CN103441537B - Distributing wind power plant active optimization regulation and control method equipped with energy-accumulating power station - Google Patents

Distributing wind power plant active optimization regulation and control method equipped with energy-accumulating power station Download PDF

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CN103441537B
CN103441537B CN201310241773.4A CN201310241773A CN103441537B CN 103441537 B CN103441537 B CN 103441537B CN 201310241773 A CN201310241773 A CN 201310241773A CN 103441537 B CN103441537 B CN 103441537B
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mrow
msub
power
wind
mtd
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CN103441537A (en
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邢作霞
王文杰
杨俊友
刘劲松
李玉婷
姜立兵
崔嘉
王海鑫
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State Grid Corp of China SGCC
Shenyang University of Technology
Electric Power Research Institute of State Grid Liaoning Electric Power Co Ltd
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State Grid Corp of China SGCC
Shenyang University of Technology
Electric Power Research Institute of State Grid Liaoning Electric Power Co Ltd
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Priority to PCT/CN2014/000576 priority patent/WO2014201849A1/en
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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
    • H02J3/48—Controlling the sharing of the in-phase component
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
    • F03D—WIND MOTORS
    • F03D7/00—Controlling wind motors 
    • F03D7/02—Controlling wind motors  the wind motors having rotation axis substantially parallel to the air flow entering the rotor
    • F03D7/028—Controlling wind motors  the wind motors having rotation axis substantially parallel to the air flow entering the rotor controlling wind motor output power
    • F03D7/0284—Controlling wind motors  the wind motors having rotation axis substantially parallel to the air flow entering the rotor controlling wind motor output power in relation to the state of the electric grid
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
    • F03D—WIND MOTORS
    • F03D7/00—Controlling wind motors 
    • F03D7/02—Controlling wind motors  the wind motors having rotation axis substantially parallel to the air flow entering the rotor
    • F03D7/04—Automatic control; Regulation
    • F03D7/042—Automatic control; Regulation by means of an electrical or electronic controller
    • F03D7/048—Automatic control; Regulation by means of an electrical or electronic controller controlling wind farms
    • 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
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • 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
    • H02J3/381—Dispersed generators
    • 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
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
    • F05B—INDEXING SCHEME RELATING TO WIND, SPRING, WEIGHT, INERTIA OR LIKE MOTORS, TO MACHINES OR ENGINES FOR LIQUIDS COVERED BY SUBCLASSES F03B, F03D AND F03G
    • F05B2270/00—Control
    • F05B2270/10—Purpose of the control system
    • F05B2270/20—Purpose of the control system to optimise the performance of a machine
    • 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
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/28—The renewable source being wind energy
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • 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
    • Y02E10/72—Wind turbines with rotation axis in wind direction
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • 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
    • Y02E10/76—Power conversion electric or electronic aspects
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E70/00—Other energy conversion or management systems reducing GHG emissions
    • Y02E70/30—Systems combining energy storage with energy generation of non-fossil origin

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  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Sustainable Development (AREA)
  • Sustainable Energy (AREA)
  • Chemical & Material Sciences (AREA)
  • Combustion & Propulsion (AREA)
  • Mechanical Engineering (AREA)
  • General Engineering & Computer Science (AREA)
  • Wind Motors (AREA)
  • Control Of Eletrric Generators (AREA)
  • Supply And Distribution Of Alternating Current (AREA)

Abstract

The present invention relates to a kind of distributing wind power plant active optimization equipped with energy-accumulating power station to regulate and control method, the bound constraint and monomer power generation minimax limit value that it is counted and wind-powered electricity generation networking directive/guide exports active power set constraints and according to wind-powered electricity generation and accumulation power supply monomer power generation characteristics, establish active power output constraint condition.For the external condition of wind power plant operation, it is divided into ration the power supply operation and operation of not rationing the power supply, operation of rationing the power supply is with pitch control load and loss minimization, the minimum optimization aim of frequency fluctuation；Operation do not ration the power supply with maximal wind-energy capture efficiency and loss minimization, the minimum optimization aim of frequency fluctuation, using objective layered optimization problem as object function.Solved using particle cluster algorithm.The active power for wind power loss that this research to export by energy-storage system effect, which minimizes, stablizes output, realizes that energy-storage system is connected with the effective of existing dispatching running way with this, while reach optimum economic benefit.

Description

Distributing wind power plant active optimization regulation and control method equipped with energy-accumulating power station
Technical field
The present invention relates to a kind of distributing wind power plant active optimization equipped with energy-accumulating power station to regulate and control method, belongs to wind power plant simultaneously Network operation active power controller technical field.
Background technology
With great attention of the country to renewable energy power generation, China's wind-powered electricity generation has become Optimization of Energy Structure and promotion can The important new industry of sustainable development.But with large-scale wind power it is grid-connected after, the security of electric system, reliability, electricity Energy quality and dispatching of power netwoks can all be influenced be subject to wind-power electricity generation fluctuation and randomness.Centralized bulk power grid has close coupling Property, and track change with being unable to flexibility and reliability.And distributing access Wind Power Project refer to be located at power load immediate vicinity, not with For the purpose of extensive long-distance sand transport electric power, caused electric power accesses power grid nearby, and in the Wind Power Project of locality consumption.It It can preferably solve the problems, such as that centralization is wind power-generating grid-connected caused.In this context, country proposes development point Dissipate the policy of formula wind-powered electricity generation.
