CN104598728A - Wind power generation-including power system state estimation method taking frequency change into consideration - Google Patents

Abstract

The invention discloses a wind power generation-including power system state estimation method taking frequency change into consideration. As large-scale wind power is connected into power grids, the fluctuation of wind power output has significant impact on power grid frequency, so conventional state estimation models are already no longer applicable. On the basis of a synchronous generator quasi-stable state model, a load quasi-stable state model and an asynchronous wind-driven generator simplified RX model, the method introduces frequency deviation as a new state variable into a state estimation process, moreover, new zero-injection power measurement is constructed for generators and load nodes, and ultimately, a state estimation model taking frequency deviation into consideration is created. An example simulation result shows that the model can effectively give consideration to the frequency deviation of a system, and thereby the precision of a state estimation result is increased remarkably.

Description

A kind of power system state estimation method containing wind-power electricity generation taking into account frequency change

Technical field

Invention relates to a kind of power system state estimation method containing wind-power electricity generation taking into account frequency change, belongs to Operation of Electric Systems and control technology field.

Background technology

As the core of energy management system (Energy Management System, EMS), Power system state estimation, by the process to raw data, obtains the best estimate of quantity of state.Traditional weighted least-squares method (Weighted LeastSquares, WLS) state estimation algorithm estimated quality and constringency performance very well, are classical solution and the theoretical foundation of state estimation, adapt to various types of measurement system.

Asynchronous blower fan simplifies the characteristic that RX model had both taken into full account asynchronous generator itself, and set forth the characteristics of output power of asynchronous wind driven generator in more detail, little compared with the calculated amount of traditional RX model again, precision meets calculation requirement.

But state estimation model of the prior art only considers the slippage of blower fan, the not frequency change of Study system.Along with large-scale wind power access electrical network, the undulatory property of wind power output can make a significant impact mains frequency.

Summary of the invention

The invention provides a kind of power system state estimation method containing wind-power electricity generation taking into account frequency change, the frequency departure of system is set up new state estimation model as new quantity of state, associate power element also adopts the model considering frequency characteristic, the method effectively can take into account the frequency departure of system, solve the problems of the prior art, there is engineer applied and be worth.

The present invention for achieving the above object, adopts following technical scheme:

Take into account the power system state estimation method containing wind-power electricity generation of frequency change, comprise the following steps successively:

(1) network parameter and the measurement amount of electric system is obtained;

(2) network parameter utilizing step (1) to obtain and measurement amount carry out state estimation procedure initialization;

(3) state estimation model containing wind-power electricity generation taking into account frequency change is set up:

min J(x)＝[z-h(x)] ^TW[z-h(x)]

Wherein, J is objective function; The transposition of T representing matrix; W is diagonal angle weight matrix; X is quantity of state, and dimension n=2N-1, N is nodes; Z is measurement amount, dimension m, m>n; H is that m ties up non-linear measurement function;

(4) consider that blower fan slippage s and system frequency deviation Δ f sets up new Jacobian matrix:

$H=\left[\begin{array}{cccc}\frac{\∂P}{\∂\mathrm{\θ}}& \frac{\∂P}{\∂V}& \frac{\∂P}{\∂s}& \frac{\∂P}{\∂\mathrm{\Δf}}\\ \frac{\∂Q}{\∂\mathrm{\θ}}& \frac{\∂Q}{\∂V}& \frac{\∂Q}{\∂s}& \frac{\∂Q}{\∂\mathrm{\Δf}}\\ \frac{\∂P_k}{\∂\mathrm{\θ}}& \frac{{\∂P}_k}{\∂V}& \frac{\∂P_k}{\∂s}& \frac{\∂P_k}{\∂\mathrm{\Δf}}\\ \frac{\∂Q_k}{\∂\mathrm{\θ}}& \frac{{\∂Q}_k}{\∂V}& \frac{\∂Q_k}{\∂s}& \frac{\∂Q_k}{\∂\mathrm{\Δf}}\end{array}\right]$

