CN103887808A - Wind farm energy storage lithium-ion electricity optimizing control method based on set inertial energy storage - Google Patents

Abstract

The invention discloses a wind farm energy storage lithium-ion electricity optimizing control method based on set inertial energy storage, and relates to a wind farm hybrid energy storage system combined mode and a capacity control method thereof. The wind farm energy storage lithium-ion electricity optimizing control method based on set inertial energy storage is characterized by comprising the following steps that (1) wind farm prediction capture power in a traditional control mode is calculated according to a wind farm prediction wind speed; (2) fast Fourier transform is conducted on the wind farm prediction power, so that a wind electricity power spectral characteristic curve, an output power high-frequency signal and an output power low-frequency signal are obtained; (3) the high-frequency component for restraining active output power of a set is stored through inertial kinetic energy of the set itself when wind farm output power undergoes primary smoothing; (4) a lithium battery is used for energy storage so that a smoothing task to the low-frequency component of wind farm output power waves can be achieved; (5) an evaluation index is established, and wind farm lithium battery capacity is controlled in an optimizing mode. According to the technical scheme, electric energy quality and energy storage economic benefits can be improved, and the service life of batteries is prolonged.

Description

The electrically optimized control method of wind energy turbine set energy storage lithium based on unit set inertia energy storage

Technical field

The invention belongs to active power of wind power field control technology field, refer more particularly to energy-storage system progress control method.

Background technology

Wind power generation is the important channel that solves environmental pollution and energy crisis, is that China realizes the strategic emphasis of " adjusting structure, short transition " and the main direction of development low-carbon economy, the emphasis of Ye Shi China energy development.But wind energy has the fluctuation that randomness, intermittence cause wind-powered electricity generation, bring the wind-powered electricity generation quality of power supply and the challenge of the aspect of dissolving.Energy-storage system can absorb and release energy by control strategy, is the available means of smooth wind power power output.

The energy storage mode that can be used for wind energy turbine set mainly comprises chemical cell energy storage, flywheel energy storage, Power Flow, the energy storage of drawing water, compressed-air energy storage, unit set inertia energy storage.Because chemical cell energy-storage system response speed is slow, be difficult to the wind power fluctuation of level and smooth 0.01～1Hz, and electric power system is very responsive to the power fluctuation of this frequency range.The flywheel energy storage response time is fast, and has extended cycle life, easy to maintenance, has good development prospect, but is badly in need of breaking through at technical elements such as rotor strength design, low-watt consumption magnetic bearings at present.Power Flow comprises superconducting energy storage and ultracapacitor energy storage, these two kinds of energy storage modes itself have that probability density is high, charge and discharge circulation life is long, the charging interval is short, high reliability, but price is too expensive, and capacitor voltage endurance capability is not high enough, should not be in wind energy turbine set large capacity applications.In addition, from drawing water, smooth wind power field power output is defeated on a large scale with compressed-air energy storage, but is subject to the constraint of geographical conditions, and construction bureau is sex-limited large, cannot extensive use.Wind turbine group rotor inertia energy storage, by regulating rotary rotor speed, is temporarily stored in the part wind energy of catching on rotor with the form of kinetic energy, in needs, discharges.This kind of energy storage mode fast response time, energy density is high, effectively smooth high frequencies power fluctuation, but due to rotor stored energy capacitance and limited time, be difficult to suppress low frequency power fluctuation.

Visible, single energy storage mode is difficult to the wind energy turbine set power smooth effect that reaches desirable.Therefore need suitable energy storage mode to combine, realize output power fluctuation of wind farm level and smooth by hybrid energy-storing; Need suitable energy-storage system progress control method, in promoting the quality of power supply, extend energy storage device useful life, reduce energy storage investment and maintenance cost.

Summary of the invention

The present invention utilizes the inertia energy storage of unit own and the complementation of two kinds of mode characteristics of lithium battery energy storage battery, composition mixed energy storage system.Tradition output power fluctuation of wind farm major part is between 0.01～1Hz, and energy mainly concentrates on 0～10 ^-4hz.Utilize the inertia kinetic energy storage of unit own to suppress high fdrequency component between 0.01～1Hz and the crest value in the short time, provide a kind of electrically optimized control method of wind energy turbine set energy storage lithium based on inertia energy storage, the level and smooth power low-frequency fluctuation (10 of lithium battery energy storage battery simultaneously ^-5～0.01Hz) part, the method considers the factors such as the economic benefit, lithium battery life-span, the level and smooth target of power of energy-storage system, solves in battery energy storage running, frequently to discharge and recharge conversion and overcharge and cross to put operating state the lithium battery life-span brought to adverse effect problem.

For realizing above-mentioned target, the invention provides a kind of electrically optimized control method of wind energy turbine set energy storage lithium based on unit set inertia energy storage, it specifically comprises the following steps:

1, according to wind energy turbine set prediction of wind speed, calculate wind energy turbine set under traditional control model and predict the power of catching,

$P_w^f\left(t\right)=\left\{\begin{array}{cc}0& v_f\left(t\right)<v_{\mathrm{in}},v_f\left(t\right)>v_{\mathrm{out}}\\ 0.5\mathrm{\&rho;}{\mathrm{AC}}_p(\mathrm{\&lambda;},\mathrm{\&beta;})v_f^3\left(t\right)& v_{\mathrm{in}}<v_f\left(t\right)<v_{\mathrm{rate}}\\ P_{\mathrm{rate}}& v_{\mathrm{rate}}<v_f\left(t\right)<v_{\mathrm{out}}\end{array}\right.---\left(1\right)$

In formula:

expression unit is predicted the wind power of catching; v _f(t) represent wind energy turbine set prediction of wind speed; ρ represents atmospheric density; v _in, v _rate, v _outrepresent respectively incision wind speed, rated wind speed and the output wind speed of wind-powered electricity generation unit; A is impeller wind sweeping area; C _p(λ, β) is power coefficient.

