mtd> <mtd> <mo>...</mo> </mtd> <mtd> <mrow> <msup> <msub> <mi>&amp;delta;</mi> <mrow> <mn>1</mn> <mi>n</mi> </mrow> </msub> <mo>*</mo> </msup> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <msup> <msub> <mi>&amp;delta;</mi> <mn>21</mn> </msub> <mo>*</mo> </msup> </mrow> </mtd> <mtd> <mrow> <msup> <msub> <mi>&amp;delta;</mi> <mn>22</mn> </msub> <mo>*</mo> </msup> </mrow> </mtd> <mtd> <mo>...</mo> </mtd> <mtd> <mrow> <msup> <msub> <mi>&amp;delta;</mi> <mrow> <mn>2</mn> <mi>n</mi> </mrow> </msub> <mo>*</mo> </msup> </mrow> </mtd> </mtr> <mtr> <mtd> <mo>...</mo> </mtd> <mtd> <mo>...</mo> </mtd> <mtd> <mo>...</mo> </mtd> <mtd> <mo>...</mo> </mtd> </mtr> <mtr> <mtd> <mrow> <msup> <msub> <mi>&amp;delta;</mi> <mn>251</mn> </msub> <mo>*</mo> </msup> </mrow> </mtd> <mtd> <mrow> <msup> <msub> <mi>&amp;delta;</mi> <mn>252</mn> </msub> <mo>*</mo> </msup> </mrow> </mtd> <mtd> <mo>...</mo> </mtd> <mtd> <mrow> <msup> <msub> <mi>&amp;delta;</mi> <mrow> <mn>25</mn> <mi>n</mi> </mrow> </msub> <mo>*</mo> </msup> </mrow> </mtd> </mtr> </mtable> </mfenced> </mrow>
Then, the covariance matrix R=(s of X are calculatedij)n×n：
<mrow> <msub> <mi>s</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <mo>=</mo> <mfrac> <mn>1</mn> <mrow> <mn>25</mn> <mo>-</mo> <mn>1</mn> </mrow> </mfrac> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mn>25</mn> </munderover> <mrow> <mo>(</mo> <msubsup> <mi>&amp;delta;</mi> <mrow> <mi>k</mi> <mi>i</mi> </mrow> <mo>*</mo> </msubsup> <mo>-</mo> <mover> <msubsup> <mi>&amp;delta;</mi> <mi>i</mi> <mo>*</mo> </msubsup> <mo>&amp;OverBar;</mo> </mover> <mo>)</mo> </mrow> <mrow> <mo>(</mo> <msubsup> <mi>&amp;delta;</mi> <mrow> <mi>k</mi> <mi>j</mi> </mrow> <mo>*</mo> </msubsup> <mo>-</mo> <mover> <msubsup> <mi>&amp;delta;</mi> <mi>j</mi> <mo>*</mo> </msubsup> <mo>&amp;OverBar;</mo> </mover> <mo>)</mo> </mrow> <mo>,</mo> <mi>i</mi> <mo>,</mo> <mi>j</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mn>2</mn> <mo>,</mo> <mn>...</mn> <mo>,</mo> <mi>n</mi> </mrow>
The eigenvalue λ of R is obtainediAnd corresponding orthogonalization unit character vector ui=[ui1,ui2,…,uin]Xia.By characteristic value from big λ is shown to float1≥λ2≥…≥λm, λiCorresponding unit character vector uiIt is exactly principal component FiThe coefficient on former variable, Then i-th of principal component F of former variableiFor：
Fi=ui1δ1+ui2δ2+…+uinδn
The variance contribution ratio of principal component is used for the size for reflecting information content, βiFor：
<mrow> <msub> <mi>&amp;beta;</mi> <mi>i</mi> </msub> <mo>=</mo> <msub> <mi>&amp;lambda;</mi> <mi>i</mi> </msub> <mo>/</mo> <munderover> <mo>&amp;Sigma;</mo> <mi>i</mi> <mi>m</mi> </munderover> <msub> <mi>&amp;lambda;</mi> <mi>i</mi> </msub> <mo>,</mo> <mi>i</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mn>2</mn> <mo>,</mo> <mn>...</mn> <mo>,</mo> <mi>m</mi> </mrow>
Finally to select several principal components is determined by accumulative variance contribution ratio G (m), and the expression formula of G (m) is：
<mrow> <mi>G</mi> <mrow> <mo>(</mo> <mi>m</mi> <mo>)</mo> </mrow> <mo>=</mo> <munderover> <mo>&amp;Sigma;</mo> <mi>i</mi> <mi>m</mi> </munderover> <msub> <mi>&amp;lambda;</mi> <mi>i</mi> </msub> <mo>/</mo> <munderover> <mo>&amp;Sigma;</mo> <mi>k</mi> <mi>n</mi> </munderover> <msub> <mi>&amp;lambda;</mi> <mi>k</mi> </msub> </mrow>
