CN107579546A - Marine wind electric field optimal reactive power allocation method based on double-fed fan motor unit blower fan topological structure - Google Patents
Marine wind electric field optimal reactive power allocation method based on double-fed fan motor unit blower fan topological structure Download PDFInfo
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Abstract
The present invention relates to a kind of marine wind electric field optimal reactive power allocation method based on double-fed fan motor unit blower fan topological structure, 1) by calculating the idle limit of marine wind electric field double-fed fan motor unit, the transverter of double-fed fan motor unit is controlled to carry out Reactive-power control, using double-fed fan motor unit as wind power plant continuous reactive source；2) by marine wind electric field it is idle control variables choice be generator node the idle output of double-fed fan motor unit, and the capacity of offshore boosting station low-pressure side and the reactive-load compensation point reactive-load compensation equipment of land centralized control center two is set, Wind turbines are equivalent to the constant pressure power source of controlled current flow, and the power transfer characteristic identical principle based on actual wind power plant Yu equivalent wind power plant, the wind power plant Equivalent Model of offshore wind farm system is established, precondition is established for marine wind electric field idle work optimization；Reactive-load compensation is carried out to the blower fan cluster of marine wind electric field double-fed fan motor unit using CMO algorithms.The present invention can preferably determine the reactive compensation capacity under marine wind electric field maximum operational mode, improve stability, the security of Operation of Electric Systems.
Description
Technical field
The present invention relates to a kind of marine wind electric field optimal reactive power allocation side based on double-fed fan motor unit blower fan topological structure
Method is a kind of based on double-fed fan motor unit (DFIG) (doubly fed induction generator) blower fan group of planes topology knot
Structure and fully meter and its Reactive-power control, and consider the reactive compensation configuration method of extra large cable direct-to-ground capacitance and turn-to-turn capacitance.Belong to
Power system reactive power compensation technical field.
Background technology
Because offshore wind speed enriches, there is the remarkable advantages such as high wind speed, low wind shear, low turbulent flow, high production, to environment
Influence small, be not take up land area, and offshore wind farm will not cause noise pollution, therefore wind in recent years to human residential environment
Hair is established by cable to present from the land trend shifted to sea.
Offshore wind power equipment fault restoration is completed by maintenance vessel launching-out operation mostly, and operation expense is than land wind-powered electricity generation
It is high.Therefore, very high is required to offshore wind farm system reliability.Wherein, Scheme of Reactive Power Compensation design is particularly critical.But due to sea
The direct-to-ground capacitance of bottom cable and turn-to-turn capacitance are larger, the dynamic reactive distribution of marine wind electric field and its compensation demand and land wind-powered electricity generation
There is larger difference field, thus land Reactive Compensation in Wind Farm scheme is not suitable for marine wind electric field.
Early stage wind power plant mainstream model is cage modle wind power generating set, because cage modle unit does not adjust reactive power output
Ability, therefore the direction studied is mainly concentrated in configuring on the reactive power compensator such as capacitor for wind power plant.With wind
Group of motors manufactures and the continuous development of control technology, the higher double-fed fan motor unit of wind energy transformation rate turn into wind-powered electricity generation main force type.
Doubly fed induction generator (abbreviation DFIG) has PQ uneoupled control abilities, using the wind-powered electricity generation field energy of doubly fed induction generator (abbreviation DFIG)
It is enough dynamically to continuously adjust reactive power output, voltage support is provided for power network, therefore can be as the reactive power in wind power plant
Source.
Current research is mainly concentrated in determining the Reactive-power control ability of double-fed fan motor unit and utilizes double-fed unit
Participate in the research of wind power plant reactive power compensation policy.And with the continuous increase of wind farm grid-connected capacity, recent domestic
Numerous studies have been carried out in terms of idle work optimization：Some document utilization artificial intelligence and some optimization methods, such as genetic algorithm, grain
Swarm optimization, neural network algorithm etc. all achieve certain achievement；The also current research of some documents is mainly concentrated in
Determine the Reactive-power control ability of double-fed fan motor unit and participated in using double-fed unit in the research of wind power plant reactive power compensation policy.
But according to the method for " the participating in wind power plant reactive power compensation policy using double-fed unit ", however it remains the benefit of reactive-load compensation point
Repay the problems such as capacity is big, discrete device cost payout is high, system operation is unstable, security is poor and operating cost is high.
The content of the invention
The purpose of the present invention, reactive-load compensation point be present to solve existing double-fed unit participation wind power plant reactive power compensation
Reactive compensation capacity it is big, discrete device adjustment cost expenditure is high, system operation is unstable, security is poor and operating cost is high etc.
A kind of problem, there is provided marine wind electric field optimal reactive power allocation method based on double-fed fan motor unit blower fan topological structure.With nothing
The reactive compensation capacity of work(compensation point is small, discrete device adjustment cost expenditure is low, system run all right, the security discrepancy in elevation and operation
The features such as cost is low.
The purpose of the present invention can be achieved through the following technical solutions：
Marine wind electric field optimal reactive power allocation method based on double-fed fan motor unit blower fan topological structure, it is characterised in that：
1) by calculating the idle limit of marine wind electric field double-fed fan motor unit, the transverter of double-fed fan motor unit is controlled to enter
Row Reactive-power control, using double-fed fan motor unit as wind power plant continuous reactive source；
2) by marine wind electric field it is idle control variables choice be generator node the idle output of double-fed fan motor unit,
And the capacity of offshore boosting station low-pressure side and the reactive-load compensation point reactive-load compensation equipment of land centralized control center two is set, by wind-powered electricity generation
Unit is equivalent to the constant pressure power source of controlled current flow, and identical with the power transfer characteristic of equivalent wind power plant based on actual wind power plant
Principle, establish the wind power plant Equivalent Model of offshore wind farm system, precondition established for marine wind electric field idle work optimization；
3) on the basis of considering that double-fed fan motor unit blower fan topological structure influences with extra large cable direct-to-ground capacitance, turn-to-turn capacitance,
Reactive-load compensation is carried out to the blower fan cluster of marine wind electric field double-fed fan motor unit using CMO algorithms.
The purpose of the present invention can also be achieved through the following technical solutions：
Further, the 1) put in using double-fed fan motor unit as during wind power plant continuous reactive source, the double-fed fan motor machine
The stator side of group is joined directly together with power network, and rotor-side is connected with power network by net side transverter and pusher side transverter, is achieved in
The two-way flow of rotor-side power, and then realize the variable speed constant frequency operation of double-fed blower fan.
Further, the 1) put in control the transverter of double-fed fan motor unit to carry out Reactive-power control, refer to the double-fed wind
Group of motors is by realizing active and idle uneoupled control to converter Control so that double-fed fan motor unit has dynamic regulation idle
Ability.
Further, the 1) put in when controlling the transverter of double-fed fan motor unit to carry out Reactive-power control, when net side transverter
The idle reactive power Q sent equal to stator side idle, double-fed fan motor unit is sent is not sentS,
QT=QS (3-1)
Double-fed fan motor unit DFIG optimal power curve of pursuit formula can use formula (3-2) to represent：
PT=Kopt(1-s)3 (3-2)
In formula：PTActive power is sent for double-fed fan motor unit DFIG；Proportionality constant when Kopt is optimum speed；S is
Revolutional slip,
Double-fed fan motor unit DFIG is idle limit QTBy stator current IsWith rotor current IrInfluence it is as follows：
In formula：UsFor stator voltage；xsFor stator reactance；xmFor excitation reactance.
Further, it is main to consider that marine wind electric field is idle in the wind power plant Equivalent Model of offshore wind farm system is established
The constraints of the object function and satisfaction of optimization and active power output and idle output；
The target wind function is electric to reduce internal active power loss, balanced wind power plant internal node with electric field idle work optimization
Pressure, the cost payout for reducing purchase discrete device is target, and its calculation is：
MinF=n1Ploss+n2||ΔVG||2+n3fcost (3-5)
Wherein：For the active loss of system, NiFor branch road
Number；gkFor branch road k conductance；ui, ujFor the voltage magnitude of load bus；θijThe phase angle of voltage between load bus i, j
Difference, | | Δ VG||2=∑ Δ VGi 2=∑ (VGi-1)2For node voltage departure, VGiFor the perunit value of node voltage, fcost=S1
ΔC1+S2ΔC2For the cost payout of discrete device regulation, S1, Δ C1Cost and regulation variable quantity for buyer capacitor；
S2, Δ C2Adjustment cost and regulation variable quantity for buyer SVC (SVC is SVC)；
n1, n2, n3Active loss index, hub node voltage deviation index and discrete device are adjusted respectively in object function
The weight coefficient of index is saved, weight coefficient is calculated by analytic hierarchy process (AHP) (analytic hierarchy process, AHP)
Go out；
The constraints of the active power output and idle output need to meet below equation：
In formula：PGi, QGiRespectively generator i active power output and idle output；PDi, QDiRespectively load bus i's has
Workload power and load or burden without work power；QCFor reactive-load compensation amount；Gij, Bij, θijConductance, susceptance respectively between node i, j
And phase difference of voltage；N is node total number；
In order to ensure safe operation of power system, also to meet following inequality constraints condition：
Control the inequality constraints condition of variable：
QC, i min, QC, i maxThe upper lower limit value of reactive compensation capacity, N are represented respectivelycFor the set of reactive-load compensation point, QG, i min,
QG, i maxRepresent that generator i sends the upper lower limit value of reactive power respectively；NGFor generator node set,
The inequality constraints condition of state variable：
Ui min≤Ui≤Ui max, i ∈ NL (3-8)
Ui min, Ui maxThe bound of node i voltage, N are represented respectivelyLRepresent system node set.