Distributing wind power plant equipped with energy-accumulating power station, which is directly accessed low-voltage network, can reduce transmission losses and investment Expense, improves the power supply reliability of power distribution network, largely ensures energy security.Electric energy matter is exported however as to wind power plant Amount, saving energy and decreasing loss and electricity net safety stable requirement improve increasingly, have by carrying out to the distributing wind power plant equipped with energy-accumulating power station Work(optimizes the research with operation problem, is the most effective means for reducing grid loss and ensureing power grid operation.By to having Work(power supply（Wind turbine and energy-accumulating power station）Reasonable disposition and active loss Reasonable Regulation And Control, mains frequency fluctuation can be reduced, subtracted Few electric network active loss, so that electric system being capable of safe and stable operation.
For the real power control and optimizing research of wind power plant, it has been proposed that many optimization methods.It is proposed separate unit wind turbine Group can carry out the active power coordination control strategy between each Wind turbines in high wind speed, middle wind speed and low wind speed stage, carry High wind power plant power generation margin；It is proposed a kind of a kind of wind-powered electricity generation field control method using fan rotor kinetic energy as energy accumulating device, To reduce energy fluctuation in short-term, wind farm grid-connected stability is improved；Consider the closest with output-power fluctuation relation Unit, and contribute and be controlled to suppress the fluctuation etc. contributed to it.These methods can realize the active optimization of wind field.
But the distributing active optimization problem equipped with energy-accumulating power station is directed to, research both domestic and external is seldom now.It is and above-mentioned Optimization method does not account for the multidimensional function relation between the active power that Wind turbines send and its own loss, therefore nothing Method is meeting to make wind power generating set overall losses reach minimum in grid entry point frequency fluctuation safe range as far as possible.
The content of the invention
Goal of the invention
The present invention provides a kind of distributing wind power plant active optimization regulation and control method equipped with energy-accumulating power station, and the purpose is to solve The problem of wind power generating set overall losses are excessive in grid entry point frequency fluctuation safe range present in conventional mode, its pin The service conditions different to wind field establish multiple objective function, while effectively control frequency fluctuation, additionally it is possible to reduce wind turbine change Paddle load, reduces wind power plant active loss.
Technical solution
A kind of control method of the distributing active power of wind power field equipped with energy-accumulating power station, it is characterised in that：Its step is such as Under：
The first step, wind field wind speed, rotation speed of fan, each unit wattful power are measured by SCADA detections control and acquisition system Rate, transformer substation side active power, unit and enter net side three-phase voltage, electric current, frequency, power factor, energy-storage system charge and discharge electric work Then these data are sent control centre by rate and grid entry point power quality data by communication cable；
Second step, set wind power swing and unit output constraints as:
Pi,min≤Pi≤Pi,max（1）
（1）Formula constrains for unit output bound；（2）Formula for consider energy-storage system wind power fluctuation range about Beam, in the time window of 1min or 30min, the amplitude of variation of system synthesis output power must be total no more than wind power plant specified defeated Go out power pratedγ1Or γ30, γ1With γ30Provided by Grid code, the amplitude of variation of system synthesis output power is maximum Value subtracts the difference of minimum value；
3rd step, passes through the fan outlet voltage U measured in real timef, overhead transmission line electric current I, case change no-load loss rate With proportion of goods damageds β under nominal load1、β2, obtain the circuit total losses P in wind fieldL, it is collated obtain for：
Wherein c1,c2,c3It is as follows for coefficient, expression formula：
Wherein：A is power output coefficient；N is wind turbine number；PeFor every Fans rated capacity；I is overhead transmission line electric current Value；R is overhead line resistance per unit length value；L is the length of each bar circuit of overhead line；N1For fan outlet cable bar number；StFor case Varying capacity；rcFor the resistance value of cable unit length；LcFor cable line length；
4th step, calculates two other optimization aim：Feather pneumatic drag coefficient Cd, grid entry point frequency fluctuation Δ f：
Δ p is the active power output for needing to adjust；pbcThe active power output under operating status is unloaded for Wind turbines；fb, fcFor The Wind turbines of setting are not involved in the frequency upper limit value and lower limit value of frequency modulation；fa, fdFor the upper and lower limit of the Wind turbines frequency modulation section of setting Value；pdFor fdThe corresponding active power output of point；
Wherein：β is propeller pitch angle, α is inflow angle, is measurable data；
5th step, for the external condition of wind power plant operation, is divided into ration the power supply operation and operation of not rationing the power supply, both of these case is most Wind power plant active power output adjustment is all carried out afterwards, and obtained optimization aim above is brought into object function；
Ration the power supply situation：Optimization aim is frequency fluctuation the Δ f and P of grid entry pointL.WhenWhen, Pref To dispatch the active output valve of given wind field, pitch control Δ β need to be carried out, optimization aim need to increase feather aerodynamic drag system at this time Number Cd, object function is as follows at this time：
Do not ration the power supply situation：When wind speed υ is less than rated wind speed υrWhen, maximal power tracing is carried out to wind turbine and controls MPPT, it is excellent Change target Δ f and PL；When wind speed υ is less than or equal to rated wind speed υrWhen, pitch control, optimization aim C are carried out to wind turbined, Δ f And PL；
Wherein：h1,h2,h3And l1,l2,l3Weight coefficient when respectively rationing the power supply and not rationing the power supply,
Constraints is：
Δf≤Δfbc（11）
（11）Frequency fluctuation range constraint, Δ fbcFor frequency shift (FS) limit value；（12）Power grid power supply Constraints of Equilibrium, PDBorn to be total The demand of lotus；
6th step, multiple target active optimization is carried out with the vehicle routing optimization algorithm based on population.
