CN113419462B - Power grid current composite prediction control method based on harmonic interference observer - Google Patents

Power grid current composite prediction control method based on harmonic interference observer Download PDF

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CN113419462B
CN113419462B CN202110774044.XA CN202110774044A CN113419462B CN 113419462 B CN113419462 B CN 113419462B CN 202110774044 A CN202110774044 A CN 202110774044A CN 113419462 B CN113419462 B CN 113419462B
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power grid
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李文硕
杨钰琨
郭雷
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Hangzhou Innovation Research Institute of Beihang University
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Abstract

A power grid current composite prediction control method based on a harmonic interference observer is characterized in that the interference observer is combined with a prediction controller to achieve anti-interference tracking control of power grid current under the conditions of inverter switch harmonic waves and grid side voltage fluctuation, and control accuracy and robustness of a grid-connected inverter are improved. In the design process of the composite control method, firstly, aiming at harmonic interference caused by the switching action of a grid-connected inverter, a harmonic interference observer is designed to carry out real-time estimation and feedforward compensation on the harmonic interference; secondly, designing a composite predictive controller based on an interference feedforward compensation term, and realizing robust tracking control of current under the condition that the voltage of a power grid fluctuates; and finally, reasonably selecting parameters of the composite controller, and simultaneously ensuring the anti-interference capability and closed loop stability of the system, so that the grid-connected inverter can output stable three-phase voltage and current. The grid-connected inverter composite prediction control method is suitable for the voltage source inversion process of a three-phase grid-connected system, can improve the accuracy and robustness of current tracking control, and improves the power consumption quality of a power grid user.

Description

Power grid current composite prediction control method based on harmonic interference observer
Technical Field
The invention relates to a power grid current composite prediction control method based on a harmonic interference observer, and belongs to the technical field of electric power.
Background
With the continuous consumption of global electric energy and the increasing aggravation of environmental problems, fossil fuel is used as a main energy source consumed by human, adverse effects are brought by improper treatment in the using process of the fossil fuel, and the fossil fuel is environment-friendly for people on the premise that China insists on implementing sustainable development strategies. Awareness is gradually increased, and more green energy is developed and utilized by human beings. The traditional grid form (power generation, distribution and utilization) is also changing. In the aspect of new energy power generation, renewable clean energy represented by wind power generation, hydrogen energy, solar energy and the like is favored domestically, and the wind energy and the solar power generation in 2017 in China are increased by 34% and 74% in 2016. The green energy sources such as water conservancy power generation, wind power generation, nuclear power generation, natural gas and solar power generation account for 18 percent of the total amount. Prediction of the Chinese Committee: the demand for renewable energy in china will continue to increase, and new energy will account for up to 16% by 2020, which is expected to exceed oil.
In a new energy power generation system, most of the new energy power generation systems adopt a three-phase inverter as an interface circuit to realize energy conversion and grid-connected power generation. In an inverter power generation system, unlike conventional thermal power generation, new energy electric power such as wind energy and solar energy has low density dispersibility on a spatial scale and strong random fluctuation on a time scale. The large-scale access of new energy electric power can cause the 'load' and 'source' of the power grid to present strong randomness and volatility, and great challenges are brought to the operation and control of the power grid. With the continuous addition of new energy, the new energy grid-connected inverter mainly based on light energy is connected to a power grid in a large scale, so that the safe and stable operation capability of the power grid is reduced. In the grid connection process, various interferences are faced in the inversion process, and not only the interferences brought by the inverter but also the interferences existing in the power grid. The inverter is controlled by PWM, the output result of the inverter carries higher harmonics, and the result is filtered by a filter, but the obtained result is still not ideal, and the problems of harmonic interference and point voltage fluctuation are still caused. The performance of the power electronic system is also affected by various forms of unknown disturbance in the operation process, such as perturbation of parameters of circuit input voltage, load power, inductance, capacitance, parasitic resistance and the like caused by external environment or working condition change. More importantly, the interferences take various forms, such as time-varying circuit parameters and uncertainty of external environment, which may take the form of harmonic variables, step variables, slopes or parabolas and other high-order characteristic variables, and the existence of the interferences can seriously affect the control performance of the system. The invention provides a grid current composite prediction control method based on a harmonic interference observer, wherein the influence of interference carried by an inversion process on the inversion process is great, so that a composite control strategy is designed, and the harmonic interference observer is designed to carry out real-time estimation and feedforward compensation on the harmonic interference aiming at the harmonic interference caused by the switching action of a grid-connected inverter; furthermore, a composite predictive controller is designed based on the interference feedforward compensation term, and the robust tracking control of the current is realized under the condition that the voltage of the power grid fluctuates; and finally, reasonably selecting parameters of the composite controller, and simultaneously ensuring the anti-interference capability and closed loop stability of the system, so that the grid-connected inverter outputs stable three-phase voltage and current.