Further, carrying out reactive-load compensation method to offshore wind farm cluster using CMO algorithms is：The CMO algorithms are cell
Film optimized algorithm, specific algorithm are as follows：
1) initial calculation parameter is set, initializes material group, blower fan in every one-dimensional power system of expression respectively of material solution
The compensation capacity of the idle and reactive-load compensation point sent；
2) Load flow calculation is carried out to each material in material group, judges whether the inequality constraints bar for meeting idle work optimization
Part, filter out so that the material of object function minimum is designated as XbestAnd record its value and place algebraically；
3) concentration division is carried out to material group, according to concentration division factor into high concentration liposoluble substance (FS), high concentration
Non-fat-soluble material (NS), low concentration material (LS)；Calculate the concentration of each material position, by material concentration from it is small to
Big sequence, the material for coming preceding 50% is LS, and the material for coming rear 50% is HS, is then by the material that odd bits are come in HS
FS, the material for coming even bit are NS；
The calculation formula of material Y concentration：
In formula：N represents XiDistance in (i=1 ..., m) to Y meets formula's
Number, m represent material sum, and r is radius factor, generally takes 0.4~0.6, XiI-th of material solution is represented, Y represents to need to solve
Concentration material solution；
4) each material free diffusing motion of high concentration liposoluble substance group, is transferred to low by the high concentration side of cell membrane
Concentration side, whole process had not both needed carrier to randomly select a thing in low concentration material group LS first also without energy
Matter LSrandiAs target is spread, the unit direction vector of diffusion is calculated：
Then, high concentration material FSiIt is diffused by vectorial F direction, obtains new material newFSi：
Each FS is moved in formula (3-11), rand () represents that random movement step-length span is [0,1], FkTable
Show vectorial F kth dimension, after this motion process, by the starting substance group FS, be changed into new material group new FS, to new
Solution carries out Load flow calculation, judges idle work optimization constraints；Contrasted with original matter solution result, if novel substance solution target letter
Number is less than original matter solution object function and then substitutes former solution with new explanation, otherwise retains former solution, moves locn times, take wherein optimal conduct
FS final position；
5) each material of high concentration non-fat-soluble material group is spread by assisting, and is transferred to by the high concentration side of cell membrane
Low concentration side, whole process process need carrier, it is not necessary to energy, in order to enter to the forms of motion of high concentration non-fat-soluble material
Row limitation, algorithm introduce carrier factor cfiConcept：
If carrier factor cfiMore than certain random number rand () in [0,1], then the material can assist to spread, otherwise, to
Current optimal solution direction motion；
As high concentration non-fat-soluble material NSiWhen meeting carrier condition, locn is spread in high concentration lateral movement to low concentration side
It is secondary, and best diffusion position is chosen as final result, randomly select a material in low concentration material group LS first
LSrandiAs target is spread, the unit direction vector of diffusion is calculated：
Then, high concentration non-fat-soluble material NSiIt is diffused by vectorial F direction, obtains new material newNSi：
As high concentration non-fat-soluble material NSiWhen being unsatisfactory for carrier condition, it is to current optimal material XbestSpread in direction
Locn times, and best diffusion position is chosen as final result：
6) low concentration material is transferred to high concentration side by active transport from the low concentration side of cell membrane, and whole process both needed
Want carrier, it is also desirable to which energy, in order to limit the forms of motion of low concentration material, algorithm introduces energy factors efiAnd load
Body factor cfiConcept：
If energy factors efiMore than certain random number rand () in [0,1], then the material meets energy condition, if carrier
Factor cfiMore than certain random number rand () in [0,1], then the material meets carrier condition, for certain low concentration material LSi,
First determine whether it meets energy condition, then judge whether it meets carrier condition；
As low concentration material LSiWhen being unsatisfactory for energy condition, random motion locn times in the region of search of material is chosen
Final result of the best position as the material：
As low concentration material LSiWhen both having met energy condition or having met carrier condition, active transport can be now carried out, its
Locn is moved to high concentration material HS (i.e. high concentration liposoluble substance FS and high concentration non-fat-soluble material NS summation) direction
It is secondary, and choose the best position result final as its；
First, a material HS is randomly selected in high concentration material group HSrandiAs target is spread, the list of diffusion is calculated
Position direction vector：
Secondly, low concentration material LSiIt is diffused by vectorial F direction, obtains new material newLSi：
If low concentration material LSiMeet energy condition and be unsatisfactory for carrier strip part, then make it to current optimal material XbestSide
To diffusion locn times, and best position is chosen as final result：
7) all substances solution is updated replacement, judges whether to meet iterations requirement, exported if meeting optimal
Material solution, and by optimal material solution object function of each generation and the images outputting of optimal solution movement locus；If not satisfied, then from second
Step continues iteration.
The present invention has substantive distinguishing features following prominent and significant progress：
1st, the idle limit of the invention by calculating double-fed fan motor unit, controls the transverter of double-fed fan motor unit to carry out nothing
Work(is adjusted, using double-fed fan motor unit as wind power plant continuous reactive source；It is to generate electricity by the idle variables choice that controls of wind power plant
The idle output of double-fed fan motor unit of machine node, and offshore boosting station low-pressure side and land centralized control center's reactive-load compensation equipment
Capacity is set, on the basis of the offshore wind farm cluster based on topological structure, using CMO algorithms (i.e. cell membrane algorithm Cell
Membrane Optimization) reactive-load compensation is carried out to offshore wind farm cluster；Therefore being capable of existing double-fed unit participation wind-powered electricity generation
Reactive compensation capacity that reactive power compensation has reactive-load compensation point is big, discrete device adjustment cost expenditure is high, system operation
Unstable, the problems such as security is poor and operating cost is high, have that the reactive compensation capacity of reactive-load compensation point is small, discrete device regulation
The features such as cost payout is low, system run all right, the low security discrepancy in elevation and operating cost and beneficial effect.
2nd, present invention may determine that during marine wind electric field rated power operation the idle output of double-fed fan motor unit (DFIG) and
The compensation capacity of reactive-load compensation point.The motion of matter direction of its algorithm has an interactivity, material disaggregation flattening, therefore can be effective
Ground avoid existing power system from existing reactive compensation capacity is big, discrete device adjustment cost expenditure is high, system operation is unstable,
The technical problems such as security difference, realize that operating cost is low, the prominent substantive features such as operation is more economical, stable.
3rd, the present invention combines electric field idle work optimization to the demand of algorithm, cell membrane algorithm (Cell Membrane
Optimization) carry out calculating the reactive-load compensation of offshore wind farm cluster, form a kind of intelligent algorithm with superperformance, with
Solves Reactive Power Optimazation Problem, this algorithm motion of matter direction has interactivity, material disaggregation flattening, improves global optimizing energy
Power, while optimal material solution is carried out to circulate optimizing by dimension, and previous generation's optimal solution is inherited, convergence rate is improved, algorithm has
Good concurrency, reduce the risk for being absorbed in locally optimal solution.
4th, the present invention is fully taking into account double-fed fan motor unit (DFIG) group of planes topological structure, Reactive-power control ability and sea
On the basis of cable direct-to-ground capacitance influences with turn-to-turn capacitance, marine wind electric field idle work optimization model is established, it is active to reduce wind power plant
Generating set node voltage, reduction discrete device adjustment cost expenditure are target in loss, balanced wind power plant, pass through CMO algorithms
To model solution, marine wind electric field reactive compensation capacity is determined, CMO algorithms are applied to marine wind electric field idle work optimization, thus
The reactive compensation capacity under marine wind electric field maximum operational mode is preferably determined, improves stability, the peace of Operation of Electric Systems
Quan Xing.
Brief description of the drawings
Fig. 1 is the double-fed fan motor unit structure chart of the present invention.
