CN103441537A - Method for optimizing and regulating and controlling active power of distributed wind power plant with energy storage power station - Google Patents

Abstract

The invention relates to a method for optimizing and regulating and controlling active power of a distributed wind power plant with an energy storage power station. According to the method, the constraint condition is set to top and bottom limitation constraint output by the active power and maximum and minimum limiting values of single body power generation according to the wind power net-in guide rule, and the output constraint condition of the active power is set up according to the wind power and energy storage power source single body power generation characteristic. According to the external condition of wind power plant operation, the method is divided into limited power operation and unlimited power operation, the optimization objective of the limited power operation is to enable pitch control loads, line loss and frequency fluctuation to be minimum, the optimization objective of the unlimited power operation is to enable wind energy capture efficiency to be maximum and the line loss and the frequency fluctuation to be minimum, and the objective function of the unlimited power operation is the multiple target layered optimization problem. The particle swarm optimization is used for carrying out solution. According to the method, the wind power active power output under the effect of an energy storage system is output stably with minimized loss, and therefore effective connection between the energy storage system and an existing scheduling operation mode and optimum economic benefits are achieved.

Description

The meritorious optimization regulating method of distributing wind energy turbine set of being furnished with energy-accumulating power station

Technical field

The present invention relates to a kind of meritorious optimization regulating method of distributing wind energy turbine set of being furnished with energy-accumulating power station, belong to wind farm grid-connected operation active power control technology field.

Background technology

Along with the great attention of country to renewable energy power generation, China's wind-powered electricity generation has become Optimization of Energy Structure and has promoted the important new industry of sustainable development.But along with large-scale wind power grid-connected after, the fail safe of electric power system, reliability, the quality of power supply and dispatching of power netwoks all can be subject to the impact of wind power generation fluctuation and randomness.Centralized large electrical network has close coupling, and can not follow the tracks of variation in flexibility and reliability ground.And distributing access Wind Power Project refers to and is positioned near the power load center, not take and transmit electric power at a distance on a large scale as purpose, the electric power produced accesses electrical network nearby, and the Wind Power Project of dissolving in locality.It can solve centralized wind power-generating grid-connected some produced problems preferably.Under this background, country has proposed the policy of development distributing wind-powered electricity generation.

The distributing wind energy turbine set of being furnished with energy-accumulating power station directly accesses low-voltage network and can reduce transmission losses and investment cost, improves the power supply reliability of power distribution network, guarantees to a great extent energy security.Yet along with the wind energy turbine set output quality of power supply, saving energy and decreasing loss and electricity net safety stable are required increasingly to improve, by carrying out the meritorious research of optimizing with operation problem of distributing wind energy turbine set to being furnished with energy-accumulating power station, it is the effective means that reduces grid loss and guarantee power grid operation.By the reasonable disposition to meritorious power supply (blower fan and energy-accumulating power station) and the Reasonable Regulation And Control of active loss, can reduce the mains frequency fluctuation, reduce the electric network active loss, thereby make the electric power system can safe and stable operation.

Real power control and optimization research for wind energy turbine set, proposed many optimization methods.Propose separate unit wind-powered electricity generation unit and can carry out the active power coordination control strategy between each typhoon group of motors in high wind speed, middle wind speed and low wind speed stage, improve wind energy turbine set generating nargin; Propose a kind of a kind of wind energy turbine set control method using fan rotor kinetic energy as energy accumulating device, to reduce energy fluctuation in short-term, improve wind farm grid-connected stability; Consider the unit the closest with the output-power fluctuation relation, and it is exerted oneself and is controlled fluctuation that suppresses to exert oneself etc.These methods can realize the meritorious optimization of wind field.

But be directed to the meritorious optimization problem of the distributing of being furnished with energy-accumulating power station, present research both domestic and external seldom.And above-mentioned optimization method is not considered active power that the wind-powered electricity generation unit sends and the multidimensional function relation between himself loss, therefore can't in meeting grid-connected dot frequency fluctuation safe range, make as far as possible the wind turbine generator overall losses reach minimum.

Summary of the invention

Goal of the invention

The invention provides a kind of meritorious optimization regulating method of distributing wind energy turbine set of being furnished with energy-accumulating power station, its objective is the excessive problem of wind turbine generator overall losses in the existing grid-connected dot frequency fluctuation safe range of solution mode in the past, its service conditions different for wind field is set up multiple objective function, when effectively control frequency fluctuates, can also reduce blower variable-pitch load, reduce the wind energy turbine set active loss.

Technical scheme

A kind of control method of being furnished with the distributing active power of wind power field of energy-accumulating power station, it is characterized in that: its step is as follows:

The first step, detect and control and acquisition system is measured wind field wind speed, rotation speed of fan, each unit active power, transformer substation side active power, unit and networking side three-phase voltage, electric current, frequency, power factor, energy-storage system and discharged and recharged power and site power quality data also by SCADA, then these data are sent to control centre by communication cable;

Second step, setting wind power fluctuation and unit output constraints are:

P _i,min≤P _i≤P _i,max （1）

$\left\{\begin{array}{c}\underset{i=\mathrm{0,1},...59}{\max }Y(k-i)-\underset{i=\mathrm{0,1},...59}{\min }Y(k-i)\≤{\mathrm{\γ}}_1{p}_{\mathrm{rated}}\\ \underset{i=\mathrm{0,1},...1799}{\max }Y(k-i)-\underset{i=\mathrm{0,1},...1799}{\min }Y(k-i)\≤{\mathrm{\γ}}_{30}{p}_{\mathrm{rated}}\end{array}\right.---\left(2\right)$