Wherein, P and Q represents corresponding meritorious and idle of common generator respectively; P _kand Q _kbe respectively corresponding meritorious and idle of the access node k of asynchronous blower fan; Wherein with dimension identical with the number of system apoplexy electric field node;

(5) by initial each quantity of state V ⁽⁰⁾, θ ⁽⁰⁾, s ⁽⁰⁾, Δ f ⁽⁰⁾calculated value h (the x that calculated amount is measured ^(k)) and Jacobian matrix H (x ^(k)), wherein, θ represents voltage phase angle, and V represents voltage magnitude, and s is slippage, and Δ f is frequency departure amount, and 0 represents original state amount;

(6) solving state correction amount x ^(k), judge whether to meet the condition of convergence, if max{ Δ V ^(k)|, | Δ θ ^(k)|, | Δ s ^(k)|, | Δ f ^(k)| > λ, iterations k=k+1, revise quantity of state V ^(k+1)=V ^(k)+ Δ V ^(k), θ ^(k+1)=θ ^(k)+ Δ θ ^(k), s ^(k+1)=s ^(k)+ Δ s ^(k), Δ f ^(k+1)=Δ f ^(k)+ Δ Δ f ^(k), until eligible, Output rusults, wherein, k is iterations.

In above-mentioned steps (2), initialized content comprises: arrange iteration precision λ, maximum iteration time and aerogenerator slippage initial value and frequency departure initial value, forms bus admittance matrix.

In above-mentioned steps (1), network parameter comprises: bus numbering, title, building-out capacitor, the branch road of transmission line of electricity number, headend node and endpoint node numbering, resistance in series, series reactance, shunt conductance, shunt susceptance, transformer voltage ratio and impedance, the atmospheric density of wind energy turbine set, wind speed, blower fan type parameter, system original frequency.

In above-mentioned steps (1), measurement amount z comprises: node voltage amplitude, node inject active power and reactive power, the active power of common line branch road and transformer branch and reactive power.

The above-mentioned Power system state estimation containing wind-power electricity generation taking into account frequency change is on the basis that synchronous generator quasi steady state model, load quasi steady state model and asynchronous blower fan simplify RX model, frequency departure is incorporated in state estimation procedure as new quantity of state, and construct zero new injecting power to generator and load bus to measure, finally establish the state estimation model considering frequency departure.Simulation Example result shows that this model effectively can take into account the frequency departure of system, and state estimation result precision is improved, and has future in engineering applications.

Accompanying drawing explanation

Fig. 1 is the inventive method process flow diagram.

The example system applied containing the Power system state estimation of wind-power electricity generation taking into account frequency change that Fig. 2 proposes for the present invention, employing be IEEE-14 node system.

Fig. 3 is the Γ shape simple equivalent circuit of asynchronous machine in embodiment.

Fig. 4 is two states estimation model average voltage evaluated error.

Embodiment

The present invention analyzes the frequency characteristic of blower fan for the quasi steady state model of asynchronous machine.In order to simplify calculating, the present invention adopts RX model.The asynchronous machine of capacity comparatively large (being greater than 40kW), due to its X ₁<<X _m, and R ₁and R _mnegligible, can Approximate Equivalent be the Γ shape circuit shown in Fig. 3.

R in Fig. 3 ₁, R ₂, R _mbe respectively stator resistance, rotor resistance, excitation resistance, X ₁, X ₂and X _mrepresent stator reactance, rotor reactance and excitation reactance respectively, s is slippage, and Δ f is frequency departure amount, P _gand Q _grepresent active power value and reactive power value respectively.