Disclosure of Invention
The technical problem of the invention is solved: the method overcomes the defects of the prior art, provides a power grid current composite prediction control method based on a harmonic interference observer, compensates harmonic interference in the power grid inversion process, inhibits voltage fluctuation interference existing at a power grid end, ensures the anti-interference capability and closed loop stability of a system, and well meets the grid connection requirement of the power grid.
In order to achieve the purpose, the technical scheme of the invention is as follows: extracting real-time phase frequency data of a power grid by using a phase-locked loop, and carrying out abc-dq change on actual current of the power grid by combining the detected phase frequency data to obtain the actual dq axis current value of the power grid as a feedback signal of a current controller; the method comprises the steps of designing an interference observer aiming at harmonic interference, observing the interference, carrying out control adjustment by inner-loop feedforward compensation and then selecting reasonable parameters by designing a model prediction controller, inhibiting voltage fluctuation interference existing on the side of a power grid, finally obtaining stable current control output, and further controlling an inverter so as to output high-quality voltage and current signals to the power grid.
The invention discloses a power grid current composite prediction control method based on a harmonic interference observer, which comprises the following steps of:
firstly, applying kirchhoff's law to a phase-locked loop, a current controller, a voltage source inverter and an LCL filter which are involved in the grid inversion process and combining synchronous coordinate transformation to obtain a differential equation which is satisfied by dq-axis current; combining the dynamic characteristics of the switch harmonic interference with a dq-axis current differential equation to establish a state space model facing current tracking control;
secondly, designing a harmonic interference observer according to a state space model of current tracking control and dynamic characteristics of harmonic interference of a switch, and estimating and compensating the harmonic interference generated by the switching action of the inverter in real time;
thirdly, designing a model predictive controller according to a state space model of the current tracking control in the first step based on uncertain factors of voltage fluctuation, voltage mutation and voltage flicker existing in the power grid, and ensuring the robustness of the current tracking control of the power grid under the uncertain factors;
and fourthly, compounding the harmonic interference observer in the second step with the model prediction controller in the third step to obtain a compound prediction control law containing a harmonic interference feedforward compensation term, and realizing simultaneous compensation and inhibition of unknown fluctuation of the switching harmonic waves and the power grid voltage of the inverter.
In the first step, the dq-axis current differential equation is:
Figure BDA0003153663670000031
Figure BDA0003153663670000032
wherein wdAnd wqRepresents the mapping of the harmonic disturbance w generated by the system on the dq axis, LT＝Lg+Lc，Lg、LcInductance of the grid side of the LCL filter and inductance of the inverter side, R, respectivelyT＝rg+rc，rg、rcThe resistance value of the grid end of the LCL filter and the resistance value of the inverter side, ucdAnd ucqInput voltages u of dq axes, respectivelygdAnd ugqGrid voltage, i, of dq axis respectivelygdAnd igqThe dq axis grid currents are respectively;
the state space model of the current tracking control is as follows:
Figure BDA0003153663670000033
y＝Cx
wherein:
Figure BDA0003153663670000034
state vector x ═ iq,id]Input vector U ═ Ucd,Ucq]Wherein U iscd＝ucd-ugd,Ucq＝ucq-ugq,ucdAnd ucqInput voltages u of dq axes, respectivelygdAnd ugqGrid voltage of dq axis, harmonic interference w0＝[wd,wq]，wd、wqHarmonic interference, L, respectively to the dq axisT＝Lg+Lc，RT＝rg+rc，rcAnd rgIs the equivalent resistance of the inverter and grid inductances.
In the second step, the disturbance observer is designed as follows:
Figure BDA0003153663670000035
wherein
Figure BDA0003153663670000036
For the interference estimation value, u is the control input of the grid-connected inverter system, A, B is a matrix A, B of a state space equation in the subsequent derivation process, x is a state vector, L is a design value, the pole position is determined, and z is an intermediate variable. And designing the L value, wherein LB is a Hurwitz matrix or the sign is negative, so that the estimated value of the interference approaches to the true value of the interference, namely, when the LB matrix is negative or the Hurwitz matrix, the estimated interference value is more accurate.