The all wind-powered electricity generation units of wind energy turbine set were predicted and are caught power summation in the t moment:

$P_{\mathrm{tot}}^f\left(t\right)=\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{P}_{\mathrm{wi}}^f\left(t\right)---\left(2\right)$

In formula: n represents wind energy turbine set unit number of units;

divide and represent that power summation is caught in the prediction of t moment wind energy turbine set and power is caught in the prediction of i platform unit.

2, to wind energy turbine set, power is caught in prediction

carry out Fourier transform, obtain wind power amplitude-versus-frequency curve, be divided into high and low frequency two parts, the frequency that HFS covers is 0.01～1Hz, and the frequency that low frequency part covers is 10 ^-5～0.01Hz.

3, utilize the inertia kinetic energy storage of unit own level and smooth for the first time when Power Output for Wind Power Field is carried out, suppress the meritorious high fdrequency component of exerting oneself of unit, comprise the steps:

(3-1) set up traditional control model leeward group of motors system model.

$P_w^f\left(t\right)=k{\mathrm{\&omega;}}_m^3\left(t\right)---\left(3\right)$

$J\frac{d{\mathrm{\&omega;}}_m\left(t\right)}{\mathrm{dt}}=T_m-T_e---\left(4\right)$

In formula, ω _m(t) represent t moment system mechanics rotating speed; K=0.5 ρ C _p(λ, β) RA/ λ, λ=R ω _m/ v _f, represent tip speed ratio; R represents impeller radius; T _mrepresent the torque of wind-powered electricity generation unit; T _efor the electromagnetic torque of generator; J represents system equivalent moment of inertia.

(3-2) calculate wind-powered electricity generation unit power change values Δ E _w.The wind-powered electricity generation power of the assembling unit is caught power in prediction

p between level and smooth rear power output for the first time _out(t) change, changing value is by rotor storage kinetic energy Δ E _kcompensate, specific as follows shown in:

$\mathrm{\&Delta;}{E}_w={\&Integral;}_0^T(P_w^f\left(t\right)-P_{\mathrm{out}}\left(t\right))\mathrm{dt}---\left(5\right)$

ΔE _u＝ΔE _k (6)

Rotor storage capacity is subject to the restriction of generating unit speed, inertia kinetic energy memory range represent the maximum (top) speed that wind-powered electricity generation unit can bear; ω _minthe minimum speed allowing while representing to generate electricity by way of merging two or more grid systems.

(3-3), on traditional wind turbine model, set up the control system of wind turbines based on the storage of rotor inertia kinetic energy.

1) traditional control model leeward group of motors system model being done to linearization process obtains

Δ E _kwith Δ P _outbetween three, relation is as follows:

$\mathrm{\&Delta;}{P}_w^f={\mathrm{J\&omega;}}_{\mathrm{<figure-callout\; id="0"\; label="m"\; filenames="HSA0000102476680000021.png,HSA0000102476680000032.png"\; state="\{\{state\}\}">m</figure-callout>}0}\frac{\mathrm{d\&Delta;}{\mathrm{\&omega;}}_m}{\mathrm{dt}}+\mathrm{\&Delta;}{P}_{\mathrm{out}}---\left(7\right)$

In formula, P (t)=T ω _m(t), T is torque, and P (t) is t moment active power;

represent to predict and catch power change values; Δ P _outrepresent wind-powered electricity generation unit level and smooth power output changing value for the first time; Δ ω _mbe expressed as the mechanical separator speed changing value of system; 0 subscript represents systematic steady state amount, lower same.

2) utilize partial differentiation, ask for respectively

and P _out(t) small-signal disturbance:

$\mathrm{\&Delta;}{\tilde{P}}_w^f=\frac{{\mathrm{\&lambda;}}_0{{\mathrm{<figure-callout\; id="0"\; label="C\; p"\; filenames="HSA0000102476680000021.png,HSA0000102476680000032.png"\; state="\{\{state\}\}">C</figure-callout>}}_p}^{\&prime;}}{C_{p0}}(\mathrm{\&Delta;}{\widetilde{\mathrm{\&omega;}}}_m-\mathrm{\&Delta;}{\tilde{v}}_f)+3\mathrm{\&Delta;}{\tilde{v}}_f---\left(8\right)$

$\mathrm{\&Delta;}{\tilde{P}}_{\mathrm{out}}=\frac{\mathrm{\&Delta;}{P}_{\mathrm{out}}}{P_{w0}^f}=\frac{3k{\mathrm{\&omega;}}_{\mathrm{<figure-callout\; id="0"\; label="m"\; filenames="HSA0000102476680000021.png,HSA0000102476680000032.png"\; state="\{\{state\}\}">m</figure-callout>}0}^3}{P_{w0}^f}\mathrm{\&Delta;}{\widetilde{\mathrm{\&omega;}}}_m---\left(9\right)$