For above-mentioned Multiobjective Optimal Control Problems, search is iterated using particle swarm optimization algorithm, seeks optimal solution, walked It is rapid as follows：
①:Input fan outlet voltage, power factor, main transformer parameter and actual input power, virtual voltage with The ratio of rated voltage, case become the parameters such as the proportion of goods damageds under no-load loss rate and nominal load, propeller pitch angle, inflow angle.Calculate wind field Interior circuit total losses, frequency fluctuation and resistance coefficient；
②:Dimension, maximum iteration and population are set；
③:Bring the result obtained in step1 into formula（9）（10）In, obtain fitness value fminMake fminEqual to current The position p of particleid (t)；
④:Initialized location and speed, calculate the position p of individual optimal particleid (t), and by this pid (t)It is set to The position p for global optimum's particle that population currently searches outgd (t)；
⑤:If current particle fitness value is less than individual extreme value, current individual extreme value p is updatedibest；
⑥:If current particle fitness value is less than global extremum, current global extremum p is updatedgbest；
⑦:By formula（25）（26）Renewal speed vector and position vector；
Vid (t+1)=wVid (t)+c1r1·(pid (t)-Xid (t))+c2r2·(pgd (t)-Xid (t)) i=1,2 ..., n（25）
Xid (t+1)=Xid (t)+Vid (t+1),Xid min≤Xid (t)≤Xid maxI=1,2 ..., n（26）
T is current cycle time in formula；c1、c2For particle weights coefficient；ω is inertia weight；r1、r2For（0,1）It is interior equal Even distribution random numbers；Vid、XidFor the Position And Velocity of i-th dimension particle；
Step8:Fitness value is calculated with the velocity vector after renewal and position vector；
Step9:Repeat step5 to step7；
Step10:Judge iterations, satisfaction then exports result；Otherwise Step7 is returned to.
Advantage and effect
The present invention is directed to the exterior operation characteristic of the distributing wind power plant equipped with energy-accumulating power station, it is proposed that under operating condition Multiple target active optimization method, i.e. the distributing wind power plant active optimization regulation and control method equipped with energy-accumulating power station：Judging wind power plant is It is no to be run in the case of rationing the power supply, carry out multiobjective optimal control according to wind conditions.
（1）Required data are measured by SCADA system, these data are then sent into control centre by communication cable.
（2）Set wind power swing and unit output constraints.
（3）Calculate case and become nominal load loss Pn, case change no-load loss P0, electricity that fan outlet is connected with case low pressure side Cable line loss P1, each bar line power loss Ploss.The collated circuit total losses P obtained in wind fieldL。
（4）Calculate two other optimization aim：Feather pneumatic drag coefficient Cd, grid entry point frequency fluctuation Δ f.
（5）For the external condition of wind power plant operation, it is divided into rationing the power supply and operation and does not ration the power supply operation, both of these case all finally Carry out wind power plant active power output adjustment.Multi objective control is carried out according to wind conditions, obtained optimization aim above is brought into In object function.
（6）Multiple target active optimization is carried out with the vehicle routing optimization algorithm based on population.
Particularly advantage of the invention is as follows with good effect：
1st, according to wind field service condition and wind conditions, establish multiple objective function by different level, by adjust line loss, frequency, The variables such as load carry out the regulation and control of active power.
2nd, this control method is being pacified by wind-powered electricity generation permeability based in the range of power distribution network is set in guarantee power swing Premised in line range for the national games, the stability of system is improved.
3rd, it is highly practical, the adjusting of active power is carried out available for the multi objective control of whole distributing wind power plant, with Realize that the active loss of whole wind field minimizes.
Brief description of the drawings
Fig. 1 energy storage proportioning wind-powered electricity generation disperses to access power grid typical topology figure；
The active hierarchy optimization control strategy flow chart of Fig. 2 wind fields；
Fig. 3 variable pitches effect is with wind speed change curve;
The resistance curve of Fig. 4 aerofoil profiles;
Fig. 5 is that maximal power tracing optimal control principle schematic is in Fig. 2；
Flow charts of the Fig. 6 based on particle cluster algorithm.
Embodiment：
The present invention will be further described below in conjunction with the accompanying drawings.
As shown in Figure 1, control object proposed by the present invention is：Wind turbines and energy-accumulating power station converge together accesses 10kV Local substation circuit, then accesses public access point by 10kV/35kV（PCC/1）；With in regional power grid, also having, m is a same The wind electricity storage station of original mold formula, converge 35kV after be delivered to different terminal user's loads；35kV accesses public big electricity after can boosting Net.
The basic ideas of the present invention are：Frequency fluctuation, variable pitch load and the line of power grid can be optimized by Optimum Regulation Path loss consumes, and reduces the active loss of power grid, and improves quality of voltage, is safely and reliably run using electric equipment.
The active optimization problem considered in the present invention, can be defined as follows:By various regulating measures, meeting frequency Under conditions of constraint and operation constraint, make object function optimal.Therefore active optimization problem is actually one typical The combinatorial optimization problem of belt restraining.