(1) formula is the constraint of unit output bound; (2) formula is for considering the wind energy turbine set power fluctuation range constraint of energy-storage system, and in the time window of 1min or 30min, the amplitude of variation of system synthesis power output must be not more than the total specified power output p of wind energy turbine set _ratedγ ₁or γ ₃₀, γ ₁with γ ₃₀by the Grid code regulation, the amplitude of variation of system synthesis power output is that maximum deducts the poor of minimum value;

The 3rd step, by the fan outlet voltage U measured in real time _f, the overhead transmission line electric current I, case becomes proportion of goods damageds β under no-load loss rate and nominal load ₁, β ₂, obtain the circuit total losses P in wind field _l, through arrangement obtain into:

$P_L=3\&times;I^2\&times;r\&times;L+{\mathrm{<figure-callout\; id="1"\; label="c"\; filenames="HDA00003365232900011.png"\; state="\{\{state\}\}">c</figure-callout>}}_1\&times;{{\mathrm{<figure-callout\; id="2"\; label="U\; f"\; filenames="DEST\_PATH\_130929140203.png,HDA00003365232900011.png"\; state="\{\{state\}\}">U</figure-callout>}}_f}^2+{\mathrm{<figure-callout\; id="2"\; label="c"\; filenames="DEST\_PATH\_130929140203.png,HDA00003365232900011.png"\; state="\{\{state\}\}">c</figure-callout>}}_2\frac{1}{{\mathrm{\&beta;}}_1}+c_3\frac{1}{{\mathrm{\&beta;}}_2}---\left(3\right)$

C wherein ₁, c ₂, c ₃for coefficient, expression formula is as follows:

${\mathrm{<figure-callout\; id="1"\; label="c"\; filenames="HDA00003365232900011.png"\; state="\{\{state\}\}">c</figure-callout>}}_1=a^2\&times;\frac{\mathrm{<figure-callout\; id="1"\; label="N\; N"\; filenames="HDA00003365232900011.png"\; state="\{\{state\}\}">N</figure-callout>}}{N_{}}\&times;P_e\&times;r_c\&times;L_c---\left(4\right)$

${\mathrm{<figure-callout\; id="2"\; label="c"\; filenames="DEST\_PATH\_130929140203.png,HDA00003365232900011.png"\; state="\{\{state\}\}">c</figure-callout>}}_2=\frac{N\&times;S_t}{100}---\left(5\right)$

$c_3=\frac{N\&times;a^2\&times;{{\mathrm{<figure-callout\; id="2"\; label="P\; e"\; filenames="DEST\_PATH\_130929140203.png,HDA00003365232900011.png"\; state="\{\{state\}\}">P</figure-callout>}}_e}^2}{100\&times;S_t}---\left(6\right)$

Wherein: a is the power stage coefficient; N is the blower fan number; P _efor every Fans rated capacity; I is the overhead transmission line current value; R is overhead wire resistance per unit length value; The length that L is each circuit of overhead wire; N ₁for fan outlet cable number; S _tfor the case varying capacity; r _cresistance value for the cable unit length; L _cfor cable length;

The 4th step, calculate two other optimization aim: variable pitch pneumatic drag coefficient C _d, and the frequency fluctuation Δ f of site:

$\mathrm{\&Delta;f}=\left\{\begin{array}{cc}\frac{\mathrm{\&Delta;p}(f_a-f_b)}{1-p_{\mathrm{bc}}}& f_a<f<f_b\\ \frac{\mathrm{\&Delta;p}(f_c-f_d)}{p_{\mathrm{bc}}-p_d}& f_c<f<f_d\end{array}\right.---\left(7\right)$

Δ p is for needing meritorious the exerting oneself of adjusting; p _bcfor meritorious the exerting oneself under wind-powered electricity generation unit unloading running status; f _b, f _cfor the wind-powered electricity generation unit of setting does not participate in the frequency upper limit value and lower limit value of frequency modulation; f _a, f _dupper limit value and lower limit value for the wind-powered electricity generation unit frequency modulation section set; p _dfor f _dmeritorious the exerting oneself that point is corresponding;

$\frac{\mathrm{dP}}{{\mathrm{dC}}_d}=\frac{\mathrm{dP}}{\mathrm{d\&beta;}}\&CenterDot;\frac{\mathrm{d\&beta;}}{\mathrm{d\&alpha;}}\&CenterDot;\frac{\mathrm{d\&alpha;}}{d{C}_d}---\left(8\right)$

Wherein: β is that propeller pitch angle, α are inflow angle, but the measurement data of being;

The 5th step, for the external condition of wind energy turbine set operation, be divided into ration the power supply operation and the operation of not rationing the power supply, and both of these case finally all carries out the meritorious adjustment of exerting oneself of wind energy turbine set, and top tried to achieve optimization aim is brought in target function;

The situation of rationing the power supply: optimization aim for and frequency fluctuation Δ f and the P of site _l.When

the time, P _reffor dispatching the meritorious output valve of given wind field, need be become oar and be controlled Δ β, now optimization aim need increase variable pitch pneumatic drag coefficient C _d, now target function is as follows:

$\min f_x=\left\{\begin{array}{cc}{h}_1{C}_d+h_2{P}_L+h_3\mathrm{\&Delta;f}& (P_B\left(k\right)+\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{P}_i\left(k\right)\&GreaterEqual;P_{\mathrm{ref}})\\ h_2{P}_L+h_3\mathrm{\&Delta;f}& (P_B\left(k\right)+\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{P}_i\left(k\right)\&le;P_{\mathrm{ref}})\end{array}\right.---\left(9\right)$