In formula, when stable state, have

and

about v _fand ω (t) _m(t) function lambda ₀=R ω _m0/ v _f0c _p0'=dC _p(λ)/d λ: $\mathrm{\&Delta;}{\tilde{P}}_w^f=\mathrm{\&Delta;}{P}_w^f/P_{w0}^f;\mathrm{\&Delta;}{\widetilde{\mathrm{\&omega;}}}_m=\mathrm{\&Delta;}{\mathrm{\&omega;}}_m/{\mathrm{\&omega;}}_{\mathrm{<figure-callout\; id="0"\; label="m"\; filenames="HSA0000102476680000021.png,HSA0000102476680000032.png"\; state="\{\{state\}\}">m</figure-callout>}0};\mathrm{\&Delta;}{\tilde{v}}_f=\mathrm{\&Delta;}{v}_f/\mathrm{\&Delta;}{\mathrm{<figure-callout\; id="0"\; label="v\; f"\; filenames="HSA0000102476680000021.png,HSA0000102476680000032.png"\; state="\{\{state\}\}">v</figure-callout>}}_f.$

3) carrying out the controlled ssystem transfer function of Laplace transform is:

$G\left(s\right)=\frac{\mathrm{\&Delta;}{\tilde{P}}_{\mathrm{out}}\left(s\right)}{\mathrm{\&Delta;}{\tilde{v}}_f\left(s\right)}=\frac{3}{1+\frac{J}{3k{\mathrm{\&omega;}}_{m0}}}---\left(10\right)$

Adopt wind-powered electricity generation unit control based on the storage of rotor inertia kinetic energy can to whole system fluctuation play the effect of low pass filter, its cut-off frequency is according to fan performance curve, moment of inertia and the adjusting of unit steady-state speed.System is carried out once level and smooth to power output by the inertia kinetic energy storage of unit own, suppress high fdrequency component.

4,, according to predicted power confidential interval, determine the wind energy turbine set plan P that exerts oneself _plan(t), set up lithium battery capacity E _band the Mathematical Modeling between the battery charging and discharging time, by regulate the charging and discharging lithium battery time control lithium battery capacity, complete to output power fluctuation of wind farm in 10 ^-5the level and smooth task of low frequency component between～0.01Hz, power output is followed the tracks of wind energy turbine set plan and is exerted oneself.

(4-1) wind energy turbine set short term scheduling strategy.According to the confidential interval of power output after the storage of unit set inertia kinetic energy is stabilized

while determining charging and discharging lithium battery, plan to exert oneself P _plan(t).When lithium cell charging, by wind energy turbine set prediction power output confidential interval lowest power curve

definite plan P that exerts oneself _plan(t); When lithium battery electric discharge, according to wind energy turbine set prediction power output confidential interval maximum power curve

definite plan P that exerts oneself _plan(t), after lithium battery energy storage battery secondary is level and smooth, power output tracking plan is exerted oneself.

$P_{\mathrm{plan}}\left(t\right)=P_{\mathrm{all}}^f\left(t\right)+P_{\mathrm{bess}}\left(t\right)---\left(11\right)$

In formula, P _bess(t) represent lithium battery stores power;

p when charging _bess(t) get negative, P when electric discharge _bess(t) just get;

(4-2) the control model of capacity when lithium cell charging:

$E_b={\&Integral;}_{t_i}^{t_{i+1}}[P_{\mathrm{all}}^f\left(t\right)-P_{\mathrm{plan}}\left(t\right)]\mathrm{dt}\&times;{\mathrm{\&eta;}}_{\mathrm{loss}}+E_0---\left(12\right)$

T ₁(i)＝t _i+1-t _i (13)

In formula: at the i time interval [t _i, t _i+1],

represent wind energy turbine set prediction power output confidential interval lowest power curve

upper minimum value; E _brepresent lithium battery rated capacity; E ₀represent lithium battery initial capacity; η _lossrepresent the capacity loss in charging process; T ₁(i) represent the charging interval.

(4-3) the control model of capacity when lithium battery discharges:

$E_b={\&Integral;}_{t_{i+1}}^{t_{i+2}}[P_{\mathrm{plan}}-P_{\mathrm{all}}^f\left(t\right)]\mathrm{dt}\&times;{\mathrm{\&eta;}}_{\mathrm{loss}}+E_0---\left(14\right)$

T ₂(i+1)＝t _i+2-t _i+1 (15)

T ₁+T ₂＞T (16)

In formula: at the i+1 time interval [t _i+1, t _i+2],

represent wind energy turbine set prediction power output confidential interval peak power curve

upper maximum; T ₂(i+1) represent discharge time, T is the programming dispatching time.

5, the balance based between battery life and mixed energy storage system cost, and consider that lithium battery energy storage battery discharges and recharges number of times and discharges and recharges the impact of the degree of depth on battery life, controls lithium battery capacity.According to wind energy turbine set prediction power output confidential interval, obtain different lithium battery capacity values, set up energy-storage system performance index s, by reducing performance index, finally determine lithium battery capacity value.S is as follows for its performance index:

$\min s=\frac{\mathrm{\&alpha;}+\mathrm{\&beta;}{E}_b}{L_b}---\left(17\right)$

In formula: α represents the initial fixed investment of lithium battery energy storage battery system; The required investment of the β unit of representative stored energy capacitance; L _brepresent the lithium battery life-span.

