CN105186525B - Power Network Partitioning method under wind power integration - Google Patents
Power Network Partitioning method under wind power integration Download PDFInfo
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Abstract
The invention discloses Power Network Partitioning method under wind power integration, comprise the following steps：To consider that the whole network electrical distance expected matrix of wind power probability characteristics replaces the electrical distance matrix under a certain trend section as Regionalization basis, PQ partition of nodes is realized based on AP clusters；Defined using perturbation method and consider that the PV node region voltage of wind-powered electricity generation probability characteristics regulates and controls sensitivity；The PV node subregion sorted based on sensitivity, node division considers the connectivity of region and controllability first, and most sensitive PQ regions are controlled while ensureing to sort out PV node to it as far as possible.Index evaluation result shows that the partition scheme that institute's extracting method is obtained obtains good result, can provide auxiliary reference for voltage control under access wind-powered electricity generation.
Description
Technical field
The present invention relates to Power Network Partitioning method under wind power integration.
Background technology
Tertiary voltage control turns into a kind of universally recognized voltage control mode of power system, and practical application effect is good.
And its optimized integration is the rational subregion of system node.Therefore effective partition method is voltage-controlled important topic.
Conventional voltage subregion can be summarized as following five class in method：Clustering algorithm；Graph theory；Intelligent heuristics algorithm；It is mixed
Box-like algorithm；Using structure characteristic analysis as the other method of representative.Existing partition method can preferably be applied to traditional power network,
But the sub-area division for causing flow state to change at random will be accessed applied to large-scale wind power to face the challenge.
In grid nodes subregion conventional method the method based on cluster due to it is directly perceived, quick the advantages of be widely used.Wind-powered electricity generation
Deng new energy access power network cause node based on sensitivity between electrical distance frequently change at random, to traditional partition method
Application bring difficulty.Existing document points out that sub-area division requirement is tried one's best stably, is selected with reducing pilot bus under different subregions
Select and changed with control strategy.Therefore how to obtain relatively stable and meeting voltage control requirement in the case of wind-powered electricity generation fluctuation reasonable point
Area is difficult point.Existing document proposes that by wind-powered electricity generation node processing be PV node, expects to obtain stable wind power output by active, enters
And take traditional fuzzy to cluster subregion.This method has processing simple, the small advantage of operand.But wind-powered electricity generation is used as instability energy
Source, current asynchronous or double-fed blower fan is both needed to absorb idle from system side and then sets up magnetic field, therefore wind-powered electricity generation is processed as with electricity
The PV node of pressure regulating power not fully tallies with the actual situation；Simultaneously wind power output is eliminated by disposably asking for active expectation
Fluctuation is difficult to embody the influence that the fluctuation of electrical distance causes subregion.In addition most literature proposes subregion high cohesion
The zoning requirements of lower coupling, but rarely document carries out division result assessment with quantizating index.There is document multiple target to quantify to comment
Estimate the reactive voltage dual-stage partition method Proceedings of the CSEEs 2009,29 (16) of characteristic, propose that five quantify mark first
Standard makes landmark breakthrough in terms of subregion assessment, but its index definition based on active phase angular sensitivity can not be intuitively anti-
Reflect the voltage controlling ability of subregion；The index depends on the preferable number of partitions specified and region desired node number simultaneously, with one
Determine subjectivity.Therefore the fluctuation sex chromosome mosaicism and objective effective subregion evaluation index that wind power integration is brought are power network access wind-powered electricity generations
The where the shoe pinches of subregion afterwards.
The content of the invention
To solve the deficiency that prior art is present, the invention discloses Power Network Partitioning method under wind power integration,
The present invention chooses AP clusters and is used as core partition method.The fluctuation sex chromosome mosaicism brought for wind power integration, to consider wind power
Between the node of probability characteristics electrical distance expected matrix substitution using the electrical distance matrix under single trend section as subregion according to
According to.Consider that PQ nodes are different from PV node response process, be primarily based on AP clustering algorithms to PQ partition of nodes.Perturbation method is based on again
Definition considers that each PV node regulates and controls sensitivity to the region voltage of each PQ subregions during wind power probability characteristics, is ensureing region company
Realize that PV node is sorted out to suitable PQ subregions while taking into account area based on preferential sensitivity principle on the premise of the general character and controllability
Domain optimal voltage control, completes the whole network subregion.Finally assessed to carry out objective effective subregion out of the interval decoupling of cluster, area
Coupling and subregion voltage control capability set out define subregion quality evaluation index division result is estimated.
To achieve the above object, concrete scheme of the invention is as follows：
Power Network Partitioning method under wind power integration, comprises the following steps：
Step one：Replaced with the whole network electrical distance expected matrix for considering wind power probability characteristics under a certain trend section
Electrical distance matrix as Regionalization basis, PQ partition of nodes is realized based on AP clusters；
Step 2：Definition considers that region voltage regulation and control of each PV node to each PQ subregions are sensitive during wind power probability characteristics
Degree, obtains PV node partition data and prepares；
Step 3：Regulate and control the PV node subregion of sensitivity sequence based on region voltage, node division considers that region connects first
The general character and controllability, most sensitive PQ regions are controlled while ensureing to sort out PV node to it；
Step 4：Subregion quality is defined from the subarea management and the aspect of PV node voltage control capability two of PQ nodes
Close coupling interval weak coupling index and the sensitive index of PV node regulating and controlling voltage in evaluation index, including area, quantification of targets subregion will
Ask, partition scheme is estimated.