A kind of distributing wind power plant active optimization equipped with energy-accumulating power station regulates and controls method, as shown in Fig. 2, it the step of such as Under：
The first step, wind field wind speed, rotation speed of fan, each unit wattful power are measured by SCADA detections control and acquisition system Rate, transformer substation side active power and enter net side three-phase voltage, frequency at unit, power factor, energy-storage system charge-discharge electric power, and Then these data are sent control centre by site power quality data by communication cable.
Second step, set wind power swing and unit output constraints as:
1st, unit output bound constrains：
Pi,min≤Pi≤Pi,max（1）
P in formulai,min, Pi,maxThe respectively minimum value and maximum of unit output.
2nd, the power swing range constraint of energy-storage system is considered：
When energy-storage system responds charge-discharge electric power command value, can obtain：
PO(k+1)=PW(k)+PB(k) （2）
PO(k) it is the synthesis output power at current time；PW(k) wind power for being current time k；PB(k) it is energy storage system The charge-discharge electric power of system.
The energy that energy-storage system stores at current time is：
EB(0) it is the primary power of energy-storage system.
P is taken respectivelyO(k) and EB(k) it is state variable x1(k) and x2(k), PW(k) it is considered as external disturbance variable r (k), PB (k) input quantity u (k), the then state-space model for stabilizing undulated control system are as follows in order to control：
In formula：Y (k) is the output of process matrix.
Common M moment, wherein k=0,1 ..., M-1.
In the time window of any 1min, the amplitude of variation of system synthesis output power（Maximum subtracts the difference of minimum value）Must The total rated output power p of wind power plant must be not more thanratedγ1；In the time window of any 30min, system synthesis output power Amplitude of variation must be not more than the total rated output power p of wind power plantratedγ30, γ1With γ30Provided by Grid code.
3rd step, the collection electric line of wind power plant is divided into cable collection electric line and overhead line collection electric line, relative to thermal power plant For, the collection electric line of wind power plant is increasingly complex, the power distribution network small-sized close to one.Pass through this between wind turbine and booster stations During a small-sized power distribution network transimission power, the line loss that can not be ignored can be produced, and thermal power plant can not examine during operation Consider these losses.Active power loss calculating is carried out to cable and aerial two kinds of current collection Decision Making of Line Schemes.
Calculate case and become nominal load loss Pn, case change no-load loss P0, cable that fan outlet is connected with case low pressure side Path loss consumes P1, each bar line power loss Ploss.The collated circuit total losses P obtained in wind fieldL。
PlossIt is lost for each bar line power：
Ploss=3 × I2× R=3 × I2×r×L （7）
Wherein：I is line current；R is unit length resistance value；L is the length of each bar circuit.
P1The cable run loss being connected for fan outlet with case low pressure side：
Wherein：A is power output coefficient；PeFor every Fans rated capacity；N is wind turbine sum；N1For fan outlet electricity Cable way；UfFor fan outlet voltage；rcFor the resistance value of cable unit length；LcFor cable length.
P0Become no-load loss for case：
Wherein：StFor case varying capacity；β1For the proportion of goods damageds under zero load.
PnBecome nominal load loss for case：
Wherein：β2For the proportion of goods damageds under nominal load.
Circuit total losses in wind field are：
PL=Ploss+P1+P0+Pn（11）
It is collated obtain for：
Wherein c1,c2,c3It is as follows for coefficient, expression formula：
4th step, calculates two other optimization aim：Feather pneumatic drag coefficient Cd, grid entry point frequency fluctuation Δ f.
1st, caught when Wind turbines are run on rated wind speed, it is necessary to which propeller pitch angle is adjusted with reducing the energy of wind wheel Obtain, so as to adjust active power generating capacity.During feather, pneumatic equipment bladess can bear feather caused by aerodynamic force Load, the aerodynamic loading for calculating Wind turbines is analyzed with blade element-momentum, establishes nonlinear function.By air force Caused feather load is represented by:
Wherein：ClFor lift coefficient；CdFor resistance coefficient；β is propeller pitch angle；θ for make a concerted effort and tangential force angle.
As can be seen that feather load is related with pitch angle caused by air force, so changing propeller pitch angle can change Wind energy conversion system aerodynamic load.But under same wind speed, propeller pitch angle is smaller, and the wind energy of wind energy conversion system capture is bigger, while wind-force Machine bears that load is also bigger, so wind energy conversion system load becomes a short slab for restricting unit safety stable operation.In order to prevent Excessive feather load infringement unit service life, must assess rack load when studying feather, makes load Risk minimization.Wherein resistance coefficient CdActive loss caused by feather load can largely be represented.
Wherein ρ is atmospheric density；v1For air velocity；C is leaf chord length at radius R；DD is the resistance acted on blade Power；Dr is foline thickness.
β is propeller pitch angle,It is as shown in Figure 3 with the relation of wind speed；α is inflow angle,Relation as shown in figure 4, can To find out showed sinusoidal characteristic within the specific limits, thus drafted for：
SoIt can pass through（18）Obtain.
WhereinRelation can also be obtained by the data measured in real time.So it can finally obtain active and resistance The relation of coefficient.
2nd, limit value f of the system frequency beyond settinga＜ f ＜ fbOr fc＜ f ＜ fdWhen, Wind turbines adjustment is contributed, response System frequency changes, and is specially：
Wherein Δ p is the active power output for needing to adjust；pbcThe active power output under operating status is unloaded for Wind turbines；fb, fcThe frequency upper limit value and lower limit value of frequency modulation is not involved in for the Wind turbines of setting；fa, fdFor setting Wind turbines frequency modulation section it is upper and lower Limit value；pdFor fdThe corresponding active power output of point.Each amount is per unit value, and power reference value is the active power output determined by wind speed, frequently Rate a reference value is rated frequency 50Hz.