Fig. 2 is the P- that the present invention considers double-fed fan motor unit (DFIG) after double-fed fan motor unit (DFIG) maximum power tracing
Q curve maps.
Fig. 3 is the idle work optimization flow chart of the invention based on CMO algorithms.
Fig. 4 is the object function convergence curve figure of the CMO algorithms of the present invention.
Fig. 5 is the offshore wind farm field structure of the present invention.
Fig. 6 is the idle output table of double-fed fan motor unit (DFIG) each unit of the present invention.
The content of the invention
Below in conjunction with accompanying drawing, the present invention is described in further detail.
Marine wind electric field optimal reactive power allocation method based on double-fed fan motor unit blower fan topological structure,
1) by calculating the idle limit of marine wind electric field double-fed fan motor unit, the transverter of double-fed fan motor unit is controlled to enter
Row Reactive-power control, using double-fed fan motor unit as wind power plant continuous reactive source；
2) by marine wind electric field it is idle control variables choice be generator node the idle output of double-fed fan motor unit,
And the capacity of offshore boosting station low-pressure side and the reactive-load compensation point reactive-load compensation equipment of land centralized control center two is set, by wind-powered electricity generation
Unit is equivalent to the constant pressure power source of controlled current flow, and identical with the power transfer characteristic of equivalent wind power plant based on actual wind power plant
Principle, establish the wind power plant Equivalent Model of offshore wind farm system, precondition established for marine wind electric field idle work optimization；
3) on the basis of considering that double-fed fan motor unit blower fan topological structure influences with extra large cable direct-to-ground capacitance, turn-to-turn capacitance,
Reactive-load compensation is carried out to the blower fan cluster of marine wind electric field double-fed fan motor unit using CMO algorithms.
In embodiment, as shown in figure 1, the 1) put in using double-fed fan motor unit as during wind power plant continuous reactive source, it is described
The stator side of double-fed fan motor unit is joined directly together with power network, and rotor-side passes through net side transverter and pusher side transverter phase with power network
Even, the two-way flow of rotor-side power is achieved in, and then realizes the variable speed constant frequency operation of double-fed blower fan；Wherein control double-fed wind
The transverter of group of motors carries out Reactive-power control, refers to that the double-fed fan motor unit is active and idle by being realized to converter Control
Uneoupled control so that double-fed fan motor unit has dynamic regulation reactive power capability.
In method, when the transverter of middle control double-fed fan motor unit carries out Reactive-power control, when net side transverter does not send nothing
Work(, the idle reactive power Q sent equal to stator side that double-fed fan motor unit is sentS,
QT=QS (3-1)
The optimal power curve of pursuit formula approximation of double-fed fan motor unit (DFIG) can use formula (3-2) to represent：
PT=Kopt(1-s)3 (3-2)
In formula：PTActive power is sent for double-fed fan motor unit (DFIG)；Proportionality constant when Kopt is optimum speed；s
For revolutional slip,
Double-fed fan motor unit (DFIG) is idle limit QTBy stator current IsWith rotor current IrInfluence it is as follows：
In formula：UsFor stator voltage；xsFor stator reactance；xmFor excitation reactance.
It is main to consider marine wind electric field trend, state variable in the wind power plant Equivalent Model of offshore wind farm system is established
With the constraints of control variable；
The wind power plant idle work optimization reduces purchase to reduce internal active power loss, balanced wind power plant internal node voltages
The cost payout of discrete device is target, and its calculation is：
MinF=n1Ploss+n2||ΔVG||2+n3fcost (3-5)
Wherein：For the active loss of system, NiFor branch road
Number；gkFor branch road k conductance；ui, ujFor the voltage magnitude of load bus；θijFor load bus i, the phase angle of voltage between j
Difference, | | Δ VG||2=Σ Δs VGi 2=Σ (VGi-1)2For node voltage departure, VGiFor the perunit value of node voltage, fcost=S1
ΔC1+S2ΔC2For the cost payout of discrete device regulation, S1, Δ C1Cost and regulation variable quantity for buyer capacitor；
S2, Δ C2Adjustment cost and regulation variable quantity for buyer SVC (SVC is SVC)；
n1, n2, n3Active loss index, hub node voltage deviation index and discrete device are adjusted respectively in object function
The weight coefficient of index is saved, weight coefficient is calculated by analytic hierarchy process (AHP) (analytic hierarchy process, AHP)
Go out；
The constraints of the active power output and idle output need to meet below equation：
In formula：PGi, QGiRespectively generator i active power output and idle output；PDi, QDiRespectively load bus i's has
Workload power and load or burden without work power；QCFor reactive-load compensation amount；Gij, Bij, θijConductance, susceptance respectively between node i, j
And phase difference of voltage；N is node total number；
In order to ensure safe operation of power system, also to meet following inequality constraints condition：
Control the inequality constraints condition of variable：
QC, i min, QC, i maxThe upper lower limit value of reactive compensation capacity, N are represented respectivelycFor the set of reactive-load compensation point, QG, i min,
QG, i maxRepresent that generator i sends the upper lower limit value of reactive power respectively；NGFor generator node set,
The inequality constraints condition of state variable：
Ui min≤Ui≤Ui max, i ∈ NL (3-8)
Ui min, Ui maxThe bound of node i voltage, N are represented respectivelyLRepresent system node set.
Carrying out reactive-load compensation method to offshore wind farm cluster using CMO algorithms is：The CMO algorithms are that cell membrane optimization is calculated
Method, specific algorithm is as follows, as shown in Figure 3：
1) initial calculation parameter is set, initializes material group, blower fan in every one-dimensional power system of expression respectively of material solution
The compensation capacity of the idle and reactive-load compensation point sent；
2) Load flow calculation is carried out to each material in material group, judges whether the inequality constraints bar for meeting idle work optimization
Part, filter out so that the material of object function minimum is designated as XbestAnd record its value and place algebraically；
3) concentration division is carried out to material group, according to concentration division factor into high concentration liposoluble substance (FS), high concentration
Non-fat-soluble material (NS), low concentration material (LS)；Calculate the concentration of each material position, by material concentration from it is small to
Big sequence, the material for coming preceding 50% is LS, and the material for coming rear 50% is HS, is then by the material that odd bits are come in HS
FS, the material for coming even bit are NS；
The calculation formula of material Y concentration：
In formula：N represents XiDistance in (i=1 ..., m) to Y meets formula's
Number, m represent material sum, and r is radius factor, generally takes 0.4~0.6, XiI-th of material solution is represented, Y represents to need to solve
Concentration material solution；
4) each material free diffusing motion of high concentration liposoluble substance group, is transferred to low by the high concentration side of cell membrane
Concentration side, whole process had not both needed carrier to randomly select a thing in low concentration material group LS first also without energy
Matter LSrandiAs target is spread, the unit direction vector of diffusion is calculated：
Then, high concentration material FSiIt is diffused by vectorial F direction, obtains new material newFSi：
Each FS is moved in formula (3-11), rand () represents that random movement step-length span is [0,1], FkTable
Show vectorial F kth dimension, after this motion process, by the starting substance group FS, be changed into new material group new FS, to new
Solution carries out Load flow calculation, judges idle work optimization constraints；Contrasted with original matter solution result, if novel substance solution target letter
Number is less than original matter solution object function and then substitutes former solution with new explanation, otherwise retains former solution, moves locn times, take wherein optimal conduct
FS final position；
5) each material of high concentration non-fat-soluble material group is spread by assisting, and is transferred to by the high concentration side of cell membrane
Low concentration side, whole process process need carrier, it is not necessary to energy, in order to enter to the forms of motion of high concentration non-fat-soluble material
Row limitation, algorithm introduce carrier factor cfiConcept：
If carrier factor cfiMore than certain random number rand () in [0,1], then the material can assist to spread, otherwise, to
Current optimal solution direction motion；
As high concentration non-fat-soluble material NSiWhen meeting carrier condition, locn is spread in high concentration lateral movement to low concentration side
It is secondary, and best diffusion position is chosen as final result, randomly select a material in low concentration material group LS first
LSrandiAs target is spread, the unit direction vector of diffusion is calculated：
Then, high concentration non-fat-soluble material NSiIt is diffused by vectorial F direction, obtains new material newNSi：
As high concentration non-fat-soluble material NSiWhen being unsatisfactory for carrier condition, it is to current optimal material XbestSpread in direction
Locn times, and best diffusion position is chosen as final result：
6) low concentration material is transferred to high concentration side by active transport from the low concentration side of cell membrane, and whole process both needed
Want carrier, it is also desirable to which energy, in order to limit the forms of motion of low concentration material, algorithm introduces energy factors efiAnd load
Body factor cfiConcept：
If energy factors efiMore than certain random number rand () in [0,1], then the material meets energy condition, if carrier
Factor cfiMore than certain random number rand () in [0,1], then the material meets carrier condition, for certain low concentration material LSi,
First determine whether it meets energy condition, then judge whether it meets carrier condition；
As low concentration material LSiWhen being unsatisfactory for energy condition, random motion locn times in the region of search of material is chosen
Final result of the best position as the material：
As low concentration material LSiWhen both having met energy condition or having met carrier condition, active transport can be now carried out, its
Locn is moved to high concentration material HS (i.e. high concentration liposoluble substance FS and high concentration non-fat-soluble material NS summation) direction
It is secondary, and choose the best position result final as its；
First, a material HS is randomly selected in high concentration material group HSrandiAs target is spread, the list of diffusion is calculated
Position direction vector：
Secondly, low concentration material LSiIt is diffused by vectorial F direction, obtains new material newLSi：
If low concentration material LSiMeet energy condition and be unsatisfactory for carrier strip part, then make it to current optimal material XbestSide
To diffusion locn times, and best position is chosen as final result：
7) all substances solution is updated replacement, judges whether to meet iterations requirement, exported if meeting optimal
Material solution, and by optimal material solution object function figure of each generation it is (as shown in Figure 4) output；If not satisfied, then continue from second step
Iteration.