A kind of electrically optimized control method of wind energy turbine set energy storage lithium based on inertia energy storage proposed by the invention, utilizes the inertia kinetic energy storage of unit own and the complementation of two kinds of mode characteristics of lithium battery energy storage battery, composition mixed energy storage system.A kind of lithium battery capacity control method and a kind of short term scheduling strategy of considering battery life and energy storage cost is provided.Compared with existing energy storage technology, can solve single battery energy storage technology and be applied to the operating state problem that frequently discharges and recharges conversion and super-charge super-discharge existing when wind farm grid-connected; Adopt with different levels method plan exerted oneself to wind energy turbine set that to carry out power level and smooth, reach the lifting quality of power supply, improved electrical network to the dissolve object of ability of wind energy turbine set, do not increasing under the prerequisite of equipment cost simultaneously, reduce wind energy turbine set energy storage scale, reduced energy storage cost.

Brief description of the drawings

Fig. 1 is a kind of concrete implementation mode of the electrically optimized control method of wind energy turbine set energy storage lithium flow chart based on unit set inertia energy storage of the present invention.

Fig. 2 is the electrically optimized control method system of the wind energy turbine set energy storage lithium control block diagram based on unit set inertia energy storage.

Fig. 3 is unit set inertia kinetic energy storage control principle drawing.

Fig. 4 is that power profile is caught in wind energy turbine set prediction.

Fig. 5 is that wind energy turbine set is caught power amplitude-versus-frequency curve

Fig. 6 is Power Output for Wind Power Field curve after the inertia energy storage of unit own is level and smooth.

Fig. 7 is power stage value and wind energy turbine set plan value of exerting oneself after the inertia kinetic energy storage of unit own is once level and smooth.

Fig. 8 is the lithium battery residual capacity (SOC) of exerting oneself corresponding with plan.

Fig. 9 is the lithium battery optimum capacity under different predicted power confidence levels.

Embodiment

Utilize accompanying drawing and example to further illustrate a kind of electrically optimized control method of wind energy turbine set energy storage lithium based on unit set inertia energy storage of the present invention.Should be noted that it is only exemplary the following describes, instead of in order to limit the scope of the invention with and to apply.

Method of the present invention is: first according to the prediction of wind speed of predicting wind speed of wind farm system, calculate wind energy turbine set under traditional control model and predict the power of catching; Then wind energy turbine set prediction is caught to power and carry out Fourier transform, obtain the power signal of wind power spectral characteristic curve and different frequency range; Then utilize again the inertia kinetic energy storage of unit own to carry out Power Output for Wind Power Field level and smooth for the first time, the high fdrequency component of filtering output-power fluctuation between 0.01～1Hz and the crest value in the short time; Finally utilize lithium battery energy storage battery complete to output power fluctuation of wind farm in 10 ^-5the level and smooth task of low frequency component between～0.01Hz is considered battery life and energy storage economic benefit, optimal control lithium battery capacity simultaneously.As shown in Figure 1, Fig. 2 represents system architecture diagram to detailed operation flow chart.

The electrically optimized control method embodiment of wind energy turbine set energy storage lithium based on inertia kinetic energy storage that this patent proposes is as follows:

1, according to wind energy turbine set prediction of wind speed, calculate wind energy turbine set under traditional control model and predict the power of catching,

$P_w^f\left(t\right)=\left\{\begin{array}{cc}0& v_f\left(t\right)<v_{\mathrm{in}},v_f\left(t\right)>v_{\mathrm{out}}\\ 0.5\mathrm{\&rho;}{\mathrm{AC}}_p(\mathrm{\&lambda;},\mathrm{\&beta;})v_f^3\left(t\right)& v_{\mathrm{in}}<v_f\left(t\right)<v_{\mathrm{rate}}\\ P_{\mathrm{rate}}& v_{\mathrm{rate}}<v_f\left(t\right)<v_{\mathrm{out}}\end{array}\right.---\left(1\right)$

In formula:

expression unit is predicted the wind power of catching; v _f(t) represent wind energy turbine set prediction of wind speed; ρ represents atmospheric density; v _in, v _rate, v _outrepresent respectively incision wind speed, rated wind speed and the output wind speed of wind-powered electricity generation unit; A is impeller wind sweeping area; C _p(λ, β) is power coefficient.

The all wind-powered electricity generation units of wind energy turbine set were predicted and are caught power summation in the t moment:

$P_{\mathrm{tot}}^f\left(t\right)=\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{P}_{\mathrm{wi}}^f\left(t\right)---\left(2\right)$

In formula: n represents wind energy turbine set unit number of units;

divide and represent that power summation is caught in the prediction of t moment wind energy turbine set and power is caught in the prediction of i platform unit.

2, to wind energy turbine set, power is caught in prediction

carry out Fourier transform, obtain wind power amplitude-versus-frequency curve, be divided into high and low frequency two parts, the frequency that HFS covers is 0.01～1Hz, and the frequency that low frequency part covers is 10 ^-5～0.01Hz.

