CN109919398A - The zonal reserve Optimal Configuration Method of electric system containing wind-powered electricity generation based on figure partitioning algorithm - Google Patents
The zonal reserve Optimal Configuration Method of electric system containing wind-powered electricity generation based on figure partitioning algorithm Download PDFInfo
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Abstract
The invention discloses a kind of zonal reserve Optimal Configuration Method of electric system containing wind-powered electricity generation based on figure partitioning algorithm, comprising: establish the equivalent graph theory model of electric system region optimal dividing problem；Calculate the probability distribution of each line power；The obstruction risk indicator for finding out each transmission line of electricity of system determines the side right weight values of the equivalent undirected weighted graph of electric system；Establish the mathematic optimal model for solving minimal cut problem；Include the minimal cut tree of all nodes using the building of Gomory-Hu algorithm, selects the smallest k-1 side of weight, system is divided into k region；Establish the unit generation and spare integrated distribution model of meter and Network Security Constraints；Parameter assesses the economic benefit before and after subregion.The present invention passes through the zone configuration to unit reserve in system, efficiently solve the obstruction of the transmission line of electricity due to caused by wind-powered electricity generation and route random fault, and part spare the problem of can not putting into operation, ensure that economy and reliability to reduce system total operating cost.
Description
Technical field
The present invention relates to the generation of electricity by new energy scheduling fields of electric system, and in particular to a kind of containing based on figure partitioning algorithm
Wind-powered electricity generation electric system zonal reserve Optimal Configuration Method.
Background technique
Wind-powered electricity generation is as a kind of inexpensive, environmental-friendly, huge renewable energy of Technology Potential, in recent years in power grid
Specific gravity constantly rises.However, there is intermittent and fluctuation in wind-powered electricity generation, large-scale grid connection to power grid bring it is many not
Certainty proposes huge challenge to the operation and decision of system.Generate electricity spare one as in Ancillary Services In Electricity Market
Basic content plays a crucial role maintenance power system security reliability service.In ahead market, dispatching of power netwoks people
Member needs to provide enough spare capacities to guarantee that system maintains electric quantity balancing under accident or prediction error condition.Traditional day
Preceding reserved type module is from the unit reserve capacity of whole system level setting fixed proportion, therefore, although the power generation of system is spare
It is sufficient, it is contemplated that spare be unable to get of the limitation of line transmission capacity, configuration makes full use of, and network may still face safe fortune
Capable risk, and then lead to the emergency response measure of abandonment, cutting load or other non-economies.
It in order to cope with the above problem, on the one hand can cause defeated by the precision of prediction of raising wind-powered electricity generation, reduction prediction error
A possibility that resistance plug or other risks, it is often more important that foundation is able to reflect current system operating status, and count and it is all not
The back scheduling model for determining information (such as wind-powered electricity generation fluctuation, forecast accident), realizes the real-time dynamic configuration and essence to system reserve
ZOOM analysis avoids under-reserve or the wasting of resources, improves spare schedulable ability and utilization efficiency.
The existing spare Optimal Configuration Method of power generation is broadly divided into two classes: certainty and probabilistic approach.Tradition is really
Spare capacity is usually set as the wind-powered electricity generation prediction power output of fixed proportion by qualitative method, and meets the N-1 safety criterion of system.This
Though method is simple and easy, fails to consider the uncertain factors such as wind-powered electricity generation prediction error, excessively high increase unit operating cost.Probability
Property method based on random or robust planning theory, face magnanimity wind-powered electricity generation timing scene when, computing cost is huge, as a result
Also tend to be conservative, be also difficult to reach the requirement of practical engineering application at present.Moreover, the studies above is from whole system level mostly
To determine total stand-by requirement, flexible configuration and fine-grained management of the shortage to standby resources.
Summary of the invention
Goal of the invention: it is directed to the transmission blocking problem that may be present during back scheduling of electric system containing wind-powered electricity generation, is mentioned
For a kind of zonal reserve Optimal Configuration Method of electric system containing wind-powered electricity generation based on figure partitioning algorithm, it is only that this method has used for reference micro-capacitance sensor
Autonomous feature is found, guarantees making full use of for spare capacity as far as possible in each region, system can be reduced with lesser cost
System obstruction risk, improves spare utilization efficiency and electric network reliability.