When accumulative variance contribution ratio is more than 85%, the information that these main variables reflect original variable enough is considered as, it is right The m answered is exactly the preceding m principal component extracted.
4. appraisal procedure according to claim 1, it is characterised in that：In the step (3), for first principal component variance Contribution rate is more than 85% example, extracts first principal component, builds first principal component virtual synchronous generator.First principal component is virtually sent out The equation of rotor motion of motor is expressed as：
<mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <mfrac> <mrow> <msub> <mi>dF</mi> <mn>1</mn> </msub> </mrow> <mrow> <mi>d</mi> <mi>t</mi> </mrow> </mfrac> <mo>=</mo> <msub> <mi>w</mi> <mn>1</mn> </msub> <mo>-</mo> <msub> <mi>&amp;omega;</mi> <mi>n</mi> </msub> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <msub> <mi>M</mi> <mi>T</mi> </msub> <mfrac> <mrow> <msub> <mi>dw</mi> <mn>1</mn> </msub> </mrow> <mrow> <mi>d</mi> <mi>t</mi> </mrow> </mfrac> <mo>=</mo> <msub> <mi>P</mi> <mi>m</mi> </msub> <mo>-</mo> <msub> <mi>P</mi> <mi>e</mi> </msub> </mrow> </mtd> </mtr> </mtable> </mfenced>
In formula：
<mrow> <msub> <mi>M</mi> <mi>T</mi> </msub> <mo>=</mo> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <msub> <mi>M</mi> <mi>i</mi> </msub> <mo>,</mo> <mi>i</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mn>2</mn> <mo>,</mo> <mn>...</mn> <mo>,</mo> <mi>n</mi> <mo>;</mo> </mrow>
<mrow> <msub> <mi>P</mi> <mi>m</mi> </msub> <mo>=</mo> <msub> <mi>M</mi> <mi>T</mi> </msub> <mrow> <mo>(</mo> <mfrac> <mrow> <msub> <mi>u</mi> <mn>11</mn> </msub> <msub> <mi>P</mi> <mrow> <mi>m</mi> <mn>1</mn> </mrow> </msub> </mrow> <msub> <mi>M</mi> <mn>1</mn> </msub> </mfrac> <mo>+</mo> <mfrac> <mrow> <msub> <mi>u</mi> <mn>12</mn> </msub> <msub> <mi>P</mi> <mrow> <mi>m</mi> <mn>2</mn> </mrow> </msub> </mrow> <msub> <mi>M</mi> <mn>2</mn> </msub> </mfrac> <mo>+</mo> <mn>...</mn> <mo>+</mo> <mfrac> <mrow> <msub> <mi>u</mi> <mrow> <mn>1</mn> <mi>n</mi> </mrow> </msub> <msub> <mi>P</mi> <mrow> <mi>m</mi> <mi>n</mi> </mrow> </msub> </mrow> <msub> <mi>M</mi> <mi>n</mi> </msub> </mfrac> <mo>)</mo> </mrow> <mo>;</mo> </mrow>
<mrow> <msub> <mi>P</mi> <mi>e</mi> </msub> <mo>=</mo> <msub> <mi>M</mi> <mi>T</mi> </msub> <mrow> <mo>(</mo> <mfrac> <mrow> <msub> <mi>u</mi> <mn>11</mn> </msub> <msub> <mi>P</mi> <mrow> <mi>e</mi> <mn>1</mn> </mrow> </msub> </mrow> <msub> <mi>M</mi> <mn>1</mn> </msub> </mfrac> <mo>+</mo> <mfrac> <mrow> <msub> <mi>u</mi> <mn>12</mn> </msub> <msub> <mi>P</mi> <mrow> <mi>e</mi> <mn>2</mn> </mrow> </msub> </mrow> <msub> <mi>M</mi> <mn>2</mn> </msub> </mfrac> <mo>+</mo> <mn>...</mn> <mo>+</mo> <mfrac> <mrow> <msub> <mi>u</mi> <mrow> <mn>1</mn> <mi>n</mi> </mrow> </msub> <msub> <mi>P</mi> <mrow> <mi>e</mi> <mi>n</mi> </mrow> </msub> </mrow> <msub> <mi>M</mi> <mi>n</mi> </msub> </mfrac> <mo>)</mo> </mrow> <mo>+</mo> <mrow> <mo>(</mo> <msub> <mi>u</mi> <mn>11</mn> </msub> <mo>+</mo> <msub> <mi>u</mi> <mn>12</mn> </msub> <mo>+</mo> <mn>...</mn> <mo>+</mo> <msub> <mi>u</mi> <mrow> <mn>1</mn> <mi>n</mi> </mrow> </msub> <mo>)</mo> </mrow> <msub> <mi>P</mi> <mrow> <mi>C</mi> <mi>O</mi> <mi>I</mi> </mrow> </msub> <mo>;</mo> </mrow>
<mrow> <msub> <mi>P</mi> <mrow> <mi>C</mi> <mi>O</mi> <mi>I</mi> </mrow> </msub> <mo>=</mo> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <mrow> <mo>(</mo> <msub> <mi>P</mi> <mrow> <mi>m</mi> <mi>i</mi> </mrow> </msub> <mo>-</mo> <msub> <mi>P</mi> <mrow> <mi>e</mi> <mi>i</mi> </mrow> </msub> <mo>)</mo> </mrow> <mo>,</mo> <mi>i</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mn>2</mn> <mo>,</mo> <mn>...</mn> <mo>,</mo> <mi>n</mi> <mo>;</mo> </mrow>