The technical method of the present invention is concisely introduced with simulation calculation below：
As shown in figure 5, CMO algorithms are used in marine wind electric field, wind energy turbine set installed capacity is every 3MVA, totally 12,
Every interval 0.5km, blower fan spacing is at least above the height of blower fan, collector system voltage class 35kV, through offshore boosting station liter
To 110kV.
Shown in the following subordinate list 1 of line parameter circuit value.Reactive power compensator position is located at 25,27 nodes, is computed that each pair can be obtained
Present the idle output (as shown in Figure 6) of Wind turbines (DFIG) and reactive compensation capacity is respectively at 25,27 sections
1.8672MVar、0MVar。
The network parameter of subordinate list 1
The inventive method innovative point and benefit mainly have following three points：
1. considering influence of the Wind turbines topology distribution to wind power plant idle work optimization, Wind turbines group of planes reactive requirement is studied
Assignment problem between Wind turbines, by calculating the idle limit of double-fed fan motor unit, abundant note and double-fed fan motor unit
(DFIG) Reactive-power control ability, using double-fed fan motor unit (DFIG) as wind power plant continuous reactive source, reactive-load compensation point is reduced
Compensation capacity, reduce discrete device adjustment cost expenditure.
2. fully using for reference land wind power plant equivalent modeling Research Thinking, wind-powered electricity generation group is equivalent to the constant pressure power of controlled current flow
Source, on this basis, the power transfer characteristic identical principle based on actual wind power plant Yu equivalent wind power plant, establish offshore wind farm
The idle work optimization model of system, precondition is established for marine wind electric field idle work optimization.
3. consider that blower fan topological structure is idle with applying CMO algorithms to carry out offshore wind farm cluster on the basis of extra large cable influence
Compensation.
The algorithm motion of matter direction has interactivity, material disaggregation flattening, improves global optimizing ability；Simultaneously to most
Excellent material solution carries out circulating optimizing by dimension, and inherits previous generation's optimal solution, improves convergence rate；Algorithm has well parallel
Property, reduce the risk for being absorbed in locally optimal solution.The idle output and nothing of double-fed fan motor unit (DFIG) are calculated by the algorithm
The compensation capacity of work(compensation point, ensure the security, reliability and economy of system operation.
Claims (6)
1. the marine wind electric field optimal reactive power allocation method based on double-fed fan motor unit blower fan topological structure, it is characterised in that：
1) by calculating the idle limit of marine wind electric field double-fed fan motor unit, the transverter of double-fed fan motor unit is controlled to carry out nothing
Work(is adjusted, using double-fed fan motor unit as wind power plant continuous reactive source；
2) by marine wind electric field it is idle control variables choice be generator node the idle output of double-fed fan motor unit, and
The capacity of offshore boosting station low-pressure side and the reactive-load compensation point reactive-load compensation equipment of land centralized control center two is set, by Wind turbines
The constant pressure power source of controlled current flow is equivalent to, and the power transfer characteristic identical based on actual wind power plant and equivalent wind power plant is former
Then, the wind power plant Equivalent Model of offshore wind farm system is established, precondition is established for marine wind electric field idle work optimization；
3) on the basis of considering that double-fed fan motor unit blower fan topological structure influences with extra large cable direct-to-ground capacitance, turn-to-turn capacitance, application
CMO algorithms carry out reactive-load compensation to the blower fan cluster of marine wind electric field double-fed fan motor unit.
2. the marine wind electric field optimal reactive power allocation according to claim 1 based on double-fed fan motor unit blower fan topological structure
Method, it is characterised in that：The 1) put in using double-fed fan motor unit as during wind power plant continuous reactive source, the double-fed fan motor unit
Stator side be joined directly together with power network, rotor-side is connected with power network by net side transverter and pusher side transverter, be achieved in turn
The two-way flow of sub- side power, and then realize the variable speed constant frequency operation of double-fed blower fan.
3. the marine wind electric field optimal reactive power allocation according to claim 1 based on double-fed fan motor unit blower fan topological structure
Method, it is characterised in that：The 1) put in control the transverter of double-fed fan motor unit to carry out Reactive-power control, refer to the double-fed fan motor
Unit is by realizing active and idle uneoupled control to converter Control so that double-fed fan motor unit has dynamic regulation nonfunctional
Power.
4. the marine wind electric field optimal reactive power allocation according to claim 1 based on double-fed fan motor unit blower fan topological structure
Method, it is characterised in that：The 1) put in when controlling the transverter of double-fed fan motor unit to carry out Reactive-power control, when net side transverter not
Send the idle reactive power Q sent equal to stator side idle, double-fed fan motor unit is sentS,
QT=QS (3-1)
Double-fed fan motor unit DFIG optimal power curve of pursuit formula approximation can use formula (3-2) to represent：
PT=Kopt(1-s)3 (3-2)
In formula：PTActive power is sent for double-fed fan motor unit DFIG；Proportionality constant when Kopt is optimum speed；S is slip
Rate,
Double-fed fan motor unit (DFIG) is idle limit QTBy stator current IsWith rotor current IrInfluence it is as follows：
<mrow>
<msub>
<mi>Q</mi>
<mi>T</mi>
</msub>
<mo>=</mo>
<mo>&PlusMinus;</mo>
<msqrt>
<mrow>
<msup>
<mrow>
<mo>(</mo>
<mn>3</mn>
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<mi>U</mi>
<mi>s</mi>
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<mi>I</mi>
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</mrow>
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<msup>
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<mi>P</mi>
<mi>T</mi>
</msub>
<mrow>
<mn>1</mn>
<mo>-</mo>
<mi>s</mi>
</mrow>
</mfrac>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
</mrow>
</msqrt>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>3</mn>
<mo>-</mo>
<mn>3</mn>
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</mrow>
</mrow>
<mrow>
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<mi>Q</mi>
<mi>T</mi>
</msub>
<mo>=</mo>
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<mn>3</mn>
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<mi>U</mi>
<mi>s</mi>
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<mi>x</mi>
<mi>s</mi>
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<mo>&PlusMinus;</mo>
<msqrt>
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<mrow>
<mo>(</mo>
<mn>3</mn>
<mo>(</mo>
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<mi>x</mi>
<mi>m</mi>
</msub>
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<msub>
<mi>x</mi>
<mi>s</mi>
</msub>
</mrow>
<mo>)</mo>
<msub>
<mi>U</mi>
<mi>s</mi>
</msub>
<msub>
<mi>I</mi>
<mi>r</mi>
</msub>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
<mo>-</mo>
<msup>
<mrow>
<mo>(</mo>
<mfrac>
<msub>
<mi>P</mi>
<mi>T</mi>
</msub>
<mrow>
<mn>1</mn>
<mo>-</mo>
<mi>s</mi>
</mrow>
</mfrac>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
</mrow>
</msqrt>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>3</mn>
<mo>-</mo>
<mn>4</mn>
<mo>)</mo>
</mrow>
</mrow>
In formula：UsFor stator voltage；xsFor stator reactance；xmFor excitation reactance.
