CN106292295A - The method that superconducting energy storage based on Implicit Generalized PREDICTIVE CONTROL suppression Electromechanical Disturbance is propagated - Google Patents

Abstract

The invention discloses the method that a kind of superconducting energy storage based on Implicit Generalized PREDICTIVE CONTROL suppression Electromechanical Disturbance is propagated, S1: converted by Laplace, set up the complex frequency domain model that power system Electromechanical Disturbance is propagated, the propagation law of disturbance in theory analysis power system；S2: install superconducting magnetic energy storage additional on the bus of described power system, utilizes generalized predictive control principle to control the input and output active power of superconducting magnetic energy storage, suppresses described Electromechanical Disturbance to propagate；S3: utilize the inhibition that the Electromechanical Disturbance in power system is propagated by simulation software checking active controller.The present invention is by quick and precisely following the tracks of the change of generator amature angular velocity incremental difference under different disturbances, it is achieved the suppression to Electromechanical Disturbance, and can make rapid system stability, and the method has the advantages such as simple, fast response time, control accuracy height, non-overshoot.

Description

The method that superconducting energy storage based on Implicit Generalized PREDICTIVE CONTROL suppression Electromechanical Disturbance is propagated

Technical field

The present invention relates to the method that a kind of superconducting energy storage based on Implicit Generalized PREDICTIVE CONTROL suppression Electromechanical Disturbance is propagated.

Background technology

The electricity needs of rapid growth, causes China's electrical network to become more complicated and huge, and power system dynamic step response is more Adding complexity, Power System Disturbances is propagated the stability influence to electrical network and is become huger so that by disturbance cause extensive The probability of power grid accident greatly increases, and ultimately results in and is difficult to suppress Power System Disturbances to propagate.The power system moment is subject to Various disturbances, the mechanical output making electromotor is uneven with the electromagnetic power of output, and generator amature rotation speed change, no longer with same Step rotating speed runs.So that electromotor enter a dynamic process, disturbance propagation in systems show as system frequency time Between and spatially present spatial and temporal distributions characteristic.The rule propagated in systems according to disturbance, fills by installing energy storage on bus additional Put, take suitable control measure, the disturbance propagation in system can be efficiently controlled, improve system frequency distribution character, it is achieved The stability of raising system.

Correlational study shows, the generator speed caused by Electromechanical Disturbance in system dynamically changes, in systems with ripple Form is propagated and presents spatial and temporal distributions characteristic.Continuum modeling (Continuum Modeling) is by very big for spatial distribution span Power system to be considered as the spatially electromotor of continuous distribution, transmission line of electricity and load overall, generator amature rotary inertia, resistance Buddhist nun and line impedance are represented by the density function of continuous distribution, and are incorporated into electromotor and wave equation, obtain about time and sky Between partial differential equation of second order, and by means of wave mechanical correlation theory, study disturbance fluctuation pattern in systems, thus Disclose the mechanism of transmission of disturbance in system, provide new visual angle for research power system electromechanical dynamic characteristic.

Superconducting magnetic energy storage can quickly, independently control meritorious and reactive power at four-quadrant, and its performance depends on institute The control mode used, only uses effective control mode, SMES just can be made to suppress the biography of Electromechanical Disturbance quickly and accurately Broadcast.Voltage and current double closed-loop PI control be the most extensively, the most practical control mode, input current and output voltage are separately controlled, Outer voltage output controls input current, fast track current-order as current-order, current inner loop.But due to current transformer Nonlinear characteristic, stability and the systematic function of PI controller are more sensitive to Parameters variation and external disturbance, robustness Poor.Do not rely on controlled system mathematical model, devise SMES nonlinear pid controller, there is simple in construction, be prone to real Existing, adaptable feature, but its parameter designing also needs to study further.Fuzzy logic control SMES is used to improve system special Property, this control method of simulation results show effectiveness in terms of improving the stabilization of power grids, but because relating to complicated algorithm, work Journey implements and acquires a certain degree of difficulty.For solving the problems referred to above, generalized predictive control is used to realize the effective control to SMES herein System.