Wherein, F1For the rotor angle of first principal component virtual synchronous generator；w1For the rotor angle speed of first principal component virtual synchronous generator Degree；ωnFor synchronous rotor angular speed；Pm、PeThe respectively equivalent mechanical output of first principal component virtual synchronous generator and equivalent output Power.
5. appraisal procedure according to claim 1, it is characterised in that：In the step (3), first principal component coefficient is just The corresponding generator of value is an advanced group of planes, and first principal component coefficient is that the generator corresponding to negative value is a hysteresis group of planes.
6. appraisal procedure according to claim 1, it is characterised in that：Using the time as parameter in the step (4), by The rotor angle of one principal component virtual synchronous generator and corresponding equivalent output power, equivalent mechanical output are mapped to two to the moment one by one In dimension coordinate, the P- δ images track of first principal component virtual synchronous generator is formed.It is empty that first principal component is calculated using law of equal areas The stability margin of motor is sent out, this transient stability margin being calculated is denoted as the transient stability margin of primal system.
Wherein law of equal areas calculation formula is as follows：
For unstability example, stability margin ηunIt is expressed as：
<mrow> <msub> <mi>&amp;eta;</mi> <mrow> <mi>u</mi> <mi>n</mi> </mrow> </msub> <mo>=</mo> <mfrac> <mrow> <msub> <mi>A</mi> <mrow> <mi>d</mi> <mi>e</mi> <mi>c</mi> </mrow> </msub> <mo>-</mo> <msub> <mi>A</mi> <mrow> <mi>i</mi> <mi>n</mi> <mi>c</mi> </mrow> </msub> </mrow> <msub> <mi>A</mi> <mrow> <mi>i</mi> <mi>n</mi> <mi>c</mi> </mrow> </msub> </mfrac> <mo>&amp;times;</mo> <mn>100</mn> <mi>%</mi> <mo>&lt;</mo> <mn>0</mn> </mrow>
In formula：
<mrow> <msub> <mi>A</mi> <mrow> <mi>i</mi> <mi>n</mi> <mi>c</mi> </mrow> </msub> <mo>=</mo> <munderover> <mo>&amp;Integral;</mo> <msub> <mi>&amp;delta;</mi> <mi>o</mi> </msub> <msub> <mi>&amp;delta;</mi> <mi>&amp;tau;</mi> </msub> </munderover> <mrow> <mo>(</mo> <msub> <mi>P</mi> <mi>m</mi> </msub> <mo>-</mo> <msub> <mi>P</mi> <mi>e</mi> </msub> <mo>)</mo> </mrow> <mi>d</mi> <mi>&amp;delta;</mi> </mrow>
<mrow> <msub> <mi>A</mi> <mrow> <mi>de</mi> <mi>c</mi> </mrow> </msub> <mo>=</mo> <munderover> <mo>&amp;Integral;</mo> <msub> <mi>&amp;delta;</mi> <mi>&amp;tau;</mi> </msub> <msub> <mi>&amp;delta;</mi> <mrow> <mi>U</mi> <mi>E</mi> <mi>P</mi> </mrow> </msub> </munderover> <mrow> <mo>(</mo> <msub> <mi>P</mi> <mi>e</mi> </msub> <mo>-</mo> <msub> <mi>P</mi> <mi>m</mi> </msub> <mo>)</mo> </mrow> <mi>d</mi> <mi>&amp;delta;</mi> </mrow>
Wherein AincThe kinetic energy of moment to excision time instant τ occurs for failure increases area；AdecIt it is the failure removal moment to unstable The kinetic energy of equalization point UEP reduces area；δoFor before failure at system operating point first principal component virtual synchronous generator rotor angle；δτ For the rotor angle of failure removal moment first principal component virtual synchronous generator；δUEPFor the first principal component at unstable equilibrium point UEP Virtual synchronous generator rotor angle；PeFor the equivalent output power of first principal component virtual synchronous generator；PmIt virtually generates electricity for first principal component The equivalent mechanical output of machine.