5. the marine wind electric field optimal reactive power allocation according to claim 1 based on double-fed fan motor unit blower fan topological structure
Method, it is characterised in that：It is main to consider that marine wind electric field is idle excellent in the wind power plant Equivalent Model of offshore wind farm system is established
The object function of change and the constraints met；
The target wind function be to reduce active power loss inside marine wind electric field, balanced internal node voltages, reduce purchase from
It is target to be casually arranged with standby cost payout, and its calculation is：
Min F=n1Ploss+n2||ΔVG||2+n3fcost (3-5)
Wherein：For the active loss of system, NiFor circuitry number；gk
For branch road k conductance；ui, ujFor the voltage magnitude of load bus；θijThe phase angle difference of voltage between load bus i, j, | |
ΔVG||2=∑ Δ VGi 2=∑ (VGi-1)2For node voltage departure, VGiFor the perunit value of node voltage, fcost=S1ΔC1+
S2ΔC2For the cost payout of discrete device regulation, S1, Δ C1Cost and regulation variable quantity for buyer capacitor；S2, Δ
C2Adjustment cost and regulation variable quantity for buyer SVC；
n1, n2, n3Active loss index, hub node voltage deviation index and discrete device regulation refer to respectively in object function
Target weight coefficient, weight coefficient are calculated by analytic hierarchy process (AHP) (analytic hierarchy process, AHP)；
The constraints of the active power output and idle output need to meet below equation：
<mrow>
<mfenced open = "{" close = "">
<mtable>
<mtr>
<mtd>
<mrow>
<msub>
<mi>P</mi>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
</msub>
<mo>-</mo>
<msub>
<mi>P</mi>
<mrow>
<mi>D</mi>
<mi>i</mi>
</mrow>
</msub>
<mo>=</mo>
<msub>
<mi>U</mi>
<mi>i</mi>
</msub>
<msubsup>
<mo>&Sigma;</mo>
<mrow>
<mi>j</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>N</mi>
</msubsup>
<msub>
<mi>U</mi>
<mi>j</mi>
</msub>
<mrow>
<mo>(</mo>
<msub>
<mi>G</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
</msub>
<msub>
<mi>cos&theta;</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>B</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
</msub>
<msub>
<mi>sin&theta;</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
</msub>
<mo>)</mo>
</mrow>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<msub>
<mi>Q</mi>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>Q</mi>
<mi>C</mi>
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<mo>-</mo>
<msub>
<mi>Q</mi>
<mrow>
<mi>D</mi>
<mi>i</mi>
</mrow>
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<msub>
<mi>U</mi>
<mi>i</mi>
</msub>
<msubsup>
<mo>&Sigma;</mo>
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<mi>j</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>N</mi>
</msubsup>
<msub>
<mi>U</mi>
<mi>j</mi>
</msub>
<mrow>
<mo>(</mo>
<msub>
<mi>G</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
</msub>
<msub>
<mi>sin&theta;</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>B</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
</msub>
<msub>
<mi>cos&theta;</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
</msub>
<mo>)</mo>
</mrow>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
<mo>,</mo>
<mi>i</mi>
<mo>&Element;</mo>
<mo>&lsqb;</mo>
<mn>1</mn>
<mo>,</mo>
<mi>N</mi>
<mo>&rsqb;</mo>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>3</mn>
<mo>-</mo>
<mn>6</mn>
<mo>)</mo>
</mrow>
</mrow>
In formula：PGi, QGiRespectively generator i active power output and idle output；PDi, QDiRespectively load bus i's is active negative
Lotus power and load or burden without work power；QCFor reactive-load compensation amount；Gij, Bij, θijConductance, susceptance and electricity respectively between node i, j
Press phase angle difference；N is node total number；
In order to ensure safe operation of power system, also to meet following inequality constraints condition：
Control the inequality constraints condition of variable：
<mrow>
<mfenced open = "{" close = "">
<mtable>
<mtr>
<mtd>
<mrow>
<msup>
<msub>
<mi>Q</mi>
<mrow>
<mi>C</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
</msub>
<mi>min</mi>
</msup>
<mo>&le;</mo>
<msub>
<mi>Q</mi>
<mrow>
<mi>C</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
</msub>
<mo>&le;</mo>
<msup>
<msub>
<mi>Q</mi>
<mrow>
<mi>C</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
</msub>
<mi>max</mi>
</msup>
<mo>,</mo>
</mrow>
</mtd>
<mtd>
<mrow>
<mi>i</mi>
<mo>&Element;</mo>
<msub>
<mi>N</mi>
<mi>c</mi>
</msub>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<msup>
<msub>
<mi>Q</mi>
<mrow>
<mi>C</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
</msub>
<mi>min</mi>
</msup>
<mo>&le;</mo>
<msub>
<mi>Q</mi>
<mrow>
<mi>C</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
</msub>
<mo>&le;</mo>
<msup>
<msub>
<mi>Q</mi>
<mrow>
<mi>C</mi>
<mo>,</mo>
<mi>i</mi>
</mrow>
</msub>
<mi>max</mi>
</msup>
<mo>,</mo>
</mrow>
</mtd>
<mtd>
<mrow>
<mi>i</mi>
<mo>&Element;</mo>
<msub>
<mi>N</mi>
<mi>G</mi>
</msub>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>3</mn>
<mo>-</mo>
<mn>7</mn>
<mo>)</mo>
</mrow>
</mrow>
QC, i min, QC, i maxThe upper lower limit value of reactive compensation capacity, N are represented respectivelycFor the set of reactive-load compensation point, QG, i min, QG, i max
Represent that generator i sends the upper lower limit value of reactive power respectively；NGFor generator node set,
The inequality constraints condition of state variable：
Ui min≤Ui≤Ui max, i ∈ NL (3-8)
Ui min, Ui maxThe bound of node i voltage, N are represented respectivelyLRepresent system node set.
6. the marine wind electric field optimal reactive power allocation according to claim 1 based on double-fed fan motor unit blower fan topological structure
Method, it is characterised in that：Carrying out reactive-load compensation method to offshore wind farm cluster using CMO algorithms is：The CMO algorithms are cell membrane
Optimized algorithm, specific algorithm are as follows：
1) initial calculation parameter is set, initializes material group, blower fan is sent in every one-dimensional power system of expression respectively of material solution
Idle and reactive-load compensation point compensation capacity；
2) Load flow calculation is carried out to each material in material group, judges whether the inequality constraints condition for meeting idle work optimization, sieved
Select so that the material of object function minimum is designated as XbestAnd record its value and place algebraically；
3) concentration division is carried out to material group, it is non-fat into high concentration liposoluble substance (FS), high concentration according to concentration division factor