Generalized predictive control (GPC, Generalized Predictive Control) is as a kind of main optimum control System strategy, uses the control strategies such as multi-step prediction, rolling optimization and feedback compensation to be controlled control object, effective gram of energy Model in clothes control is inaccurate, non-linear, the impact of time variation, can also tackle excessive Parameters variation simultaneously.

Summary of the invention

It is an object of the invention to provide a kind of superconducting energy storage based on Implicit Generalized PREDICTIVE CONTROL suppression Electromechanical Disturbance to propagate Method, the suppression to Electromechanical Disturbance can be realized, and system stability can be made rapidly, its fast response time, and control accuracy is high.

For solving above-mentioned technical problem, the present invention provides a kind of superconducting energy storage based on Implicit Generalized PREDICTIVE CONTROL to suppress machine The method that electric disturbance is propagated, the method comprises the following steps:

S1: converted by Laplace, sets up the complex frequency domain model that power system Electromechanical Disturbance is propagated, theory analysis electric power The propagation law of disturbance in system；

S2: install superconducting magnetic energy storage additional on the bus of described power system, draws random dry according to described propagation law The object disturbed, utilizes active controller to control the input and output wattful power of superconducting magnetic energy storage according to generalized predictive control principle Rate, it is achieved suppress described Electromechanical Disturbance to propagate.

Further, the method also includes:

S3: utilize the inhibition that Electromechanical Disturbance in power system is propagated by simulation software checking active controller.

Further, described step S2 comprises the following steps:

S21: install superconducting magnetic energy storage additional on the bus of described power system, according to the propagation law of disturbance in power system Controlled autoregressive integrated moving average model is used to describe the object of random disturbances as forecast model, by band forgetting factor Least squares identification method obtains the optimum control amount of described forecast model；

S22: use the rotor velocity increment in described power system to control to survey model as inputting of forecast model Active power, it was predicted that the active power of model exports in power system by superconducting magnetic energy storage, it is achieved suppression Electromechanical Disturbance Propagate.

Further, the constraints that described optimum control amount meets is:

Δu(k)_min≤Δu(k)≤Δu(k)_max

In formula, Δ u (k) is the optimum control amount of forecast model, Δ u (k)_minFor the lower limit of controlled quentity controlled variable, Δ u (k)_maxFor The higher limit of controlled quentity controlled variable.

The invention have the benefit that the present invention to pass through under different disturbances and quick and precisely follow the tracks of generator amature angular velocity The change of incremental difference, uses generalized predictive control superconducting magnetic energy storage, it is achieved the suppression to Electromechanical Disturbance, and can make rapid system Stable, the method has the advantages such as simple, fast response time, control accuracy height, non-overshoot.Further, the application is by adopting Obtain the optimum control amount of described forecast model by the least squares identification method of band forgetting factor, effectively prevent due to super Lead the energy storage device non-linear parametric modeling caused problem inaccurate, loaded down with trivial details.

Accompanying drawing explanation

Fig. 1 is the schematic diagram of uniform chain type power system；

Fig. 2 is the schematic diagram of uniform chained form system kth section；

Fig. 3 is the SMES schematic diagram under generalized predictive control；

Fig. 4 is the curve chart of 60 electromotor chained form system disturbing signals；

Fig. 5 is the curve chart that disturbance 1 effect issues rotor angle of electric machine speed increment difference；

Fig. 6 is the curve chart of First generator amature angular velocity incremental difference under disturbance 1,2 and 3 acts on；

Fig. 6-1 is the shaped form figure of First generator amature angular velocity incremental difference under disturbance 4 acts on；

Fig. 7 is the schematic diagram of SMES in parallel on the 3rd article of bus；

Fig. 8 is the performance diagram following the tracks of set-point；

Fig. 9 is controller input curve figure；

Figure 10 is the curve chart that disturbance 1 acts on lower rotor part angular velocity incremental difference；

Figure 11 is the curve chart of disturbance 1 lower rotor part phase angle incremental difference；

Figure 12 is the curve chart of SMES active power of output P.