Further, between PQ nodes electrical distance definition：
The voltage sensibility defined using trend Jacobian matrix between PQ nodes is as follows：
In formula：βijFor voltage sensibility between node i and j；It is N*N square formations, N is the whole network
The number of PQ nodes,For trend Jacobian matrix, αijAnd αjjRespectively α i rows j row and j row j column elements；
AP clustering algorithms allow using asymmetric electrical distance matrix as input, define electrical distance matrix between PQ nodes
It is as follows：
In formula：N is the whole network PQ node numbers.
Further, electrical distance expected matrix is set up under wind power integration：
Wind power probability characteristics is characterized using discrete probability distribution, wind-powered electricity generation active power output historical sample is united
Meter, it is assumed that wind-powered electricity generation nominal output is Pe, will exert oneself interval [0,100%Pe] it is discrete turn to f it is interval, count wind-powered electricity generation active power output
Sample falls in each interval frequency, calculates each interval probability, takes power interval intermediate value to be exerted oneself as each interval typical case successively
Scene, can obtain wind-powered electricity generation probability distribution；
The stabilization that each scene of exerting oneself obtained by discretization is considered under the probability is exerted oneself, the timing of wind-powered electricity generation permeability one, when
Wind-powered electricity generation scene is with active power output Pk(k=1,2 ..., f) access power network, access point is processed as PQ nodes, by traditional power network electrically away from
Electrical distance matrix D (k) is as shown in formula (3) between obtaining PQ nodes from the mode of asking for, and correspondence probability is pk；
D (k) in formulaij(i ∈ [1, N], j ∈ [1, N]) expression wind power output is PkWhen, it is electric between node i and node j
Distance is D (k)ij；
Electrical distance is asked for expecting between PQ nodes under each scene, obtains stable electrical distance expected matrix ED substitutions a certain
Electrical distance matrix under trend section is used as the Regionalization basis under wind power integration；
Wherein, ED is electrical distance expected matrix between the whole network PQ nodes.
Further, PQ partition of nodes is realized based on AP clusters, to consider the electricity of wind power probability characteristics between PQ nodes
Gas is apart from expected matrix as input, and distance is smaller more similar between AP clustering algorithm defining nodes, therefore by the electrical distance phase
Matrix ED matrix each elements are hoped to take negative value to can obtain similarity matrix S, can be automatically derived with matrix S input AP clustering algorithms
Optimum cluster result.
Further, voltage sensibility is influenceed by running status and network parameter between node, electricity of the PV node to PQ nodes
Pressure regulation and control sensitivity relation：
F(i)·ΔVPV(i)=Δ VPQ(i) (5)
In formula：ΔVPV(i) with Δ VPQ(i) PV node under running status i is illustrated respectively in PQ node voltages to change；F
(i) it is the regulating and controlling voltage sensitivity matrix under running status i；
Under running status i, regulating and controlling voltage sensitivity matrix of the M PV node to N number of PQ nodes is defined based on perturbation method
It is as follows：
In formula, F (i) arbitrary elementsWherein Δ VPV(i)yWith Δ VPQ(i)xIt is illustrated respectively in
PV node y voltages Perturbation and corresponding PQ nodes x voltage variety under running status i.
Fluctuation will be presented in the regulating and controlling voltage sensitivity under wind power integration of same PV node, be expected with regulating and controlling voltage sensitivity
Characterize and consider ability of regulation and control of the PV node to each PQ nodes under wind power probability characteristics.
Further, wind-powered electricity generation statistical probability distribution rule definition：
In formula：F arbitrary elementsRepresent that PV node x is to PQ nodes y under wind power integration
Regulating and controlling voltage sensitivity.
Because the original state that PV node is sorted out is L PQ subregion, region voltage of the PV node to PQ subregions is defined for this
It is that the PV node regulates and controls the desired average of sensitivity, definition to all node voltages in the PQ subregions to regulate and control sensitivity：
In formula：G arbitrary elementsRepresent PV node x to PQ subregions ΩyRegion voltage
Regulate and control sensitivity；R is ΩyInterior any PQ node numbers；nyFor ΩyIn contained PQ nodes, Fxr is F arbitrary elements, represents wind
Regulating and controlling voltage sensitivity of the lower PV node x to PQ nodes r is electrically accessed, M is the number of the whole network PV node.
Further, PV node subregion can be realized on the basis of the regulation and control sensitivity of its region voltage to each PQ subregions.Section
Point is divided considers the connectivity of region and controllability first, and most sensitive PQ is controlled while ensureing to sort out PV node to it as far as possible
Region, detailed process is as follows：
(1) the region voltage regulation and control sensitivity sequence by all PV nodes to first PQ subregion, it is ensured that connective feelings
Most sensitive PV node merger Ru Gai areas are selected under condition；Remaining region similarly carries out reactive source node selection, and PV sections are chosen every time
Ensure that each PQ subregions have an idle source node behind the PV node that the forefoot area that should be excluded during point had been selected, first subzone,
Ensure subregion controllability；
(2) PV node of remaining non-merger is sorted, single PV node is regulated and controled into spirit to the region voltage of all PQ subregions
Sensitivity is sorted, and the PV node is divided into sensitivity highest PQ subregions in the case where ensureing connectedness.It is sequentially completed all
PV node is divided.
Voltage partition lacks quantification of targets and assesses subregion effect, therefore is referred to based on the Silhoutte that electrical distance is defined
Mark is quantified the quality of division result, to assess division result quality.