The situation of not rationing the power supply: when wind speed υ is less than rated wind speed υ _rthe time, blower fan is carried out to maximal power tracing and control MPPT, optimization aim Δ f and P _l; When wind speed υ is less than or equal to rated wind speed υ _rthe time, blower fan being become to oar and controlled, optimization aim is C _d, Δ f and P _l;

$\min f_x=\left\{\begin{array}{cc}{l}_2{P}_L+l_3\mathrm{\&Delta;f}& (\mathrm{\&upsi;}<{\mathrm{\&upsi;}}_r,\mathrm{MPPT})\\ l_1{C}_d+l_2{P}_L+l_3\mathrm{\&Delta;f}& (\mathrm{\&upsi;}\&GreaterEqual;{\mathrm{\&upsi;}}_r,\mathrm{\&Delta;\&beta;})\end{array}\right.---\left(10\right)$

Wherein: h ₁, h ₂, h ₃and l ₁, l ₂, l ₃be respectively the weight coefficient when rationing the power supply and not rationing the power supply,

Constraints is:

Δf≤Δf _bc （11）

$P_B+\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{P}_i=P_D+P_L---\left(12\right)$

(11) frequency fluctuation range constraint, Δ f _bcfor the frequency shift (FS) limit value; (12) mains supply Constraints of Equilibrium, P _ddemand for total load;

The 6th step, use the vehicle route optimized algorithm based on population to carry out the meritorious optimization of multiple target.

For above-mentioned Multiobjective Optimal Control Problems, adopt particle swarm optimization algorithm to carry out iterative search, ask optimal solution, step is as follows:

1.: input fan outlet voltage, power factor, main transformer parameter and actual input power, the ratio of virtual voltage and rated voltage, the proportion of goods damageds under case change no-load loss rate and nominal load, propeller pitch angle, the parameters such as inflow angle.Calculate the circuit total losses in wind field, frequency fluctuation and resistance coefficient;

2.: dimension, maximum iteration time and population are set;

3.: the result obtained in step1 is brought in formula (9) (10), obtain fitness value f _minmake f _minequal the position p of current particle _id ^(t);

4.: initialized location and speed, calculate the position p of first individual optimal particle _id ^(t), and by this p _id ^(t)be made as the position p of the current global optimum's particle searched out of population _gd ^(t);

5.: if current particle fitness value is less than individual extreme value, upgrade current individual extreme value p _ibest;

6.: if current particle fitness value is less than global extremum, upgrade current global extremum p _gbest;

7.: by formula (25) (26) renewal speed vector and position vector;

V _id ^(t+1)＝w·V _id ^(t)+c ₁r ₁·(p _id ^(t)-X _id ^(t))+c ₂r ₂·(p _gd ^(t)-X _id ^(t))i＝1,2,...,n （25）

X _id ^(t+1)＝X _id ^(t)+V _id ^(t+1),X _id ^min≤X _id ^(t)≤X _id ^maxi＝1,2,...,n （26）

In formula, t is current cycle time; c ₁, c ₂for the particle weight coefficient; ω is inertia weight; r ₁, r ₂for (0,1) interior uniform random number; V _id, X _idit is the Position And Velocity of i dimension particle;

Step8: with the velocity vector after upgrading and position vector, calculate fitness value;

Step9: repeat step5 to step7;

Step10: judgement iterations, satisfied Output rusults; Otherwise get back to Step7.

Advantage and effect

The present invention is directed to the outside operation characteristic of the distributing wind energy turbine set of being furnished with energy-accumulating power station, the meritorious optimization method of multiple target under ruuning situation has been proposed,, the meritorious optimization regulating method of distributing wind energy turbine set of being furnished with energy-accumulating power station: judge that whether wind energy turbine set is moved in the situation of rationing the power supply, and carries out multiobjective optimal control according to wind conditions.

(1) measure desired data by the SCADA system, then these data are sent to control centre by communication cable.

(2) set wind power fluctuation and unit output constraints.

(3) calculate case and become nominal load loss P _n, case becomes no-load loss P ₀, the cable line loss P that fan outlet is connected with the case low pressure side ₁, each line power loss P _loss.Circuit total losses P in arrangement obtains wind field _l.

(4) calculate two other optimization aim: variable pitch pneumatic drag coefficient C _d, and the frequency fluctuation Δ f of site.

(5) for the external condition of wind energy turbine set operation, be divided into ration the power supply operation and the operation of not rationing the power supply, both of these case finally all carries out the meritorious adjustment of exerting oneself of wind energy turbine set.Carry out multi objective control according to wind conditions, top tried to achieve optimization aim is brought in target function.

(6) use the vehicle route optimized algorithm based on population to carry out the meritorious optimization of multiple target.

Concrete advantage of the present invention and good effect are as follows:

1, according to wind field service conditions and wind conditions, set up by different level multiple objective function, carry out the regulation and control of active power by regulating the variablees such as line loss, frequency, load.

2, to take the wind-powered electricity generation permeability be basis to this control method in the scope that power distribution network is set, and at guaranteed output, fluctuate is prerequisite in the safe operation scope, has improved the stability of system.

3, practical, the multi objective control that can be used for whole distributing wind energy turbine set is carried out the adjusting of active power, with the active loss that realizes whole wind field, minimizes.