Technical solution: to achieve the above object, the present invention provides a kind of electric system containing wind-powered electricity generation based on figure partitioning algorithm
Zonal reserve Optimal Configuration Method, comprising:
The zonal reserve Optimal Configuration Method of electric system containing wind-powered electricity generation based on figure partitioning algorithm, includes the following steps:
S1: the equivalent graph theory model of electric system optimal region partition problem is established；
S2: consider the influence of wind-powered electricity generation and route random fault to electric network swim, calculate the probability distribution of each line power；
S3: according to line power characteristic distributions, the obstruction risk indicator of each transmission line of electricity of system is found out, determines electric system
The side right weight values of equivalent undirected weighted graph；
S4: according to the equivalent weighted graph of system, the mathematic optimal model for solving minimal cut problem is established, the area after guaranteeing segmentation
Transmission blocking least risk in domain；
S5: including the minimal cut tree of all nodes using the building of Gomory-Hu algorithm, select the smallest k-1 side of weight,
System is divided into k region；
S6: according to the electric system after subregion, the unit generation and spare combined dispatching of meter and Network Security Constraints are established
Model；
S7: each Unit Commitment state, generated energy and each region unit reserve configuration amount are solved using CPLEX, calculates and abandons
Air quantity, cutting load amount, transmission blocking time, the index values such as standby tunable degree capacity assess the economic benefit before and after subregion.
Further, the equivalent graph theory model established in the step S1 include: by electric power networks with containing only pointed set V and
The undirected weighted graph G=(V, E) of side collection E composition indicates, wherein at the node v ∈ V of figure, transmission line e formed grid nodes v-shaped
Each side e ∈ E of figure, provides the mathematical expression of system realm optimal dividing problem, and wherein optimization aim is to pass route in region
Defeated obstruction least risk, and meet the constraint condition of the connectivity in graph theory, balance and validity.
Further, step S2 is stated to include the following steps:
S2-1: establishing the Gaussian error model of wind-power electricity generation, is expressed as obeying mean value for wind power as point prediction power outputStandard deviation isNormal distribution, whereinThe dispersion degree of reflection prediction error；
S2-2: influence of the line fault to trend in meter and N-1 forecast accident utilizes line fault distribution factor modified line
The transmission distribution factor on road；
S2-3: according to DC power flow equation and revised transmission distribution factor, the expression formula of each Line Flow is obtained；
S2-4: the mean value and variance of Line Flow is calculated in the expression formula and probability distribution of combined circuit trend.
Further, the step S3 specifically: invert, obtain to the probability density function of the obtained Line Flow of step S2
It to the cumulative distribution function of Line Flow, is limited in conjunction with the maximum transfer capacity of route, line transmission obstruction is calculated
Risk probability, and on this basis, define the side weight index of the equivalent undirected weighted graph of electric system.
Further, the equivalent weighted graph of electric system for relying on step S1 to establish in the step S4, based on being cut in graph theory
The definition of side and cut edge capacity converts electric system spare partitions problem to the Combinatorial Optimization Model for solving minimal cut, so that
Cut edge capacity after segmentation is minimum, the transmission blocking greatest risk being equivalent at the interconnection of zone boundary.
Further, pass through calculating using Gomory-Hu algorithm in the step S5 | V | -1 time max-flow min-cut is asked
The Gomory-Hu tree of equal value (being abbreviated as G-H tree) for inscribing structural map G, the weight on each side is between two nodes on G-H equivalent tree
Minimal cut value, by side right value according to ascending sequence successively trimming, until the quantity of subgraph reaches k, (removal k-1 item is cut
Side), the G-H tree after division is mapped back into original image to get the k optimal region of figure G is arrived.
Further, the step S6 specifically: scheduling phase, foundation consider the electricity of zonal reserve a few days ago in electric system
It can consider on the basis of the Unit Combination model of traditional considering security constraint with spare joint optimal operation model, the model
Subregion is carried out to system reserve, increases the constraint requirements of zonal reserve capacity, guarantees the spare capacity for having abundant in each region,
Interregional standby transport demand is reduced, it is spare unavailable caused by utmostly avoiding because of transmission blocking.The target of model is
The expected cost for keeping system total is minimum, comprising: generator operation cost, spinning reserve cost, unit unloaded cost and start-up cost.
Constraint condition include: unit minimum start-off time constraints, the constraint of unit output bound, unit ramp loss, power-balance about
Beam and line security constraint.