Detailed description of the invention

Below the detailed description of the invention of the present invention is described, in order to those skilled in the art understand this Bright, it should be apparent that the invention is not restricted to the scope of detailed description of the invention, from the point of view of those skilled in the art, As long as various changes limit and in the spirit and scope of the present invention that determine, these changes are aobvious and easy in appended claim Seeing, all utilize the innovation and creation of present inventive concept all at the row of protection.

A kind of superconducting energy storage based on Implicit Generalized PREDICTIVE CONTROL suppression Electromechanical Disturbance propagate method, the method include with Lower step:

S1: converted by Laplace, sets up the complex frequency domain model that power system Electromechanical Disturbance is propagated, theory analysis electric power The propagation law of disturbance in system, concrete grammar is as follows:

Fig. 1 is a discrete electric power system model of chain type, and in figure, R is transmission line of electricity resistance, and X is transmission line reactance, and M is for sending out Motor angular momentum, D is the sub-rotor damping that generates electricity.

According to the practical operation situation of power system, herein system shown in Figure 1 model is done following setting: (1) owns Busbar voltage perunit value is 1.0；(2) transmission line parameter is identical and R/X ＜ ＜ 1, i.e. ignores line resistance；(3) Generator Tool power invariability is constant；(4) the phase difference of voltage δ between adjacent bus is less, meets sin δ ≈ δ, cos δ ≈ 1；(5) D/M ＜ ＜ 1。

Fig. 2 shows through-put power P of kth bar circuit_kWith kth and k+1 bar busbar voltage phase angle theta_kAnd θ_k+1Relation be:

$P_{k,k+1}=\frac{U_k\·U_{k+1}}{X}sin({\mathrm{\θ}}_k-{\mathrm{\θ}}_{k+1})---\left(1\right)$

In formula, U_kAnd U_k+1Represent kth bar and+1 busbar voltage of kth respectively,WithB For the susceptance between kth bar and+1 bus of kth, simplify formula (1) and obtain

$P_{k,k+1}\≈\frac{1}{X}({\mathrm{\θ}}_k-{\mathrm{\θ}}_{k+1})\≈B({\mathrm{\θ}}_k-{\mathrm{\θ}}_{k+1})---\left(2\right)$

The power increment Δ p of kth bar circuit_kWith kth bar bus place electromotor node voltage phase angle increment Delta θ_kRelation For

Δp_k(t)≈BΔθ_k(t) (3)

Owing to ignoring electromotor internal impedance, generator amature angle is equal to the busbar voltage phase angle being connected, therefore generator speed Increment is

${\mathrm{\Δ\ω}}_k\left(t\right)=\frac{1}{{\mathrm{\ω}}_s}\frac{{\mathrm{d\Δ\θ}}_k\left(t\right)}{dt}=\frac{1}{2\mathrm{\π}f}\frac{{\mathrm{d\Δ\θ}}_k\left(t\right)}{dt}---\left(4\right)$

On kth bar bus, the equation that waves of electromotor is:

$M\frac{{\mathrm{d\Δ\θ}}_k^2\left(t\right)}{{\mathrm{dt}}^2}+D\frac{{\mathrm{d\Δ\θ}}_k\left(t\right)}{dt}=-{\mathrm{\Δp}}_k\left(t\right)---\left(5\right)$

Can obtain by formula (5) being done Laplace conversion

s²Δθ_k(s)=M^-1[-DsΔθ_k(s)-B(2Δθ_k(s)-Δθ_k+1(s)-Δθ_k-1(s))] (6)

S2: install superconducting magnetic energy storage on the bus of power system additional, the propagation law of disturbance in power system uses and is subject to Control autoregression integration moving average model describes the object of random disturbances as forecast model, by a young waiter in a wineshop or an inn for band forgetting factor Multiplication discrimination method obtains the optimum control amount of described forecast model；The output of generalized predictive control superconducting magnetic energy storage (SMES) Active power schematic diagram is as it is shown on figure 3, use the rotor velocity increment in power system as the input control of forecast model Survey the active power of model, it was predicted that the active power of model exports in power system by superconducting magnetic energy storage, it is achieved suppression Electromechanical Disturbance is propagated.