The accompanying drawing explanation

Fig. 1 energy storage proportioning wind-powered electricity generation disperses access electrical network canonical topology structure chart;

Fig. 2 wind field hierarchy optimization control strategy flow chart of gaining merit;

Fig. 3 becomes the oar effect with the wind speed change curve;

The drag characteristic curve of Fig. 4 aerofoil profile;

Fig. 5 is that in Fig. 2, maximal power tracing optimal control principle schematic is;

The flow chart of Fig. 6 based on particle cluster algorithm.

Embodiment:

Below in conjunction with accompanying drawing, the present invention will be further described.

As shown in Figure 1, the control object that the present invention proposes is: the wind-powered electricity generation unit confluxes and accesses the local transformer station of 10kV loop together with energy-accumulating power station, then by 10kV/35kV, accesses public access point (PCC/1); In regional electrical network, also have the wind electricity storage station of m same pattern, be delivered to different terminal use's loads after the 35kV that confluxes; The 35kV public large electrical network of rear access that can boost.

Basic ideas of the present invention are: can optimize frequency fluctuation, change oar load and the line loss of electrical network by Optimum Regulation, reduce the active loss of electrical network, and improve quality of voltage, the electricity consumption device security is moved reliably.

The meritorious optimization problem of considering in the present invention can be defined as follows: by various regulating measures, under the condition that meets frequency constraint and operation constraint, make the target function optimum.Therefore meritorious optimization problem is actually the combinatorial optimization problem of a typical belt restraining.

A kind of distributing wind energy turbine set being furnished with energy-accumulating power station optimization regulating method of gaining merit, as shown in Figure 2, its step is as follows:

The first step, detect and control and acquisition system is measured the wind field wind speed by SCADA, rotation speed of fan, each unit active power, transformer substation side active power, unit and networking side three-phase voltage, frequency, power factor, energy-storage system discharges and recharges power, and the site power quality data, then these data is sent to control centre by communication cable.

Second step, setting wind power fluctuation and unit output constraints are:

1, unit output bound constraint:

P _i,min≤P _i≤P _i, _max （1）

P in formula _{i, min}, P _{i, max}be respectively minimum value and the maximum of unit output.

2, consider the power fluctuation range constraint of energy-storage system:

When the energy-storage system response discharges and recharges power command value, can obtain:

P _O(k+1)＝P _W(k)+P _B(k) （2）

P _o(k) be the synthetic power output of current time; P _w(k) be the wind power of current time k; P _b(k) be the power that discharges and recharges of energy-storage system.

The energy that energy-storage system stores at current time is:

$E_B\left(k\right)=E_B\left(0\right)-\mathrm{\&Delta;t}\underset{j=1}{\overset{k}{\mathrm{\&Sigma;}}}{P}_B\left(j\right)---\left(3\right)$

E _b(0) be the primary power of energy-storage system.

Get respectively P _oand E (k) _b(k) be state variable x ₁and x (k) ₂(k), P _w(k) be considered as external disturbance variable r (k), P _b(k) be control inputs amount u (k), the state-space model of stabilizing the fluctuation control system is as follows:

$\left\{\begin{array}{c}{x}_1(k+1)=r\left(k\right)+u\left(k\right)\\ x_2(k+1)=x_2\left(k\right)-u\left(k\right)\end{array}\right.---\left(4\right)$

$Y\left(k\right)=\left[\begin{array}{c}{y}_1\left(k\right)\\ y_2\left(k\right)\end{array}\right]=\left[\begin{array}{c}{x}_1\left(k\right)\\ x_2\left(k\right)\end{array}\right]---\left(5\right)$

In formula: Y (k) is the output of process matrix.

$\left\{\begin{array}{c}\underset{i=\mathrm{0,1},...59}{\max }Y(k-i)-\underset{i=\mathrm{0,1},...59}{\min }Y(k-i)\&le;{\mathrm{\&gamma;}}_1{p}_{\mathrm{rated}}\\ \underset{i=\mathrm{0,1},...1799}{\max }Y(k-i)-\underset{i=\mathrm{0,1},...1799}{\min }Y(k-i)\&le;{\mathrm{\&gamma;}}_{30}{p}_{\mathrm{rated}}\end{array}\right.---\left(6\right)$

M moment altogether, k=0 wherein, 1 ..., M-1.

In the time window of 1min, the amplitude of variation of system synthesis power output (maximum deducts the poor of minimum value) must be not more than the total specified power output p of wind energy turbine set arbitrarily _ratedγ ₁; In the time window of any 30min, the amplitude of variation of system synthesis power output must be not more than the total specified power output p of wind energy turbine set _ratedγ ₃₀, γ ₁with γ ₃₀by Grid code, stipulated.

The 3rd step, the current collection circuit of wind energy turbine set is divided into cable current collection circuit and overhead wire current collection circuit, and with respect to thermal power plant, the current collection circuit of wind energy turbine set is more complicated, close to a small-sized power distribution network.While between wind turbine and booster stations, passing through this small-sized power distribution network through-put power, can produce the line loss can not be ignored, and thermal power plant can not consider these losses at run duration.Cable and built on stilts two kinds of current collection Decision Making of Line Schemes are carried out to active power loss calculating.

Calculate case and become nominal load loss P _n, case becomes no-load loss P ₀, the cable line loss P that fan outlet is connected with the case low pressure side ₁, each line power loss P _loss.Circuit total losses P in arrangement obtains wind field _l.

P _lossfor each line power loss:

P _loss＝3×I ²×R＝3×I ²×r×L （7）

Wherein: I is line current; R is the resistance per unit length value; The length that L is each circuit.