3, utilize the inertia kinetic energy storage of unit own level and smooth for the first time when Power Output for Wind Power Field is carried out, suppress the meritorious high fdrequency component of exerting oneself of unit.Comprise the steps:

(3-1) set up traditional control model leeward group of motors system model.

$P_w^f\left(t\right)=k{\mathrm{\&omega;}}_m^3\left(t\right)---\left(3\right)$

$J\frac{d{\mathrm{\&omega;}}_m\left(t\right)}{\mathrm{dt}}=T_m-T_e---\left(4\right)$

In formula, ω _m(t) represent t moment system mechanics rotating speed; K=0.5 ρ c _p(λ, β) RA/ λ, λ=R ω _m/ v _f, represent tip speed ratio; R represents impeller radius; T _mrepresent the torque of wind-powered electricity generation unit; T _efor the electromagnetic torque of generator; J represents system equivalent moment of inertia.

(3-2) calculate wind-powered electricity generation unit power change values Δ E _w.The wind-powered electricity generation power of the assembling unit is caught power in prediction

p between level and smooth rear power output for the first time _out(t) change, changing value is by rotor storage kinetic energy Δ E _kcompensate, specific as follows shown in:

$\mathrm{\&Delta;}{E}_w={\&Integral;}_0^T(P_w^f\left(t\right)-P_{\mathrm{out}}\left(t\right))\mathrm{dt}---\left(5\right)$

ΔE _w＝ΔE _k (6)

Rotor storage capacity is subject to the restriction of generating unit speed, inertia kinetic energy memory range

ω _maxrepresent the maximum (top) speed that wind-powered electricity generation unit can bear; ω _minthe minimum speed allowing while representing to generate electricity by way of merging two or more grid systems.

(3-3) on traditional wind turbine model, set up the control system of wind turbines based on the storage of rotor inertia kinetic energy, its step is as follows:

1) traditional control model leeward group of motors system model being done to linearization process obtains

Δ E _kwith Δ P _outbetween three, relation is as follows:

$\mathrm{\&Delta;}{P}_w^f={\mathrm{J\&omega;}}_{\mathrm{<figure-callout\; id="0"\; label="m"\; filenames="HSA0000102476680000021.png,HSA0000102476680000032.png"\; state="\{\{state\}\}">m</figure-callout>}0}\frac{\mathrm{d\&Delta;}{\mathrm{\&omega;}}_m}{\mathrm{dt}}+\mathrm{\&Delta;}{P}_{\mathrm{out}}---\left(7\right)$

In formula, P (t)=T ω _m(t), T is torque, and P (t) is t moment active power;

represent to predict and catch power change values; Δ P _outrepresent wind-powered electricity generation unit level and smooth power output changing value for the first time; Δ ω _mbe expressed as the mechanical separator speed changing value of system; 0 subscript represents systematic steady state amount, lower same.

2) utilize partial differentiation, ask for respectively

and P _out(t) small-signal disturbance:

$\mathrm{\&Delta;}{\tilde{P}}_w^f=\frac{{\mathrm{\&lambda;}}_0{{\mathrm{<figure-callout\; id="0"\; label="C\; p"\; filenames="HSA0000102476680000021.png,HSA0000102476680000032.png"\; state="\{\{state\}\}">C</figure-callout>}}_p}^{\&prime;}}{C_{p0}}(\mathrm{\&Delta;}{\widetilde{\mathrm{\&omega;}}}_m-\mathrm{\&Delta;}{\tilde{v}}_f)+3\mathrm{\&Delta;}{\tilde{v}}_f---\left(8\right)$

$\mathrm{\&Delta;}{\tilde{P}}_{\mathrm{out}}=\frac{\mathrm{\&Delta;}{P}_{\mathrm{out}}}{P_{w0}^f}=\frac{3k{\mathrm{\&omega;}}_{\mathrm{<figure-callout\; id="0"\; label="m"\; filenames="HSA0000102476680000021.png,HSA0000102476680000032.png"\; state="\{\{state\}\}">m</figure-callout>}0}^3}{P_{w0}^f}\mathrm{\&Delta;}{\widetilde{\mathrm{\&omega;}}}_m---\left(9\right)$

In formula, when stable state, have

and

about v _fand ω (t) _m(t) function lambda ₀=R ω _m0/ v _f0c _p0'=dC _p(λ)/d λ; $\mathrm{\&Delta;}{\tilde{P}}_w^f=\mathrm{\&Delta;}{P}_w^f/P_{w0}^f;\mathrm{\&Delta;}{\widetilde{\mathrm{\&omega;}}}_m=\mathrm{\&Delta;}{\mathrm{\&omega;}}_m/{\mathrm{\&omega;}}_{\mathrm{<figure-callout\; id="0"\; label="m"\; filenames="HSA0000102476680000021.png,HSA0000102476680000032.png"\; state="\{\{state\}\}">m</figure-callout>}0};\mathrm{\&Delta;}{\tilde{v}}_f=\mathrm{\&Delta;}{v}_f/\mathrm{\&Delta;}{\mathrm{<figure-callout\; id="0"\; label="v\; f"\; filenames="HSA0000102476680000021.png,HSA0000102476680000032.png"\; state="\{\{state\}\}">v</figure-callout>}}_f.$

3) carrying out the controlled ssystem transfer function of Laplace transform is:

$G\left(s\right)=\frac{\mathrm{\&Delta;}{\tilde{P}}_{\mathrm{out}}\left(s\right)}{\mathrm{\&Delta;}{\tilde{v}}_f\left(s\right)}=\frac{3}{1+\frac{J}{3k{\mathrm{\&omega;}}_{m0}}}---\left(10\right)$

Adopt wind-powered electricity generation unit control based on the storage of rotor inertia kinetic energy can to whole system fluctuation play the effect of low pass filter, its cut-off frequency is according to fan performance curve, moment of inertia and the adjusting of unit steady-state speed.System is carried out once level and smooth to power output by the inertia kinetic energy storage of unit own, suppress high fdrequency component.