Soluble substance (NS), low concentration material (LS)；The concentration of each material position is calculated, material concentration is arranged from small to large
Sequence, the material for coming preceding 50% is LS, and the material for coming rear 50% is HS, is then FS by the material that odd bits are come in HS,
The material for coming even bit is NS；
The calculation formula of material Y concentration：
<mrow>
<mi>c</mi>
<mi>o</mi>
<mi>n</mi>
<mo>=</mo>
<mfrac>
<mi>n</mi>
<mi>m</mi>
</mfrac>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>3</mn>
<mo>-</mo>
<mn>9</mn>
<mo>)</mo>
</mrow>
</mrow>
In formula：N represents XiDistance in (i=1 ..., m) to Y meets formulaNumber,
M represents material sum, and r is radius factor, generally takes 0.4~0.6, XiI-th of material solution is represented, it is dense that Y represents that needs solve
The material solution of degree；
4) each material free diffusing motion of high concentration liposoluble substance group, low concentration is transferred to by the high concentration side of cell membrane
Side, whole process had not both needed carrier to randomly select a material in low concentration material group LS first also without energy
LSrandiAs target is spread, the unit direction vector of diffusion is calculated：
<mrow>
<mover>
<mi>F</mi>
<mo>&RightArrow;</mo>
</mover>
<mo>=</mo>
<mfrac>
<mrow>
<msup>
<mi>LS</mi>
<mrow>
<mi>r</mi>
<mi>a</mi>
<mi>n</mi>
<mi>d</mi>
<mi>i</mi>
</mrow>
</msup>
<mo>-</mo>
<msup>
<mi>FS</mi>
<mi>i</mi>
</msup>
</mrow>
<mrow>
<mo>|</mo>
<mo>|</mo>
<msup>
<mi>LS</mi>
<mrow>
<mi>r</mi>
<mi>a</mi>
<mi>n</mi>
<mi>d</mi>
<mi>i</mi>
</mrow>
</msup>
<mo>-</mo>
<msup>
<mi>FS</mi>
<mi>i</mi>
</msup>
<mo>|</mo>
<mo>|</mo>
</mrow>
</mfrac>
<mo>=</mo>
<mfrac>
<mrow>
<msup>
<mi>LS</mi>
<mrow>
<mi>r</mi>
<mi>a</mi>
<mi>n</mi>
<mi>d</mi>
<mi>i</mi>
</mrow>
</msup>
<mo>-</mo>
<msup>
<mi>FS</mi>
<mi>i</mi>
</msup>
</mrow>
<msqrt>
<mrow>
<msubsup>
<mo>&Sigma;</mo>
<mrow>
<mi>k</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>n</mi>
</msubsup>
<msup>
<mrow>
<mo>(</mo>
<msubsup>
<mi>LS</mi>
<mi>k</mi>
<mrow>
<mi>r</mi>
<mi>a</mi>
<mi>n</mi>
<mi>d</mi>
<mi>i</mi>
</mrow>
</msubsup>
<mo>-</mo>
<msubsup>
<mi>FS</mi>
<mi>k</mi>
<mi>i</mi>
</msubsup>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
</mrow>
</msqrt>
</mfrac>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>3</mn>
<mo>-</mo>
<mn>10</mn>
<mo>)</mo>
</mrow>
</mrow>
Then, high concentration material FSiIt is diffused by vectorial F direction, obtains new material newFSi：
<mrow>
<msubsup>
<mi>newFS</mi>
<mi>k</mi>
<mi>i</mi>
</msubsup>
<mo>=</mo>
<mfenced open = "{" close = "">
<mtable>
<mtr>
<mtd>
<mrow>
<msubsup>
<mi>FS</mi>
<mi>k</mi>
<mi>i</mi>
</msubsup>
<mo>+</mo>
<mi>r</mi>
<mi>a</mi>
<mi>n</mi>
<mi>d</mi>
<mrow>
<mo>(</mo>
<mi> </mi>
<mo>)</mo>
</mrow>
<mo>*</mo>
<msub>
<mi>F</mi>
<mi>k</mi>
</msub>
<mrow>
<mo>(</mo>
<msub>
<mi>u</mi>
<mi>k</mi>
</msub>
<mo>-</mo>
<msubsup>
<mi>LS</mi>
<mi>k</mi>
<mrow>
<mi>r</mi>
<mi>a</mi>
<mi>n</mi>
<mi>d</mi>
<mi>i</mi>
</mrow>
</msubsup>
<mo>)</mo>
</mrow>
</mrow>
</mtd>
<mtd>
<mrow>
<msub>
<mi>F</mi>
<mi>k</mi>
</msub>
<mo>&GreaterEqual;</mo>
<mn>0</mn>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<msubsup>
<mi>FS</mi>
<mi>k</mi>
<mi>i</mi>
</msubsup>
<mo>+</mo>
<mi>r</mi>
<mi>a</mi>
<mi>n</mi>
<mi>d</mi>
<mrow>
<mo>(</mo>
<mi> </mi>
<mo>)</mo>
</mrow>
<mo>*</mo>
<msub>
<mi>F</mi>
<mi>k</mi>
</msub>
<mrow>
<mo>(</mo>
<msubsup>
<mi>LS</mi>
<mi>k</mi>
<mrow>
<mi>r</mi>
<mi>a</mi>
<mi>n</mi>
<mi>d</mi>
<mi>i</mi>
</mrow>
</msubsup>
<mo>-</mo>
<msub>
<mi>l</mi>
<mi>k</mi>
</msub>
<mo>)</mo>
</mrow>
</mrow>
</mtd>
<mtd>
<mrow>
<msub>
<mi>F</mi>
<mi>k</mi>
</msub>
<mo><</mo>
<mn>0</mn>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
<mo>,</mo>
<mi>k</mi>
<mo>=</mo>
<mn>1</mn>
<mo>,</mo>
<mn>2......</mn>
<mo>,</mo>
<mi>n</mi>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>3</mn>
<mo>-</mo>
<mn>11</mn>
<mo>)</mo>
</mrow>
</mrow>
Each FS is moved in formula (3-11), rand () represents that random movement step-length span is [0,1], FkRepresent to
F kth dimension is measured, after this motion process, by the starting substance group FS, is changed into new material group new FS, new explanation is entered
Row Load flow calculation, judge idle work optimization constraints；Contrasted with original matter solution result, if novel substance solution object function is small
Former solution then is substituted with new explanation in original matter solution object function, otherwise retains former solution, moves locn times, take wherein optimal as FS's
Final position；
5) each material of high concentration non-fat-soluble material group is spread by assisting, and is transferred to by the high concentration side of cell membrane low dense
Side is spent, whole process process needs carrier, it is not necessary to energy, in order to limit the forms of motion of high concentration non-fat-soluble material
System, algorithm introduce carrier factor cfiConcept：
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<msup>
<mi>cf</mi>
<mi>i</mi>
</msup>
<mo>=</mo>
<mfrac>
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<mi>f</mi>
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<msup>
<mi>NS</mi>
<mi>i</mi>
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<mi>min</mi>
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</msub>
<mi>f</mi>
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<mi>NS</mi>
<mi>j</mi>
</msup>
</mrow>
<mo>)</mo>
<mo>)</mo>
</mrow>
</mrow>
<mrow>
<msub>
<mi>max</mi>
<mi>j</mi>
</msub>
<mi>f</mi>
<mrow>
<mo>(</mo>
<mo>(</mo>
<mrow>
<msup>
<mi>NS</mi>
<mi>j</mi>
</msup>
</mrow>
<mo>)</mo>
<mo>)</mo>
</mrow>
<mo>-</mo>
<msub>
<mi>min</mi>
<mi>j</mi>
</msub>
<mi>f</mi>
<mrow>
<mo>(</mo>
<mo>(</mo>
<mrow>
<msup>
<mi>NS</mi>
<mi>j</mi>
</msup>
</mrow>
<mo>)</mo>
<mo>)</mo>
</mrow>
</mrow>
</mfrac>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>3</mn>
<mo>-</mo>
<mn>12</mn>
<mo>)</mo>
</mrow>
</mrow>
If carrier factor cfiMore than certain random number rand () in [0,1], then the material can assist to spread, otherwise, to current
Move in optimal solution direction；
As high concentration non-fat-soluble material NSiWhen meeting carrier condition, high concentration lateral movement to low concentration side is spread locn times, and
Best diffusion position is chosen as final result, randomly selects a material LS in low concentration material group LS firstrandi
As target is spread, the unit direction vector of diffusion is calculated：