The damping merit that one machine infinity bus system Damping Power containing SMES is introduced by system self Damping Power and SMES Rate is constituted.By controlling SMES equivalent parameters, can effectively control D_SMES, when SMES introduces positive damping, improve system total damping, Effectively suppression Electromechanical Disturbance is propagated.The parameter selecting SMES is provided that the SMES system of 400MJ/300MVA, rated line voltage 20kV, rated frequency 60Hz, superconducting magnet inductance value 2H, superconducting magnet rated current 20kA, the AC of SMES current transformer Impedance and induction reactance 0.007p.u. and 0.22p.u. respectively, the minimum and maximum electric current allowed in superconducting magnet running is 2kA And 20kA, the rated voltage of DC bus capacitor is 40kV, DC side equivalent capacity 375 μ F, the maximum change of current reference input Rate is 200p.u./s.

The present invention uses implicit algorithm as the correction algorithm of generalized forecast control method, it is to avoid line solver A large amount of intermediate operations of Diophantine equation, improve response speed.

Generalized predictive control uses controlled autoregressive integrated moving average model description by the object of random disturbances:

A(z^-1) y (k)=B (z^-1)u(k-1)+C(z^-1)ξ(k)/Δ (7)

In formula, Y (k), u (k), ξ ((k) be respectively output of system, the input of system and meansigma methods be 0 discrete White noise.A(z^-1)、B(z^-1) and C (z^-1) it is respectively n_a、n_bAnd n_cThe z on rank^-1Multinomial, Δ=1-z^-1, z^-1Calculate for rear shifting Son, such as z^-1Y (k)=y (k-1).If system time lags is more than zero, wherein multinomial B (z^-1) coefficient b₀、b₁、Arrange It is 0, represents control object corresponding time lag number.In order to simplify calculating process, C (z^-1) it is usually arranged as 1.

The optimality criterion in k moment uses object function

$\min J\left(k\right)=\underset{j=1}{\overset{n}{\Σ}}{\[y(k+j)-w(k+j)\]}^2+\underset{j=1}{\overset{m}{\Σ}}\mathrm{\λ}\left(j\right){\[\mathrm{\Δ}u(k+j-1)\]}^2---\left(8\right)$

In formula, n is prediction length, and m is for controlling length, and output expected value is w (k+j)=α^jy(k)+(1-α^j)y_r, y_rFor Setting value, y (k) is that system currently exports, and α is soft and smooth coefficient.

Optimum output predictive value is

$\hat{Y}=G\mathrm{\Δ}U+f---\left(9\right)$

In formula, Y is prediction output sequence, and Δ U is controlling increment sequence；Δ U=[Δ u (k), Δ u (k+1) ..., Δ u (k +n-1)]^T, f=[f (k+1), f (k+2) ..., f (k+n)]^T。

Make W=[w (k+1), w (k+2) ..., w (k+n)]^T, use optimum prediction valueReplace Y, then formula (10) be GPC Excellent control law

Δ U=(G^TG+λI)^-1G^T(W-f) (10)

In formula, softening coefficient lambda and setting value vector W are it is known that matrix G and open-loop prediction vector f are unknown.Implicit expression is from the side of rectification Method is according to inputoutput data, by predictive equation direct identification G and f.

Can obtain n predictor arranged side by side according to formula (9) is

$\left\{\begin{array}{c}y(k+1)=g_0\mathrm{\Δ}u\left(k\right)+f(k+1)+E_1\mathrm{\ξ}(k+1)\\ y(k+2)=g_1\mathrm{\Δ}u\left(k\right)+g_0\mathrm{\Δ}u(k+1)+f(k+2)+E_2\mathrm{\ξ}(k+2)\\ ......\\ y(k+n)=g_{n-1}\mathrm{\Δ}u\left(k\right)+...+g_0\mathrm{\Δ}u(k+n-1)+f(k+n)+E_n\mathrm{\ξ}(k+n)\end{array}\right.---\left(11\right)$

Be can be seen that in G, all elements is all in last equation by formula (11), therefore formula (11) last equation is entered Row identification can obtain G.Can be obtained by formula (11)