Further, expected based on electrical distance between PQ nodes under Silhouttte indexs and wind power integration strong in definition
The interval weak coupling index of coupling is as follows：
In formula：QNJiRepresent the coupling index of i-th of PQ subregion；QNJ represents the whole network PQ subarea management indexs；ai(t)
Represent subregion i interior nodes t and all PQ nodes electrical distance averages in area；bi(t) represent subregion i interior nodes t to owning outside area
PQ node electrical distance averages；CiSituation is passed through for indicating PQ subregions i with the presence or absence of node, when there are one or more nodes
Not with any node around it point to same area, then there is isolated node or there is reachability problem in subregion, this seasonSo that QNJ=-1；Otherwise Ci=1, niFor PQ nodes in subregion i；L is the PQ numbers of partitions；QNJiAnd QNJ
Value between [- 1,1].
Further, the sensitive index of PV node regulating and controlling voltage：
PV node is so that in regulating and controlling voltage sensitivity point to optimal PQ regions, ideally, each PV node is with maximum
Sensitivity control region interior nodes voltage, while hardly perturbing area exterior node voltage, thus meaning is set out, legal based on perturbing
The adopted sensitive indices P VC of PV node regulating and controlling voltage is as follows：
In formula：PVCjRepresent the PV node j sensitive index of regulating and controlling voltage；PVC represents that the whole network PV node regulating and controlling voltage is sensitive
Index；ΩjFor PQ node sets in PV node j affiliated areas, Ω gathers for the whole network PQ,It is scalar region ΩjInterior PV distributions
Equilibrium degree parameter, when area's PV node number is more than 0 and PV node is directly connected PQ nodes point to same area then
OtherwiseDue to wind power integration, PV node voltage control sensitivity is different under different scenes, | Δ Up| with | Δ Uq| it is respectively
PQ nodes p and q voltage magnitude perturbation absolute value, using voltage deviation processing fluctuation problem is expected after wind-powered electricity generation injection, i.e.,The lower PQ nodes p of wind-powered electricity generation scene i accesses voltage magnitude Perturbation；ΔUqi
The lower PQ nodes q of wind-powered electricity generation scene i accesses voltage magnitude Perturbation, Pi is wind-powered electricity generation scene i probability.
Beneficial effects of the present invention：
Herein for the sub-area division in the case of access wind-powered electricity generation, expected with the electrical distance for considering wind power probability characteristics
The fluctuation that matrix replaces the electrical distance matrix under single trend section and as Regionalization basis wind power integration can be overcome to bring is asked
Topic.It is electricity to define two objective subregion project evaluation chain indexs from PQ partition of nodes coupling and PV node voltage controlling ability
The quantitative evaluation of subregion is pressed to provide effective reference.Index evaluation result shows that the partition scheme that institute's extracting method is obtained obtains good effect
Really, auxiliary reference can be provided for voltage control under access wind-powered electricity generation.
Brief description of the drawings
Fig. 1 New England39 node systems；
Fig. 2 New England39 node system division result figures；
Embodiment：
The present invention is described in detail below in conjunction with the accompanying drawings：
PQ partition of nodes based on AP clustering algorithms：
First, the PQ node electrical distance expected matrixes of wind power probability characteristics are introduced
It is very ripe in the method for contact tight ness rating between electrical distance sign node under traditional electric network model, in operation shape
Deterministic electrical distance matrix between state and network parameter can obtain PQ nodes when determining by Jacobian matrix.Wind power integration power network
After will cause under consolidated network structure electrical distance matrix that there is uncertainty.Therefore, set forth herein to consider that wind power is general
The whole network electrical distance expected matrix of rate feature replaces the electrical distance matrix under a certain trend section to be used as Regionalization basis.With this
The fluctuation sex chromosome mosaicism brought after processing wind-powered electricity generation injection obtains stable subregion.
Wherein, between PQ nodes electrical distance definition：
Voltage sensibility is obtained based on the Jacobian matrix obtained by Load flow calculation and then the method for electrical distance is defined perhaps
All applied in many documents and obtained good result.
The voltage sensibility that existing literature is defined using trend Jacobian matrix between PQ nodes is as follows：
In formula：βijFor voltage sensibility between node i and j；It is N*N square formations, N N are complete
Net the number of PQ nodes.For trend Jacobian matrix.αijAnd αjjRespectively α i rows j row and j row j column elements.
AP clustering algorithms allow using asymmetric electrical distance matrix as input, and electrical distance between PQ nodes is defined herein
Matrix is as follows：
In formula：N is the whole network PQ node numbers；DijRepresent the electrical distance between arbitrary node i to node j.
Secondly, electrical distance expected matrix is set up under wind power integration：
The direct basis of subregion is electrical distance matrix, is non-linear relation between node power and electrical distance, is used
Consider that the electrical distance of wind power probability characteristics is expected, can more accurately describe influence of the wind-powered electricity generation fluctuation to electrical distance, directly
The factor directly perceived for portraying influence subregion is connect, makes electrical distance expected matrix gained partition scheme used that there is wind power integration stronger
Adaptability.
Wind power probability characteristics is characterized using discrete probability distribution, wind-powered electricity generation active power output historical sample is united
Meter.Assuming that wind-powered electricity generation nominal output is Pe, will exert oneself interval [0,100%Pe] it is discrete turn to f it is interval.Count wind-powered electricity generation active power output
Sample falls in each interval frequency, calculates each interval probability.Power interval intermediate value is taken to be exerted oneself as each interval typical case successively
Scene, can obtain wind-powered electricity generation probability distribution.
The stabilization that each scene of exerting oneself obtained by discretization is considered under the probability is exerted oneself.The timing of wind-powered electricity generation permeability one, when
Wind-powered electricity generation scene is with active power output Pk(k=1,2 ..., f) access power network, and access point is processed as PQ nodes.By traditional power network electrically away from
Electrical distance matrix D (k) is as shown in formula (3) between obtaining PQ nodes from the mode of asking for, and correspondence probability is pk。
D (k) in formulaij(i ∈ [1, N], j ∈ [1, N]) expression wind power output is PkWhen, it is electric between node i and node j
Distance is D (k)ij。
Electrical distance is asked for expecting between PQ nodes under each scene, obtains stable electrical distance expected matrix ED substitutions a certain
Electrical distance matrix under trend section is used as the Regionalization basis under wind power integration.