In order to consider the impact of grid side frequency departure on synchronous generator, synchronous generator adopts quasi steady state model below:

$P_G=P_{G\_\mathrm{set}}-\frac{P_R}{R_R}\mathrm{\&Delta;f}$

$Q_G=Q_{G\_\mathrm{set}}+a_Q(-\frac{P_R}{R_R}\mathrm{\&Delta;f})+b_Q{(-\frac{P_R}{R_R}\mathrm{\&Delta;f})}^2$

In formula: P _gand Q _grepresent the active power value that synchronous generator exports and reactive power value respectively, P _{g_set}and Q _{g_set}the initial active power value of synchronous generator and reactive power value respectively, P _rspecified active power value, R _rthe speed change rate of corresponding synchronous generator, a _qand b _qbe the idle corresponding adjustment factor of exerting oneself of synchronous generator, Δ f represents frequency departure amount, i.e. the deviation of frequency and ratings during systematic steady state.

The quasi steady model of load adopts the static model considering frequency change, and its multinomial model can be expressed as follows:

$P_L=P_{L\_\mathrm{set}}(1+K_p\mathrm{\&Delta;f})(p_p+p_c\left(\frac{V_L}{V_{\mathrm{LB}}}\right)+p_z{\left(\frac{V_L}{V_{\mathrm{LB}}}\right)}^2)$

$Q_L=P_{L\_\mathrm{set}}(1+K_q\mathrm{\&Delta;f})(q_p+q_c\left(\frac{V_L}{V_{\mathrm{LB}}}\right)+q_z{\left(\frac{V_L}{V_{\mathrm{LB}}}\right)}^2)$

In formula: P _land Q _lrepresent the meritorious of this load respectively and without work value, P _{l_set}and Q _{l_set}represent the meritorious and idle initial value of this load respectively, K _pand K _qrepresent that load is gained merit and the mediating effect+6 coefficient of idle correspondence respectively.P _p, p _c, p _zand q _p, q _c, q _zrepresent load model static voltage characteristic coefficient, V _land V _lBbe voltage runtime value and the load voltage value of this load respectively, Δ f is frequency departure amount.

The measurement equation of Power system state estimation is:

z＝h(x)+ε

In formula: x is quantity of state (dimension n=2N-1, N is nodes); Z is measurement amount (dimension m, m>n); H is that m ties up non-linear measurement function; ε is that m ties up error in measurement.

The objective function set up by criterion of least squares is as follows:

min J(x)＝[z-h(x)] ^TW[z-h(x)]

Wherein J is objective function, the transposition of T representing matrix, and W is diagonal angle weight matrix, W _ii=1/ σ _i ², σ _ifor standard deviation.

Generally, h (x) is nonlinear function, therefore adopts the method for iteration to solve.Make x ₀the a certain approximate value of x, can at x ₀near Taylor expansion is carried out to h (x), retain once item, and ignore the nonlinear terms of more than secondary, obtain:

h(x)≈h(x ₀)+H(x ₀)Δx

Δ x=x-x in formula ₀, the Jacobian matrix that H (x) is h (x).This formula is substituted in objective function, can obtain:

J(x)＝[Δz-H(x ₀)Δx] ^TW[Δz-H(x ₀)Δx]

Δ z=z-h (x in formula ₀), above formula is launched formula and obtains:

J(x)＝Δz ^T[W-WH(x ₀)Σ(x ₀)H ^T(x ₀)W]Δz

+[Δx-Σ(x ₀)H ^T(x ₀)WΔz] ^TΣ ^-1(x ₀)[Δx-Σ(x ₀)H ^T

×(x ₀)WΔz]

Σ (x in formula ₀)=[H ^t(x ₀) WH (x ₀)] ^-1.

In above formula, the right Section 1 and Δ x have nothing to do.Therefore, make J (x) minimum, Section 2 should be 0, thus has:

Δx ^(l)＝[H ^T(x ^(l))WH(x ^(l))] ^-1H ^T(x ^(l))W[z-h(x ^(l))]

x ^(l+1)＝x ^(l)+Δx ^(l)

Wherein l represents iterations, and x carries out iterated revision by above formula, until objective function is close to minimum.