5th step, for the external condition of wind power plant operation, is divided into ration the power supply operation and operation of not rationing the power supply, both of these case is most Wind power plant active power output adjustment is all carried out afterwards.Obtained optimization aim above is brought into object function.
1st, ration the power supply situation：Optimization aim is frequency fluctuation the Δ f and P of grid entry pointL.WhenWhen, need Carry out pitch control Δ β.PrefTo dispatch the active output valve of given wind field.Optimization aim need to increase feather aerodynamic drag at this time Coefficient Cd.Object function is as follows at this time：
2nd, do not ration the power supply situation：When wind speed υ is less than rated wind speed υrWhen, maximal power tracing control MPPT is carried out to wind turbine, Optimization aim Δ f and PL；When wind speed υ is less than or equal to rated wind speed υrWhen, pitch control, optimization aim C are carried out to wind turbined, Δ F and PL。
Wherein：h1,h2,h3And l1,l2,l3Weight coefficient when respectively rationing the power supply and not rationing the power supply.
Maximal power tracing controls MPPT using optimal tip speed ratio method.Wind energy conversion system is maintained when wind speed changes Tip speed ratio λ remain at optimum value λOPTPlace, λOPTObtained generally by calculating or testing, so under any wind speed Wind energy conversion system is all maximum to the utilization rate of wind energy.Fig. 5 is its control principle block diagram, it makees the measured value of wind speed and wind energy conversion system rotating speed The input signal of system in order to control, by the way that actual tip speed ratio λ at this time is calculated, then with optimal tip speed ratio λOPTPhase Compare, errors values is sent into controller, and the output of controller control inverter adjusts rotation speed of fan, so as to ensure blade tip speed Than optimal.
According to above-mentioned object function（21）（22）, constraints is：
Frequency fluctuation range constraint：
Δf≤Δfbc（23）
WhereinFor frequency shift (FS) limit value.
Power grid power supply Constraints of Equilibrium：
Wherein PDFor the demand of total load.
6th step, multiple target active optimization is carried out with based on particle swarm optimization algorithm.
For above-mentioned Multiobjective Optimal Control Problems, search is iterated using particle swarm optimization algorithm, seeks optimal solution, walked It is rapid as follows：
Step1:Input fan outlet voltage, power factor, main transformer parameter and actual input power, virtual voltage With the ratio of rated voltage, case becomes the parameters such as the proportion of goods damageds under no-load loss rate and nominal load, propeller pitch angle, inflow angle.Calculate wind Circuit total losses in, frequency fluctuation and resistance coefficient.
step2:Dimension, maximum iteration and population are set；
step3:Bring the result obtained in step1 into formula（21）（22）In, obtain fitness value fmin, make fminIt is equal to The position p of current particleid (t)；
Step4:Initialized location and speed, calculate the position p of individual optimal particleid (t), and by this pid (t) It is set to the position p for global optimum's particle that population currently searches outgd (t)；
Step5:If current particle fitness value is less than individual extreme value, current individual extreme value p is updatedibest；
Step6:If current particle fitness value is less than global extremum, current global extremum p is updatedgbest；
Step7:By formula（25）（26）Renewal speed vector and position vector.
Vid (t+1)=wVid (t)+c1r1·(pid (t)-Xid (t))+c2r2·(pgd (t)-Xid (t)) i=1,2 ..., n（25）
Xid (t+1)=Xid (t)+Vid (t+1),Xid min≤Xid (t)≤Xid maxI=1,2 ..., n（26）
T is current cycle time in formula；c1、c2For particle weights coefficient；ω is inertia weight；r1、r2For（0,1）It is interior equal Even distribution random numbers；Vid、XidFor the Position And Velocity of i-th dimension particle；
Step8:Fitness value is calculated with the velocity vector after renewal and position vector；
Step9:Repeat step5 to step7；
Step10:Judge iterations, satisfaction then exports result；Otherwise Step7 is returned to.