Wherein, ED is electrical distance expected matrix between the whole network PQ nodes.EDij(i ∈ [1, N], j ∈ [1, N]) represents node i
Consider that the electrical distance under wind-powered electricity generation injection is expected between node j.
PQ partition of nodes is realized based on AP clusters：
AP clusters are a kind of new unmanned Supervised Clustering Methods being published in 2007 on science.Algorithm is only with opinion
Similarity matrix is input between domain node.Using between PQ nodes consider wind power probability characteristics electrical distance expected matrix as
Distance is smaller more similar between input, AP clustering algorithm defining nodes, therefore takes negative value to can obtain phase ED matrix each elements
Like degree matrix S.Can automatically derived optimum cluster result with S gusts of input AP clustering algorithms.Algorithm details are referring to document：Frey B
J,Dueck D.Clustering by passing messages between data points[J].science,2007,
315(5814):972-976.。
Next step will define each PV node when considering wind power probability characteristics and regulate and control spirit to the region voltage of each PQ subregions
Sensitivity, obtains PV node partition data and prepares.
Regulate and control the PV node subregion of sensitivity sequence under wind power integration based on region voltage：
Complete to need behind PQ partition of nodes to carry out subregion classification to PV node, it is ensured that cause in the case of connective each subregion without
Work(source distribution is uniform and ensures that each reactive source is controlled the optimal voltage of each PQ subregions as far as possible.
Electricity between the PV node region voltage regulation and control sensitivity nodes for considering wind power probability characteristics is defined using perturbation method
Pressure sensitivity is influenceed by running status and network parameter, and according to document, (YUN will is white, Liu Yutian, Liang Jun, waits to consider wind power
Fluctuate pilot bus system of selection [J] Automation of Electric Systems of probability characteristics, 2014,38 (9)：20~25.) exist it is as follows
Regulating and controlling voltage sensitivity relation of the PV node to PQ nodes：
F(i)·ΔVPV(i)=Δ VPQ(i) (5)
In formula：ΔVPV(i) with Δ VPQ(i) PV node under running status i is illustrated respectively in PQ node voltages to change；F
(i) it is the regulating and controlling voltage sensitivity matrix under running status i.
Under running status i, regulating and controlling voltage sensitivity matrix of the M PV node to N number of PQ nodes is defined based on perturbation method
It is as follows：
In formula, F (i) arbitrary elementsWherein Δ VPV(i)yWith Δ VPQ(i)xIt is illustrated respectively in
PV node y voltages Perturbation and corresponding PQ nodes x voltage variety under running status i.
Fluctuation will be presented in the regulating and controlling voltage sensitivity under wind power integration of same PV node.Expected with regulating and controlling voltage sensitivity
Characterize and consider ability of regulation and control of the PV node to each PQ nodes under wind power probability characteristics.
Restrained and defined based on wind-powered electricity generation statistical probability distribution：
In formula：F arbitrary elementsRepresent that PV node x is to PQ nodes y under wind power integration
Regulating and controlling voltage sensitivity.
Because the original state that PV node is sorted out is L PQ subregion, region voltage of the PV node to PQ subregions is defined for this
It is that the PV node regulates and controls the desired average of sensitivity to all node voltages in the PQ subregions to regulate and control sensitivity.Definition：
In formula：G arbitrary elementsRepresent PV node x to PQ subregions ΩyRegion voltage
Regulate and control sensitivity；R is ΩyInterior any PQ node numbers；nyFor ΩyIn contained PQ nodes, Fxr is F arbitrary elements, represents wind
Regulating and controlling voltage sensitivity of the lower PV node x to PQ nodes r is electrically accessed, M is the number of the whole network PV node.
Regulate and control the PV node subregion of sensitivity sequence based on region voltage：
PV node subregion can be realized on the basis of the regulation and control sensitivity of its region voltage to each PQ subregions.Node division is first
Consider the connectivity of region and controllability, most sensitive PQ regions are controlled while ensureing to sort out PV node to it as far as possible.Specifically
Process is as follows：
(1) the region voltage regulation and control sensitivity sequence by all PV nodes to first PQ subregion, it is ensured that connective feelings
Most sensitive PV node merger Ru Gai areas are selected under condition；Remaining region similarly carries out reactive source node selection, and PV sections are chosen every time
The PV node that the forefoot area that should be excluded during point had been selected.Ensure that each PQ subregions have an idle source node behind first subzone,
Ensure subregion controllability.
(2) PV node of remaining non-merger is sorted.Single PV node is regulated and controled into spirit to the region voltage of all PQ subregions
Sensitivity is sorted, and the PV node is divided into sensitivity highest PQ subregions in the case where ensureing connectedness.It is sequentially completed all
PV node is divided.
PQ nodes are the most nodes of power network, and PQ partition of nodes is first carried out in the case where the number of partitions is unknown and is conducive to giving point
Area's algorithm enough information is to draw the rational number of partitions.AP clustering algorithms can ensure that PQ partition of nodes is connective simultaneously.PV
PQ subregions are first carried out during node merger and select idle source node, make each subregion containing extremely on the premise of connectedness is ensured
A few idle source node, to meet voltage control requirement.