Because the access of wind-powered electricity generation, state estimation model of the present invention, on the basis of basic weighted least-squares method, is not only introduced slippage s and is introduced update equation as quantity of state, but also consider frequency offset Δ f.So the correction of state estimation expands to Δ x=[Δ θ Δ V Δ s Δ Δ f] ^t, θ represents voltage phase angle, and V represents voltage magnitude, obtains the new piecemeal Expanded Jacobian matrix containing s and Δ f to be:

$H=\left[\begin{array}{cccc}\frac{\&PartialD;P}{\&PartialD;\mathrm{\&theta;}}& \frac{\&PartialD;P}{\&PartialD;V}& \frac{\&PartialD;P}{\&PartialD;s}& \frac{\&PartialD;P}{\&PartialD;\mathrm{\&Delta;f}}\\ \frac{\&PartialD;Q}{\&PartialD;\mathrm{\&theta;}}& \frac{\&PartialD;Q}{\&PartialD;V}& \frac{\&PartialD;Q}{\&PartialD;s}& \frac{\&PartialD;Q}{\&PartialD;\mathrm{\&Delta;f}}\\ \frac{\&PartialD;P_k}{\&PartialD;\mathrm{\&theta;}}& \frac{{\&PartialD;P}_k}{\&PartialD;V}& \frac{\&PartialD;P_k}{\&PartialD;s}& \frac{\&PartialD;P_k}{\&PartialD;\mathrm{\&Delta;f}}\\ \frac{\&PartialD;Q_k}{\&PartialD;\mathrm{\&theta;}}& \frac{{\&PartialD;Q}_k}{\&PartialD;V}& \frac{\&PartialD;Q_k}{\&PartialD;s}& \frac{\&PartialD;Q_k}{\&PartialD;\mathrm{\&Delta;f}}\end{array}\right]$

In formula: P and Q represents corresponding the gaining merit with idle of common generator respectively.P _kand Q _kbe respectively corresponding the gaining merit with idle of access node k of asynchronous blower fan.Wherein with dimension identical with the number of system apoplexy electric field node.

In system, conventional node injecting power is expressed as:

$P_i=V_i\underset{j=1}{\overset{n}{\mathrm{\&Sigma;}}}{V}_j(G_{\mathrm{ij}}\cos {\mathrm{\&theta;}}_{\mathrm{ij}}+B_{\mathrm{ij}}\sin {\mathrm{\&theta;}}_{\mathrm{ij}})$

$Q_i=V_i\underset{j=1}{\overset{n}{\mathrm{\&Sigma;}}}{V}_j(G_{\mathrm{ij}}\sin {\mathrm{\&theta;}}_{\mathrm{ij}}+B_{\mathrm{ij}}\cos {\mathrm{\&theta;}}_{\mathrm{ij}})$

In formula: P _iand Q _irepresent that node i is injected respectively meritorious and idle; V _iand V _jrepresent the voltage magnitude of node i and j respectively; θ _ijit is the phase difference of voltage that node i arrives node j; G _ijand B _ijthen represent the conductance in node admittance battle array between corresponding node i and j and susceptance; N is system node sum.

When taking into account generator frequency characteristic, build generator node zero injecting power, this type of generator node zero injecting power can be expressed as:

$P_{\mathrm{Gi}}=P_{G\_\mathrm{set}}-\frac{R_R}{R_R}\mathrm{\&Delta;f}+V_i\underset{j=1}{\overset{n}{\mathrm{\&Sigma;}}}(G_{\mathrm{ij}}\cos {\mathrm{\&theta;}}_{\mathrm{ij}}+B_{\mathrm{ij}}\sin {\mathrm{\&theta;}}_{\mathrm{ij}})=0$

$Q_{\mathrm{Gi}}=Q_{G\_\mathrm{set}}+a_Q(-\frac{P_R}{R_R}\mathrm{\&Delta;f})+b_Q{(-\frac{P_R}{R_R}\mathrm{\&Delta;f})}^2+V_i\underset{j=1}{\overset{n}{\mathrm{\&Sigma;}}}{V}_j(G_{\mathrm{ij}}{\sin \mathrm{\&theta;}}_{\mathrm{ij}}-B_{\mathrm{ij}}\cos {\mathrm{\&theta;}}_{\mathrm{ij}})=0$

In formula: P _giand Q _girepresent that generator i injects respectively meritorious and idle.