Further, the Unit Combination model a few days ago of the considerations of relying on step S6 to establish in step S7 zonal reserve,
The plan start and stop state of each unit day part, generated energy and each region standby configuration amount are solved using CPLEX software.Real-time
Scheduling phase uses two kinds of control measures of abandonment and cutting load, calculates abandonment amount, cutting load amount, transmission according to practical wind-powered electricity generation scene
Blocking time, the indexs such as standby tunable degree capacity assess proposed zonal reserve configuration method bring economic benefit.
The utility model has the advantages that compared with prior art, the present invention having following advantage:
1, the present invention can improve system by optimizing the configuration and utilization rate of standby resources in relatively inexpensive mode
In the operational safety under the random perturbations such as wind-powered electricity generation or line fault.
2, by carrying out dynamic partition to unit reserve the obstruction risk of route can be effectively reduced, sufficiently benefit in the present invention
It is provided with the zonal reserve of configuration, according to the uncertainty degree flexible configuration standby resources of wind-powered electricity generation, avoids part spare capacity in reality
When scheduling in because backlog it is limited, can effectively improve standby tunable degree ability in the Real-Time Scheduling stage, reduce abandonment amount and
Cutting load amount, to improve the economy and reliability of operation of power networks.
Detailed description of the invention
Fig. 1 is flow chart of the method for the present invention；
Fig. 2 is equivalent G-H tree and the spare partitions result for improving 14 node system of IEEE.
Specific embodiment
As shown in Figure 1, the present invention provide it is a kind of based on figure partitioning algorithm the zonal reserve of electric system containing wind-powered electricity generation optimization match
Method is set, is included the following steps:
S1: the equivalent graph theory model of electric system optimal region partition problem is established；
S2: consider the influence of wind-powered electricity generation and route random fault to electric network swim, calculate the probability distribution of each line power；
S3: according to line power characteristic distributions, the obstruction risk indicator of each transmission line of electricity of system is found out, determines electric system
The side right weight values of equivalent undirected weighted graph；
S4: according to the equivalent weighted graph of system, the mathematic optimal model for solving minimal cut problem is established, the area after guaranteeing segmentation
Transmission blocking least risk in domain；
S5: including the minimal cut tree of all nodes using the building of Gomory-Hu algorithm, select the smallest k-1 side of weight,
System is divided into k region；
S6: according to the electric system after subregion, the unit generation and spare combined dispatching of meter and Network Security Constraints are established
Model；
S7: each Unit Commitment state, generated energy and each region unit reserve configuration amount are solved using CPLEX, calculates and abandons
Air quantity, cutting load amount, transmission blocking time, the index values such as standby tunable degree capacity assess the economic benefit before and after subregion
The present embodiment cases of design by taking IEEE-14 bus test system as an example is respectively connected to 4 at node 2,4,10 and 14
The wind power plant that seat capacity is 100MW, a few days ago prediction and reality go out force data (every interval 15min) and derive from Jiangsu electric power saving tune
Degree center.Assuming that the standard deviation of wind-powered electricity generation prediction error is the 15% of its mean value (point prediction value).Due under standard operation conditions, line
Road trend only account for rated capacity less than 50%, transmission safety margin it is larger.It, will in order to increase a possibility that transmission blocking occurs
The rated capacity of each route is contracted to the 40% of original value.Load, fired power generating unit and other network parameters remain unchanged.In order to be
System comprehensively verifies the validity of the method for the present invention, and different wind power integration amount P are arrangedWWith spare area quantity NZUnder 4 scenes
(scene 1:PW=1, NZ=2；Scene 2:PW=1, NZ=3；Scene 3:PW=1.5, NZ=2；Scene 4:PW=1.5, NZ=3.),
PW=1.5 indicate original wind power output (PW=1) 50% is improved.
In the present embodiment, the equivalent graph theory model established in step S1 specifically: utilize Graph Theory by electric system
It is expressed as a undirected weighted graph G=(V, E), point set v the ∈ V, E that wherein V is made of each node v of network are transmission line e
The side collection e ∈ E of formation.The weight on each side should reflect zonal reserve criterion: whole system is divided into K area by node-home
Domain, so that the transmission blocking least risk in each region.And meet following basic constraint:
Connectivity constraint: at least there are other in a paths and the region in each node in subregion rear region
Node of anticipating is connected, and guarantees that the connectivity of network topology, the i.e. order of adjacency matrix meet:
R(Ak)=nk-1,k∈K (1)
In formula, AkFor the adjacency matrix for scheming G, nkFor the number of region k interior knot.