Subregion quality evaluation index：
Lot of documents provides the requirement of voltage partition, but rarely document proposes to weigh the quantizating index of subregion effect.Electricity
Pressure subregion first has to ensure that subregion is connective；Close coupling by stages Approximate Decoupling inside subregion is required simultaneously；PV node carries out electricity
It should ensure that most strong on the control of area's interior nodes voltage during pressure regulation and control while influenceing minimum to area's exterior node.It is this herein from PQ nodes
Subarea management and the aspect of PV node voltage control capability two are set out and define subregion quality evaluation index.Quantification of targets subregion will
Ask, objective evaluation can be carried out to partition scheme.
Close coupling interval weak coupling index in PQ node districts：
PQ nodes are most nodes in power network, thus final subregion can be assessed based on the coupling power of PQ partition of nodes
Coupling.Cluster Silhouttte indexs can effectively reflect compactness and interval separability in cluster area, therefore be based on
Electrical distance expects that the interval weak coupling index of close coupling is such as in definition between PQ nodes under Silhouttte indexs and wind power integration
Under：
In formula：QNJiRepresent the coupling index of i-th of PQ subregion；QNJ represents the whole network PQ subarea management indexs；ai(t)
Represent subregion i interior nodes t and all PQ nodes electrical distance averages in area；bi(t) represent subregion i interior nodes t to owning outside area
PQ node electrical distance averages；CiSituation is passed through for indicating PQ subregions i with the presence or absence of node, when there are one or more nodes
Not with any node around it point to same area, then there is isolated node or there is reachability problem in subregion, this seasonSo that QNJ=-1；Otherwise Ci=1.niFor PQ nodes in subregion i；L is the PQ numbers of partitions；
QNJiAnd QNJ value is between [- 1,1].Index is with the big small quantization the whole network couplings of QNJ, the bigger table of its value
Show and couple stronger in the area of the better i.e. the whole network partition scheme of subarea management while interval coupling is weaker.As the QNJ of different schemes
Index is close, each subregion QNJ under same schemeiWhen fluctuating little, illustrate that each subarea management level is approximate, overall plan is more
Rationally.
The sensitive index of PV node regulating and controlling voltage：
PV node is with regulating and controlling voltage sensitivity point to optimal PQ regions.Ideally, each PV node is with maximum
Sensitivity control region interior nodes voltage, while hardly perturbing area exterior node voltage.Thus meaning is set out, legal based on perturbing
The adopted sensitive indices P VC of PV node regulating and controlling voltage is as follows：
In formula：PVCjRepresent the PV node j sensitive index of regulating and controlling voltage；PVC represents that the whole network PV node regulating and controlling voltage is sensitive
Index；ΩjFor PQ node sets in PV node j affiliated areas, Ω gathers for the whole network PQ.It is scalar region ΩjInterior PV distributions
Equilibrium degree parameter, when area's PV node number is more than 0 and PV node is directly connected PQ nodes point to same area then
OtherwiseDue to wind power integration, PV node voltage control sensitivity is different under different scenes.|ΔUp| with | Δ Uq| it is respectively
PQ nodes p and q voltage magnitude perturbation absolute value.Using voltage deviation processing fluctuation problem is expected after wind-powered electricity generation injection, i.e.,
Index is proposed based on perturbation method.When j-th of PV node voltage perturbation, whole PQ nodes electricity in the PV affiliated areas
The ratio between pressure increment absolute value sum and the whole network PQ node voltage increment absolute value sums can reflect the PV to one's respective area voltage control
Ability processed and perturbing area external voltage ability.M PV node degree of control average can reflect all PV node integrated voltage controls of the whole network
Ability processed.PVCjWith PVC values between [- 1,1], desired value represents that subregion voltage control sensitivity is higher closer to 1.When
When different schemes PVC indexs are close, each sensitive indices P VC of PV node regulating and controlling voltage under same schemejFluctuation is smaller to represent each nothing
Work(source node ability of regulation and control is close, and overall plan regulating and controlling voltage is more excellent.
Subregion assesses subarea management and PV node voltage controlling ability respectively from PQ nodes, takes into account consideration node
The factor such as subregion is connective and whether PV node distribution is uniform.Due to most optimal sorting can be automatically determined using AP clustering algorithms herein
Area's number, it is taken as that gained cluster has met preferable number of partitions index.(Wang Kaijun, Zhang Junying, Li Dan wait adaptively to imitate to document
Penetrate propagation clustering [J] automation journals, 2007,33 (12)：1242~when 1246.) pointing out to N number of point cluster, it is rational optimal
The cluster numbers upper limit isSimulation result shows that the AP cluster numbers of partitions meet this requirement, therefore also reflects that AP clusters are applied to
The validity of grid nodes subregion.Two indexs are defined herein to cover document substantially (Chen Xia, Sun Haishun, Sui Xianchao wait a kind of
Region couples degree index and its application study [J] electric power system protection and controls in voltage power-less zonal control, 2011,
39(7)：83~88.) in index evaluation all factors.It is prominent to assess subregion voltage control capability, and without it is artificial it is subjective because
Element can carry out objective quantification assessment to division result.
Sample calculation analysis：Using the node systems of New England39 shown in Fig. 1 as analogue system, randomly select No. 12 nodes and enter
Sector-style is electrically accessed.Added wind-powered electricity generation exerts oneself sampled data for 1 year as sample using Ji NORTEL net wind field, and the sampling interval is 5min, specified
Active power output is 200MW.Wind-powered electricity generation injection node processing is PQ nodes, and No. 31 balance nodes are not involved in subregion and are directly divided to straight
Connect subregion where connected PQ nodes.