For stablizing example, preceding several points of first pendulum solstics FEP are first passed through with the higher quadratic function minimum two of redundancy Multiplication predicts the virtual power-angle curve of first pendulum solstics FEP to unstable equilibrium point UEP.If virtual Pe(δ) curve is：
Pe(δ)=a0+a1δ+a2δ2,a0≠0
A in formula0, a1, a2For unknown variable.
Stability margin η is expressed as：
<mrow> <mi>&amp;eta;</mi> <mo>=</mo> <mfrac> <msub> <mi>A</mi> <mrow> <mi>d</mi> <mi>e</mi> <mi>c</mi> <mo>.</mo> <mi>p</mi> <mi>o</mi> <mi>t</mi> </mrow> </msub> <mrow> <msubsup> <mi>A</mi> <mrow> <mi>d</mi> <mi>e</mi> <mi>c</mi> </mrow> <mo>*</mo> </msubsup> <mo>+</mo> <msub> <mi>A</mi> <mrow> <mi>d</mi> <mi>e</mi> <mi>c</mi> <mo>.</mo> <mi>p</mi> <mi>o</mi> <mi>t</mi> </mrow> </msub> </mrow> </mfrac> <mo>&amp;times;</mo> <mn>100</mn> <mi>%</mi> </mrow>
In formula：
<mrow> <msub> <mi>A</mi> <mrow> <mi>d</mi> <mi>e</mi> <mi>c</mi> <mo>.</mo> <mi>p</mi> <mi>o</mi> <mi>t</mi> </mrow> </msub> <mo>=</mo> <munderover> <mo>&amp;Integral;</mo> <msub> <mi>&amp;delta;</mi> <mrow> <mi>F</mi> <mi>E</mi> <mi>P</mi> </mrow> </msub> <msub> <mi>&amp;delta;</mi> <mrow> <mi>U</mi> <mi>E</mi> <mi>P</mi> </mrow> </msub> </munderover> <mrow> <mo>(</mo> <msub> <mi>P</mi> <mi>m</mi> </msub> <mo>-</mo> <msub> <mi>P</mi> <mi>e</mi> </msub> <mo>)</mo> </mrow> <mi>d</mi> <mi>&amp;delta;</mi> </mrow>
<mrow> <msubsup> <mi>A</mi> <mrow> <mi>d</mi> <mi>e</mi> <mi>c</mi> </mrow> <mo>*</mo> </msubsup> <mo>=</mo> <munderover> <mo>&amp;Integral;</mo> <msub> <mi>&amp;delta;</mi> <mi>&amp;tau;</mi> </msub> <msub> <mi>&amp;delta;</mi> <mrow> <mi>F</mi> <mi>E</mi> <mi>P</mi> </mrow> </msub> </munderover> <mrow> <mo>(</mo> <msub> <mi>P</mi> <mi>e</mi> </msub> <mo>-</mo> <msub> <mi>P</mi> <mi>m</mi> </msub> <mo>)</mo> </mrow> <mi>d</mi> <mi>&amp;delta;</mi> </mrow>
Wherein Adec.potRepresenting, which makes the image reach Instability state, also wants increased Implantation Energy, it can put down in P- δ With by fabricating path P on facee(δ)、Pm(δ), δ axis and straight line δ=δFEPThe area that is enclosed is measured.A* decFor the failure removal moment The kinetic energy of τ systems at the FEP of solstics reduces area；δτFor the rotor of failure removal moment first principal component virtual synchronous generator Angle；δFEPHeaded by put FEP at first principal component virtual synchronous generator rotor angle；δUEPHeaded by put UEP at first principal component it is virtual Generator amature angle；PeFor the equivalent output power of first principal component virtual synchronous generator；PmFor first principal component virtual synchronous generator Equivalent mechanical output.ηunValue range [- 1,0], ηunValue is smaller, and the unstable degree of system is bigger；η value range [0, 1], η values are bigger, and system stability margin is bigger.
CN201711352495.4A 2017-12-15 2017-12-15 Power system transient stability evaluation method based on principal component analysis Active CN108054768B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201711352495.4A CN108054768B (en) 2017-12-15 2017-12-15 Power system transient stability evaluation method based on principal component analysis