4,, according to predicted power confidential interval, determine the wind energy turbine set plan P that exerts oneself _plan(t), set up lithium battery capacity E _band the functional relation between the battery charging and discharging time, by regulate the charging and discharging lithium battery time control lithium battery capacity, complete to output power fluctuation of wind farm in 10 ^-5the level and smooth task of low frequency component between～0.01Hz, power output is followed the tracks of wind energy turbine set plan and is exerted oneself.

(4-1) wind energy turbine set short term scheduling strategy.According to the confidential interval of power output after the storage of unit set inertia kinetic energy is stabilized

while determining charging and discharging lithium battery, plan to exert oneself P _plan(t).When lithium cell charging, by wind energy turbine set prediction power output confidential interval lowest power curve definite plan P that exerts oneself _plan(t); When lithium battery electric discharge, according to wind energy turbine set prediction power output confidential interval maximum power curve

definite plan P that exerts oneself _plan(t), after lithium battery energy storage battery secondary is level and smooth, power output tracking plan is exerted oneself.

$P_{\mathrm{plan}}\left(t\right)=P_{\mathrm{all}}^f\left(t\right)+P_{\mathrm{bess}}\left(t\right)---\left(11\right)$

In formula, P _bess(t) represent lithium battery stores power;

p when charging _bess(t) get negative, P when electric discharge _bess(t) just get;

(4-2) the control model of capacity when lithium cell charging:

$E_b={\&Integral;}_{t_i}^{t_{i+1}}[P_{\mathrm{all}}^f\left(t\right)-P_{\mathrm{plan}}\left(t\right)]\mathrm{dt}\&times;{\mathrm{\&eta;}}_{\mathrm{loss}}+E_0---\left(12\right)$

T ₁(i)＝t _i+1-t _i (13)

In formula: at the i time interval [t _i, t _i+1],

represent wind energy turbine set prediction power output confidential interval lowest power curve

upper minimum value; E _brepresent lithium battery rated capacity; E ₀represent lithium battery initial capacity; η _lossrepresent the capacity loss in charging process; T ₁(i) represent the charging interval.

(4-3) the control model of capacity when lithium battery discharges:

$E_b={\&Integral;}_{t_{i+1}}^{t_{i+2}}[P_{\mathrm{plan}}-P_{\mathrm{all}}^f\left(t\right)]\mathrm{dt}\&times;{\mathrm{\&eta;}}_{\mathrm{loss}}+E_0---\left(14\right)$

T ₂(i+1)＝t _i+2-t _i+1 (15)

T ₁+T ₂＞T (16)

In formula: at the i+1 time interval [t _i+1, t _i+2],

represent wind energy turbine set prediction power output confidential interval peak power curve

upper maximum; T ₂(i+1) represent discharge time, T is the programming dispatching time.

5, the balance based between battery life and mixed energy storage system cost, and consider that lithium battery energy storage battery discharges and recharges number of times and discharges and recharges the impact of the degree of depth on battery life, controls lithium battery capacity.When predicted power confidence level is different with standard deviation, obtain different lithium battery capacity values, set up energy-storage system performance index s, by reducing performance index, finally determine lithium battery capacity value.S is as follows for its performance index:

$\min s=\frac{\mathrm{\&alpha;}+\mathrm{\&beta;}{E}_b}{L_b}---\left(17\right)$

In formula: α represents the initial fixed investment of lithium battery energy storage battery system; The required investment of the β unit of representative stored energy capacitance; L _brepresent the lithium battery life-span.

6, embodiment

This example is in conjunction with the basic parameter of the extensive battery energy storage system of the actual construction of domestic somewhere wind energy turbine set, by hybrid energy-storing technology, wind energy turbine set prediction power output is processed, based on inertia kinetic energy storage and the consideration to factors such as energy storage cost, battery lifes, optimal control lithium battery capacity.In example, wind energy turbine set is made up of 10 5MW wind-driven generators, 5MW wind-powered electricity generation unit rated speed ω _rate=135rad/s, unit incision wind speed v _m=3m/s, output wind speed v _out=25m/s, rated wind speed v _rate=11.4m/s.

(6-1) calculate wind energy turbine set under traditional control model according to wind energy turbine set prediction of wind speed value and catch power, and obtain wind power confidential interval according to wind energy turbine set prediction of wind speed confidence level.Wind energy turbine set shown in Fig. 4 through unit set inertia energy storage stabilize after high, medium and low three the section power profiles of power output confidential interval.Fig. 5 is that wind energy turbine set is caught power amplitude-versus-frequency curve, and wind energy turbine set is caught power and obtained amplitude-versus-frequency curve through Fourier transform, and wind energy turbine set is caught power energy and mainly concentrated on 0～10 as can be seen from Figure ^-4low frequency part between Hz, and HFS energy is low.