PQ partition of nodes：NORTEL net wind field 1 year wind-powered electricity generation active power output historical sample point in Ji is counted first, obtained
To wind-powered electricity generation probability distribution.Sample shows that the bigger respective frequencies of active power output are smaller and 0 sample of exerting oneself occurs than more frequently special
Point.Therefore exerted oneself using 0 and individually count interval slightly larger interval division mode when exerting oneself big.During due to exerting oneself big probability compared with
Influence very little small thus to electrical distance expected matrix, therefore the power interval after nominal output 40% is merged, shape
It is into four discretization power intervals0%Pe, (0%Pe, 20%Pe], (20%Pe, 40%Pe], (40%Pe, 100%Pe].Statistics
Annual wind-powered electricity generation active power output sample falls in each interval frequency, and calculates each interval probability.Four typical cases are taken to exert oneself scene
Respectively each interval intermediate value.Statistical probability is as shown in table 1.When calculating wind-powered electricity generation permeability is 50%, each scene wind power output.Wind-powered electricity generation
Kept when being implanted sequentially according to scene each generator output account for total load ratio power distribution it is constant.
The output of wind electric field statistical probability of table 1
Calculate under each scene electrical distance matrix between PQ nodes respectively, and asked for according to probability between the whole network PQ nodes electrically
Distance is expected.Cluster and input in this, as AP, show that the whole network PQ node clustering results are
{1,2,3,25},{4,5,6,7,8,9,10,11,12,13,14},{15,16,17,18,21,22,23,24,27},
{19,20},{26,28,29}.Division result shows that PQ node clusterings do not occur reachability problem；Document [26] is pointed out to N number of point
During cluster, the rational optimum cluster upper limit isI.e. N=29, gained cluster numbers are clustered for 29 PQ nodes of the whole networkAP clusters meet this requirement well.Therefore carrying out PQ partition of nodes based on AP clusters can automatically derived rationalization partition
Number, and in the absence of reachability problem.
PV node subregion：After the completion of PQ partition of nodes, then PV node defined to the regions of each PQ subregions electricity based on perturbation method
Pressure regulation and control sensitivity, PV node subregion is completed based on sensitivity sequence.Calculate and consider each PV node under wind power probability characteristics
Region voltage regulation and control sensitivity to each PQ subregions is as shown in table 2.PV node subregion domain is 9 nothings in addition to balance nodes
Work(source node.Travel through each PQ subregions successively first, each PQ subregions is selected most sensitive successively in the case where ensureing connectedness
PV node.As shown in table 2, subregion 1 chooses No. 30 nodes, and subregion 2 chooses most sensitive No. 32 sections in remaining idle source node
Point, remaining subregion chooses 35 successively, 33, No. 38 nodes.Now each subregion, which divides 1 PV node, can ensure that region voltage is controllable
Property.Remaining 4 PV nodes divide the PV node to the maximum PQ of sensitivity after its sensitivity to each PQ subregions is sorted successively
In region.Thus the whole network subregion is completed, division result is as shown in table 3.Each subregion is saved containing at least one PV after the completion of subregion
Point, voltage controllability and subregion connectedness are satisfied by.
The PV node region voltage of table 2 regulates and controls sensitivity
The system whole-network division results of 3 New England of table 39
System partitioning schematic diagram is as shown in Figure 2.As seen from Figure 2.Reachability problem is not present in division result, and respectively
PV node is also divided to its direct-connected PQ nodes region.Gained division result is approximate with document [24] result, only part of nodes point
Area is different, will compare both division results by quantification of targets below.
The PVC quantitative evaluation results contrasts of table 4
Subregion based on quantizating index is assessed：
It is quantitative evaluation division result after the completion of the whole network subregion, calculates PVC the and QNJ indexs difference of this paper partition schemes
As shown in table 4 and table 5.This paper division results are contrasted with document [24] division result, document [24] index difference is calculated
As shown in table 4 and table 6.QNJ indexs indicate in the area of subregion stiffness of coupling and interval decoupling degree, its value [- 1,1] it
Between, index shows that more greatly the stronger interval coupling of coupling is weaker in cluster area, i.e., clustering result quality is good.As a result this paper square partitions are shown
Case the whole network QNJ indexs are higher, and each subregion index is more uniformly fluctuated less, does not occur negative value, therefore this paper subregions are in area
Good result is obtained in close coupling interval weak coupling index.PVC index expressions PV node is to region voltage control sensitivity.
As a result show that the overall PV node control sensitivity of this paper subregions is high, each PV control effects are more uniformly fluctuated less, compared with document
[24] partition scheme obtains more preferable effect.
This paper QNJ quantitative evaluation results of table 5
The document of table 6 [24] QNJ quantitative evaluation results
Document [24]：Qiao Liang, Lu Jiping, Huang Hui, wait learning algorithms partition method [J] the power networks of containing wind field
Technology, 2010,34 (10):163~168.
Wind power integration causes network operation state to have stochastic volatility, it is considered between the lower the whole network node of wind-powered electricity generation injection electrically away from
Replace the electrical distance matrix under single trend section as Regionalization basis from expected matrix, acquisition adapts to various wind power outputs
Stable the whole network subregion.Consider that PQ nodes are different from PV node response process, be primarily based on AP clustering algorithms and PQ nodes are carried out
Subregion；Then it is real based on preferential sensitivity principle on the premise of the connectivity of region and controllability is ensured using PV node as domain
Existing PV node is sorted out to suitable PQ subregions to be controlled while taking into account region optimal voltage, is finally completed the whole network subregion.Finally from poly-
Coupling and the requirement of subregion voltage control capability are set out in class interval decoupling, area, define subregion quality evaluation index, objective
Evaluate subregion quality.Simulation result shows the feasibility and validity of this paper institutes extracting method.