P ₁the cable line loss be connected with the case low pressure side for fan outlet:

${\mathrm{<figure-callout\; id="1"\; label="P"\; filenames="HDA00003365232900011.png"\; state="\{\{state\}\}">P</figure-callout>}}_1=N\&times;{\mathrm{<figure-callout\; id="1"\; label="N"\; filenames="HDA00003365232900011.png"\; state="\{\{state\}\}">N</figure-callout>}}_1\&times;3\&times;{(a\&times;\frac{P_e}{\sqrt{3}/U_f/N_1})}^2\&times;r_c\&times;L_c---\left(8\right)$

Wherein: a is the power stage coefficient; P _efor every Fans rated capacity; N is the blower fan sum; N ₁for fan outlet cable way; U _ffor fan outlet voltage; r _cresistance value for the cable unit length; L _cfor cable length.

P ₀for case becomes no-load loss:

${\mathrm{<figure-callout\; id="0"\; label="P"\; filenames="DEST\_PATH\_130929140203.png,HDA00003365232900032.png"\; state="\{\{state\}\}">P</figure-callout>}}_0=N\&times;\frac{S_t/{\mathrm{\&beta;}}_1}{100}---\left(9\right)$

Wherein: S _tfor the case varying capacity; β ₁for the proportion of goods damageds under zero load.

P _nfor case becomes the nominal load loss:

$P_n=N\&times;{(a\&times;\frac{P_e}{S_t})}^2\&times;\frac{S_t/{\mathrm{\&beta;}}_2}{100}---\left(10\right)$

Wherein: β ₂for the proportion of goods damageds under nominal load.

Circuit total losses in wind field are:

P _L＝P _loss+P ₁+P ₀+P _n （11）

Through arrangement obtain into:

$P_L=3\&times;I^2\&times;r\&times;L+{\mathrm{<figure-callout\; id="1"\; label="c"\; filenames="HDA00003365232900011.png"\; state="\{\{state\}\}">c</figure-callout>}}_1\&times;{{\mathrm{<figure-callout\; id="2"\; label="U\; f"\; filenames="DEST\_PATH\_130929140203.png,HDA00003365232900011.png"\; state="\{\{state\}\}">U</figure-callout>}}_f}^2+{\mathrm{<figure-callout\; id="2"\; label="c"\; filenames="DEST\_PATH\_130929140203.png,HDA00003365232900011.png"\; state="\{\{state\}\}">c</figure-callout>}}_2\frac{1}{{\mathrm{\&beta;}}_1}+c_3\frac{1}{{\mathrm{\&beta;}}_2}---\left(12\right)$

C wherein ₁, c ₂, c ₃for coefficient, expression formula is as follows:

$c_1=a^2\&times;\frac{\mathrm{<figure-callout\; id="1"\; label="N\; N"\; filenames="HDA00003365232900011.png"\; state="\{\{state\}\}">N</figure-callout>}}{N_{}}\&times;P_e\&times;r_c\&times;L_c---\left(13\right)$

$c_2=\frac{N\&times;S_t}{100}---\left(14\right)$

$c_3=\frac{N\&times;a^2\&times;{{\mathrm{<figure-callout\; id="2"\; label="P\; e"\; filenames="DEST\_PATH\_130929140203.png,HDA00003365232900011.png"\; state="\{\{state\}\}">P</figure-callout>}}_e}^2}{100\&times;S_t}---\left(15\right)$

The 4th step, calculate two other optimization aim: variable pitch pneumatic drag coefficient C _d, and the frequency fluctuation Δ f of site.

When 1, the wind-powered electricity generation unit moves on rated wind speed, need to be regulated propeller pitch angle to reduce the energy capture of wind wheel, thereby be regulated the active power generating capacity.In the variable pitch process, pneumatic equipment blades made can bear the variable pitch load that aerodynamic force causes, with the aerodynamic loading of momentum-foline theoretical analysis and calculation wind-powered electricity generation unit, sets up nonlinear function.The variable pitch load caused by air force can be expressed as:

$M_Z={\&Integral;}_0^R{\mathrm{dM}}_Z={\&Integral;}_0^{R}0.5\mathrm{\&rho;}{\mathrm{<figure-callout\; id="1"\; label="v"\; filenames="HDA00003365232900011.png"\; state="\{\{state\}\}">v</figure-callout>}}_1^2\mathrm{<figure-callout\; id="2"\; label="c\; C\; l"\; filenames="DEST\_PATH\_130929140203.png,HDA00003365232900011.png"\; state="\{\{state\}\}">c</figure-callout>}\sqrt{{C_l}^{}}\sqrt{{{}_{}}^2+{{\mathrm{<figure-callout\; id="2"\; label="C\; d"\; filenames="DEST\_PATH\_130929140203.png,HDA00003365232900011.png"\; state="\{\{state\}\}">C</figure-callout>}}_d}^2}\&CenterDot;\mathrm{BC}\sin (\mathrm{\&beta;}+\mathrm{\&theta;})\mathrm{dr}---\left(16\right)$

Wherein: C _lfor lift coefficient; C _dfor resistance coefficient; β is propeller pitch angle; θ is for making a concerted effort and the tangential force angle.

Can find out, the variable pitch load that air force causes is relevant with pitch angle, so change propeller pitch angle, can change the wind energy conversion system aerodynamic load.Yet, under same wind speed, propeller pitch angle is less, the wind energy that wind energy conversion system is caught is larger, and the wind energy conversion system bearing load is also larger simultaneously, so wind energy conversion system load becomes a short slab of restriction unit safety stable operation.In order to prevent excessive variable pitch load infringement unit useful life, when the research variable pitch, must be assessed unit load, make the load risk minimization.Resistance coefficient C wherein _dthe active loss that representing variable pitch load causes to a great extent.

