CN105576653B - A kind of 220kV sections power network power supply capacity optimization method - Google Patents
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Abstract
The invention discloses a kind of 220kV sections power network power supply capacity optimization method, including step：1) to the initialization of 220kV sections power network power supply capacity Optimized model；2) initial load population is generated, and initialization iterations k=1 is set；3) calculate under each particle normal operating mode and the trend under the methods of operation of N 1 and verified；4) the load balancing degree λ of each particle is calculated；5) the adaptive angle value of each particle is calculated；6) according to the velocity information of adaptive angle value more new particle；7) load value of more new particle, and update iterations k=k+1；8) whether reach the condition of convergence, if it is export optimal load value, repeated 3)~8 if the condition of convergence is not reaching to) step, until meeting the condition of convergence.The present invention considers the isostatic equilibrium of load, it is high effectively to avoid some transformer station's load factors of optimization load appearance, and the extremely low situation of load factor of some transformer stations, the Optimal Load of calculating can give the operation of power system and planning personnel to provide more valuable reference.
Description
Technical field
The present invention relates to the technical field of power network evaluation of power supply capability, refers in particular to a kind of consideration load balancing balance
220kV sections power network power supply capacity optimization method.
Background technology
Power supply capacity described in this patent, refer to that power network meets N-1 safety criterions in certain power supply area, and consider net
Peak load deliverability under network practical operation situation, it substantially also refers to net capability (Total Supply
Capability, TSC).
Power supply capacity can reflect the margin of safety of supply of the power network to load to a certain extent, and it can be the fortune of power network
Row provides certain reference with planning personnel, can reduce cost to greatest extent, improve the benefit of power network.But only by closing
The sharing of load scheme of optimization is managed, could be that power network brings higher benefit.Current most of documents are carried out to power supply capacity
During optimization, the result of optimization occurs that the load factor of some transformer stations is very high, and the load factor of some transformer stations is low-down
Situation, and in actual power system, there is certain requirement to the harmony of sharing of load, therefore, this load distribution scheme
Very likely reduce the reliability of power system power supply.In order that the sharing of load of optimization is balanced, close to the operation of actual electric network
Situation, this patent propose the power supply capacity object function for considering load balancing balance on the basis of power supply capacity.By this
Object function calculates Optimal Load, can effectively avoid problem above, can give operation and the planning personnel of power system
More valuable reference is provided.
When calculating power supply capacity, according to complete electric network model and accurate computational methods and consider that N-1 is quiet
State security constraint, it may appear that the difficulty in numerical computations；Without considering grid structure or causing knot again to the model that rack simplifies
The error of fruit is excessive, and application value is had a greatly reduced quality.With the development of 500kV and its above power network, 220kV power networks exist
In actual motion, in order to improve power supply reliability, through the mode frequently with districting operation, a big net is divided into several pieces
Area, relatively independent between each section, this causes decoupling of the calculating in units of section point to 220kV power network power supply capacities
Analysis is possibly realized.This patent decouples the 220kV sections of research from bulk power grid come out first, then right according to this feature
This 220kV sections power network is powered capacity calculation.
The method for calculating power supply capacity at present is broadly divided into analytic method, linear programming model method, Nonlinear Programming Method and intelligence
Energy algorithm etc..Analytic method is typically abstracted as power supply capacity can have the analytic expression of physical significance come directly to power supply with some
Ability is calculated, and such as FVSI (quick voltage stability index) method, this method has typically carried out many vacations to the power network of research
If therefore can only be roughly the power supply capacity to power network evaluate；Linear programming technique, power supply energy is such as calculated based on DC power flow
Power method can typically be converted to linear programming technique to solve, and this method typically considers the grid structure of power network, but due to neglecting
The influence of voltage landing and network loss to TSC has been omited, therefore has had certain influence to power supply capacity computational accuracy；Nonlinear Programming Method,
This method is generally the method sought nonlinear model and proposed, such as interior point method, and there are this method strict data to derive, and calculate speed
Degree is fast, but this method requires higher to the initial value of system, is not easy to restrain；One kind that intelligent algorithm recent decades grow up
Heuristic, such as simulated annealing, genetic algorithm, particle cluster algorithm etc., this kind of algorithm have good adaptivity, self-organizing
The features such as property.(PSO) compare compared with other intelligent algorithms.