Y (k+n)=g_n-1Δu(k)+…+g₀Δu(k+n-1)+f(k+n)+E_nξ(k+n) (12)

Make X (k)=[Δ u (k), Δ u (k+1) ..., Δ u (k+n-1), 1], θ (k)=[g_n-1,g_n-2,…,g₀,f(k+ n)]^T,

Then formula (12) abbreviation is

Y (k+n)=X (k) θ (k)+E_nξ(k+n) (13)

Output predictive value is

Y ((k+n) | k)=X (k) θ (k) (14)

At moment k, X (k-n) it is known that E_nξ (k+n) be meansigma methods be the white noise of zero, use common method of least square to estimate Meter parameter vector θ (k).But, usual E_nξ (k+n) is not white noise, therefore uses control strategy to be combined with parameter estimation, i.e. uses The estimated value of auxiliary output predictionReplacement output predictive value y (k | (k-n)), it is believed thatWith reality Actual value y (k) is the poorest for white noise ε (k).Y (k | (k-n)) is made to represent k-n moment n step output predictive value,Table Show k-n moment n step auxiliary output prediction estimated value, i.e. by

$\hat{y}\left(k\right|\left(k-n\right))+\mathrm{\ϵ}\left(k\right)=y\left(k\right|\left(k-n\right))+E_n\mathrm{\ξ}\left(k\right)---\left(15\right)$

$y\left(k\right)-\hat{y}\left(k\right|\left(k-n\right))=\mathrm{\ϵ}\left(k\right)---\left(16\right)$

Draw

$y\left(k\right)=\hat{X}(k-n)\mathrm{\θ}\left(k\right)+\mathrm{\ϵ}\left(k\right).$

Employing Least Square Method parameter vector θ (k):

$\left\{\begin{array}{c}\widehat{\mathrm{\θ}}\left(k\right)=\widehat{\mathrm{\θ}}(k-1)+K\left(k\right)F\\ K\left(k\right)=P(k-1){\hat{X}}^T(k-n)M^{-1}\\ P\left(k\right)=\[I-K\left(k\right)\hat{X}(k-n)\]P(k-1)/{\mathrm{\λ}}_1\end{array}\right.---\left(17\right)$

In formula,λ₁For forgetting factor, 0 < λ₁< 1,

Matrix G can be obtained by formula (17):

N in the k moment walks estimated valueFor

$\hat{y}\left(\right(k+n\left)\right|k)=\hat{X}\left(k\right)\widehat{\mathrm{\&theta;}}\left(k\right)---\left(19\right)$

Predicted vector f of subsequent time is

$f=\left(\begin{array}{c}f(k+1)\\ f(k+2)\\ \&CenterDot;\\ \&CenterDot;\\ \&CenterDot;\\ f(k+n)\end{array}\right)=\left(\begin{array}{c}\hat{y}\left(\right(k+2)\left|k\right)\\ \hat{y}\left(\right(k+3)\left|k\right)\\ \&CenterDot;\\ \&CenterDot;\\ \&CenterDot;\\ \hat{y}\left(\right(k+n+1)\left|k\right)\end{array}\right)+\left(\begin{array}{c}1\\ 1\\ \&CenterDot;\\ \&CenterDot;\\ \&CenterDot;\\ 1\end{array}\right)e(k+1)---20)$

Trying to achieve G and f, the optimum control amount that can obtain current time according to formula (10) is

U (k)=u (k-1)+g^T(W-f) (21)

In formula, g^TFor matrix (G^TG+λI)^-1G^TThe 1st row.

One great advantage of GPC algorithm be because by be controlled by constraint satisfaction prediction optimization make The process constraints of energy system.Therefore in the application, the constraints that optimum control amount meets is

Δu(k)_min≤Δu(k)≤Δu(k)_max

In formula, Δ u (k) is the optimum control amount of forecast model, Δ u (k)_minFor the lower limit of controlled quentity controlled variable, Δ u (k)_maxFor The higher limit of controlled quentity controlled variable.