(6-2) utilize the inertia kinetic energy storage of unit own Power Output for Wind Power Field curve to be carried out level and smooth for the first time.Filtering output electric energy high-frequency fluctuation component (0.01～1Hz) and the crest value in the short time, reduce the demand of wind energy turbine set to lithium battery capacity and the phenomenon frequently discharging and recharging, and optimizes battery capacity control.As shown in Figure 3, upper strata is the control of unit wheel speed to concrete control principle drawing, and intermediate layer is the storage of rotor kinetic energy, and lower floor is frequency control.Fig. 6 is the design sketch before and after the inertia kinetic energy storage of unit own is stabilized Power Output for Wind Power Field.

(6-3) on the basis of unit set inertia kinetic energy storage, utilize lithium battery energy storage battery complete to output power fluctuation of wind farm in 10 ^-5the level and smooth task of low frequency component between～0.01Hz.Fig. 7 be in 40 hours after the inertia kinetic energy storage of unit own is level and smooth Power Output for Wind Power Field and the plan of the short-term wind-electricity field oscillogram of exerting oneself, in charge and discharge process of lithium battery, charging capacity equals discharge capacity, in figure, in 40 hours, show that 5 discharge and recharge the cycle nearly, effectively solved battery energy storage operation and frequently discharged and recharged conversion and super-charge super-discharge phenomenon the lithium battery life-span brought to adverse effect problem.Fig. 8 is the lithium battery residual capacity (SOC) of exerting oneself corresponding with wind energy turbine set short-term plan.SOC=1 when lithium battery charges completely, SOC=0.2 when lithium battery discharges completely.

(6-4) as shown in Figure 9, it is 99.74% that power confidence level is caught in wind energy turbine set prediction, standard deviation is 0.01 o'clock, utilize the wind energy turbine set power prediction data of a year as smooth object, when lithium battery energy storage battery capacity is 30MWh, 40MWh, 60MWh, the capacity control method that patent of the present invention provides is discharged and recharged number of times (charge-discharge cycle) completely and respectively is 1462 times, 1096 times, 746 times, and performance index s is followed successively by 470.25,387.77,450.02 and (in this example, gets α=8 × 10 ⁵, β=6.5 × 10 ⁴), therefore from energy-storage system cost, battery life and the balance of smooth effect three aspects:, the best stored energy capacitance of lithium battery is 40MWh, and 30MW is part stored energy capacitance, and 60MW is complete stored energy capacitance.

Although above the illustrative embodiment of the present invention is described; so that technical staff understands the present invention; but it is to be noted the scope of embodiment of the invention is not restricted to; those skilled in the art are obtained to enlightenment according to embodiment of the present invention; just can expect other its substantial equivalences replacements without creative work, all within protection range of the present invention.

Claims (7)

1. the electrically optimized control method of wind energy turbine set energy storage lithium based on unit set inertia energy storage, is characterized in that, comprises the following steps:

A, calculate wind energy turbine set under traditional control model according to wind energy turbine set prediction of wind speed and predict the power of catching;

B, wind energy turbine set prediction is caught to power carry out fast Fourier transform, obtain Power Output for Wind Power Field high-frequency signal and low frequency signal;

C, utilize the inertia kinetic energy storage of unit own level and smooth for the first time when carrying out Power Output for Wind Power Field, suppress the meritorious high fdrequency component of exerting oneself of unit;

D, according to prediction power output confidential interval, determine the wind energy turbine set plan P that exerts oneself _plan(t), set up lithium battery capacity E _band the Mathematical Modeling between the battery charging and discharging time, by regulating the charging and discharging lithium battery time to control lithium battery capacity, completes the level and smooth task to Power Output for Wind Power Field ripple low frequency component;

E, balance based between battery life and mixed energy storage system cost, consider wind energy turbine set predicted power confidence level, sets up evaluation index, optimal control wind energy turbine set lithium battery capacity.

2. the electrically optimized control method of wind energy turbine set energy storage lithium based on unit set inertia energy storage as claimed in claim 1, it is characterized in that: described steps A) in, according to wind energy turbine set prediction of wind speed, calculate wind energy turbine set under traditional control model and predict that the power concrete grammar of catching is as follows:

In formula:

expression unit is predicted the wind power of catching; v _f(t) represent wind energy turbine set prediction of wind speed; ρ represents atmospheric density; v _in, v _rate, v _outrepresent respectively incision wind speed, rated wind speed and the output wind speed of wind-powered electricity generation unit; A is impeller wind sweeping area; C _p(λ, β) is power coefficient;

The all wind-powered electricity generation units of wind energy turbine set were predicted and are caught power summation in the t moment:

In formula: n represents wind energy turbine set unit number of units;

divide and represent that power summation is caught in the prediction of t moment wind energy turbine set and power is caught in the prediction of i platform unit.

3. the electrically optimized control method of wind energy turbine set energy storage lithium based on unit set inertia energy storage as claimed in claim 1, is characterized in that: described step B) in, to wind energy turbine set, power is caught in prediction

carry out fast Fourier transform, obtain wind power amplitude-frequency spectral property curve, be divided into high and low frequency two parts, the frequency that HFS covers is 0.01～1Hz, and the frequency that low frequency part covers is 10 ^-5～0.01Hz.