Balance constraint: each region should include at least the minimum node number N of settingmin.The constraint is in order to avoid shape
At the region of single node, each interregional size relative equilibrium is maintained:
nk≥Nmin (2)
Validity constraint: a unit and load should at least be contained in the same area, and total spare capacity can ensure
Stabilize the undulate quantity of source lotus power.
In the present embodiment, step S2 specifically includes following process:
1. establishing the Gaussian error model of wind-power electricity generation, wind power is expressed as to obey the point a few days ago that mean value is t moment
Prediction power outputStandard deviation isNormal distribution, whereinThe dispersion degree of reflection prediction error；
2. influence of the line fault to trend in N-1 forecast accident is considered, using line fault distribution factor to original
Line transmission distribution factor is modified:
In formula,For the failure distribution factor that route k breaks down to the l articles route in forecast accident；pkFor route k's
Probability of malfunction；Γn,lFor line transmission distribution factor total after amendment, the N-1 of the injecting power comprising node n and all routes
Transmission distribution factor of the failure to the l articles route.
3. according to DC power flow equation and revised transmission distribution factor Γn,l, obtain each Line Flow plCalculating
Expression formula is；
In formula, pn、dnAnd wnFired power generating unit power output, load and wind power output at respectively node n.
4. (wind-powered electricity generation goes out for probability distribution and the input stochastic variable of Line Flow due to the linear characteristic of formula (4) DC power flow
Power) distribution it is consistent, also Normal Distribution, the calculating of mean value and variance are as follows:
In formula, RwIndicate the correlation matrix of multiple output of wind electric field；ΣwFor pair of each output of wind electric field variance composition
Angle battle array, Σw=diag (σw1,σw2,…)。
In the present embodiment, step S3 specifically: when some for discontinuity surface, the general of transmission blocking occurs for each route
Rate may be expressed as:
In formula, plFor the actual power of route l；Pl maxFor the maximum transfer capacity of route；FlAnd Fl -Respectively plAccumulation
Distribution function and its inverse function.To Line Flow plCumulative distribution function FlIt inverts, obtains its inverse function Fl-.According to formula (8)
The risk probability of line transmission obstruction can be calculated, and on this basis, define corresponding side weight index are as follows:
ωl(e)=1-Pr (| pl|≥Pl max) (9)
In the present embodiment, step S4 specifically: the equivalent weighted graph G=(V, E) of electric system for relying on step S1 to establish,
The minimal cut that electric system spare partitions problem is converted into solution figure is asked in definition based on cut edge in graph theory and cut edge capacity
Topic, so that the cut edge capacity after segmentation is minimum, the transmission blocking greatest risk being equivalent at the interconnection of zone boundary.Assuming that will figure
G is divided into k disjoint set C altogether1,C2,…,Ck, then minimal cut problem is represented by the Combinatorial Optimization that formula (10) is established
Model:
In formula, u, v are to be located at set C in figure GiAnd CjTwo interior nodes, ω (u, v) indicate the weight of cut edge (u, v).
In the present embodiment, step S5 specifically: pass through calculating using Gomory-Hu algorithm | V | -1 max-flow minimum
The Gomory-Hu tree of equal value (being abbreviated as G-H tree) of problem structural map G is cut, the method and step for constructing equivalence G-H tree is as follows:
1. initialization: setting the number of iterations i=1, Z be to scheme the regional ensemble that is formed after G division, under primary condition, Z=
{G}。
2. arbitrarily choosing a kind of division of Z, the subregion of Z is obtained
3. in region ZiUpper a pair of of node of any selection
4. finding node u, the minimal cut between v, by ZiIt is divided into two sub-regionsWith
5. in regionWithBetween increase newly a lineEnabling its weight ω (e) ∈ W is the capacity cut.
6. updating respectivelyWithSide right value between interior each node and region:
7. updating set Z, make that it includes new regionsWith
8. if i≤| V | -1, return step 2；Otherwise, step 9 is gone to.
9. obtaining G-H tree G '=(V ', E ') of equal value, wherein V '=V ∩ VZ, E '=W.