Although above-mentioned the embodiment of the present invention is described with reference to accompanying drawing, not to present invention protection model
The limitation enclosed, one of ordinary skill in the art should be understood that on the basis of technical scheme those skilled in the art are not
Need to pay various modifications or deform still within protection scope of the present invention that creative work can make.
Claims (10)
1. Power Network Partitioning method under wind power integration, it is characterized in that, comprise the following steps：
Step one：Electricity under a certain trend section is replaced with the whole network electrical distance expected matrix for considering wind power probability characteristics
Gas distance matrix realizes PQ partition of nodes as Regionalization basis based on AP clusters；
Step 2：Definition considers that each PV node regulates and controls sensitivity to the region voltage of each PQ subregions during wind power probability characteristics,
PV node partition data is obtained to prepare；
Step 3：Regulate and control the PV node subregion of sensitivity sequence based on region voltage, node division considers the connectivity of region first
And controllability, control most sensitive PQ regions while ensureing to sort out PV node to it；
Step 4：Subregion quality evaluation is defined from the subarea management and the aspect of PV node voltage control capability two of PQ nodes
Close coupling interval weak coupling index and the sensitive index of PV node regulating and controlling voltage in index, including area, quantification of targets zoning requirements are right
Partition scheme is estimated.
2. Power Network Partitioning method under wind power integration as claimed in claim 1, it is characterized in that, between PQ nodes electrically away from
From definition：
The voltage sensibility defined using trend Jacobian matrix between PQ nodes is as follows：
<mrow>
<msub>
<mi>&beta;</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
</msub>
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<mo>&part;</mo>
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</msub>
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<mo>=</mo>
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<mi>&alpha;</mi>
<mrow>
<mi>i</mi>
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<mi>&alpha;</mi>
<mrow>
<mi>j</mi>
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</mrow>
</msub>
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<mo>-</mo>
<mo>-</mo>
<mrow>
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</mrow>
In formula：βijFor voltage sensibility between node i and j；It is N*N square formations, N saves for the whole network PQ
The number of point,For trend Jacobian matrix, αijAnd αjjRespectively α i rows j row and j row j column elements；
AP clustering algorithms allow using asymmetric electrical distance matrix as input, and electrical distance matrix is such as between defining PQ nodes
Under：
3. Power Network Partitioning method under wind power integration as claimed in claim 2, it is characterized in that, set up under wind power integration
Electrical distance expected matrix：
Wind power probability characteristics is characterized using discrete probability distribution, wind-powered electricity generation active power output historical sample is counted, it is false
If wind-powered electricity generation nominal output is Pe, will exert oneself interval [0,100%Pe] it is discrete turn to f it is interval, statistics wind-powered electricity generation active power output sample falls
In each interval frequency, each interval probability is calculated, takes power interval intermediate value to be exerted oneself scene as each interval typical case successively, can
Obtain wind-powered electricity generation probability distribution；
The stabilization that each scene of exerting oneself obtained by discretization is considered under the probability is exerted oneself, the timing of wind-powered electricity generation permeability one, works as wind-powered electricity generation
Scene is with active power output Pk(k=1,2 ..., f) access power network, and access point is processed as PQ nodes, asked by traditional power network electrical distance
Take mode obtain PQ nodes between electrical distance matrix D (k) as shown in formula (3), correspondence probability be pk；
D (k) in formulaij(i ∈ [1, N], j ∈ [1, N]) expression wind power output is PkWhen, the electrical distance between node i and node j
For D (k)ij；
Electrical distance is asked for expecting between PQ nodes under each scene, obtains stable electrical distance expected matrix ED and replaces a certain trend
Electrical distance matrix under section is used as the Regionalization basis under wind power integration；
Wherein, ED is electrical distance expected matrix between the whole network PQ nodes.
4. Power Network Partitioning method under wind power integration as claimed in claim 1, it is characterized in that, clustered and realized based on AP
PQ partition of nodes, to consider that the electrical distance expected matrix of wind power probability characteristics is used as input between PQ nodes, AP, which is clustered, to be calculated
Distance is smaller more similar between law regulation node, therefore takes negative value to can obtain electrical distance expected matrix ED matrix each elements
Similarity matrix S, can automatically derived optimum cluster result with matrix S input AP clustering algorithms.
5. Power Network Partitioning method under wind power integration as claimed in claim 1, it is characterized in that, pressure sensitive between node
Degree is influenceed by running status and network parameter, regulating and controlling voltage sensitivity relation of the PV node to PQ nodes：
F(i)·ΔVPV(i)=Δ VPQ(i) (5)
In formula：ΔVPV(i) with Δ VPQ(i) PV node under running status i is illustrated respectively in PQ node voltages to change；F (i) is fortune
Regulating and controlling voltage sensitivity matrix under row state i；
Under running status i, M PV node is defined based on perturbation method as follows to the regulating and controlling voltage sensitivity matrix of N number of PQ nodes：
In formula, F (i) arbitrary elementsWherein Δ VPV(i)yWith Δ VPQ(i)xIt is illustrated respectively in operation
PV node y voltages Perturbation and corresponding PQ nodes x voltage variety under state i；
Fluctuation will be presented in the regulating and controlling voltage sensitivity under wind power integration of same PV node, expect to characterize with regulating and controlling voltage sensitivity
Consider ability of regulation and control of the PV node to each PQ nodes under wind power probability characteristics.