In the third step, the model predictive controller designs and controls the predictive controller on line aiming at the power grid model, and the model predictive control algorithm is as follows:
Figure BDA0003153663670000041
changing the problem into a convex quadratic programming problem and inquiring the convex quadratic programmingSolving the problem to obtain UkThe first element of the control period is extracted and used as the control quantity of the control period, the circulation is carried out again, the steps are carried out again at the next moment, the control quantity of the current moment is obtained, the online rolling optimization is carried out, and the real-time control result is obtained, wherein UkFor predicting the control quantity in the time domain, H and fTIs a constraint term;
Uk＝[u(k|k)Tu(k+1|k)T…u(k+M-1|k)Tu(k+M|k)T…u(k+P-1|k)T]Tp is a prediction time domain, M is a control time domain, u (k +1| k) in parentheses represents a control amount at the time when k +1 is predicted at the time, and so on.
H＝2(ΘTQΘ+W)
fT＝2ETQΘ
Wherein E ═ Ψ x (k) -RkX (k) is the system k time state, Rk＝[r(k+1)T r(k+2)T … r(k+P)T]TTo predict the reference sequence in the time domain, r (k +1) represents the reference value at time k +1, and so on,
Figure BDA0003153663670000042
Figure BDA0003153663670000043
for the discretized system state matrix, Q, W is a constraint matrix for solving the optimization problem.
Compared with the prior art, the invention has the advantages that: the method adopts the interference observer, and designs the harmonic interference observer to carry out real-time estimation and feedforward compensation on the harmonic interference aiming at the harmonic interference caused by the switching action of the grid-connected inverter; furthermore, a composite predictive controller is designed based on the interference feedforward compensation term, and the robust tracking control of the current is realized under the condition that the voltage of the power grid fluctuates; and finally, reasonably selecting parameters of the composite controller, and simultaneously ensuring the anti-interference capability and closed loop stability of the system, so that the grid-connected inverter can output stable three-phase voltage and current.
Drawings
FIG. 1 is a block flow diagram of a composite controller design of the present invention;
FIG. 2 is a block diagram of the current predictive controller of the present invention in conjunction with a DOBC control strategy;
FIG. 3 is a simulation diagram of the present invention simulating tracking of dq-axis current reference inputs in the presence of grid voltage ripple interference;
FIG. 4 is a simulation diagram of the actual three-phase current of the power grid of the simulation original PI control method of the invention;
FIG. 5 is a simulation diagram of the actual three-phase current of the power grid of the simulation compound control method of the invention.
Detailed Description
The invention is applied to a power grid inversion system, and the specific implementation process is as follows: firstly, extracting the actual phase frequency of the power grid through a phase-locked loop (PLL) at a power grid coupling Point (PCC) to obtain the real-time phase theta of the power gridPCCThe current value is used as the input of a synchronous coordinate converter, and the actual current value i of the power grid after passing through an LCL filter is usedg,abcAlso as the input signal of the synchronous coordinate converter, combines with the phase information of the power grid to carry out synchronous coordinate change to obtain the value i of the synchronous coordinate system of the actual power grid currentg,dqThen i isg,dqAnd a reference current
Figure BDA0003153663670000051
And as input, current anti-interference control is carried out through a current composite controller to obtain stable current output, the control output value controls PWM to obtain PWM waves required by inversion, and then the switch of an IGBT of the inverter is controlled to control the inversion process, so that the voltage and current waveforms output by the inverter are in the same frequency and phase with the actual power grid voltage and current waveforms obtained at a power grid coupling point, and high-quality voltage and current are transmitted to a power grid.