The weight on each side is the minimal cut value between two nodes on G-H equivalent tree, by side right value according to ascending
Sequence successively trimming, until the quantity of subgraph reaches k (k-1 cut edge of removal).G-H tree after division is mapped back into original image, i.e.,
Obtain the k optimal region of figure G.Fig. 2 is to improve 14 node system of IEEE in the present embodiment to use Gomory-Hu algorithm construction
Equivalent G-H tree and spare partitions result schematic diagram.
In the present embodiment, step S6 specifically: scheduling phase, foundation consider the electricity of zonal reserve a few days ago in electric system
It can consider on the basis of the Unit Combination model of traditional considering security constraint with spare joint optimal operation model, the model
Subregion is carried out to system reserve, increases the constraint requirements of zonal reserve capacity, guarantees the spare capacity for having abundant in each region,
Interregional standby transport demand is reduced, it is spare unavailable caused by utmostly avoiding because of transmission blocking.The target of model is
The expected cost for keeping system total is minimum, comprising: generator operation cost, spinning reserve cost, unit unloaded cost and start-up cost.
In formula:For all fired power generating unit set；For scheduling slot set；WithRespectively indicate machine
G is in the power output of period t, starting state, switch state and reserve level for group, whereinWithFor 0-1 variable；CgFor the power generation of unit
Cost coefficient；SUCgFor the start-up cost coefficient of unit；NCgFor unloaded cost coefficient；RCgFor stand-by cost coefficient.
Constraint condition includes system and single Unit commitment.
Unit commitment:
System restriction:
In formula:For all node sets of system；For transmission line set；For spare area set；UTgAnd DTgFor
The minimum machine open/close time of unit g；It contributes for the prediction a few days ago of wind-powered electricity generation t moment；For the load function on t moment node n
Rate；WithThe respectively generated output upper and lower bound of unit g；WithRespectively the unit g single period upwards,
The downward rate of climb upper limit；For rate of climb of the unit g in 10min；γ indicates spare capacity coefficient, spare capacity ginseng
Number γDAnd γWIt is set to 3% and 5%.
Formula (12)-(18) are unit operation constraint, including unit minimum start-off time constraints formula (12)-(15)；Machine
Group power output bound constraint formula (16)；Unit ramp loss formula (17)；And unit reserve capacity is within the 10min response time
Constraint formula (18).Formula (19)-(22) are the constraint of whole system level, and formula (19) is power-balance constraint；Formula (20) is route
Line Flow is expressed as the linear combination of each node injecting power using the DC flow model of formula (4) by security constraint；Formula
(21) guarantee that system reserve capacity copes with generator N-1 failure；Formula (22) is regional reserve capacity constraint, it is contemplated that wind-powered electricity generation
With the uncertainty of load prediction, take in region the sub-fraction of wind-powered electricity generation and load total amount as the smallest regional reserve capacity.
In the present embodiment, step S7 specifically: the Unit Combination a few days ago of the considerations of relying on step S6 to establish zonal reserve
Model solves the plan start and stop state of each unit day part, generated energy and each region standby configuration amount using CPLEX software.
Two kinds of control measures of abandonment and cutting load are used in the Real-Time Scheduling stage, wherein abandonment and cutting load cost coefficient CcrAnd ClsRoot
According to mixed economy loss appraisal caused by it, 0.2 yuan/kWh and 25 yuan/kWh is taken respectively.Day is carried out within annual 365 days to 2018
Preceding and Real-Time Scheduling takes daily mean (desired value) and from system operation cost, abandonment amount, cutting load amount, spare use and line
Unit Combination model (the i.e. original scene P of road congestion situations etc. and traditional considering security constraintW=1, NZ=1) it carries out
Compare, simulation result is as shown in table 1.Wherein, it is as follows newly to define spare utilization index η:
In formula: molecule indicates abandonment and cutting load total amount during Real-Time Scheduling；Denominator indicates scheduling phase plan a few days ago
Unit reserve amount.The spare leveling to the systems random perturbation such as wind-powered electricity generation, line fault of value reflection configuration.η is bigger,
Illustrate that the spare contribution to recovery system electric quantity balancing is bigger, corresponding spare transmission capacity and utilization rate are also bigger.