This patent establishes a kind of Nonlinear programming Model of the consideration N-1 Static Security Constraints based on AC power flow, and
Load balancing balance is considered on the basis of power supply capacity, belongs to multiple target, the category of Non-Linear Programming, therefore, carries herein
Go out using particle cluster algorithm to 220kV sections power network power supply capacity solve, this method with other algorithms compared with have calculate simply,
The features such as calculating speed is fast.
The content of the invention
The shortcomings that it is an object of the invention to overcome prior art and deficiency, there is provided a kind of to consider what load balancing balanced
220kV sections power network power supply capacity optimization method, effectively avoiding optimization load, some transformer station's load factors occur high, and
The extremely low situation of the load factors of some transformer stations, the Optimal Load of calculating can give the operation of power system and planning personnel to provide
More valuable reference, particle cluster algorithm is used when solving 220kV section power network power supply capacity Optimized models, have and calculate
Conveniently, the features such as calculating speed is fast, can be with the bigger power network of adopting said method calculation scale.
To achieve the above object, technical scheme provided by the present invention is：A kind of 220kV sections power network power supply capacity optimization
Method, comprise the following steps：
1) to the initialization of 220kV sections power network power supply capacity Optimized model；
2) initial load population is generated, and initialization iterations k=1 is set；
3) calculate under each particle normal operating mode and the trend under the N-1 methods of operation and verified；
4) the load balancing degree λ of each particle is calculated；
5) the adaptive angle value of each particle is calculated；
6) according to the velocity information of adaptive angle value more new particle；
7) load value of more new particle, and update iterations k=k+1；
8) whether reach the condition of convergence, if it is export optimal load value, weighed if the condition of convergence is not reaching to
Again 3)~8 step), until meeting the condition of convergence.
In step 1), the initialization to 220kV sections power network power supply capacity Optimized model, comprise the following steps：
1.1) basic parameter of particle cluster algorithm, including inertia weight ω, accelerated factor c' and c ", population scale are set
NP, convergence precision ε and maximum iteration K；
1.2) basic parameter of Newton-Laphson method, including convergence precision ε are setNRWith maximum iteration T；
1.3) parameter of double--layer grids of 220kV sections power network is extracted and inputted, includes the 220kV of input 500kV transforming plant main transformers
The voltage V of sidenAnd phase angle thetan, the parameter of rack, load parameter and voltage constraint and the constraint of phase angle difference；Wherein, the ginseng of rack
Number includes each branch resistance Rli, reactance Xli, susceptance value B over the groundliAnd maximum carrying capacity Imax,li, load parameter includes each load
The peak load value of pointAnd minimal negative charge values Sdi。
In step 3), calculate under each particle normal operating mode and the trend under the N-1 methods of operation and verified,
Comprise the following steps：
3.1) bus admittance matrix is formed：Formed normal operating mode under bus admittance matrix and according to each N-1 failures
The bus admittance matrix that bus admittance matrix under modification normal operating mode is formed under each N-1 failures；
3.2) n is setpop=0, each particle in population is calculated successively according to following steps under normal operating mode and N-1
Trend under the method for operation, and carry out heat-stable entertoxin；
3.3) the t in populationpopGroup load value, which is brought into the formula for calculating trend deviation, calculates each node power injustice
WeighWherein Δ P, Δ Q distinguish the deviation of finger joint point active power and reactive power, whether judge strength of current deviation
Meet the condition of convergence；As met, then step 3.6) is jumped to, is such as unsatisfactory for, then carry out step 3.4)；
3.4) trend is generated by the variable inputted and existing bus admittance matrix, calculates Jacobian matrix J：
Wherein, H is n-1 rank square formations, and its element isN is (n-1) × m rank matrixes, and its element isK is m × (n-1) rank matrix, and its element isL is m rank square formations, and its element is