When taking into account frequency character of load, build zero injecting power of load bus, now zero injecting power of load bus can be expressed as:

$\begin{array}{c}{P}_{\mathrm{Li}}=P_{L\_\mathrm{set}}(1+K_p\mathrm{\&Delta;f})(p_p+p_c\left(\frac{V_L}{V_{\mathrm{LB}}}\right)+p_z{\left(\frac{V_L}{V_{\mathrm{LB}}}\right)}^2)\\ +V_i\underset{j=1}{\overset{n}{\mathrm{\&Sigma;}}}{V}_j(G_{\mathrm{ij}}\cos {\mathrm{\&theta;}}_{\mathrm{ij}}+B_{\mathrm{ij}}\sin {\mathrm{\&theta;}}_{\mathrm{ij}})=0\end{array}$

$\begin{array}{c}{Q}_{\mathrm{Li}}=Q_{L\_\mathrm{set}}(1+K_q\mathrm{\&Delta;f})(q_p+q_c\left(\frac{V_L}{V_{\mathrm{LB}}}\right)+q_z{\left(\frac{V_L}{V_{\mathrm{LB}}}\right)}^2)\\ +V_i\underset{j=1}{\overset{n}{\mathrm{\&Sigma;}}}{V}_j(G_{\mathrm{ij}}\sin {\mathrm{\&theta;}}_{\mathrm{ij}}-B_{\mathrm{ij}}\cos {\mathrm{\&theta;}}_{\mathrm{ij}})=0\end{array}$

In formula: P _liand Q _lirepresent that load i injects respectively meritorious and idle.

By the various each element deriving Jacobi matrix H above, wherein part partitioned matrix element is as follows:

$\frac{{\&PartialD;P}_{\mathrm{ki}}}{{\&PartialD;V}_i}=-\frac{{2s}_i{R}_{2i}{V}_i}{s_i^2{X}_{12i}^2{(1+\mathrm{\&Delta;f})}^2+R_{2i}^2}$

$\frac{{\&PartialD;P}_{\mathrm{ki}}}{{\&PartialD;s}_i}=\frac{R_{2i}{V}_i^2{s}_i^2{X}_{12i}^2{(1+\mathrm{\&Delta;f})}^2-R_{2i}^3{V}_i^2}{{(s_i^2{X}_{12i}^2{(1+\mathrm{\&Delta;f})}^2+R_{2i}^2)}^2}$

$\frac{{\&PartialD;P}_{\mathrm{ki}}}{\&PartialD;\mathrm{\&Delta;f}}=\frac{2(1+\mathrm{\&Delta;f})R_{2i}{V}_i^2{s}_i^3{X}_{12i}^2}{{(s_i^2{X}_{12i}^2{(1+\mathrm{\&Delta;f})}^2+R_{2i}^2)}^2}$

$\frac{\&PartialD;Q_{\mathrm{ki}}}{{\&PartialD;V}_i}=-\frac{2V_i}{X_{\mathrm{mi}}(1+\mathrm{\&Delta;f})}-\frac{{2V}_i{s}_i^2{X}_{12i}(1+\mathrm{\&Delta;f})}{s_i^2{X}_{12i}^2{(1+\mathrm{\&Delta;f})}^2+R_{2i}^2}$

$\frac{{\&PartialD;Q}_{\mathrm{ki}}}{\&PartialD;s_i}=-\frac{{2s}_i{V}_i^2{X}_{12i}(1+\mathrm{\&Delta;f})R_{2i}^2}{{(s_i^2{X}_{12i}^2{(1+\mathrm{\&Delta;f})}^2+R_{2i}^2)}^2}$