The comparison of 1 different scenes dispatching result of table
As shown in Table 1, (the P under identical wind-powered electricity generation scaleW=1), the economic cost of expectation a few days ago of original scene is
3864920 yuan, reduce 78762 yuan and 156964 yuan, but actual motion cost (4417680 yuan) respectively compared with scene 1 and scene 2
But higher than 4348662 yuan of scene 1 and 4324124 yuan of scene 2.This is because traditional Unit Combination model result is excessively managed
Wanting does not consider the transmission blocking being likely to occur during actual schedule, spare the problem of can not coming into operation, is in particular in
It is expected that on blocking time (7h) and spare utilization index (65.3%).Because Line Flow it is out-of-limit caused by a large amount of abandonments and cutting load
Amount (114.2MWh and 23.1MWh) dramatically increases final total operating cost.For scene 3 and scene 4, since wind-powered electricity generation holds
Amount increases to 1.5 times of initial value, and compared to the first two scene, generator operation cost and cutting load amount be a few days ago and in real time
It reduces, but abandonment amount is significantly increased respectively to 158.2MWh and 151.5MWh, corresponding blocking time is elongated, under spare utilization rate
Drop.In addition, scene 2 and scene 4 are all distinguished in the economy and reliability perspectives of operation of power networks as spare area number increases
Better than scene 1 and scene 3, although the power generation and alternative plan of scheduling phase a few days ago is relatively conservative, biggish wind-powered electricity generation is adapted to
Equal random fluctuations, reduce transmission blocking risk and abandonment and cutting load amount to the greatest extent, pursue integrated operation Optimum cost.
Shown in sum up, a kind of zonal reserve of electric system containing wind-powered electricity generation based on figure partitioning algorithm proposed by the present invention, which optimizes, matches
Method is set, can avoid part spare capacity in Real-Time Scheduling according to the uncertainty degree flexible configuration standby resources of wind-powered electricity generation
Because backlog is limited, spare utilization rate is improved.And random perturbation caused by wind-powered electricity generation or line fault can be successfully managed,
The robustness and economy for taking into account operation plan, are particularly suitable for the electric system of high proportion wind-electricity integration.
Claims (10)
1. the zonal reserve Optimal Configuration Method of electric system containing wind-powered electricity generation based on figure partitioning algorithm, it is characterised in that: including as follows
Step:
S1: the equivalent graph theory model of electric system optimal region partition problem is established；
S2: consider the influence of wind-powered electricity generation and route random fault to electric network swim, calculate the probability distribution of each line power；
S3: according to line power characteristic distributions, the obstruction risk indicator of each transmission line of electricity of system is found out, determines that electric system is equivalent
The side right weight values of undirected weighted graph；
S4: according to the equivalent weighted graph of system, the mathematic optimal model for solving minimal cut problem is established, in the region after guaranteeing segmentation
Transmission blocking least risk；
S5: include the minimal cut tree of all nodes using the building of Gomory-Hu algorithm, select the smallest k-1 side of weight, will be
System is divided into k region；
S6: according to the electric system after subregion, the unit generation and spare integrated distribution model of meter and Network Security Constraints are established；
S7: solving each Unit Commitment state, generated energy and each region unit reserve configuration amount using CPLEX, parameter value,
Assess the economic benefit before and after subregion.
2. electric system containing the wind-powered electricity generation zonal reserve Optimal Configuration Method according to claim 1 based on figure partitioning algorithm,
It is characterized by: establishing equivalent graph theory model in the step S1 specifically:
Electric power networks are indicated with the undirected weighted graph G=(V, E) containing only pointed set V and side collection E composition, wherein grid nodes v
Each side e ∈ E for forming node v ∈ V, transmission line e the formation figure of figure, provides the mathematical table of system realm optimal dividing problem
It reaches, wherein optimization aim is to make route transmission blocking least risk in region, and meet the connectivity in graph theory, balance and have
The constraint condition of effect property.
3. electric system containing the wind-powered electricity generation zonal reserve Optimal Configuration Method according to claim 1 based on figure partitioning algorithm,
It is characterized by: the step S2 includes the following steps:
S2-1: establishing the Gaussian error model of wind-power electricity generation, is expressed as obeying mean value for wind power as point prediction power outputMark
Quasi- difference isNormal distribution, whereinThe dispersion degree of reflection prediction error；
S2-2: influence of the line fault to trend in meter and N-1 forecast accident utilizes line fault distribution factor amendment route
Transmit distribution factor；
S2-3: according to DC power flow equation and revised transmission distribution factor, the expression formula of each Line Flow is obtained；
S2-4: the mean value and variance of Line Flow is calculated in the expression formula and probability distribution of combined circuit trend.