Claims (2)

  1. A kind of 1. control method of the distributing active power of wind power field equipped with energy-accumulating power station, it is characterised in that：Its step is as follows：
    The first step, wind field wind speed, rotation speed of fan, each unit active power, change are measured by SCADA detections control and acquisition system Power station side active power, unit and enter net side three-phase voltage, electric current, frequency, power factor, energy-storage system charge-discharge electric power and simultaneously Then these data are sent control centre by site power quality data by communication cable；
    Second step, set wind power swing and unit output constraints as:
    Pi,min≤Pi≤Pi,max (1)
    <mrow> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <munder> <mi>max</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>0</mn> <mo>,</mo> <mn>1</mn> <mo>,</mo> <mn>...59</mn> </mrow> </munder> <mi>Y</mi> <mrow> <mo>(</mo> <mi>k</mi> <mo>-</mo> <mi>i</mi> <mo>)</mo> </mrow> <mo>-</mo> <munder> <mi>min</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>0</mn> <mo>,</mo> <mn>1</mn> <mo>,</mo> <mn>...59</mn> </mrow> </munder> <mi>Y</mi> <mrow> <mo>(</mo> <mi>k</mi> <mo>-</mo> <mi>i</mi> <mo>)</mo> </mrow> <mo>&amp;le;</mo> <msub> <mi>&amp;gamma;</mi> <mn>1</mn> </msub> <msub> <mi>p</mi> <mrow> <mi>r</mi> <mi>a</mi> <mi>t</mi> <mi>e</mi> <mi>d</mi> </mrow> </msub> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <munder> <mi>max</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>0</mn> <mo>,</mo> <mn>1</mn> <mo>,</mo> <mn>...1799</mn> </mrow> </munder> <mi>Y</mi> <mrow> <mo>(</mo> <mi>k</mi> <mo>-</mo> <mi>i</mi> <mo>)</mo> </mrow> <mo>-</mo> <munder> <mi>min</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>0</mn> <mo>,</mo> <mn>1</mn> <mo>,</mo> <mn>...1799</mn> </mrow> </munder> <mi>Y</mi> <mrow> <mo>(</mo> <mi>k</mi> <mo>-</mo> <mi>i</mi> <mo>)</mo> </mrow> <mo>&amp;le;</mo> <msub> <mi>&amp;gamma;</mi> <mn>30</mn> </msub> <msub> <mi>p</mi> <mrow> <mi>r</mi> <mi>a</mi> <mi>t</mi> <mi>e</mi> <mi>d</mi> </mrow> </msub> </mrow> </mtd> </mtr> </mtable> </mfenced> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </mrow>
    (1) formula constrains for unit output bound；(2) formula constrains for the wind power fluctuation range of consideration energy-storage system, In the time window of 1min or 30min, the amplitude of variation of system synthesis output power must be not more than wind power plant always specified output work Rate pratedγ1Or γ30, γ1With γ30Provided by Grid code, the amplitude of variation of system synthesis output power subtracts for maximum Go the difference of minimum value；
    3rd step, passes through the fan outlet voltage U measured in real timef, overhead transmission line electric current I, case becomes no-load loss rate and specified The lower proportion of goods damageds β of load1、β2, obtain the circuit total losses P in wind fieldL, it is collated obtain for：
    <mrow> <msub> <mi>P</mi> <mi>L</mi> </msub> <mo>=</mo> <mn>3</mn> <mo>&amp;times;</mo> <msup> <mi>I</mi> <mn>2</mn> </msup> <mo>&amp;times;</mo> <mi>r</mi> <mo>&amp;times;</mo> <mi>L</mi> <mo>+</mo> <msub> <mi>c</mi> <mn>1</mn> </msub> <mo>&amp;times;</mo> <msup> <msub> <mi>U</mi> <mi>f</mi> </msub> <mn>2</mn> </msup> <mo>+</mo> <msub> <mi>c</mi> <mn>2</mn> </msub> <mfrac> <mn>1</mn> <msub> <mi>&amp;beta;</mi> <mn>1</mn> </msub> </mfrac> <mo>+</mo> <msub> <mi>c</mi> <mn>3</mn> </msub> <mfrac> <mn>1</mn> <msub> <mi>&amp;beta;</mi> <mn>2</mn> </msub> </mfrac> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>3</mn> <mo>)</mo> </mrow> </mrow>
    Wherein c1,c2,c3It is as follows for coefficient, expression formula：
    <mrow> <msub> <mi>c</mi> <mn>1</mn> </msub> <mo>=</mo> <msup> <mi>a</mi> <mn>2</mn> </msup> <mo>&amp;times;</mo> <mfrac> <mi>N</mi> <msub> <mi>N</mi> <mn>1</mn> </msub> </mfrac> <mo>&amp;times;</mo> <msub> <mi>P</mi> <mi>e</mi> </msub> <mo>&amp;times;</mo> <msub> <mi>r</mi> <mi>c</mi> </msub> <mo>&amp;times;</mo> <msub> <mi>L</mi> <mi>c</mi> </msub> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>4</mn> <mo>)</mo> </mrow> </mrow>
    <mrow> <msub> <mi>c</mi> <mn>2</mn> </msub> <mo>=</mo> <mfrac> <mrow> <mi>N</mi> <mo>&amp;times;</mo> <msub> <mi>S</mi> <mi>t</mi> </msub> </mrow> <mn>100</mn> </mfrac> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>5</mn> <mo>)</mo> </mrow> </mrow>
    <mrow> <msub> <mi>c</mi> <mn>3</mn> </msub> <mo>=</mo> <mfrac> <mrow> <mi>N</mi> <mo>&amp;times;</mo> <msup> <mi>a</mi> <mn>2</mn> </msup> <mo>&amp;times;</mo> <msup> <msub> <mi>P</mi> <mi>e</mi> </msub> <mn>2</mn> </msup> </mrow> <mrow> <mn>100</mn> <mo>&amp;times;</mo> <msub> <mi>S</mi> <mi>t</mi> </msub> </mrow> </mfrac> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>6</mn> <mo>)</mo> </mrow> </mrow>
    Wherein：A is power output coefficient；N is wind turbine number；PeFor every Fans rated capacity；I is overhead transmission line electric current；R is frame Ceases to be busy resistance per unit length value；L is the length of each bar circuit of overhead line；N1For fan outlet cable bar number；StFor case varying capacity； rcFor the resistance value of cable unit length；LcFor cable line length；
    4th step, calculates two other optimization aim：Feather pneumatic drag coefficient Cd, grid entry point frequency fluctuation Δ f：
    <mrow> <mi>&amp;Delta;</mi> <mi>f</mi> <mo>=</mo> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mfrac> <mrow> <mi>&amp;Delta;</mi> <mi>p</mi> <mrow> <mo>(</mo> <msub> <mi>f</mi> <mi>a</mi> </msub> <mo>-</mo> <msub> <mi>f</mi> <mi>b</mi> </msub> <mo>)</mo> </mrow> </mrow> <mrow> <mn>1</mn> <mo>-</mo> <msub> <mi>p</mi> <mrow> <mi>b</mi> <mi>c</mi> </mrow> </msub> </mrow> </mfrac> </mtd> <mtd> <mrow> <msub> <mi>f</mi> <mi>a</mi> </msub> <mo>&lt;</mo> <mi>f</mi> <mo>&lt;</mo> <msub> <mi>f</mi> <mi>b</mi> </msub> </mrow> </mtd> </mtr> <mtr> <mtd> <mfrac> <mrow> <mi>&amp;Delta;</mi> <mi>p</mi> <mrow> <mo>(</mo> <msub> <mi>f</mi> <mi>c</mi> </msub> <mo>-</mo> <msub> <mi>f</mi> <mi>d</mi> </msub> <mo>)</mo> </mrow> </mrow> <mrow> <msub> <mi>p</mi> <mrow> <mi>b</mi> <mi>c</mi> </mrow> </msub> <mo>-</mo> <msub> <mi>p</mi> <mi>d</mi> </msub> </mrow> </mfrac> </mtd> <mtd> <mrow> <msub> <mi>f</mi> <mi>c</mi> </msub> <mo>&lt;</mo> <mi>f</mi> <mo>&lt;</mo> <msub> <mi>f</mi> <mi>d</mi> </msub> </mrow> </mtd> </mtr> </mtable> </mfenced> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>7</mn> <mo>)</mo> </mrow> </mrow>
    Δ p is the active power output for needing to adjust；pbcThe active power output under operating status is unloaded for Wind turbines；fb, fcFor setting Wind turbines are not involved in the frequency upper limit value and lower limit value of frequency modulation；fa, fdFor the upper limit value and lower limit value of the Wind turbines frequency modulation section of setting；pdFor fdThe corresponding active power output of point；
    <mrow> <mfrac> <mrow> <mi>d</mi> <mi>P</mi> </mrow> <mrow> <msub> <mi>dC</mi> <mi>d</mi> </msub> </mrow> </mfrac> <mo>=</mo> <mfrac> <mrow> <mi>d</mi> <mi>P</mi> </mrow> <mrow> <mi>d</mi> <mi>&amp;beta;</mi> </mrow> </mfrac> <mo>&amp;CenterDot;</mo> <mfrac> <mrow> <mi>d</mi> <mi>&amp;beta;</mi> </mrow> <mrow> <mi>d</mi> <mi>&amp;alpha;</mi> </mrow> </mfrac> <mo>&amp;CenterDot;</mo> <mfrac> <mrow> <mi>d</mi> <mi>&amp;alpha;</mi> </mrow> <mrow> <msub> <mi>dC</mi> <mi>d</mi> </msub> </mrow> </mfrac> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>8</mn> <mo>)</mo> </mrow> </mrow>
    Wherein：β is propeller pitch angle, α is inflow angle, is measurable data；
    5th step, for the external condition of wind power plant operation, is divided into rationing the power supply and operation and does not ration the power supply operation, and both of these case all finally Wind power plant active power output adjustment is carried out, obtained optimization aim above is brought into object function；
    Ration the power supply situation：Optimization aim is frequency fluctuation the Δ f and P of grid entry pointL；WhenWhen, PrefTo adjust The active output valve of the given wind field of degree, need to carry out pitch control Δ β, optimization aim need to increase feather pneumatic drag coefficient at this time Cd, object function is as follows at this time：
    <mrow> <msub> <mi>minf</mi> <mi>x</mi> </msub> <mo>=</mo> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <msub> <mi>h</mi> <mn>1</mn> </msub> <msub> <mi>C</mi> <mi>d</mi> </msub> <mo>+</mo> <msub> <mi>h</mi> <mn>2</mn> </msub> <msub> <mi>P</mi> <mi>L</mi> </msub> <mo>+</mo> <msub> <mi>h</mi> <mn>3</mn> </msub> <mi>&amp;Delta;</mi> <mi>f</mi> </mrow> </mtd> <mtd> <mrow> <mo>(</mo> <msub> <mi>P</mi> <mi>B</mi> </msub> <mo>(</mo> <mi>k</mi> <mo>)</mo> <mo>+</mo> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>N</mi> </munderover> <msub> <mi>P</mi> <mi>i</mi> </msub> <mo>(</mo> <mi>k</mi> <mo>)</mo> <mo>&amp;GreaterEqual;</mo> <msub> <mi>P</mi> <mrow> <mi>r</mi> <mi>e</mi> <mi>f</mi> </mrow> </msub> <mo>)</mo> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <msub> <mi>h</mi> <mn>2</mn> </msub> <msub> <mi>P</mi> <mi>L</mi> </msub> <mo>+</mo> <msub> <mi>h</mi> <mn>3</mn> </msub> <mi>&amp;Delta;</mi> <mi>f</mi> </mrow> </mtd> <mtd> <mrow> <mo>(</mo> <msub> <mi>P</mi> <mi>B</mi> </msub> <mo>(</mo> <mi>k</mi> <mo>)</mo> <mo>+</mo> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>N</mi> </munderover> <msub> <mi>P</mi> <mi>i</mi> </msub> <mo>(</mo> <mi>k</mi> <mo>)</mo> <mo>&amp;le;</mo> <msub> <mi>P</mi> <mrow> <mi>r</mi> <mi>e</mi> <mi>f</mi> </mrow> </msub> <mo>)</mo> </mrow> </mtd> </mtr> </mtable> </mfenced> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>9</mn> <mo>)</mo> </mrow> </mrow>
    PB(k) it is grid entry point performance number；Do not ration the power supply situation：When wind speed υ is less than rated wind speed υrWhen, maximum power is carried out to wind turbine Tracing control MPPT, optimization aim Δ f and PL；When wind speed υ is more than or equal to rated wind speed υrWhen, pitch control is carried out to wind turbine, it is excellent Change target is Cd, Δ f and PL；
    <mrow> <msub> <mi>minf</mi> <mi>x</mi> </msub> <mo>=</mo> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <msub> <mi>l</mi> <mn>2</mn> </msub> <msub> <mi>P</mi> <mi>L</mi> </msub> <mo>+</mo> <msub> <mi>l</mi> <mn>3</mn> </msub> <mi>&amp;Delta;</mi> <mi>f</mi> </mrow> </mtd> <mtd> <mrow> <mo>(</mo> <mi>&amp;upsi;</mi> <mo>&lt;</mo> <msub> <mi>&amp;upsi;</mi> <mi>r</mi> </msub> <mo>,</mo> <mi>M</mi> <mi>P</mi> <mi>P</mi> <mi>T</mi> <mo>)</mo> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <msub> <mi>l</mi> <mn>1</mn> </msub> <msub> <mi>C</mi> <mi>d</mi> </msub> <mo>+</mo> <msub> <mi>l</mi> <mn>2</mn> </msub> <msub> <mi>P</mi> <mi>L</mi> </msub> <mo>+</mo> <msub> <mi>l</mi> <mn>3</mn> </msub> <mi>&amp;Delta;</mi> <mi>f</mi> </mrow> </mtd> <mtd> <mrow> <mo>(</mo> <mi>&amp;upsi;</mi> <mo>&amp;GreaterEqual;</mo> <msub> <mi>&amp;upsi;</mi> <mi>r</mi> </msub> <mo>,</mo> <mi>&amp;Delta;</mi> <mi>&amp;beta;</mi> <mo>)</mo> </mrow> </mtd> </mtr> </mtable> </mfenced> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>10</mn> <mo>)</mo> </mrow> </mrow>
    Wherein：h1,h2,h3And l1,l2,l3Weight coefficient when respectively rationing the power supply and not rationing the power supply, Δ β is propeller pitch angle variable quantity；
    Constraints is：
    Δf≤Δfbc (11)
    <mrow> <msub> <mi>P</mi> <mi>B</mi> </msub> <mo>+</mo> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>N</mi> </munderover> <msub> <mi>P</mi> <mi>i</mi> </msub> <mo>=</mo> <msub> <mi>P</mi> <mi>D</mi> </msub> <mo>+</mo> <msub> <mi>P</mi> <mi>L</mi> </msub> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>12</mn> <mo>)</mo> </mrow> </mrow>
    Formula (11) frequency fluctuation range constraint, Δ fbcFor frequency shift (FS) limit value；Formula (12) power grid power supply Constraints of Equilibrium, PDFor The demand of total load；
    6th step, multiple target active optimization is carried out with the vehicle routing optimization algorithm based on population.
  2. 2. the control method of the distributing active power of wind power field according to claim 1 equipped with energy-accumulating power station, its feature It is：
    For above-mentioned Multiobjective Optimal Control Problems, search is iterated using particle swarm optimization algorithm, seeks optimal solution, step is such as Under：
    ①:Input fan outlet voltage, power factor, main transformer parameter and actual input power, virtual voltage with it is specified The ratio of voltage, case become the parameters such as the proportion of goods damageds under no-load loss rate and nominal load, propeller pitch angle, inflow angle；Calculate in wind field Circuit total losses, frequency fluctuation and resistance coefficient；
    ②:Dimension, maximum iteration and population are set；
    ③:The result obtained in step1 is brought into formula (9) (10), obtains fitness value fmin, make fminEqual to current particle Position pid (t)；
    ④:Initialized location and speed, calculate the position p of individual optimal particleid (t), and by this pid (t)Population is set to work as Before the position p of global optimum's particle that searches outgd (t)；
    ⑤:If current particle fitness value is less than individual extreme value, current individual extreme value p is updatedibest；
    ⑥:If current particle fitness value is less than global extremum, current global extremum p is updatedgbest；
    ⑦:By formula (25) (26) renewal speed vector and position vector；
    Vid (t+1)=wVid (t)+c1r1·(pid (t)-Xid (t))+c2r2·(pgd (t)-Xid (t)) i=1,2 ..., n (25)
    Xid (t+1)=Xid (t)+Vid (t+1),Xid min≤Xid (t)≤Xid maxI=1,2 ..., n (26)
    T is current cycle time in formula；c1、c2For particle weights coefficient；ω is inertia weight；r1、r2To be uniformly distributed in (0,1) Random number；Vid、XidFor the Position And Velocity of i-th dimension particle；
    Step8:Fitness value is calculated with the velocity vector after renewal and position vector；
    Step9:Repeat step5 to step7；
    Step10:Judge iterations, satisfaction then exports result；Otherwise Step7 is returned to.
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