<mrow>
<mover>
<mi>F</mi>
<mo>&RightArrow;</mo>
</mover>
<mo>=</mo>
<mfrac>
<mrow>
<msup>
<mi>LS</mi>
<mrow>
<mi>r</mi>
<mi>a</mi>
<mi>n</mi>
<mi>d</mi>
<mi>i</mi>
</mrow>
</msup>
<mo>-</mo>
<msup>
<mi>NS</mi>
<mi>i</mi>
</msup>
</mrow>
<mrow>
<mo>|</mo>
<mo>|</mo>
<msup>
<mi>LS</mi>
<mrow>
<mi>r</mi>
<mi>a</mi>
<mi>n</mi>
<mi>d</mi>
<mi>i</mi>
</mrow>
</msup>
<mo>-</mo>
<msup>
<mi>NS</mi>
<mi>i</mi>
</msup>
<mo>|</mo>
<mo>|</mo>
</mrow>
</mfrac>
<mo>=</mo>
<mfrac>
<mrow>
<msup>
<mi>LS</mi>
<mrow>
<mi>r</mi>
<mi>a</mi>
<mi>n</mi>
<mi>d</mi>
<mi>i</mi>
</mrow>
</msup>
<mo>-</mo>
<msup>
<mi>NS</mi>
<mi>i</mi>
</msup>
</mrow>
<msqrt>
<mrow>
<msubsup>
<mo>&Sigma;</mo>
<mrow>
<mi>k</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>n</mi>
</msubsup>
<msup>
<mrow>
<mo>(</mo>
<msubsup>
<mi>LS</mi>
<mi>k</mi>
<mrow>
<mi>r</mi>
<mi>a</mi>
<mi>n</mi>
<mi>d</mi>
<mi>i</mi>
</mrow>
</msubsup>
<mo>-</mo>
<msubsup>
<mi>NS</mi>
<mi>k</mi>
<mi>i</mi>
</msubsup>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
</mrow>
</msqrt>
</mfrac>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>3</mn>
<mo>-</mo>
<mn>13</mn>
<mo>)</mo>
</mrow>
</mrow>
Then, high concentration non-fat-soluble material NSiIt is diffused by vectorial F direction, obtains new material newNSi：
<mrow>
<msubsup>
<mi>newNS</mi>
<mi>k</mi>
<mi>i</mi>
</msubsup>
<mo>=</mo>
<mfenced open = "{" close = "">
<mtable>
<mtr>
<mtd>
<mrow>
<msubsup>
<mi>NS</mi>
<mi>k</mi>
<mi>i</mi>
</msubsup>
<mo>+</mo>
<mi>r</mi>
<mi>a</mi>
<mi>n</mi>
<mi>d</mi>
<mrow>
<mo>(</mo>
<mi> </mi>
<mo>)</mo>
</mrow>
<mo>*</mo>
<msub>
<mi>F</mi>
<mi>k</mi>
</msub>
<mrow>
<mo>(</mo>
<msub>
<mi>u</mi>
<mi>k</mi>
</msub>
<mo>-</mo>
<msubsup>
<mi>LS</mi>
<mi>k</mi>
<mrow>
<mi>r</mi>
<mi>a</mi>
<mi>n</mi>
<mi>d</mi>
<mi>i</mi>
</mrow>
</msubsup>
<mo>)</mo>
</mrow>
</mrow>
</mtd>
<mtd>
<mrow>
<msub>
<mi>F</mi>
<mi>k</mi>
</msub>
<mo>&GreaterEqual;</mo>
<mn>0</mn>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<msubsup>
<mi>NS</mi>
<mi>k</mi>
<mi>i</mi>
</msubsup>
<mo>+</mo>
<mi>r</mi>
<mi>a</mi>
<mi>n</mi>
<mi>d</mi>
<mrow>
<mo>(</mo>
<mi> </mi>
<mo>)</mo>
</mrow>
<mo>*</mo>
<msub>
<mi>F</mi>
<mi>k</mi>
</msub>
<mrow>
<mo>(</mo>
<msubsup>
<mi>LS</mi>
<mi>k</mi>
<mrow>
<mi>r</mi>
<mi>a</mi>
<mi>n</mi>
<mi>d</mi>
<mi>i</mi>
</mrow>
</msubsup>
<mo>-</mo>
<msub>
<mi>l</mi>
<mi>k</mi>
</msub>
<mo>)</mo>
</mrow>
</mrow>
</mtd>
<mtd>
<mrow>
<msub>
<mi>F</mi>
<mi>k</mi>
</msub>
<mo><</mo>
<mn>0</mn>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
<mo>,</mo>
<mi>k</mi>
<mo>=</mo>
<mn>1</mn>
<mo>,</mo>
<mn>2......</mn>
<mo>,</mo>
<mi>n</mi>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>3</mn>
<mo>-</mo>
<mn>14</mn>
<mo>)</mo>
</mrow>
</mrow>
As high concentration non-fat-soluble material NSiWhen being unsatisfactory for carrier condition, it is to current optimal material XbestSpread locn in direction
It is secondary, and best diffusion position is chosen as final result：
<mrow>
<msubsup>
<mi>newNS</mi>
<mi>k</mi>
<mi>t</mi>
</msubsup>
<mo>=</mo>
<msubsup>
<mi>NS</mi>
<mi>k</mi>
<mi>t</mi>
</msubsup>
<mo>+</mo>
<mi>r</mi>
<mi>a</mi>
<mi>n</mi>
<mi>d</mi>
<mrow>
<mo>(</mo>
<mi> </mi>
<mo>)</mo>
</mrow>
<mo>*</mo>
<mrow>
<mo>(</mo>
<msup>
<mi>X</mi>
<mrow>
<mi>b</mi>
<mi>e</mi>
<mi>s</mi>
<mi>t</mi>
</mrow>
</msup>
<mo>-</mo>
<msubsup>
<mi>NS</mi>
<mi>k</mi>
<mi>i</mi>
</msubsup>
<mo>)</mo>
</mrow>
<mo>,</mo>
<mi>k</mi>
<mo>=</mo>
<mn>1</mn>
<mo>,</mo>
<mn>2</mn>
<mo>...</mo>
<mo>...</mo>
<mo>,</mo>
<mi>n</mi>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>3</mn>
<mo>-</mo>
<mn>15</mn>
<mo>)</mo>
</mrow>
</mrow>
6) low concentration material is transferred to high concentration side by active transport from the low concentration side of cell membrane, and whole process both needs to carry
Body, it is also desirable to which energy, in order to limit the forms of motion of low concentration material, algorithm introduces energy factors efiWith carrier because
Sub- cfiConcept：
<mrow>
<msup>
<mi>ef</mi>
<mi>i</mi>
</msup>
<mo>=</mo>
<mfrac>
<mrow>
<msub>
<mi>max</mi>
<mi>j</mi>
</msub>
<mi>f</mi>
<mrow>
<mo>(</mo>
<mo>(</mo>
<mrow>
<msup>
<mi>LS</mi>
<mi>j</mi>
</msup>
</mrow>
<mo>)</mo>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mi>f</mi>
<mrow>
<mo>(</mo>
<msup>
<mi>LS</mi>
<mi>i</mi>
</msup>
<mo>)</mo>
</mrow>
</mrow>
<mrow>
<msub>
<mi>max</mi>
<mi>j</mi>
</msub>
<mi>f</mi>
<mrow>
<mo>(</mo>
<mo>(</mo>
<mrow>
<msup>
<mi>LS</mi>
<mi>j</mi>
</msup>
</mrow>
<mo>)</mo>
<mo>)</mo>
</mrow>
<mo>-</mo>
<msub>
<mi>min</mi>
<mi>j</mi>
</msub>
<mi>f</mi>
<mrow>
<mo>(</mo>
<mo>(</mo>
<mrow>
<msup>
<mi>LS</mi>
<mi>j</mi>
</msup>
</mrow>
<mo>)</mo>
<mo>)</mo>
</mrow>
</mrow>
</mfrac>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>3</mn>
<mo>-</mo>
<mn>16</mn>
<mo>)</mo>
</mrow>
</mrow>
<mrow>
<msup>
<mi>cf</mi>
<mi>i</mi>
</msup>
<mo>=</mo>
<mfrac>
<mrow>
<mi>f</mi>
<mrow>
<mo>(</mo>
<msup>
<mi>LS</mi>
<mi>i</mi>
</msup>
<mo>)</mo>
</mrow>
<mo>-</mo>
<msub>
<mi>min</mi>
<mi>j</mi>
</msub>
<mi>f</mi>
<mrow>
<mo>(</mo>
<mo>(</mo>
<mrow>
<msup>
<mi>LS</mi>
<mi>j</mi>
</msup>
</mrow>
<mo>)</mo>
<mo>)</mo>
</mrow>
</mrow>
<mrow>
<msub>
<mi>max</mi>
<mi>j</mi>
</msub>
<mi>f</mi>
<mrow>
<mo>(</mo>
<mo>(</mo>
<mrow>
<msup>
<mi>LS</mi>
<mi>j</mi>
</msup>
</mrow>
<mo>)</mo>
<mo>)</mo>
</mrow>
<mo>-</mo>
<msub>
<mi>min</mi>
<mi>j</mi>
</msub>
<mi>f</mi>
<mrow>
<mo>(</mo>
<mo>(</mo>
<mrow>
<msup>
<mi>LS</mi>
<mi>j</mi>
</msup>
</mrow>
<mo>)</mo>
<mo>)</mo>
</mrow>
</mrow>
</mfrac>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>3</mn>
<mo>-</mo>
<mn>17</mn>
<mo>)</mo>
</mrow>
</mrow>
If energy factors efiMore than certain random number rand () in [0,1], then the material meets energy condition, if the carrier factor
cfiMore than certain random number rand () in [0,1], then the material meets carrier condition, for certain low concentration material LSi, first
Judge whether it meets energy condition, then judge whether it meets carrier condition；
As low concentration material LSiWhen being unsatisfactory for energy condition, random motion locn times in the region of search of material is chosen best
Final result of the position as the material：
<mrow>
<mi>new</mi>
<msubsup>
<mi>LS</mi>
<mi>k</mi>
<mi>i</mi>
</msubsup>
<mo>=</mo>
<msub>
<mi>l</mi>
<mi>k</mi>
</msub>
<mo>+</mo>
<mi>rand</mi>
<mrow>
<mo>(</mo>
<mo>)</mo>
</mrow>
<mo>*</mo>
<mrow>
<mo>(</mo>
<msub>
<mi>u</mi>
<mi>k</mi>
</msub>
<mo>-</mo>
<msub>
<mi>l</mi>
<mi>k</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>,</mo>
<mi>k</mi>
<mo>=</mo>
<mn>1,2</mn>
<mo>.</mo>
<mo>.</mo>
<mo>.</mo>
<mo>.</mo>