3.5) linear update equation group is solvedWherein
Correction amount θ, the Δ V of each node voltage amplitude and phase angle are obtained, each node voltage V and phase angle theta is corrected, jumps to step
3.3)；
3.6) all branch powers are calculated as follows, and make npop=npop+ 1,
Wherein, i is branch road first node, and j is branch road end-node, and tilde represents to take the conjugate of plural number,For to node
The conjugate of the admittance values of i over the ground,The conjugate of admittance value between line node i to node j；
3.7) Line Flow calculated according to step 3.6) enters row line heat-stable entertoxin；
3.8) n is judgedpop＞=NPWhether set up, wherein NPIt is such as invalid for particle populations scale, then jump to step
3.3)；Step 4) is carried out if setting up；
In step 5), the adaptive trend heat-stable entertoxin of the angle value according to step 3.7) whether by according to
In the following manner calculates, and comprises the following steps：
If 5.1) trend heat-stable entertoxin not by, according to the load value of the particle dynamically take one it is smaller from
Fitness value；
5.2) if trend heat-stable entertoxin is by the way that the adaptive angle value of the particle is according to 220kV sections power network power supply energy
The object function of power computational mathematics model calculates,
f(xC)=TSC ω1+TSC·(1-λ)·ω2
Wherein, TSC calculates according to below equation,
Wherein, SdiFor transformer station i apparent energy,For transformer station i power-factor angle；xCIt is each to control variable
The apparent energy of PQ nodes：ω1And ω2Respectively
TSC and isostatic equilibrium weight, and meet ω1+ω2=1.
In step 4), the calculation formula of the load balancing degree λ is as follows：
Wherein, d is the number of load bus in the power network of 220kV sections；δiFor transformer station i capacity-load ratio CLRHold with its benchmark
Load compares CLRSDifference, i.e. δi=CLR-CLRS；For δiThe average value of sum, i.e.,
Wherein, benchmark capacity-load ratio CLRSBy main transformer number of units, main transformer capacity and main transformer short-time overload system in transformer station
Number determines.
In step 5.2), the 220kV sections power network power supply capacity mathematical modeling is：
max f(xC)=TSC ω1+TSC·(1-λ)·ω2
Wherein, ncFor the number of N-1 forecast accidents；Work as kc=0, state during ground state is represented, ground state here refers to power train
State when normal table of uniting is run；Work as kc＞ 0, is represented in kthcState during individual forecast accident；Therefore,WithPoint
Not Wei i-th of node in kthcActive and idle amount of unbalance under individual state；For kthcIndividual state lower node i and node j
Between phase angle difference；WithRespectively i-th of node and j-th of node are in kthcVoltage magnitude during individual state；Vi WithThe respectively lower and upper limit of node i voltage magnitude；For kthcThe apparent of branch road between individual state lower node i and node j
Power；For kthcThe thermostabilization power limit of branch road between individual state lower node i and node j；WithRespectively exist
KthcThe active power output and idle output of lower i-th generator of individual state or i-th superior node；PG,i With QG,i With
Respectively i-th generator or i-th of superior node active power output, the lower and upper limit of idle output；For i-th of node
In kthcApparent energy during individual state；Si WithThe lower and upper limit of respectively i-th node apparent energy.
The present invention compared with prior art, has the following advantages that and beneficial effect：
The 220kV sections power network power supply capacity optimization method of the present invention considers load when being optimized to power supply capacity
Isostatic equilibrium, effectively avoiding optimization load, some transformer station's load factors occur high, and the load factor of some transformer stations
Extremely low situation, the Optimal Load of calculating can give the operation of power system and planning personnel to provide more valuable reference；
The net capability of power network is solved using section as least unit, the data of substantial amounts of redundancy is effectively simplified, reduces and ask
The dimension of solution problem；Particle cluster algorithm is used when solving 220kV section power network power supply capacity Optimized models, there is calculating side
Just the features such as, calculating speed is fast, can be with the bigger power network of adopting said method calculation scale.
Brief description of the drawings
Fig. 1 is the flow chart of the 220kV sections power network power supply capacity optimization method of the present invention.
Embodiment
With reference to specific embodiment, the invention will be further described.
As shown in figure 1, the 220kV sections power network power supply capacity optimization method described in the present embodiment, comprises the following steps：
1) to the initialization of 220kV sections power network power supply capacity Optimized model；
2) initial load population is generated, and initialization iterations k=1 is set；
3) calculate under each particle normal operating mode and the trend under the N-1 methods of operation and verified；
4) the load balancing degree λ of each particle is calculated；
5) the adaptive angle value of each particle is calculated；
6) according to the velocity information of adaptive angle value more new particle；
7) load value of more new particle, and update iterations k=k+1；
8) whether reach the condition of convergence, if it is export optimal load value, weighed if the condition of convergence is not reaching to
Again 3)~8 step), until meeting the condition of convergence.
Power supply capacity in the present embodiment, refer to that power network meets N-1 safety criterions in certain power supply area, and consider net
Peak load deliverability under network practical operation situation.The isostatic equilibrium of consideration load in the present embodiment is embodied in power supply energy
On the object function of power mathematical modeling.Concrete condition is as follows：
First, to the initialization of 220kV sections power network power supply capacity optimization, comprise the following steps:
The 21st, the basic parameter of particle cluster algorithm is set, such as inertia weight ω, accelerated factor c' and c ", population scale NP、
The parameter such as convergence precision ε and maximum iteration K；
The 22nd, the basic parameter of Newton-Laphson method is set, such as convergence precision εNRWith maximum iteration T etc.；
23rd, the parameter of double--layer grids of 220kV sections power network is extracted and inputs, as inputted the 220kV sides of 500kV transforming plant main transformers
Voltage VnAnd phase angle thetan, rack parameter (each branch resistance Rli, reactance Xli, susceptance value B over the groundliAnd maximum carrying capacity
Imax,li), load parameter (the peak load value of each load pointAnd minimal negative charge valuesSdi ) and voltage constraint and phase angle difference
Constraint.
2nd, initial load population is generated, and initializes iterations k=1；
The peak load value of the load parameter of input according to step 23And minimal negative charge valuesSdi , under
Formula generates initial population,
Wherein, rand refers to the random number for generating [0,1], NPFor the population scale described in step 21, N is problem
Dimension, that is, need the number of load optimized.
3rd, calculate under each particle normal operating mode and the trend under the N-1 methods of operation and verified；
It is as follows that Newton-Laphson method calculates the step of trend：
31st, bus admittance matrix is formed：Formed normal operating mode under bus admittance matrix and repaiied according to each N-1 failures
Change the bus admittance matrix that the bus admittance matrix under normal operating mode is formed under each N-1 failures；
32nd, n is setpop=0, each particle in population is calculated successively according to following steps under normal operating mode and N-1 fortune
Trend under line mode, and carry out heat-stable entertoxin.
33rd, the t in populationpopGroup load value, which is brought into the formula for calculating trend deviation, calculates each node power injustice
WeighWherein Δ P, Δ Q distinguish the deviation of finger joint point active power and reactive power, whether judge strength of current deviation
Meet the condition of convergence；As met, then step S306 is jumped to, is such as unsatisfactory for, then carry out step 34；
34th, trend is generated by the variable inputted and existing bus admittance matrix, calculates Jacobian matrix J：
Wherein, H is n-1 rank square formations, and its element isN is (n-1) × m rank matrixes, and its element isK is m × (n-1) rank matrix, and its element isL is m rank square formations, and its element is
35th, linear update equation group is solvedWherein
Correction amount θ, the Δ V of each node voltage amplitude and phase angle are obtained, each node voltage V and phase angle theta is corrected, jumps to step 33；
36th, all branch powers are calculated as follows, and make npop=npop+ 1,
Wherein, i is branch road first node, and j is branch road end-node, and tilde represents to take the conjugate of plural number,For to node
The conjugate of the admittance values of i over the ground,The conjugate of admittance value between line node i to node j.
37th, the Line Flow calculated according to step 36 enters row line heat-stable entertoxin；
38th, n is judgedpop＞=NPWhether set up, wherein NPIt is such as invalid for the particle populations scale described in step 21, then
Jump to step 33；Carried out if setting up according to the step 4) described in claim 1.
Wherein, the 220kV sections power network power supply capacity mathematical modeling is：
max f(xC)=TSC ω1+TSC·(1-λ)·ω2
Wherein, ncFor the number of N-1 forecast accidents.Work as kc=0, state during ground state is represented, ground state here refers to power train
State when normal table of uniting is run.Work as kc＞ 0, is represented in kthcState during individual forecast accident.Therefore,WithPoint
Not Wei i-th of node in kthcActive and idle amount of unbalance under individual state；For kthcIndividual state lower node i and node j
Between phase angle difference；WithRespectively i-th of node and j-th of node are in kthcVoltage magnitude during individual state；Vi With
The respectively lower and upper limit of node i voltage magnitude；For kthcThe apparent work(of branch road between individual state lower node i and node j
Rate；For kthcThe thermostabilization power limit of branch road between individual state lower node i and node j；WithRespectively
kcThe active power output and idle output of lower i-th generator of individual state or i-th superior node；PG,i With QG,i WithPoint
Wei not i-th generator or i-th of superior node active power output, the lower and upper limit of idle output；Exist for i-th of node
KthcApparent energy during individual state；Si WithThe lower and upper limit of respectively i-th node apparent energy.
4th, the load balancing degree λ of each particle is calculated；
Load balancing balance λ calculation formula are as follows：
Wherein, d is the number of load bus in the power network of 220kV sections；δiFor transformer station i capacity-load ratio CLRHold with its benchmark
Load compares CLRSDifference, i.e. δi=CLR-CLRS；For δiThe average value of sum, i.e.,
Wherein, benchmark capacity-load ratio CLRSDetermined by main transformer number of units, main transformer capacity and main transformer short-time overload coefficient in transformer station.
5th, the adaptive angle value of each particle is calculated；
According to the trend heat-stable entertoxin described in step 37 whether by calculating in such a way：
If the 51st, trend heat-stable entertoxin not by, according to the load value of the particle dynamically take one it is smaller from
Fitness value.
The 52nd, if trend heat-stable entertoxin is by the way that the adaptive angle value of the particle is according to 220kV sections power network power supply capacity
The object function of computational mathematics model calculates,
f(xC)=TSC ω1+TSC·(1-λ)·ω2
Wherein, TSC calculates according to below equation,
Wherein, SdiFor transformer station i apparent energy,For transformer station i power-factor angle.xCIt is each to control variable
The apparent energy of PQ nodes：ω1And ω2Respectively
TSC and isostatic equilibrium weight, and meet ω1+ω2=1.
6th, according to the velocity information of adaptive angle value more new particle；
Particle rapidity is updated according to equation below,
Wherein,WithRespectively particle i is in load value of the kth time iteration in jth dimension space, speed
The optimal load value passed through with itself；Kth time all particles of iteration the global optimum of jth dimension space load
Value；r′ijWith r "ijRespectively experience random number and social experience random number, span [0,1].
7th, the load value of more new particle, and update iterations k=k+1；
Particle rapidity is updated according to equation below,
8th, whether reach the condition of convergence, if it is export optimal load value, weighed if the condition of convergence is not reaching to
Multiple three~eight steps, until meeting the condition of convergence.
The condition of convergence described in this patent includes two：One is whether the poor of two optimal particle loads is less than step
It is rapid to be less than than the convergence precision ε described in step 21；One be iteration number whether be more than step 21 described in maximum change
Generation number.
Two conditions of convergence, as long as reaching one, you can think to meet the condition of convergence, algorithm should terminate, and export optimal
Load value.
Examples of implementation described above are only the preferred embodiments of the invention, and the implementation model of the present invention is not limited with this
Enclose, therefore the change that all shape, principles according to the present invention are made, it all should cover within the scope of the present invention.
Claims (2)
1. a kind of 220kV sections power network power supply capacity optimization method, it is characterised in that comprise the following steps：
1) to the initialization of 220kV sections power network power supply capacity Optimized model；
2) initial load population is generated, and initialization iterations k=1 is set；
3) calculate under each particle normal operating mode and the trend under the N-1 methods of operation and verified, comprised the following steps：
3.1) bus admittance matrix is formed：Formed normal operating mode under bus admittance matrix and according to each N-1 failures change
The bus admittance matrix that bus admittance matrix under normal operating mode is formed under each N-1 failures；
3.2) n is setpop=0, each particle in population is calculated successively according to following steps under normal operating mode and N-1 operations
Trend under mode, and carry out heat-stable entertoxin；
3.3) the t in populationpopGroup load value is brought into the formula for calculating trend deviation and calculates each node power amount of unbalanceWherein Δ P, Δ Q distinguish the deviation of finger joint point active power and reactive power, judge whether strength of current deviation meets
The condition of convergence；As met, then step 3.6) is jumped to, is such as unsatisfactory for, then carry out step 3.4)；
3.4) trend is generated by the variable inputted and existing bus admittance matrix, calculates Jacobian matrix J：
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</mfenced>
</mrow>
Wherein, H is n-1 rank square formations, and its element isN is (n-1) × m rank matrixes, and its element isK is m × (n-1) rank matrix, and its element isL is m rank square formations, and its element is
3.5) linear update equation group is solvedWherein
To the correction amount θ of each node voltage amplitude and phase angle, Δ V, each node voltage V and phase angle theta are corrected, jumps to step 3.3)；
3.6) all branch powers are calculated as follows, and make npop=npop+ 1,
<mrow>
<msub>
<mi>S</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
</msub>
<mo>=</mo>
<msubsup>
<mi>V</mi>
<mi>i</mi>
<mn>2</mn>
</msubsup>
<msub>
<mover>
<mi>y</mi>
<mo>~</mo>
</mover>
<mrow>
<mi>i</mi>
<mn>0</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mover>
<mi>V</mi>
<mo>&CenterDot;</mo>
</mover>
<mi>i</mi>
</msub>
<mrow>
<mo>(</mo>
<msub>
<mover>
<mi>V</mi>
<mo>~</mo>
</mover>
<mi>i</mi>
</msub>
<mo>-</mo>
<msub>
<mover>
<mi>V</mi>
<mo>~</mo>
</mover>
<mi>j</mi>
</msub>
<mo>)</mo>
</mrow>
<msub>
<mover>
<mi>y</mi>
<mo>~</mo>
</mover>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
</msub>
</mrow>
Wherein, i is branch road first node, and j is branch road end-node, and tilde represents to take the conjugate of plural number,For to node i over the ground
Admittance value conjugate,The conjugate of admittance value between line node i to node j；
3.7) Line Flow calculated according to step 3.6) enters row line heat-stable entertoxin；
3.8) n is judgedpop＞=NPWhether set up, wherein NPIt is such as invalid for particle populations scale, then jump to step 3.3)；
Step 4) is carried out if setting up；
4) the load balancing degree λ of each particle is calculated；Wherein, the calculation formula of the load balancing degree λ is as follows：
<mrow>
<mi>&lambda;</mi>
<mo>=</mo>
<mfrac>
<mrow>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>d</mi>
</munderover>
<msup>
<mrow>
<mo>(</mo>
<msub>
<mi>&delta;</mi>
<mi>i</mi>
</msub>
<mo>-</mo>
<mover>
<mi>&delta;</mi>
<mo>&OverBar;</mo>
</mover>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
</mrow>
<mi>d</mi>
</mfrac>
</mrow>
Wherein, d is the number of load bus in the power network of 220kV sections；δiFor transformer station i capacity-load ratio CLRWith its benchmark capacity-load ratio
CLRSDifference, i.e. δi=CLR-CLRS；For δiThe average value of sum, i.e.,
<mrow>
<mover>
<mi>&delta;</mi>
<mo>&OverBar;</mo>
</mover>
<mo>=</mo>
<mfrac>
<mrow>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>d</mi>
</munderover>
<msub>
<mi>&delta;</mi>
<mi>i</mi>
</msub>
</mrow>
<mi>d</mi>
</mfrac>
</mrow>
Wherein, benchmark capacity-load ratio CLRSDetermined by main transformer number of units, main transformer capacity and main transformer short-time overload coefficient in transformer station；
5) the adaptive angle value of each particle is calculated；Wherein, trend heat of the adaptive angle value according to step 3.7) is steady
Whether verify by calculating in such a way, comprise the following steps calmly：
If 5.1) trend heat-stable entertoxin not by, according to the load value of the particle dynamically take one it is smaller adaptive
Angle value；
5.2) if trend heat-stable entertoxin is by the way that the adaptive angle value of the particle is according to 220kV sections power network power supply capacity meter
The object function for calculating mathematical modeling calculates,
f(xC)=TSC ω1+TSC·(1-λ)·ω2
Wherein, TSC calculates according to below equation,
Wherein, SdiFor transformer station i apparent energy,For transformer station i power-factor angle；xCTo control variable, saved for each PQ
The apparent energy of point：ω1And ω2Respectively TSC and
The weight of isostatic equilibrium, and meet ω1+ω2=1；
Wherein, the 220kV sections power network power supply capacity mathematical modeling is：
max f(xC)=TSC ω1+TSC·(1-λ)·ω2
Wherein, ncFor the number of N-1 forecast accidents；Work as kc=0, state during ground state is represented, ground state here is referring to power system just
State during normal stable operation；Work as kc＞ 0, is represented in kthcState during individual forecast accident；Therefore,WithRespectively
I-th of node is in kthcActive and idle amount of unbalance under individual state；For kthcBetween individual state lower node i and node j
Phase angle difference；WithRespectively i-th of node and j-th of node are in kthcVoltage magnitude during individual state；Vi WithRespectively
For the lower and upper limit of node i voltage magnitude；For kthcThe apparent energy of branch road between individual state lower node i and node j；For kthcThe thermostabilization power limit of branch road between individual state lower node i and node j；WithRespectively in kthcIt is individual
The active power output and idle output of lower i-th generator of state or i-th superior node；PG,i With QG,i WithRespectively
I-th generator or i-th of superior node active power output, the lower and upper limit of idle output；It is i-th of node in kthcIt is individual
Apparent energy during state；Si WithThe lower and upper limit of respectively i-th node apparent energy；
6) according to the velocity information of adaptive angle value more new particle；
Particle rapidity is updated according to equation below：
<mrow>
<msubsup>
<mi>v</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
<mrow>
<mo>(</mo>
<mi>k</mi>
<mo>+</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
</msubsup>
<mo>=</mo>
<msubsup>
<mi>&omega;v</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
<mrow>
<mo>(</mo>
<mi>k</mi>
<mo>)</mo>
</mrow>
</msubsup>
<mo>+</mo>
<msup>
<mi>c</mi>
<mo>&prime;</mo>
</msup>
<msubsup>
<mi>r</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
<mrow>
<mo>&prime;</mo>
<mrow>
<mo>(</mo>
<mi>k</mi>
<mo>)</mo>
</mrow>
</mrow>
</msubsup>
<mrow>
<mo>(</mo>
<msubsup>
<mi>p</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
<mrow>
<mi>b</mi>
<mi>e</mi>
<mi>s</mi>
<mi>t</mi>
<mrow>
<mo>(</mo>
<mi>k</mi>
<mo>)</mo>
</mrow>
</mrow>
</msubsup>
<mo>-</mo>
<msubsup>
<mi>x</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
<mrow>
<mo>(</mo>
<mi>k</mi>
<mo>)</mo>
</mrow>
</msubsup>
<mo>)</mo>
</mrow>
<mo>+</mo>
<msup>
<mi>c</mi>
<mrow>
<mo>&prime;</mo>
<mo>&prime;</mo>
</mrow>
</msup>
<msubsup>
<mi>r</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
<mrow>
<mo>&prime;</mo>
<mo>&prime;</mo>
<mrow>
<mo>(</mo>
<mi>k</mi>
<mo>)</mo>
</mrow>
</mrow>
</msubsup>
<mrow>
<mo>(</mo>
<msubsup>
<mi>g</mi>
<mi>j</mi>
<mrow>
<mi>b</mi>
<mi>e</mi>
<mi>s</mi>
<mi>t</mi>
<mrow>
<mo>(</mo>
<mi>k</mi>
<mo>)</mo>
</mrow>
</mrow>
</msubsup>
<mo>-</mo>
<msubsup>
<mi>x</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
<mrow>
<mo>(</mo>
<mi>k</mi>
<mo>)</mo>
</mrow>
</msubsup>
<mo>)</mo>
</mrow>
</mrow>
Wherein,WithRespectively particle i kth time iteration the load value of jth dimension space, speed and itself
The optimal load value passed through；Kth time all particles of iteration the global optimum of jth dimension space load value；r′ij
With r "ijRespectively experience random number and social experience random number, span [0,1]；ω is inertia weight；C' and c " is
Accelerated factor；
7) basisThe load value of more new particle, and update iterations k=k+1；
8) whether reach the condition of convergence, if it is export optimal load value, repeated 3) if the condition of convergence is not reaching to
~8) step, until meeting the condition of convergence.
2. a kind of 220kV sections power network power supply capacity optimization method according to claim 1, it is characterised in that in step
1) in, the initialization to 220kV sections power network power supply capacity Optimized model, comprise the following steps：
1.1) basic parameter of particle cluster algorithm, including inertia weight ω, accelerated factor c' and c ", particle populations scale N are setP、
Convergence precision ε and maximum iteration K；
1.2) basic parameter of Newton-Laphson method, including convergence precision ε are setNRWith maximum iteration T；
1.3) parameter of double--layer grids of 220kV sections power network is extracted and inputs, including input the 220kV sides of 500kV transforming plant main transformers
Voltage VnAnd phase angle thetan, the parameter of rack, load parameter and voltage constraint and the constraint of phase angle difference；Wherein, the parameter bag of rack
Include each branch resistance Rli, reactance Xli, susceptance value B over the groundliAnd maximum carrying capacity Imax,li, load parameter includes each load point
Peak load valueAnd minimal negative charge valuesSdi 。
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| CN104462815A (en) * | 2014-12-05 | 2015-03-25 | 国家电网公司 | Target grid skeleton safety analysis method based on power flow distribution equilibrium |
| CN104484555A (en) * | 2014-11-26 | 2015-04-01 | 广州电力设计院 | Method for evaluating maximum power supply capability of 220kV self-healing looped network |
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| CN104484555A (en) * | 2014-11-26 | 2015-04-01 | 广州电力设计院 | Method for evaluating maximum power supply capability of 220kV self-healing looped network |
| CN104484832A (en) * | 2014-11-26 | 2015-04-01 | 广州电力设计院 | Method for evaluating total supplying capability of 220KV Lashou net |
| CN104462815A (en) * | 2014-12-05 | 2015-03-25 | 国家电网公司 | Target grid skeleton safety analysis method based on power flow distribution equilibrium |
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