S3: utilize simulation software (MATLAB/Simulink) checking active controller to the Electromechanical Disturbance in power system The inhibition propagated, specifically:

The uniform discrete chained form system of the phantom n=60 as shown in Figure 1 that the present invention uses.Its canonical parameter is as follows: (1) the transmission line of electricity resistance R=0, reactance X=2p.u. between adjacent generator is ignored；(2) the angular momentum M=of generator amature 20p.u., rotor damping D=0.01p.u., ignore electromotor internal impedance；(3) impedance Z of initial disturbance point-to-point B₀=0.Imitative T=10s between true time.

1, discrete chain type Power System Disturbances propagation characteristic is carried out simulation analysis.If initial disturbance is as shown in Figure 4, its In, disturbance 1 is pulse-type disturbance (disturbance betided for 0.5 moment, and amplitude is 1p.u., and when 1.2s, disturbance disappears), and this disturbance is simulated Instantaneity short trouble.Fault betides on bus 1 and load transmission line of electricity, is short-circuited and is cut off by relay protection during 0.5s Load, reclosing success, failure vanishes when 1.2s.Disturbance 2 is simulated by the input mechanical output change of battle array wind-induced wind turbine； Disturbance 3 is step signal, is equivalent to once increase load operation；Disturbance 4 is for introducing RANDOM WIND disturbance, and simulation is caused by RANDOM WIND Wind turbine input mechanical output change.

When disturbance 1 occurs at bus 1, each generator amature angular velocity incremental difference is as shown in the figure.As can be known from Fig. 5, Disturbance is maximum from the generator amature angular velocity incremental difference that perturbation distance is nearest after occurring, and disturbance passes with the form of ripple in systems Broadcast.

By Fig. 6 and Fig. 6-1 it appeared that under the effect of disturbance 1, disturbance 2 and disturbance 3 after disturbance stops, electromotor turns Sub-angular velocity incremental difference is more and more less, tends towards stability, is infinitely close to 0.Under the effect of disturbance 4 white Gaussian noise, electromotor The fluctuation of rotor velocity incremental difference acutely, can not weaken its fluctuation under the damping action of system itself, bring system huge Impact.

2, SMES based on generalized predictive control is carried out simulation analysis.Simulation parameter is arranged: Tc_p=0.026, K_v=10, T_vm=0.02, Δ P_max=0.95, Δ P_min=-0.5.Assume that system model is

Y (k)-0.92623y (k-1)=0.03773u (k-1)+ξ (k)/Δ (23)

Taking simulation parameter is: p=n=15, m=2, λ=0.04, λ₁=1, α=0.9.RLS initial parameter values: g_n-1=1, f (k+n)=1, P0=10⁵I, remaining is 0.ξ (k) ∈ [-0.2,0.2] is uniformly distributed white noise.When track reference value is square wave, Follow the tracks of the characteristic curve of set-point as shown in Figure 8.Controller input waveform is as shown in Figure 9.

3, disturbance controls emulation

Disturbance 1 occurs at bus 1, and SMES is arranged at bus 3 (as shown in Figure 8).The rotor angle speed of First electromotor Degree incremental difference changes as shown in Figure 10.Observe Figure 10 to understand and use PI to control the propagation of disturbance had certain inhibition, time When carving t=2.6s, rotor velocity incremental difference levels off to 0, and system is again stable.Under wide area PREDICTIVE CONTROL, hence it is evident that disturbance suppression Propagating and make system immediate stability, when moment t=1.65s, rotor velocity incremental difference levels off to 0.Do not add SMES at t= During 1.0695s, rotor velocity incremental difference maximum is 11 × 10^-4P.u., rotor velocity incremental difference minima during t=1.29s For-5.38 × 10^-4p.u.；It is 9.19 × 10 that PI controls rotor velocity incremental difference maximum during lower t=1.053s^-4P.u., t During=1.26s, rotor velocity incremental difference minima is-5.1 × 10^-4p.u.；Rotor angle during t=1.04s under generalized predictive control Speed increment difference maximum is 9 × 10^-4P.u., during t=1.28s, rotor velocity incremental difference minima is-2.3 × 10^{- 4}p.u.；It is 57% that contrast understand GPC control lower rotor part angular velocity incremental difference minima to reduce percentage ratio, and rotor velocity increases Amount difference deviation stationary value, its control effect is substantially better than and does not adds under SMES and PI control.