4. the electrically optimized control method of wind energy turbine set energy storage lithium based on unit set inertia energy storage as claimed in claim 1, it is characterized in that: described step C) in, utilize the inertia kinetic energy storage of unit own Power Output for Wind Power Field to be carried out level and smooth for the first time, suppress the meritorious high fdrequency component of exerting oneself of unit, comprise the steps:

(1) set up traditional control model leeward group of motors system model.

In formula, ω _m(t) represent t moment system mechanics rotating speed; K=0.5 ρ c _p(λ, β) RA/ λ, λ=R ω _m/ v _f, represent tip speed ratio; R represents impeller radius; T _mrepresent the torque of wind-powered electricity generation unit; T _efor the electromagnetic torque of generator; J represents the lower moment of inertia such as system.

(2) calculate wind-powered electricity generation unit power change values Δ E _w.The wind-powered electricity generation power of the assembling unit is caught power in prediction

p between level and smooth rear power output for the first time _out(t) change, changing value is by rotor storage kinetic energy Δ E _kcompensate, specific as follows shown in:

ΔE _w＝ΔE _k (6)

Rotor storage capacity is subject to the restriction of generating unit speed, inertia kinetic energy memory range

ω _maxrepresent the maximum (top) speed that wind-powered electricity generation unit can bear; ω _minthe minimum speed allowing while representing to generate electricity by way of merging two or more grid systems.

(3) traditional wind turbine model is done to linearization process, provide

Δ E _kwith Δ P _outnumerical relation between three, then adopts partial differentiation, obtains

and P _out(t) small-signal disturbance, carry out the unit control system transfer function that Laplace transform obtains based on inertia kinetic energy storage and be:

。

5. the electrically optimized control method of wind energy turbine set energy storage lithium based on unit set inertia energy storage as claimed in claim 1, is characterized in that: described step D) in, lithium battery capacity control model is set up and is comprised the following steps:

(1) wind energy turbine set short term scheduling strategy.According to through unit set inertia kinetic energy storage stabilize after the confidential interval of power output

while determining charging and discharging lithium battery, plan to exert oneself P _plan(t).When lithium cell charging, by wind energy turbine set prediction power output confidential interval lowest power curve

definite plan P that exerts oneself _plan(t); When lithium battery electric discharge, according to wind energy turbine set prediction power output confidential interval maximum power curve

definite plan P that exerts oneself _plan(t), after lithium battery energy storage battery secondary is level and smooth, power output tracking plan is exerted oneself.

In formula, P _bess(t) represent lithium battery stores power;

p when charging _bess(t) get negative, P when electric discharge _bess(t) just get;

(2) the control model of capacity when lithium cell charging:

T ₁(i)＝t _i+1-t _i (13)

In formula: at the i time interval [t _i, t _i+1],

represent wind energy turbine set prediction power output confidential interval lowest power curve

upper minimum value; E _brepresent lithium battery rated capacity; E ₀represent lithium battery initial capacity; η _lossrepresent the capacity loss in charging process; T ₁(i) represent the charging interval;

(3) the control model of capacity when lithium battery discharges:

T ₂(i+1)＝t _i+2-t _i+1 (15)

T ₁+T ₂＞T (16)

In formula: at the i+1 time interval [t _i+1, t _i+2],

represent wind energy turbine set prediction power output confidential interval peak power curve

upper maximum; T ₂(i+1) represent discharge time, T is the programming dispatching time.

6. the electrically optimized control method of wind energy turbine set energy storage lithium based on unit set inertia energy storage as claimed in claim 1, it is characterized in that: described step e) in, when predicted power confidence level is different with standard deviation, obtain different lithium battery capacity values, set up the energy-storage system performance index s of stored energy capacitance, cost (operating cost and cost of investment) and battery life constraint, by reducing performance index, optimal control lithium battery capacity value.S is as follows for its performance index:

In formula: α represents the initial fixed investment of lithium battery energy storage battery system; The required investment of the β unit of representative stored energy capacitance; L _brepresent the lithium battery life-span.

7. as claimed in claim 4ly utilize the inertia kinetic energy storage of unit own Power Output for Wind Power Field to be carried out level and smooth for the first time, suppress the meritorious high fdrequency component of exerting oneself of unit, it is characterized in that, the control system of wind turbines that step (3) is set up based on the storage of rotor inertia kinetic energy comprises the following steps:

1) traditional control model leeward group of motors system model being done to linearization process obtains

Δ E _kwith Δ P _outbetween three, relation is as follows:

In formula, P (t)=T ω _m(t), T is torque, and P (t) is t moment active power; represent to predict and catch power change values; Δ P _outrepresent wind-powered electricity generation unit level and smooth power output changing value for the first time; Δ ω _mbe expressed as the mechanical separator speed changing value of system; 0 subscript represents systematic steady state amount, lower same.

2) utilize partial differentiation, obtain

and P _out(t) small-signal disturbance:

In formula, when stable state, have

and

about v _fand ω (t) _m(t) function lambda ₀=R ω _m0/ v _f0c _p0'=dC _p(λ)/d λ;

3) carrying out the controlled ssystem transfer function of Laplace transform is:

。

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