4. electric system containing the wind-powered electricity generation zonal reserve Optimal Configuration Method according to claim 1 based on figure partitioning algorithm,
It is characterized by: the step S3 specifically: invert to the probability density function of the obtained Line Flow of step S2, obtain route
The cumulative distribution function of trend is limited in conjunction with the maximum transfer capacity of route, and the risk that line transmission obstruction is calculated is general
Rate, and on this basis, define the side weight index of the equivalent undirected weighted graph of electric system.
5. electric system containing the wind-powered electricity generation zonal reserve Optimal Configuration Method according to claim 1 based on figure partitioning algorithm,
It is characterized by: the step S4 includes: the equivalent weighted graph of electric system for relying on step S1 to establish, based on cut edge in graph theory and
The definition of cut edge capacity converts electric system spare partitions problem to the Combinatorial Optimization Model for solving minimal cut, so that segmentation
Cut edge capacity afterwards is minimum, the transmission blocking greatest risk being equivalent at the interconnection of zone boundary.
6. electric system containing the wind-powered electricity generation zonal reserve Optimal Configuration Method according to claim 1 based on figure partitioning algorithm,
It is characterized by: the step S5 includes: to pass through calculating using Gomory-Hu algorithm | V | -1 max-flow min-cut problem structure
The Gomory-Hu tree of equal value of figure G is made, the weight on each side is the minimal cut value between two nodes on G-H equivalent tree, by side right value
According to ascending sequence successively trimming, until the quantity of subgraph reaches k, by the G-H tree after division map back original image to get
To the k optimal region of figure G.
7. electric system containing the wind-powered electricity generation zonal reserve Optimal Configuration Method according to claim 1 based on figure partitioning algorithm,
It is characterized by: the step S6 includes: to establish the electric energy for considering zonal reserve and spare in electric system scheduling phase a few days ago
Joint optimal operation model, the model consider standby to system on the basis of the Unit Combination model of traditional considering security constraint
With subregion is carried out, increase the constraint requirements of zonal reserve capacity, the target of model is the expected cost minimum for keeping system total.
8. electric system containing the wind-powered electricity generation zonal reserve Optimal Configuration Method according to claim 7 based on figure partitioning algorithm,
It is characterized by: in the step S6 system cost include: generator operation cost, spinning reserve cost, unit unloaded cost and
Start-up cost；Constraint condition includes: unit minimum start-off time constraints, the constraint of unit output bound, unit ramp loss, function
Rate Constraints of Equilibrium and line security constraint.
9. electric system containing the wind-powered electricity generation zonal reserve Optimal Configuration Method according to claim 1 based on figure partitioning algorithm,
It is characterized by: the step S7 includes: the Unit Combination model a few days ago of zonal reserve the considerations of relying on step S6 to establish, utilize
CPLEX software solves the plan start and stop state of each unit day part, generated energy and each region standby configuration amount, in Real-Time Scheduling
Stage uses two kinds of control measures of abandonment and cutting load, calculates indices according to practical wind-powered electricity generation scene, it is standby to assess mentioned subregion
With configuration method bring economic benefit.
10. electric system containing the wind-powered electricity generation zonal reserve Optimal Configuration Method according to claim 1 based on figure partitioning algorithm,
It is characterized by: the detailed process of the Gomory-Hu tree of equal value of structural map G includes the following steps: in the step S5
1. initialization: setting the number of iterations i=1, Z be to scheme the regional ensemble that is formed after G division, under primary condition, Z={ G }；
2. arbitrarily choosing a kind of division of Z, the subregion of Z is obtained
3. in region ZiUpper a pair of of node of any selection
4. finding node u, the minimal cut between v, by ZiIt is divided into two sub-regionsWith
5. in regionWithBetween increase newly a lineEnabling its weight ω (e) ∈ W is the capacity cut；
6. updating respectivelyWithSide right value between interior each node and region:
7. updating set Z, make that it includes new regionsWith
8. if i≤| V | -1, return step 2；Otherwise, step 9 is gone to；
9. obtaining G-H tree G '=(V ', E ') of equal value, wherein V '=V ∩ VZ, E '=W.
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