<mo>.</mo>
<mo>.</mo>
<mo>,</mo>
<mi>n</mi>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>3</mn>
<mo>-</mo>
<mn>18</mn>
<mo>)</mo>
</mrow>
</mrow>
As low concentration material LSiWhen both having met energy condition or having met carrier condition, active transport can be now carried out, it is to height
Concentration X Substance HS (i.e. high concentration liposoluble substance FS and high concentration non-fat-soluble material NS summation) direction is moved locn times, and
Choose the best position result final as its；
First, a material HS is randomly selected in high concentration material group HSrandiAs target is spread, the unit side of diffusion is calculated
To vector：
<mrow>
<mover>
<mi>F</mi>
<mo>&RightArrow;</mo>
</mover>
<mo>=</mo>
<mfrac>
<mrow>
<msup>
<mi>HS</mi>
<mrow>
<mi>r</mi>
<mi>a</mi>
<mi>n</mi>
<mi>d</mi>
<mi>i</mi>
</mrow>
</msup>
<mo>-</mo>
<msup>
<mi>LS</mi>
<mi>i</mi>
</msup>
</mrow>
<mrow>
<mo>|</mo>
<mo>|</mo>
<msup>
<mi>HS</mi>
<mrow>
<mi>r</mi>
<mi>a</mi>
<mi>n</mi>
<mi>d</mi>
<mi>i</mi>
</mrow>
</msup>
<mo>-</mo>
<msup>
<mi>LS</mi>
<mi>i</mi>
</msup>
<mo>|</mo>
<mo>|</mo>
</mrow>
</mfrac>
<mo>=</mo>
<mfrac>
<mrow>
<msup>
<mi>HS</mi>
<mrow>
<mi>r</mi>
<mi>a</mi>
<mi>n</mi>
<mi>d</mi>
<mi>i</mi>
</mrow>
</msup>
<mo>-</mo>
<msup>
<mi>LS</mi>
<mi>i</mi>
</msup>
</mrow>
<msqrt>
<mrow>
<msubsup>
<mo>&Sigma;</mo>
<mrow>
<mi>k</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>n</mi>
</msubsup>
<msup>
<mrow>
<mo>(</mo>
<msubsup>
<mi>HS</mi>
<mi>k</mi>
<mrow>
<mi>r</mi>
<mi>a</mi>
<mi>n</mi>
<mi>d</mi>
<mi>i</mi>
</mrow>
</msubsup>
<mo>-</mo>
<msubsup>
<mi>LS</mi>
<mi>k</mi>
<mi>i</mi>
</msubsup>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
</mrow>
</msqrt>
</mfrac>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>3</mn>
<mo>-</mo>
<mn>19</mn>
<mo>)</mo>
</mrow>
</mrow>
Secondly, low concentration material LSiIt is diffused by vectorial F direction, obtains new material newLSi：
<mrow>
<msubsup>
<mi>newLS</mi>
<mi>k</mi>
<mi>i</mi>
</msubsup>
<mo>=</mo>
<mfenced open = "{" close = "">
<mtable>
<mtr>
<mtd>
<mrow>
<msubsup>
<mi>LS</mi>
<mi>k</mi>
<mi>i</mi>
</msubsup>
<mo>+</mo>
<mi>r</mi>
<mi>a</mi>
<mi>n</mi>
<mi>d</mi>
<mrow>
<mo>(</mo>
<mi> </mi>
<mo>)</mo>
</mrow>
<mo>*</mo>
<msub>
<mi>F</mi>
<mi>k</mi>
</msub>
<mrow>
<mo>(</mo>
<msub>
<mi>u</mi>
<mi>k</mi>
</msub>
<mo>-</mo>
<msubsup>
<mi>HS</mi>
<mi>k</mi>
<mrow>
<mi>r</mi>
<mi>a</mi>
<mi>n</mi>
<mi>d</mi>
<mi>i</mi>
</mrow>
</msubsup>
<mo>)</mo>
</mrow>
</mrow>
</mtd>
<mtd>
<mrow>
<msub>
<mi>F</mi>
<mi>k</mi>
</msub>
<mo>&GreaterEqual;</mo>
<mn>0</mn>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<msubsup>
<mi>LS</mi>
<mi>k</mi>
<mi>i</mi>
</msubsup>
<mo>+</mo>
<mi>r</mi>
<mi>a</mi>
<mi>n</mi>
<mi>d</mi>
<mrow>
<mo>(</mo>
<mi> </mi>
<mo>)</mo>
</mrow>
<mo>*</mo>
<msub>
<mi>F</mi>
<mi>k</mi>
</msub>
<mrow>
<mo>(</mo>
<msubsup>
<mi>HS</mi>
<mi>k</mi>
<mrow>
<mi>r</mi>
<mi>a</mi>
<mi>n</mi>
<mi>d</mi>
<mi>i</mi>
</mrow>
</msubsup>
<mo>-</mo>
<msub>
<mi>l</mi>
<mi>k</mi>
</msub>
<mo>)</mo>
</mrow>
</mrow>
</mtd>
<mtd>
<mrow>
<msub>
<mi>F</mi>
<mi>k</mi>
</msub>
<mo><</mo>
<mn>0</mn>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
<mo>,</mo>
<mi>k</mi>
<mo>=</mo>
<mn>1</mn>
<mo>,</mo>
<mn>2......</mn>
<mo>,</mo>
<mi>n</mi>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>3</mn>
<mo>-</mo>
<mn>20</mn>
<mo>)</mo>
</mrow>
</mrow>
If low concentration material LSiMeet energy condition and be unsatisfactory for carrier strip part, then make it to current optimal material XbestDirection is expanded
Dissipate locn times, and choose best position as final result：
<mrow>
<msubsup>
<mi>newLS</mi>
<mi>k</mi>
<mi>i</mi>
</msubsup>
<mo>=</mo>
<msubsup>
<mi>LS</mi>
<mi>k</mi>
<mi>i</mi>
</msubsup>
<mo>+</mo>
<mi>r</mi>
<mi>a</mi>
<mi>n</mi>
<mi>d</mi>
<mrow>
<mo>(</mo>
<mi> </mi>
<mo>)</mo>
</mrow>
<mo>*</mo>
<mrow>
<mo>(</mo>
<msup>
<mi>X</mi>
<mrow>
<mi>b</mi>
<mi>e</mi>
<mi>x</mi>
<mi>t</mi>
</mrow>
</msup>
<mo>-</mo>
<msubsup>
<mi>LS</mi>
<mi>k</mi>
<mi>i</mi>
</msubsup>
<mo>)</mo>
</mrow>
<mo>,</mo>
<mi>k</mi>
<mo>=</mo>
<mn>1</mn>
<mo>,</mo>
<mn>2</mn>
<mo>...</mo>
<mo>...</mo>
<mo>,</mo>
<mi>n</mi>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>3</mn>
<mo>-</mo>
<mn>21</mn>
<mo>)</mo>
</mrow>
</mrow>
7) all substances solution is updated replacement, judges whether to meet iterations requirement, optimal material is exported if meeting
Solution, and by optimal material solution object function of each generation and the images outputting of optimal solution movement locus；If not satisfied, then from second step after
Continuous iteration.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN108092277A (en) * | 2018-01-19 | 2018-05-29 | 国网江西省电力有限公司上饶供电分公司 | Active distribution network voltage control method for coordinating based on cell membrane optimization |
| CN108460228A (en) * | 2018-03-21 | 2018-08-28 | 电子科技大学 | A method of it is equivalent that wind power plant being carried out based on multi-objective optimization algorithm |
| CN108899941A (en) * | 2018-07-13 | 2018-11-27 | 中国电力科学研究院有限公司 | A kind of offshore wind farm multi-objective reactive optimization configuration method and system that soft direct sending goes out |
| CN108964127A (en) * | 2018-07-27 | 2018-12-07 | 西安交通大学 | A kind of control method of dual feedback wind power generation system fault traversing |
| CN111799812A (en) * | 2020-07-17 | 2020-10-20 | 广东电网有限责任公司电力科学研究院 | Offshore wind farm reactive power coordination control method based on reactive voltage sensitivity |
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| CN108460228B (en) * | 2018-03-21 | 2021-06-04 | 电子科技大学 | Wind power plant equivalence method based on multi-objective optimization algorithm |
| CN108899941A (en) * | 2018-07-13 | 2018-11-27 | 中国电力科学研究院有限公司 | A kind of offshore wind farm multi-objective reactive optimization configuration method and system that soft direct sending goes out |
| CN108964127A (en) * | 2018-07-27 | 2018-12-07 | 西安交通大学 | A kind of control method of dual feedback wind power generation system fault traversing |
| CN108964127B (en) * | 2018-07-27 | 2020-03-13 | 西安交通大学 | Control method for fault ride-through of double-fed wind power generation system |
| CN111799812A (en) * | 2020-07-17 | 2020-10-20 | 广东电网有限责任公司电力科学研究院 | Offshore wind farm reactive power coordination control method based on reactive voltage sensitivity |
| CN111799812B (en) * | 2020-07-17 | 2023-08-01 | 广东电网有限责任公司电力科学研究院 | Reactive voltage sensitivity-based reactive coordination control method for offshore wind farm |
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