6. Power Network Partitioning method under wind power integration as claimed in claim 1, it is characterized in that, wind-powered electricity generation statistical probability point
Bu Lv is defined：
In formula：F arbitrary elementsRepresent electricity of the PV node x to PQ nodes y under wind power integration
Pressure regulation and control sensitivity, f is the interval [0,100%P that will exert oneselfe] discretization interval number；F (i) is the voltage under running status i
Regulate and control sensitivity matrix；Pi is wind-powered electricity generation scene i probability；M is the number of the whole network PV node；N is the number of the whole network PQ nodes.
7. Power Network Partitioning method under wind power integration as claimed in claim 1, it is characterized in that, because PV node is sorted out
Original state be L PQ subregion, it is the PV node pair that PV node is defined for this to regulate and control sensitivity to the region voltages of PQ subregions
All node voltage regulation and control desired averages of sensitivity, definition in the PQ subregions：
In formula：G arbitrary elementsRepresent PV node x to PQ subregions ΩyRegion voltage regulation and control
Sensitivity；R is ΩyInterior any PQ node numbers；nyFor ΩyIn contained PQ nodes, Fxr is F arbitrary elements, represents that wind-powered electricity generation connects
Enter regulating and controlling voltage sensitivity of the lower PV node x to PQ nodes r, M is the number of the whole network PV node.
8. Power Network Partitioning method under wind power integration as claimed in claim 1, it is characterized in that, PV node subregion can be
It realizes that node division considers the connectivity of region and controllable first on the basis of region voltage regulation and control sensitivity to each PQ subregions
Property, most sensitive PQ regions are controlled while ensureing to sort out PV node to it as far as possible, detailed process is as follows：
(1) the region voltage regulation and control sensitivity sequence by all PV nodes to first PQ subregion, it is ensured that in the case of connective
The most sensitive PV node merger Ru Gai areas of selection；Remaining region similarly carries out reactive source node selection, when choosing PV node every time
Ensure that each PQ subregions have an idle source node behind the PV node that the forefoot area that should be excluded had been selected, first subzone, it is ensured that
Subregion controllability；
(2) PV node of remaining non-merger is sorted, single PV node is regulated and controled into sensitivity to the region voltage of all PQ subregions
Sequence, sensitivity highest PQ subregions are divided in the case where ensureing connectedness by the PV node, are sequentially completed all PV sections
Point is divided.
9. Power Network Partitioning method under wind power integration as claimed in claim 1, it is characterized in that, based on Silhouttte
Electrical distance expects that the interval weak coupling index of close coupling is as follows in definition between PQ nodes under index and wind power integration：
<mrow>
<msub>
<mi>QNJ</mi>
<mi>i</mi>
</msub>
<mo>=</mo>
<mfrac>
<mn>1</mn>
<msub>
<mi>n</mi>
<mi>i</mi>
</msub>
</mfrac>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>t</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
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<mi>n</mi>
<mi>i</mi>
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</munderover>
<mrow>
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<mi>b</mi>
<mi>i</mi>
</msub>
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<mo>(</mo>
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<mrow>
<mi>m</mi>
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<mi>x</mi>
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In formula：QNJiRepresent the coupling index of i-th of PQ subregion；QNJ represents the whole network PQ subarea management indexs；ai(t) represent
Subregion i interior nodes t and all PQ nodes electrical distance averages in area；bi(t) represent that subregion i interior nodes t is saved to all PQ outside area
Point electrical distance average；CiPass through situation for indicating PQ subregions i with the presence or absence of node, when exist one or more nodes not with
There is isolated node or there is reachability problem in any node point to same area, then subregion around it, this seasonSo that QNJ=-1；Otherwise Ci=1, niFor PQ nodes in subregion i；L is the PQ numbers of partitions；QNJiAnd QNJ
Value between [- 1,1].
10. Power Network Partitioning method under wind power integration as claimed in claim 1, it is characterized in that, PV node voltage is adjusted
Control sensitive index：
PV node is so that in regulating and controlling voltage sensitivity point to optimal PQ regions, ideally, each PV node is sensitive with maximum
Control region interior nodes voltage is spent, while hardly perturbing area exterior node voltage, thus meaning is set out, and PV is defined based on perturbation method
It is as follows that node voltage regulates and controls sensitive indices P VC：
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</mrow>
<mrow>
<mi>P</mi>
<mi>V</mi>
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<mrow>
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In formula：PVCjRepresent the PV node j sensitive index of regulating and controlling voltage；PVC represents the sensitive index of the whole network PV node regulating and controlling voltage；
ΩjFor PQ node sets in PV node j affiliated areas, Ω gathers for the whole network PQ,It is scalar region ΩjInterior PV distributing equilibriums degree
Parameter, when area's PV node number is more than 0 and PV node is directly connected PQ nodes point to same area thenOtherwiseDue to wind power integration, PV node voltage control sensitivity is different under different scenes, | Δ Up| with | Δ Uq| it is respectively PQ sections
Point p and q voltage magnitude perturbation absolute value, using voltage deviation processing fluctuation problem is expected after wind-powered electricity generation injection, i.e.,ΔUpi：The lower PQ nodes p of wind-powered electricity generation scene i accesses voltage magnitude Perturbation；ΔUqi
The lower PQ nodes q of wind-powered electricity generation scene i accesses voltage magnitude Perturbation, Pi is wind-powered electricity generation scene i probability, and M is the individual of the whole network PV node
Number；F is the interval [0,100%P that will exert oneselfe] discretization interval number.
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| CN108416507B (en) * | 2018-02-07 | 2021-08-20 | 天津大学 | Static sensitivity analysis method for electricity-gas coupling comprehensive energy system |
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| CN112103987B (en) * | 2020-08-06 | 2022-07-05 | 湖南大学 | Reactive voltage two-stage partition and control method for wind power access power grid |
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