$C_d=\frac{2}{\mathrm{\&rho;}\&times;{{\mathrm{<figure-callout\; id="1"\; label="v"\; filenames="HDA00003365232900011.png"\; state="\{\{state\}\}">v</figure-callout>}}_1}^2\&times;c}\&times;\frac{\mathrm{dD}}{\mathrm{dr}}---\left(17\right)$

Wherein ρ is atmospheric density; v ₁for air velocity; C is radius R place blade chord length; DD is the resistance acted on blade; Dr is foline thickness.

β is propeller pitch angle, with the relation of wind speed as shown in Figure 3; α is inflow angle,

relation as shown in Figure 4, can find out and present within the specific limits sinusoidal characteristic, thus by its draft into:

So

can obtain by (18).

Wherein

relation also can obtain by the data of real-time measurement.So finally can obtain relation meritorious and resistance coefficient.

$\frac{\mathrm{dP}}{{\mathrm{dC}}_d}=\frac{\mathrm{dP}}{\mathrm{d\&beta;}}\&CenterDot;\frac{\mathrm{d\&beta;}}{\mathrm{d\&alpha;}}\&CenterDot;\frac{\mathrm{d\&alpha;}}{d{C}_d}---\left(19\right)$

2, system frequency exceeds the limit value f of setting _a<f<f _bor f _c<f<f _dthe time, the wind-powered electricity generation unit adjusts power, and the responding system frequency change is specially:

$\mathrm{\&Delta;f}=\left\{\begin{array}{cc}\frac{\mathrm{\&Delta;p}(f_a-f_b)}{1-p_{\mathrm{bc}}}& f_a<f<f_b\\ \frac{\mathrm{\&Delta;p}(f_c-f_d)}{p_{\mathrm{bc}}-p_d}& f_c<f<f_d\end{array}\right.---\left(20\right)$

Wherein Δ p is for needing meritorious the exerting oneself of adjusting; p _bcfor meritorious the exerting oneself under wind-powered electricity generation unit unloading running status; f _b, f _cfor the wind-powered electricity generation unit of setting does not participate in the frequency upper limit value and lower limit value of frequency modulation; f _a, f _dupper limit value and lower limit value for the wind-powered electricity generation unit frequency modulation section set; p _dfor f _dmeritorious the exerting oneself that point is corresponding.Each amount is per unit value, meritorious exert oneself of power reference value for being determined by wind speed, and frequency reference value is rated frequency 50Hz.

The 5th step, for the external condition of wind energy turbine set operation, be divided into ration the power supply operation and the operation of not rationing the power supply, and both of these case finally all carries out the meritorious adjustment of exerting oneself of wind energy turbine set.Top tried to achieve optimization aim is brought in target function.

1, the situation of rationing the power supply: optimization aim for and frequency fluctuation Δ f and the P of site _l.When

the time, need be become oar and be controlled Δ β.P _reffor dispatching the meritorious output valve of given wind field.Now optimization aim need increase variable pitch pneumatic drag coefficient C _d.Now target function is as follows:

$f_x=\left\{\begin{array}{cc}{h}_1{C}_d+h_2{P}_L+h_3\mathrm{\&Delta;f}& (P_B\left(k\right)+\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{P}_i\left(k\right)\&GreaterEqual;P_{\mathrm{ref}})\\ h_2{P}_L+h_3\mathrm{\&Delta;f}& (P_B\left(k\right)+\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{P}_i\left(k\right)\&le;P_{\mathrm{ref}})\end{array}\right.---\left(21\right)$

2, the situation of not rationing the power supply: when wind speed υ is less than rated wind speed υ _rthe time, blower fan is carried out to maximal power tracing and control MPPT, optimization aim Δ f and P _l; When wind speed υ is less than or equal to rated wind speed υ _rthe time, blower fan being become to oar and controlled, optimization aim is C _d, Δ f and P _l.

$\min f_x=\left\{\begin{array}{cc}{l}_2{P}_L+l_3\mathrm{\&Delta;f}& (\mathrm{\&upsi;}<{\mathrm{\&upsi;}}_r,\mathrm{MPPT})\\ l_1{C}_d+l_2{P}_L+l_3\mathrm{\&Delta;f}& (\mathrm{\&upsi;}\&GreaterEqual;{\mathrm{\&upsi;}}_r,\mathrm{\&Delta;\&beta;})\end{array}\right.---\left(22\right)$

Wherein: h ₁, h ₂, h ₃and l ₁, l ₂, l ₃be respectively the weight coefficient when rationing the power supply and not rationing the power supply.

What maximal power tracing was controlled the MPPT employing is optimum tip speed ratio method.The tip speed ratio λ that will maintain wind energy conversion system when wind speed changes remains at optimum value λ _oPTplace, λ _oPTgenerally by calculating or the experiment acquisition, all maximum to the utilance of wind energy at any wind speed apparatus for lower wind machine like this.Fig. 5 is its control principle block diagram, and its input signal using the measured value of wind speed and wind energy conversion system rotating speed as control system, by calculating actual tip speed ratio λ now, then with optimum tip speed ratio λ _oPTcompare, the errors value is sent into controller, and rotation speed of fan is regulated in the output of controller control inverter, thereby guarantees the tip speed ratio optimum.

According to above-mentioned target function (21) (22), constraints is:

The frequency fluctuation range constraint:

Δf≤Δf _bc （23）

Wherein $\mathrm{\&Delta;}{f}_{\mathrm{bc}}=\left\{\begin{array}{c}50(1-f_b)\\ 50(f_c-1)\end{array}\right.,$ For the frequency shift (FS) limit value.

The mains supply Constraints of Equilibrium:

$P_B+\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{P}_i=P_D+P_L---\left(24\right)$

P wherein _ddemand for total load.

The 6th step, use based on particle swarm optimization algorithm and carry out the meritorious optimization of multiple target.

For above-mentioned Multiobjective Optimal Control Problems, adopt particle swarm optimization algorithm to carry out iterative search, ask optimal solution, step is as follows:

Step1: input fan outlet voltage, power factor, main transformer parameter and actual input power, the ratio of virtual voltage and rated voltage, the proportion of goods damageds under case change no-load loss rate and nominal load, propeller pitch angle, the parameters such as inflow angle.Calculate circuit total losses, frequency fluctuation and resistance coefficient in wind field.

Step2: dimension, maximum iteration time and population are set;

Step3: the result obtained in step1 is brought in formula (21) (22), obtain fitness value f _min, make f _minequal the position p of current particle _id ^(t);

Step4: initialized location and speed, calculate the position p of first individual optimal particle _id ^(t), and by this p _id ^(t)be made as the position p of the current global optimum's particle searched out of population _gd ^(t);

Step5: if current particle fitness value is less than individual extreme value, upgrade current individual extreme value p _ibest;

Step6: if current particle fitness value is less than global extremum, upgrade current global extremum p _gbest;

Step7: by formula (25) (26) renewal speed vector and position vector.

V _id ^(t+1)＝w·V _id ^(t)+c ₁r ₁·(p _id ^(t)-X _id ^(t))+c ₂r ₂·(p _gd ^(t)-X _id ^(t))i＝1,2,...,n （25）

X _id ^(t+1)＝X _id ^(t)+V _id ^(t+1),X _id ^min≤X _id ^(t)≤X _id ^maxi＝1,2,...,n （26）

In formula, t is current cycle time; c ₁, c ₂for the particle weight coefficient; ω is inertia weight; r ₁, r ₂for (0,1) interior uniform random number; V _id, X _idit is the Position And Velocity of i dimension particle;

Step8: with the velocity vector after upgrading and position vector, calculate fitness value;

Step9: repeat step5 to step7;

Step10: judgement iterations, satisfied Output rusults; Otherwise get back to Step7.

Claims (2)

1. a control method of being furnished with the distributing active power of wind power field of energy-accumulating power station, it is characterized in that: its step is as follows:

The first step, detect and control and acquisition system is measured wind field wind speed, rotation speed of fan, each unit active power, transformer substation side active power, unit and networking side three-phase voltage, electric current, frequency, power factor, energy-storage system and discharged and recharged power and site power quality data also by SCADA, then these data are sent to control centre by communication cable;

Second step, setting wind power fluctuation and unit output constraints are:

P _i,min≤P _i≤P _i,max （1）

$\left\{\begin{array}{c}\underset{i=\mathrm{0,1},...59}{\max }Y(k-i)-\underset{i=\mathrm{0,1},...59}{\min }Y(k-i)\&le;{\mathrm{\&gamma;}}_1{p}_{\mathrm{rated}}\\ \underset{i=\mathrm{0,1},...1799}{\max }Y(k-i)-\underset{i=\mathrm{0,1},...1799}{\min }Y(k-i)\&le;{\mathrm{\&gamma;}}_{30}{p}_{\mathrm{rated}}\end{array}\right.---\left(2\right)$

(1) formula is the constraint of unit output bound; (2) formula is for considering the wind energy turbine set power fluctuation range constraint of energy-storage system, and in the time window of 1min or 30min, the amplitude of variation of system synthesis power output must be not more than the total specified power output p of wind energy turbine set _ratedγ ₁or γ ₃₀, γ ₁with γ ₃₀by the Grid code regulation, the amplitude of variation of system synthesis power output is that maximum deducts the poor of minimum value;

The 3rd step, by the fan outlet voltage U measured in real time _f, the overhead transmission line electric current I, case becomes proportion of goods damageds β under no-load loss rate and nominal load ₁, β ₂, obtain the circuit total losses P in wind field _l, through arrangement obtain into:

$P_L=3\&times;I^2\&times;r\&times;L+c_1\&times;{U_f}^2+c_2\frac{1}{{\mathrm{\&beta;}}_1}+c_3\frac{1}{{\mathrm{\&beta;}}_2}---\left(3\right)$

C wherein ₁, c ₂, c ₃for coefficient, expression formula is as follows:

$c_1=a^2\&times;\frac{N}{N_1}\&times;P_e\&times;r_c\&times;L_c---\left(4\right)$

$c_2=\frac{N\&times;S_t}{100}---\left(5\right)$

$c_3=\frac{N\&times;a^2\&times;{P_e}^2}{100\&times;S_t}---\left(6\right)$

Wherein: a is the power stage coefficient; N is the blower fan number; P _efor every Fans rated capacity; I is the overhead transmission line current value; R is overhead wire resistance per unit length value; The length that L is each circuit of overhead wire; N ₁for fan outlet cable number; S _tfor the case varying capacity; r _cresistance value for the cable unit length; L _cfor cable length;

The 4th step, calculate two other optimization aim: variable pitch pneumatic drag coefficient C _d, and the frequency fluctuation Δ f of site:

$\mathrm{\&Delta;f}=\left\{\begin{array}{cc}\frac{\mathrm{\&Delta;p}(f_a-f_b)}{1-p_{\mathrm{bc}}}& f_a<f<f_b\\ \frac{\mathrm{\&Delta;p}(f_c-f_d)}{p_{\mathrm{bc}}-p_d}& f_c<f<f_d\end{array}\right.---\left(7\right)$

Δ p is for needing meritorious the exerting oneself of adjusting; p _bcfor meritorious the exerting oneself under wind-powered electricity generation unit unloading running status; f _b, f _cfor the wind-powered electricity generation unit of setting does not participate in the frequency upper limit value and lower limit value of frequency modulation; f _a, f _dupper limit value and lower limit value for the wind-powered electricity generation unit frequency modulation section set; p _dfor f _dmeritorious the exerting oneself that point is corresponding;

$\frac{\mathrm{dP}}{{\mathrm{dC}}_d}=\frac{\mathrm{dP}}{\mathrm{d\&beta;}}\&CenterDot;\frac{\mathrm{d\&beta;}}{\mathrm{d\&alpha;}}\&CenterDot;\frac{\mathrm{d\&alpha;}}{d{C}_d}---\left(8\right)$

Wherein: β is that propeller pitch angle, α are inflow angle, but the measurement data of being;

The 5th step, for the external condition of wind energy turbine set operation, be divided into ration the power supply operation and the operation of not rationing the power supply, and both of these case finally all carries out the meritorious adjustment of exerting oneself of wind energy turbine set, and top tried to achieve optimization aim is brought in target function;

The situation of rationing the power supply: optimization aim for and frequency fluctuation Δ f and the P of site _l.When

the time, P _reffor dispatching the meritorious output valve of given wind field, need be become oar and be controlled Δ β, now optimization aim need increase variable pitch pneumatic drag coefficient C _d, now target function is as follows:

${\min f}_x=\left\{\begin{array}{cc}{h}_1{C}_d+h_2{P}_L+h_3\mathrm{\&Delta;f}& (P_B\left(k\right)+\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{P}_i\left(k\right)\&GreaterEqual;P_{\mathrm{ref}})\\ h_2{P}_L+h_3\mathrm{\&Delta;f}& (P_B\left(k\right)+\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{P}_i\left(k\right)\&le;P_{\mathrm{ref}})\end{array}\right.---\left(9\right)$

The situation of not rationing the power supply: when wind speed υ is less than rated wind speed υ _rthe time, blower fan is carried out to maximal power tracing and control MPPT, optimization aim Δ f and P _l; When wind speed υ is less than or equal to rated wind speed υ _rthe time, blower fan being become to oar and controlled, optimization aim is C _d, Δ f and P _l;

$\min f_x=\left\{\begin{array}{cc}{l}_2{P}_L+l_3\mathrm{\&Delta;f}& (\mathrm{\&upsi;}<{\mathrm{\&upsi;}}_r,\mathrm{MPPT})\\ l_1{C}_d+l_2{P}_L+l_3\mathrm{\&Delta;f}& (\mathrm{\&upsi;}\&GreaterEqual;{\mathrm{\&upsi;}}_r,\mathrm{\&Delta;\&beta;})\end{array}\right.---\left(10\right)$

Wherein: h ₁, h ₂, h ₃and l ₁, l ₂, l ₃be respectively the weight coefficient when rationing the power supply and not rationing the power supply,

Constraints is:

Δf≤Δf _bc （11）

$P_B+\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{P}_i=P_D+P_L---\left(12\right)$

(11) frequency fluctuation range constraint, Δ f _bcfor the frequency shift (FS) limit value; (12) mains supply Constraints of Equilibrium, P _ddemand for total load;

The 6th step, use the vehicle route optimized algorithm based on population to carry out the meritorious optimization of multiple target.

2. control method of being furnished with the distributing active power of wind power field of energy-accumulating power station according to claim 1 is characterized in that:

For above-mentioned Multiobjective Optimal Control Problems, adopt particle swarm optimization algorithm to carry out iterative search, ask optimal solution, step is as follows:

1.: input fan outlet voltage, power factor, main transformer parameter and actual input power, the ratio of virtual voltage and rated voltage, the proportion of goods damageds under case change no-load loss rate and nominal load, propeller pitch angle, the parameters such as inflow angle.Calculate the circuit total losses in wind field, frequency fluctuation and resistance coefficient;

2.: dimension, maximum iteration time and population are set;

3.: the result obtained in step1 is brought in formula (9) (10), obtain fitness value f _min, make f _minequal the position p of current particle _id ^(t);

4.: initialized location and speed, calculate the position p of first individual optimal particle _id ^(t), and by this p _id ^(t)be made as the position p of the current global optimum's particle searched out of population _gd ^(t);

5.: if current particle fitness value is less than individual extreme value, upgrade current individual extreme value p _ibest;

6.: if current particle fitness value is less than global extremum, upgrade current global extremum p _gbest;

7.: by formula (25) (26) renewal speed vector and position vector;

V _id ^(t+1)＝w·V _id ^(t)+c ₁r ₁·(p _id ^(t)-X _id ^(t))+c ₂r ₂·(p _gd ^(t)-X _id ^(t))i＝1,2,...,n （25）

X _id ^(t+1)＝X _id ^(t)+V _id ^(t+1),X _id ^min≤X _id ^(t)≤X _id ^maxi＝1,2,...,n （26）

In formula, t is current cycle time; c ₁, c ₂for the particle weight coefficient; ω is inertia weight; r ₁, r ₂for (0,1) interior uniform random number; V _id, X _idit is the Position And Velocity of i dimension particle;

Step8: with the velocity vector after upgrading and position vector, calculate fitness value;

Step9: repeat step5 to step7;

Step10: judgement iterations, satisfied Output rusults; Otherwise get back to Step7.

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