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201711352495.4A CN108054768B (en) 2017-12-15 2017-12-15 Power system transient stability evaluation method based on principal component analysis

Publications (2)

Publication Number Publication Date
CN108054768A true CN108054768A (en) 2018-05-18
CN108054768B CN108054768B (en) 2021-06-18

Family

ID=62133363

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201711352495.4A Active CN108054768B (en) 2017-12-15 2017-12-15 Power system transient stability evaluation method based on principal component analysis

Country Status (1)

Country Link
CN (1) CN108054768B (en)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109494765A (en) * 2018-11-13 2019-03-19 北京交通大学 Alternating current-direct current combined hybrid system transient stability control method based on EEAC
CN112069727A (en) * 2020-08-20 2020-12-11 国网河南省电力公司经济技术研究院 Intelligent transient stability evaluation system and method with high reliability for power system
CN113659575A (en) * 2021-10-19 2021-11-16 武汉理工大学 Method and device for predicting transient stability of power system

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109494765A (en) * 2018-11-13 2019-03-19 北京交通大学 Alternating current-direct current combined hybrid system transient stability control method based on EEAC
CN112069727A (en) * 2020-08-20 2020-12-11 国网河南省电力公司经济技术研究院 Intelligent transient stability evaluation system and method with high reliability for power system
CN112069727B (en) * 2020-08-20 2022-10-21 国网河南省电力公司经济技术研究院 Intelligent transient stability evaluation system and method with high reliability for power system
CN113659575A (en) * 2021-10-19 2021-11-16 武汉理工大学 Method and device for predicting transient stability of power system

Also Published As

Publication number Publication date
CN108054768B (en) 2021-06-18

Similar Documents

Publication Publication Date Title
CN102074955B (en) Method based on knowledge discovery technology for stability assessment and control of electric system
Qi et al. Nonlinear model reduction in power systems by balancing of empirical controllability and observability covariances
CN108832619A (en) Transient stability evaluation in power system method based on convolutional neural networks
Yu et al. An unscented particle filtering approach to decentralized dynamic state estimation for DFIG wind turbines in multi-area power systems
CN108732528A (en) A kind of digitalized electrical energy meter method for diagnosing faults based on depth confidence network
CN103700036B (en) A kind of transient stability projecting integral method being suitable to power system Multiple Time Scales
CN108667005B (en) Power grid static and dynamic combination vulnerability assessment method considering new energy influence
CN108092319A (en) A kind of Uncertainty Analysis Method and device of short-term wind-electricity power prediction
CN108054768A (en) Transient stability evaluation in power system method based on principal component analysis
Gou et al. Novel pair‐wise relative energy function for transient stability analysis and real‐time emergency control
CN110417005A (en) In conjunction with the transient stability catastrophe failure screening technique of deep learning and simulation calculation
CN105071380A (en) Power system wide-area coherency identification method and device
CN104156542A (en) Implicit-projection-based method for simulating stability of active power distribution system
CN105023121A (en) Method for comprehensively evaluating influences imposed on power distribution network by distributed power supply access
CN112821424A (en) Power system frequency response analysis method based on data-model fusion drive
CN115640748A (en) Dynamic frequency response prediction method for generators after disturbance of power system
CN103311960A (en) Method for dividing coherent stability regions of strong-connection power grids
Hu et al. Frequency prediction model combining ISFR model and LSTM network
He et al. Power system frequency situation prediction method based on transfer learning
CN117767275A (en) Method and system for monitoring voltage support strength in real time, storage medium and electronic equipment
CN103606952B (en) A kind of machine of cutting control measure quantization method based on system acceleration energy
Liu et al. Transient rotor angle stability prediction based on deep belief network and long short-term memory network
Saunders et al. Transient stability analysis using potential energy indices for determining critical generator sets
Ma et al. Frequency security assessment for receiving-end system based on deep learning method
CN105808825B (en) A kind of roller accidental projection integration method suitable for active power distribution network dynamic simulation

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant