CN108306334A - Idle work optimization strategy inside wind power plant based on particle swarm optimization algorithm - Google Patents
Idle work optimization strategy inside wind power plant based on particle swarm optimization algorithm Download PDFInfo
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- H02J3/386—
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/50—Controlling the sharing of the out-of-phase component
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/70—Wind energy
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Abstract
Idle work optimization method inside the wind power plant based on particle swarm optimization algorithm that the present invention relates to a kind of, including：(1) wind power plant internal topology is established；(2) it uses and is pushed forward trend inside offspring's method calculating wind power plant；(3) mathematical model of idle work optimization inside wind power plant is established, the idle work optimization object function of selection is and penalty to be added in object function using wind power plant built-in system loss minimization as optimization aim, handles the out-of-limit problem of node voltage；(4) it is solved using particle swarm optimization algorithm, the reasonable distribution to the idle output of each unit is realized, to reduce the loss of grid.
Description
Technical field
The invention belongs to idle work optimization fields inside wind power plant, are related to wind power plant internal networking structure and wind-driven generator
The problem of idle output distribution is to reduce system losses.
Background technology
With full energy demand sharp increase and problem of environmental pollution it is increasingly serious, using wind energy as the new energy of representative
Development and utilization obtained more extensive concern.Wind power technology development in recent years is swift and violent, Wind turbines single-machine capacity and wind
The scale of electric field is gradually increasing, and wind-driven generator quantity multiple topology is complicated in wind power plant, and collector system circuit is long, thus
Node voltage fluctuation and via net loss caused by flow of power inside wind power plant is more apparent.The idle generation of itself is not
Energy is consumed, but its flowing in power grid necessarily causes electric current to increase, and network loss is made to increase, causes waste and voltage drop.Cause
This, idle work optimization realizes that the operation of stabilizing the economy of power grid has important reality for improving quality of voltage, reducing system losses
Meaning.
Wind power generating set generate active loss (including wind-driven generator mechanical part loss, energy conversion part
The loss that loss and case become) loss that generates of sum aggregate electric line is two kinds of main active losses inside wind power plant.With current collection
The increase of system scale, active loss of the energy caused by wind power plant internal flow is more obvious, can also influence internal node
The stability of voltage.It is mostly that wind power plant is divided into a several group of planes as a whole or by doubly fed machine group to have document, according to
And the demand of power grid carry out idle work optimization, then the reactive requirement of optimization is averagely allocated to each wind-driven generator, not
Consider the influence of wind power plant internal topology and electrical equipment to grid entry point voltage and collector system network loss.
With the increase of collector system scale, active loss of the energy caused by wind power plant internal flow is more obvious,
The stability of internal node voltages can also be influenced.In view of the above-mentioned problems, the present invention considers wind power plant internal topology to tide
The influence of stream, under the premise of ensureing each node voltage quality, to reduce system losses as target, using particle group optimizing
(PSO) the idle output of every unit is optimized in algorithm.
Invention content
The object of the present invention is to provide idle work optimization methods inside a kind of wind power plant, are ensureing each node electricity inside wind power plant
Under the premise of pressing quality, so that each double-fed induction wind driven generator is exported rational reactive power, realize reactive power on the spot
Compensation, can not only meet the needs of reactive power, but also can reduce the input of reactive-load compensation equipment, improve system voltage quality
Reduce via net loss simultaneously.The present invention optimizes the idle output of every unit using particle group optimizing (PSO) algorithm, obtains
To the idle work optimization scheme of entire wind power plant.In order to achieve the above objectives, the technical solution adopted in the present invention is as follows：
A kind of wind power plant inside idle work optimization method based on particle swarm optimization algorithm, includes the following steps：
(1) wind power plant internal topology is established：It is connected with a box type transformer per the outlet of typhoon power generator, then is led to
It crosses underground cable and is connected to cable termination tower, each wind-force line is pooled in collection bus, and wind field exports busbar voltage it is known that regarding
For the root node of the tree network, the active power and reactive power of each wind-driven generator node it is known that be considered as leaf node, remaining
Node is considered as intermediate node, and any bar branch has determining beginning node and terminal note, it is specified that a branch according to current direction
The node of upper electric current outflow is terminal note, and the node that electric current flows into is beginning node, node is numbered, the number side of each node
Formula is carried out by the feeder line tree mode of power distribution network, and node serial number carries out in the way of increasing branch one by one；
(2) it uses and is pushed forward trend inside offspring's method calculating wind power plant；
(3) mathematical model of idle work optimization inside wind power plant is established, the idle work optimization object function of selection is with wind power plant
Built-in system loss minimization is optimization aim, and penalty is added in object function, handles the out-of-limit problem of node voltage；
If the total reactive requirement of wind field is only supplied by Wind turbines, do not consider the change of regulating transformer tap, then wind power plant without
Work(optimization problem controls the idle Q that variable is wind-driven generator outputi, state variable includes：Node voltage Ui, node voltage phase
Angle θi；
(4) it is solved using particle swarm optimization algorithm, realizes the reasonable distribution to the idle output of each unit, to reduce
The loss of grid：Under the premise of guarantee wind-driven generator optimal active power output, reasonable distribution is per typhoon power generator
The idle output of idle output, the D platform units in wind power plant is considered as the D dimension location variables of particle, and optimization object function is considered as calculation
The fitness of method；Particle swarm optimization algorithm is initialized as a group random particles, and random particles are per the idle of typhoon power generator
It contributes, optimal solution is found by iteration, in each iteration, all particles update oneself by tracking two " extreme values ".
First is exactly optimal solution that particle itself is found, this solution is called individual extreme value Pbesti, i.e., sent out by current each typhoon power
The loss for whole network that output calculation obtains that motor is idle；Another extreme value is the optimal solution that entire population is found at present, this
A extreme value is global extremum Gbesti, i.e., the minimum value of via net loss in all idle allocation plans.
The technique effect of the present invention is as follows：
1. the present invention is based on particle group optimizing (PSO) algorithm, the idle output of each wind-driven generator in wind power plant inside is carried out
Optimization.The algorithm is easy to implement and does not have multi-parameter to need to adjust, and ensures that convergence rate is also very fast while effect of optimization.
2. realizing the reasonable distribution to the idle output of each wind-driven generator, can be reduced with systems stabilisation node voltage
Active loss inside wind power plant improves safety and the economy of wind power plant operation.
Description of the drawings
Fig. 1：The simplification system wiring figure of example
Fig. 2：Wind power plant topological structure numbering
Fig. 3：Load flow calculation flow chart inside wind power plant
Fig. 4：The P-Q curves of Wind turbines
Fig. 5：Particle group optimizing (PSO) algorithm calculation flow chart
Fig. 6：Active loss iterative process (total reactive power 4.95Mvar) in wind power plant
Fig. 7：Each idle output (total reactive power 4.95Mvar) of wind-driven generator
Fig. 8：System voltage level curve
Fig. 9：Active loss iterative process (total reactive power 2.475Mvar) in wind power plant
Figure 10：Each idle output (total reactive power 2.475Mvar) of wind-driven generator
Figure 11：Active loss iterative process (total reactive power 7.425Mvar) in wind power plant
Figure 12：Each idle output (total reactive power 7.425Mvar) of wind-driven generator
Specific implementation mode
The present invention provides a kind of distribution sides realizing idle work optimization inside wind power plant based on particle group optimizing (PSO) algorithm
Case carries out Load flow calculation inside wind power plant using offspring's method is pushed forward, while according to topological structure and relevant parameter, in system emulation
The wind-field model, check algorithm correctness are built in software.Technical solution is as follows：
Network topology structure of the idle work optimization dependent on inside inside wind power plant based on particle group optimizing (PSO) algorithm,
It needs to be carried out calculating trend and active loss according to network topology structure, formulates prioritization scheme, therefore initially set up in wind power plant
Portion's topological structure.Network structure inside wind power plant include main transformer inside wind power plant, wind-driven generator box type transformer,
Wind-driven generator, connecting cable and overhead line etc..Wind-driven generator externally exports active and reactive power.It is one inside wind power plant
A typical tree network is connected with a box type transformer per the outlet of typhoon power generator, then is connected to by underground cable
Cable termination tower, each wind-force line are pooled in collection bus.Wind field exports busbar voltage it is known that can be considered the tree network
Root node, for the active power and reactive power of each wind-driven generator node it is known that can be considered leaf node, remaining node is considered as centre
Node.Any bar branch has determining beginning node and terminal note, it is specified that electric current outflow on a branch according to current direction
Node is terminal note, and the node that electric current flows into is beginning node.Node is numbered, the numbering of each node is by power distribution network
Feeder line tree mode carries out, and node serial number carries out in the way of increasing branch one by one.
Trend inside wind power plant is calculated using offspring's method is pushed forward.It is rated voltage to assume initially that whole network voltage all, by end
Power load, the i.e. power of leaf node and each node voltage calculate the power attenuation of each branch, obtain each intermediate node and root section
The injecting power or Injection Current of point, and beginning power is obtained accordingly, this is back substitution process；Further according to given root node voltage
With the beginning power acquired, voltage landing is calculated by beginning terminad paragraph by paragraph, acquires each node voltage, this is to be pushed forward process.Such as
This is repeated the above process, until the power deviation of each node meets enabled condition.
Idle work optimization inside wind power plant needs to establish Reactive power control system mathematic model to ensure each node
Quality of voltage and each state variable in the reasonable scope, that is, meet corresponding constraints, on this basis according to target
Function pair is idle to be optimized.
Particle group optimizing (PSO) algorithm initialization be a group random particles (RANDOM SOLUTION), the present invention in random particles (with
Machine solution) for per the idle output of typhoon power generator.Optimal solution is found by iteration, in each iteration, all particles are logical
Tracking two " extreme value " is crossed to update oneself.First is exactly optimal solution that particle itself is found, this solution is called individual pole
Value Pbesti, i.e., the loss of the whole network obtained by current each idle output calculation of typhoon power generator.Another extreme value is
The optimal solution that entire population is found at present, this extreme value is global extremum Gbesti, i.e., network damages in all idle allocation plans
The minimum value of consumption, wherein i=1,2 ... N, N are total number of particles in this group, i.e. wind-driven generator sum.
Particle initial velocity v is generated by the idle output of each wind-driven generatori(1≤i≤N), is finding Pbesti、
GbestiWhen the two optimal values, particle is according to following formula come the speed for updating oneself and new position：
T represents current time, and t+1 represents subsequent time.It is the current speed of particle, ω is inertia weight,It is to work as
The position of preceding particle,As previously defined, rand1() and rand2() is the random number between (0,1),
c1And c2It is Studying factors.It should be controlled in the reasonable scope per the idle output of typhoon power generator, therefore viMaximum value be
Vmax(being more than 0), minimum value Vmin, work as vi＞ VmaxWhen, vi=Vmax；Work as vi＜ VminWhen, vi=Vmin。
By successive ignition, final random particles (RANDOM SOLUTION) speed vi, including the idle output of each wind-driven generator
Information is to get to idle output distribution scheme inside wind power plant；Extreme value globally optimal solution Gbesti, the loss of as network is minimum
It is worth (optimal value).
Reactive Power Optimization Algorithm for Tower inside software programming wind power plant is realized using particle group optimizing (PSO) algorithm to each unit
The reasonable distribution of idle output, to reduce the loss of grid.
The present invention is described in detail below with reference to the accompanying drawings and embodiments.
Wind power plant internal topology figure is established, if wind field includes three times collection electric lines altogether, is referred to as A loop lines, B loop lines
With C loop lines, A loop lines connect 12 typhoon power generators altogether, and B loop lines connect 10 typhoon power generators altogether, and C loop lines connect 11 wind-power electricity generations altogether
Machine.Three times 35kV overhead transmission lines are inserted into outside wind field booster stations enclosure wall, are changed to the boosted station cable duct access boosting of underground cable
In standing in 35kV switchgears.Network structure inside wind power plant includes the main transformer inside wind power plant, wind-power electricity generation case type
Transformer wind-driven generator, connecting cable and overhead line etc., wind-driven generator externally export active and reactive power, simplify wiring
Figure is as shown in Figure 1.
It is a typical tree network inside wind power plant, a box-type transformation is connected with per the outlet of typhoon power generator
Device, then cable termination tower is connected to by underground cable, upper tower is followed by overhead line, and each wind-force line is pooled in collection bus,
Outlet busbar is connected to by main transformer again.Wind power plant exports busbar voltage amplitude, phase angle it is known that i.e. balance nodes, visually
For root node.The active power and reactive power of each wind-driven generator node can be considered leaf node it is known that as PQ nodes,
Remaining node is considered as intermediate node.Any bar branch has determining beginning node and terminal note, it is specified that a branch according to current direction
The node of road electric current outflow is terminal note, and the node that electric current flows into is beginning node.Wind-driven generator node is as tree network
First layer, the father node of wind-driven generator node is layered network, as the second layer until shifting root node onto.
One main feeder of tree network carries several branches, and each branch carries respective sub-branch, the volume of each node again
Number mode is carried out by the feeder line tree mode of power distribution network, and node serial number carries out in the way of increasing branch one by one.It is wind for Fig. 2
Electric field topological structure numbering simplification figure, 1 is root node, and the outlet busbar of corresponding wind power plant is drawn next by branch 1-2
Node, number 2, then the number of branch 1-2 is 2, then extends downwardly successively and draws each branch and node, until having numbered
At.2,3,6,7,8 be intermediate node in the topological diagram, and 5,9,10 be wind-driven generator node, that is, leaf node.
Tree network trend is calculated using offspring's method is pushed forward, calculation flow chart is as shown in Figure 3.
It writes and is pushed forward offspring's method flow calculation program.The initial voltage for assuming initially that each non-equilibrium node, by each leaf node
The active power and reactive power of (i.e. wind-driven generator node) can calculate forward the injection electricity for the upper layer node being attached thereto
Stream；The voltage of each node is acquired by known root node voltage and the loss back substitution of each line voltage distribution.
The Injection Current of each leaf node, calculating side are calculated by the active power, reactive power and initial voltage value of leaf node
Formula such as following formula：
The Injection Current of each intermediate node is the sum of the electric current that each branch using the node as beginning node flows through, each branch stream
The electric current crossed is equal to the Injection Current of the terminal note of the branch, and formula is as follows:
Voltage loss calculation formula is：
ΔUx,y+jΔUy,j=(Ix,y+jIy,j)(Rj+jXj) (3)
Sequentially acquire the voltage of each load bus backward from root node, formula is：
Ux,j+jUy,j=Ux,v+jUy,v-(ΔUx,j+jΔUy,j) (4)
The voltage phasor of all nodes is released in the back substitution for completing each branch according to this, terminates an iteration process.Calculate each section
The voltage magnitude correction amount of point judges the voltage difference of each node in iterative process twice whether within allowable error, if electric
Pressure amplitude value correction amount is less than threshold value, then terminates iteration, otherwise continue iteration.
After the voltage for obtaining each node, line loss is calculated, calculation formula is：
The mathematical model of idle work optimization inside wind power plant is established, the idle work optimization object function of selection is with wind power plant inside
The minimum optimization aim of system losses, and penalty is added in object function, the out-of-limit problem of node voltage is handled, it is this
Model can not only reduce the active power loss of system, moreover it is possible to improve the quality of voltage of each node inside wind power plant.Wherein, target
Function is：
In formula, n indicates the node total number of wind power plant built-in system, nPQIndicate PQ node total numbers, Ui, UjRespectively branch is first
The voltage magnitude of end node i and branch endpoint node j, θijFor i, the phase difference of voltage of j nodes, λ is voltage penalty factor,
Ui,max, Ui,minThe respectively voltage magnitude upper and lower bound of node i.
The equality condition of each node power constraint is inside wind power plant：
Each variable inequality constraints condition is as follows：
In view of the operation characteristic of double feedback electric engine, when giving active power, the reactive power auxiliary service table of wind power generating set
It is shown as：
PiFor the active power of node i injection, QiFor the reactive power of node i injection；PdiFor the burden with power of node i,
QdiFor the load or burden without work of node i；Gij、BijRespectively node i, the conductance between j and susceptance；QGi,max、QGi,minFor the i-th typhoon
Power generator sends out the upper and lower bound of reactive power；PGi,max, PGi,minI-th typhoon power generator sends out the upper limit of active power
Value and lower limiting value.Us、Xs、Xm、IrmaxRespectively stator voltage, stator reactance, excitation reactance and rotor-side current maxima.Fig. 4
For the wind power generating set reactive power auxiliary service figure of 3.6MW.
Due to the influence of wind power plant internal topology and electrical equipment, when reactive power is transmitted inside wind power plant
Larger active power loss and node voltage can be caused to fluctuate.It can be by optimizing every double-fed induction wind driven generator output
Reactive power, and then reduce wind power plant internal transformer and circuit loss.
If the total reactive requirement of wind field is only supplied by Wind turbines, the change of regulating transformer tap is not considered, then
Wind power plant Reactive Power Optimazation Problem controls the idle Q that variable is wind-driven generator outputi, state variable includes：Node voltage Ui, section
Point voltage phase angle θi.For the nonlinear optimal problem of this multivariable, the present invention is carried out using particle group optimizing (PSO) algorithm
It solves, under the premise of guarantee wind-driven generator optimal active power output, idle output of the reasonable distribution per typhoon power generator.Wind
The idle output of D platform units in electric field is considered as the D dimension location variables of particle, and optimization object function is considered as the fitness of algorithm.
Particle constantly pursues individual optimal solution (Pbest) and group optimal solution (Gbest) in searching process according to fitness function, directly
To finding globally optimal solution.Population (PSO) algorithm flow chart is as shown in Figure 5.
Idle work optimization program inside software programming wind power plant.Particle group optimizing (PSO) algorithm flow is as follows：
(1) system initialization.Maximum iteration t is setmax, solution space dimension D, particle number N contained by population, particle
Flying speed bound vmaxAnd vmin, the bound x of particle positionmax、xmin, Studying factors c1、c2。
(2) particle position and speed initialization.First D wind-force is randomly assigned within the scope of the idle output of wind-driven generator
The reactive power of generator generates a matrix that row vector is tieed up containing N number of D：
X=[Q11,Q12,...,Q1D；Q21,Q22,...,Q2D；...；QN1,QN2,...QND] (11)
N number of particle initial velocity v is generated within the scope of particle rapidityi(1≤i≤N)。
(3) feasible solution of generation is brought into the amplitude U for being pushed forward and calculating each node voltage in network in back substitution power flow algorithmi
And phase angle thetaiAnd the total network loss P of systemloss。
(4) individual optimal value Pbesti and group optimal value Gbest initialization.Here fitness function is taken as the total net of system
Damage, using the current position of each particle as individual optimal value Pbesti, using the individual optimal value in all particles as
Gbest。
(5) inertial factor, the speed of more new particle and position are updated.And check whether particle rapidity and position are more than setting
Bound, if it is less than lower limiting value, then its value is updated to lower limiting value, conversely, being updated to upper limit value.Particle is according to following formula
To update itself speed and the position in solution space.
X in formulaiD (t)、viD (t)The D of respectively i-th of particle position and speed in the t times iteration ties up component；PbestiD (t)Indicate the D dimension components of i-th of particle individual optimal value；GbestiD (t)Indicate the D dimension components of i-th of particle group optimal value；
ω indicates inertia weight, ωmax, ωminInertial factor when respectively iteration just starts at the end of.；c1、c2For two constants
Indicate Studying factors；r1、r2For the random number between (0,1)；tmaxFor maximum iteration.
(6) it looks for novelty the fitness function of particle.Updated particle coordinate is brought into Load flow calculation and seeks its fitness letter
Numerical value.
(7) individual optimal value Pbesti and group optimal value Gbest updates.To each particle, the adaptive value f that will newly obtain
(xi) be compared with the adaptive value f (Pbesti) of its individual optimal value, if the former is better than the latter, using new value as the particle
Individual optimal value Pbesti.After individual optimal value Pbesti update, then by all individual optimal value adaptive value f (Pbesti)
The adaptive value f (Gbest) with current all optimal values is compared one by one, if the adaptive value of the individual optimal value is most better than entirety
The adaptive value of the figure of merit, then using the individual optimal value Pbesti as current group optimal value Gbest.
(8) iterations are checked, if it exceeds maximum iteration tmax, then stop calculating, output group history is optimal
Solution；Otherwise (5) are returned to, into next iteration searching process.
In wind field, overhead line conductor selects JL/G1A-150/25, JL/G1A-95/20 shaped steel core aluminum stranded wire.Wind-force is sent out
The no-load loss that motor housing becomes is 4.45kW, no-load current 0.7%, short-circuit impedance 6%.
Do not consider that each Wind turbines wind speed caused by the difference of geographical location is different, that is, thinks each wind-powered electricity generation under same wind speed
The output of unit active power is equally 1.5MW, and corresponding the upper and lower of reactive power is limited to [- 1.824,0.270] Mvar, and wind power plant is total
Reactive requirement be set as the 10% of active power, i.e. 4.95Mvar, obtained in iterative process according to particle group optimizing (PSO) algorithm
Dissipation change as shown in fig. 6, each wind-driven generator it is as shown in Figure 7 without the distribution of work.
The reactive power sent out for the unit (1~10) concatenated apart from the C loop lines of booster stations farther out is less, and distance
The reactive power that the unit (29~33) that the closer B loop lines of booster stations are connect is sent out is more.The branch BA branches of B loop lines are given a dinner for a visitor from afar
The reactive power that power generator group (20~24) the is sent out wind power generating set closer apart from booster stations less than on B loop lines (29~
33), with increase of the wind power generating set 21~24 away from booster stations distance, the reactive power sent out gradually decreases.This be by
The increase of active power loss can be caused therefore should to use up in practice in flowing of the reactive power in wind power plant on long-distance line road
Amount realizes the compensation of the total reactive requirement of wind power plant by the Wind turbines close to wind field outlet.
Voltage level curve in the front and back system of optimization is as shown in figure 8, it can clearly be seen that optimization posterior nodal point voltage fluctuation subtracts
Small, quality of voltage improves.
Under normal circumstances, the reactive power distribution of wind power plant is that the total reactive requirement of wind field is averagely allocated to each wind-force
Generator, the system losses under this method of salary distribution are 1.8854MW, and the network loss after optimization is 1.8086MW, network loss relatively optimization with
Before reduce 4.07%.In order to significantly more find out effect of optimization, total reactive requirement of wind power plant is changed into total active power
5% and 15%, Fig. 9-12 is that grid loss changes in iterative process, and it is as shown in table 1 to optimize front and back system losses.
Table 1:Grid loss result
Due to the influence of wind power plant internal topology, the flowing of reactive power on the line can influence system losses, answer
On the basis of the limit occurs without departing from wind power generating set reactive power, each wind power generating set Reactive-power control energy is given full play to
The flexibility of power optimizes the idle output of each unit, realizes reactive power in-situ compensation, can improve wind power plant internal node electricity
The stability of pressure, and reduce the input of additional reactive-load compensation equipment.
Simulation result show with particle group optimizing (PSO) algorithm realize wind power plant inside idle work optimization, can be with stability series
System node voltage, reduces system losses, improves safety and the economy of wind power plant operation.
Claims (1)
1. idle work optimization method inside a kind of wind power plant based on particle swarm optimization algorithm, includes the following steps：
(1) wind power plant internal topology is established：It is connected with a box type transformer per the outlet of typhoon power generator, then passes through ground
Cable connection is buried to cable termination tower, each wind-force line is pooled in collection bus, and wind field exports busbar voltage it is known that being considered as this
The root node of tree network, the active power and reactive power of each wind-driven generator node are it is known that be considered as leaf node, remaining node
It is considered as intermediate node, any bar branch has determining beginning node and terminal note, it is specified that a branch powers on according to current direction
The node of stream outflow is terminal note, and the node that electric current flows into is beginning node, node is numbered, the numbering of each node is pressed
The feeder line tree mode of power distribution network carries out, and node serial number carries out in the way of increasing branch one by one.
(2) it uses and is pushed forward trend inside offspring's method calculating wind power plant；
(3) mathematical model of idle work optimization inside wind power plant is established, the idle work optimization object function of selection is with wind power plant inside
The minimum optimization aim of system losses, and penalty is added in object function, handle the out-of-limit problem of node voltage；If wind
The total reactive requirement in field is only supplied by Wind turbines, does not consider the change of regulating transformer tap, then wind power plant is idle excellent
Change problem controls the idle Q that variable is wind-driven generator outputi, state variable includes：Node voltage Ui, node voltage phase angle thetai；
(4) it is solved using particle swarm optimization algorithm, the reasonable distribution to the idle output of each unit is realized, to reduce system
The loss of network：Under the premise of guarantee wind-driven generator optimal active power output, reasonable distribution is idle per typhoon power generator
It contributes, the idle output of the D platform units in wind power plant is considered as the D dimension location variables of particle, and optimization object function is considered as algorithm
Fitness；Particle swarm optimization algorithm is initialized as a group random particles, and random particles are the idle output of every typhoon power generator,
Optimal solution is found by iteration, in each iteration, all particles update oneself by tracking two " extreme values ".First
It is exactly the optimal solution that particle itself is found, this solution is called individual extreme value Pbesti, i.e., by current each typhoon power generator without
The loss for the whole network that work(output calculation obtains；Another extreme value is the optimal solution that entire population is found at present, this extreme value
It is global extremum Gbesti, i.e., the minimum value of via net loss in all idle allocation plans.
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