$\frac{{\&PartialD;Q}_{\mathrm{ki}}}{\&PartialD;\mathrm{\&Delta;f}}=\frac{V_i^2}{X_{\mathrm{mi}}{(1+\mathrm{\&Delta;f})}^2}+\frac{V_i^2{s}_i^2{X}_{12i}(s_i^2{X}_{12i}^2{(1+\mathrm{\&Delta;f})}^2-R_{2i}^2)}{{(s_i^2{X}_{12i}^2{(1+\mathrm{\&Delta;f})}^2+R_{2i}^2)}^2}$

$\frac{\&PartialD;P_{\mathrm{Gi}}}{\&PartialD;\mathrm{\&Delta;f}}=-\frac{P_R}{R_R}$

$\frac{{\&PartialD;Q}_{\mathrm{Gi}}}{\&PartialD;\mathrm{\&Delta;f}}=-a_Q\frac{P_R}{R_R}+{2b}_Q{\left(\frac{P_R}{R_R}\right)}^2\mathrm{\&Delta;f}$

$\frac{{\&PartialD;P}_{\mathrm{Li}}}{\&PartialD;V_i}=P_{L\_\mathrm{set}}(1+K_p\mathrm{\&Delta;f})(\frac{p_c}{V_{\mathrm{LB}}}+\frac{{2p}_z{V}_i}{V_{\mathrm{LB}}^2})+\frac{2}{V_i}(G_{\mathrm{ii}}{V}_i^2+P_i)$

$\frac{{\&PartialD;Q}_{\mathrm{Li}}}{\&PartialD;V_i}=Q_{L\_\mathrm{set}}(1+K_q\mathrm{\&Delta;f})(\frac{q_c}{V_{\mathrm{LB}}}+\frac{{2q}_z{V}_i}{V_{\mathrm{LB}}^2})+\frac{1}{V_i}(-B_{\mathrm{ii}}{V}_i^2+Q_i)$

In formula: P _kiand Q _kirepresent that blower fan node i is injected respectively meritorious and idle, s _irepresent the slippage that blower fan node i is corresponding.Wherein X ₁₂=X ₁+ X ₂, subscript i represents the parameter that blower fan node i is corresponding.

According to formula above by initial each quantity of state V ⁽⁰⁾, θ ⁽⁰⁾, s ⁽⁰⁾, Δ f ⁽⁰⁾calculated value h (the x that calculated amount is measured ^(k)) and Jacobian matrix H (x ^(k)), k is iterations, solves status maintenance positive quantity Δ x ^(k), then judge whether to meet the condition of convergence, if do not reach convergent requirement, revise quantity of state V ^(k+1)=V ^(k)+ Δ V ^(k), θ ^(k+1)=θ ^(k)+ Δ θ ^(k), s ^(k+1)=s ^(k)+ Δ s ^(k), Δ f ^(k+1)=Δ f ^(k)+ Δ Δ f ^(k), repeat aforesaid operations, until convergence precision reaches requirement.

Said method concrete steps are as follows:

(1) network parameter and the measurement amount of electric system is obtained.Network parameter comprises: bus numbering, title, building-out capacitor, the branch road of transmission line of electricity number, headend node and endpoint node numbering, resistance in series, series reactance, shunt conductance, shunt susceptance, transformer voltage ratio and impedance, the atmospheric density of wind energy turbine set, wind speed, blower fan type parameter, system original frequency; Measurement amount z comprises: node voltage amplitude, node inject active power and reactive power, the active power of common line branch road and transformer branch and reactive power;

(2) parameter obtained is utilized to carry out state estimation procedure initialization above.Initialized content comprises: arrange iteration precision λ, maximum iteration time, aerogenerator slippage initial value and frequency departure initial value, forms bus admittance matrix;

(3) state estimation model containing wind-power electricity generation taking into account frequency change is set up:

min J(x)＝[z-h(x)] ^TW[z-h(x)]

(4) consider that blower fan slippage s and system frequency deviation Δ f sets up new Jacobian matrix:

$H=\left[\begin{array}{cccc}\frac{\&PartialD;P}{\&PartialD;\mathrm{\&theta;}}& \frac{\&PartialD;P}{\&PartialD;V}& \frac{\&PartialD;P}{\&PartialD;s}& \frac{\&PartialD;P}{\&PartialD;\mathrm{\&Delta;f}}\\ \frac{\&PartialD;Q}{\&PartialD;\mathrm{\&theta;}}& \frac{\&PartialD;Q}{\&PartialD;V}& \frac{\&PartialD;Q}{\&PartialD;s}& \frac{\&PartialD;Q}{\&PartialD;\mathrm{\&Delta;f}}\\ \frac{\&PartialD;P_k}{\&PartialD;\mathrm{\&theta;}}& \frac{{\&PartialD;P}_k}{\&PartialD;V}& \frac{\&PartialD;P_k}{\&PartialD;s}& \frac{\&PartialD;P_k}{\&PartialD;\mathrm{\&Delta;f}}\\ \frac{\&PartialD;Q_k}{\&PartialD;\mathrm{\&theta;}}& \frac{{\&PartialD;Q}_k}{\&PartialD;V}& \frac{\&PartialD;Q_k}{\&PartialD;s}& \frac{\&PartialD;Q_k}{\&PartialD;\mathrm{\&Delta;f}}\end{array}\right]$

(5) by initial each quantity of state V ⁽⁰⁾, θ ⁽⁰⁾, s ⁽⁰⁾, Δ f ⁽⁰⁾calculated value h (the x that calculated amount is measured ^(k)) and Jacobian matrix H (x ^(k));

(6) solving state correction amount x ^(k), judge whether to meet the condition of convergence, if max{| Δ V ^(k)|, | Δ θ ^(k)|, | Δ s ^(k)|, | Δ f ^(k)| > λ, iterations k=k+1, revise quantity of state V ^(k+1)=V ^(k)+ Δ V ^(k), θ ^(k+1)=θ ^(k)+ Δ θ ^(k), s ^(k+1)=s ^(k)+ Δ s ^(k), Δ f ^(k+1)=Δ f ^(k)+ Δ Δ f ^(k), until eligible, Output rusults.

The present invention adopts the Power system state estimation containing wind-power electricity generation taking into account frequency change, and by Simulation Example, the modelling effect demonstrating the present invention's proposition is remarkable, and in the precision of electric system estimated result, is better than the model not considering frequency departure.

Introduce embodiments of the invention below:

If the average air density of wind energy turbine set is 1.225kg/m ³; The swept area of aerogenerator is 2642m ², initial slippage is-0.0044; The incision wind speed of aerogenerator, wind rating and cut-out wind speed are respectively 3m/s, 16m/s and 21m/s; Power coefficient C _pbe 0.1217.The model of aerogenerator is V52-850, and design parameter is in table 1:

Table 1V52-850 type parameter

Example:

The present invention adopts the IEEE-14 node system shown in Fig. 2, and in order to contrast the estimated accuracy of two kinds of models, when No. 3 nodes of the Wind turbines access IEEE-14 node standard test system that 40 above-mentioned aerogenerators are formed, simulation result is as shown in the table:

Table 2 estimated result and with the comparing of true value

As shown in Figure 4: when not considering frequency departure, the averaged power spectrum error of voltage magnitude and phase angle is respectively 0.3570% and 3.0257%; When considering frequency departure, the averaged power spectrum error of voltage magnitude and phase angle is respectively 0.2662% and 1.1151%.On estimated result, do not consider that the state estimation model error of frequency is obviously greater than the state estimation model considering frequency herein, absolutely proved that this paper model more can reflect the true ruuning situation containing blower fan system.