Disturbance 1 occurs at bus 1, and SMES is arranged at bus 3.The phase angle incremental difference of First electromotor changes such as Figure 11 Shown in.As shown in Figure 11: when not adding SMES, t=2.5s phase angle increment maximum is 0.2rad；When PI controls lower t=1.2s Phase angle incremental difference maximum is 0.0548rad；Under generalized predictive control, t=1.187s phase angle increment maximum value difference is 0.028rad；Contrast understands that to make system reduce percentage ratio stabilization time again under GPC controls be 52.6%, and phase angle increment subtractive Little percentage ratio is 85.9%, and GPC controls to suppress fast and effectively the propagation of Electromechanical Disturbance.

Disturbance 1 occurs at bus 1, and SMES is arranged at bus 3.SMES active power of output is as shown in figure 12.By Figure 12 Understand: it is less that PI controls lower SMES active power of output, and its output maximum is 0.4009p.u., it is impossible to effectively follow the tracks of The change of power in system；SMES stable output power under wide area PREDICTIVE CONTROL, its peak power is 0.95p.u., in time with Track changed power, effective suppression Electromechanical Disturbance is propagated.

In sum, the present invention passes through basic assumption and discrete modeling, utilizes Laplace conversion to establish Complex Power system The Electromechanical Disturbance of system propagates mathematical model and to its propagation law deployment analysis.By MATLAB, system and SMES are imitated Very, it is concluded that the change by quick and precisely following the tracks of generator amature angular velocity incremental difference under different disturbances, uses Generalized predictive control superconducting magnetic energy storage, it is achieved the suppression to Electromechanical Disturbance, and system immediate stability can be made, the method has letter The advantages such as single easy, fast response time, control accuracy height, non-overshoot.

Claims (4)

1. the method that superconducting energy storage based on an Implicit Generalized PREDICTIVE CONTROL suppression Electromechanical Disturbance is propagated, it is characterised in that bag Include following steps:

S1: converted by Laplace, is set up the complex frequency domain model that power system Electromechanical Disturbance is propagated, draws in power system and disturb Dynamic propagation law；

S2: install superconducting magnetic energy storage additional on the bus of described power system, draws random disturbances according to described propagation law Object, utilizes active controller to control the input and output active power of superconducting magnetic energy storage according to generalized predictive control principle, Realize suppressing described Electromechanical Disturbance to propagate.

The side that superconducting energy storage based on Implicit Generalized PREDICTIVE CONTROL the most according to claim 1 suppression Electromechanical Disturbance is propagated Method, it is characterised in that the method also includes:

S3: utilize the inhibition that Electromechanical Disturbance in power system is propagated by simulation software checking active controller.

The side that superconducting energy storage based on Implicit Generalized PREDICTIVE CONTROL the most according to claim 1 suppression Electromechanical Disturbance is propagated Method, it is characterised in that described step S2 comprises the following steps:

S21: install superconducting magnetic energy storage additional on the bus of described power system, uses controlled autoregressive according to described propagation law Integration moving average model describes the object of random disturbances as forecast model, by the least squares identification of band forgetting factor Method obtains the optimum control amount of described forecast model；

S22: use rotor velocity increment in described power system having as the input control forecasting model of forecast model Merit power, it was predicted that the active power of model exports in power system by superconducting magnetic energy storage, it is achieved suppression Electromechanical Disturbance passes Broadcast.

The side that superconducting energy storage based on Implicit Generalized PREDICTIVE CONTROL the most according to claim 3 suppression Electromechanical Disturbance is propagated Method, it is characterised in that in described step S21, the constraints that described optimum control amount meets is:

Δu(k)_min≤Δu(k)≤Δu(k)_max

In formula, Δ u (k) is the optimum control amount of forecast model, Δ u (k)_minFor the lower limit of controlled quentity controlled variable, Δ u (k)_maxFor controlling The higher limit of amount.