Claims (4)

1. take into account the power system state estimation method containing wind-power electricity generation of frequency change, it is characterized in that: comprise the following steps successively:

(1) network parameter and the measurement amount of electric system is obtained;

(2) network parameter utilizing step (1) to obtain and measurement amount carry out state estimation procedure initialization;

(3) state estimation model containing wind-power electricity generation taking into account frequency change is set up:

min J(x)＝[z-h(x)] ^TW[z-h(x)]

Wherein, J is objective function; The transposition of T representing matrix; W is diagonal angle weight matrix; X is quantity of state, and dimension n=2N-1, N is nodes; Z is measurement amount, dimension m, m>n; H is that m ties up non-linear measurement function;

(4) consider that blower fan slippage s and system frequency deviation Δ f sets up new Jacobian matrix:

$H=\left[\begin{array}{cccc}\frac{\&PartialD;P}{\&PartialD;\mathrm{\&theta;}}& \frac{\&PartialD;P}{\&PartialD;V}& \frac{\&PartialD;P}{\&PartialD;s}& \frac{\&PartialD;P}{\&PartialD;\mathrm{\&Delta;f}}\\ \frac{\&PartialD;Q}{\&PartialD;\mathrm{\&theta;}}& \frac{\&PartialD;Q}{\&PartialD;V}& \frac{\&PartialD;Q}{\&PartialD;s}& \frac{\&PartialD;Q}{\&PartialD;\mathrm{\&Delta;f}}\\ \frac{{\&PartialD;P}_k}{\&PartialD;\mathrm{\&theta;}}& \frac{{\&PartialD;P}_k}{\&PartialD;V}& \frac{{\&PartialD;P}_k}{\&PartialD;s}& \frac{\&PartialD;P_k}{\&PartialD;\mathrm{\&Delta;f}}\\ \frac{{\&PartialD;Q}_k}{\&PartialD;\mathrm{\&theta;}}& \frac{\&PartialD;Q_k}{\&PartialD;V}& \frac{{\&PartialD;Q}_k}{\&PartialD;s}& \frac{{\&PartialD;Q}_k}{\&PartialD;\mathrm{\&Delta;f}}\end{array}\right]$

Wherein, P and Q represents corresponding meritorious and idle of common generator respectively; P _kand Q _kbe respectively corresponding meritorious and idle of the access node k of asynchronous blower fan; Wherein with dimension identical with the number of system apoplexy electric field node;

(5) by initial each quantity of state V ⁽⁰⁾, θ ⁽⁰⁾, s ⁽⁰⁾, Δ f ⁽⁰⁾calculated value h (the x that calculated amount is measured ^(k)) and Jacobian matrix H (x ^(k)), wherein, θ represents voltage phase angle, and V represents voltage magnitude, and s is slippage, and Δ f is frequency departure amount, and 0 represents original state amount;

(6) solving state correction amount x ^(k), judge whether to meet the condition of convergence, if max{| Δ V ^(k)|, | Δ θ ^(k)|, | Δ s ^(k)|, | Δ f ^(k)| > λ, iterations k=k+1, revise quantity of state V ^(k+1)=V ^(k)+ Δ V ^(k), θ ^(k+1)=θ ^(k)+ Δ θ ^(k), s ^(k+1)=s ^(k)+ Δ s ^(k), Δ f ^(k+1)=Δ f ^(k)+ Δ Δ f ^(k), until eligible, Output rusults, wherein, k is iterations.

2. take into account the power system state estimation method containing wind-power electricity generation of frequency change as claimed in claim 1, it is characterized in that: in step (2), initialized content comprises: arrange iteration precision λ, maximum iteration time and aerogenerator slippage initial value and frequency departure initial value, forms bus admittance matrix.

3. take into account the power system state estimation method containing wind-power electricity generation of frequency change as claimed in claim 1 or 2, it is characterized in that: in step (1), network parameter comprises: bus numbering, title, building-out capacitor, the branch road of transmission line of electricity number, headend node and endpoint node numbering, resistance in series, series reactance, shunt conductance, shunt susceptance, transformer voltage ratio and impedance, the atmospheric density of wind energy turbine set, wind speed, blower fan type parameter, system original frequency.

4. take into account the power system state estimation method containing wind-power electricity generation of frequency change as claimed in claim 1 or 2, it is characterized in that: in step (1), measurement amount z comprises: node voltage amplitude, node inject active power and reactive power, the active power of common line branch road and transformer branch and reactive power.