The invention will be described in further detail below with reference to the figures and specific implementation:
as shown in fig. 1, the present invention is embodied as follows:
step 1, mathematical model establishment is carried out on an inversion process, and the specific implementation process is as follows:
as shown in fig. 1, the inversion process is modeled, and dq coordinate axis differential equations are established for the LCL filter, and the modeling result is as follows:
Figure BDA0003153663670000052
Figure BDA0003153663670000053
Figure BDA0003153663670000054
where ω is the inductive operating angular frequency, CfIs a capacitance of the filter and is,
Figure BDA0003153663670000055
is the voltage of the capacitor(s),
Figure BDA0003153663670000056
is an inductance LgThe voltage of (a) is set to be,
Figure BDA0003153663670000057
is the inverter voltage, Lg＝Lg1+Lg2，Lg1、Lg2、LcIs an inductance value r in the abstract figurecAnd rgIs the equivalent resistance of the inverter and the grid inductance,
Figure BDA0003153663670000058
and
Figure BDA0003153663670000059
are respectively an inductance Lg、LcAnd a capacitor CfThe current of (2). Furthermore, a relational expression of the system in the dq axis can be obtained through synchronous coordinate transformation, and modeling is carried out in consideration of harmonic interference, wherein the equation is as follows:
Figure BDA00031536636700000510
Figure BDA00031536636700000511
wherein wdAnd wqRepresents the mapping of the harmonic disturbance w generated by the system on the dq axis, LT＝Lg+Lc，RT＝rg+rc，ucdAnd ucqInput voltages u of dq axes, respectivelygdAnd ugqGrid voltage, i, of dq axis respectivelygdAnd igqDq-axis grid currents, respectively.
Step 2, extracting phase-frequency information of the actual power grid, wherein the specific phase-locked loop extraction process is as follows:
in general, the three-phase voltage v of the gridabcThe following were used:
Figure BDA0003153663670000061
when passing through a phase detector, firstly, Clarke transformation is carried out, and the stationary coordinate system of alpha beta is expressed as follows:
Figure BDA0003153663670000062
wherein the content of the first and second substances,
Figure BDA0003153663670000063
is the actual angular frequency of the grid, and:
Figure BDA0003153663670000064
then, after Park transformation, the expression of the dq rotation coordinate system is as follows:
Figure BDA0003153663670000065
wherein:
Figure BDA0003153663670000066
θ' is the phase angle of the rotating coordinate system.
When the rotating coordinate system is synchronous with the voltage vector, the d-axis component is coincident with the fundamental frequency direction of the voltage vector, and at the moment
Figure BDA0003153663670000067
At this time, the expression after the synchronization is,
Figure BDA0003153663670000068
at the moment, the phase-locked loop finishes phase locking to obtain real-time frequency and amplitude information theta of the power gridPCC。
Step 3, combining the extracted real-time phase information thetaPCCTo the grid current ig,abcAnd (3) carrying out synchronous coordinate transformation, wherein the specific transformation process is as follows:
in general, the three-phase current i of the gridg,abcThe following were used:
Figure BDA0003153663670000071
first, after Clarke transformation, the α β stationary coordinate system is expressed as follows:
Figure BDA0003153663670000072
wherein I is the current amplitude of the power grid,
Figure BDA0003153663670000073
then, after Park transformation, the expression of the dq rotation coordinate system is as follows:
Figure BDA0003153663670000074
wherein:
Figure BDA0003153663670000075
at this time
Figure BDA0003153663670000076
Then:
Figure BDA0003153663670000077
thus, the synchronous coordinate transformation of the current is completed, and a dq-axis power grid current signal i is obtaineddq。
And 4, designing a disturbance observer as shown in FIG. 1, and performing real-time feedforward compensation on harmonic disturbance. The block diagram of the composite controller shown in fig. 2, wherein d is harmonic interference generated by the inversion process; y is the output current; r is a reference input; the red dashed box is the disturbance observer. As is apparent from fig. 2, the DOBC has an inner and outer loop structure, where the inner loop is a disturbance observer and the outer loop is a feedback controller. Aiming at harmonic interference, a disturbance observer is designed, and the specific design process is as follows:
and (3) carrying out synchronous coordinate transformation on the system model to obtain a dq coordinate system equation:
Figure BDA0003153663670000078
Figure BDA0003153663670000079
wherein wdAnd wqRepresenting harmonic interference, L, produced by the system dq-axis systemT＝Lg+Lc，RT＝rg+rc，ucdAnd ucqInput voltages u of dq axes, respectivelygdAnd ugqGrid voltage, i, of dq axis respectivelygdAnd igqDq-axis grid currents, respectively.
For the convenience of control design, a dq differential equation is written as a state space expression, and the state space equation of the system is established as follows:
Figure BDA0003153663670000081
y＝Cx
wherein:
Figure BDA0003153663670000082
state vector x ═ iq,id]Input vector U ═ Ucd,Ucq]Wherein U iscd＝ucd-ugd,Ucq＝ucq-ugqHarmonic interference w0＝[wd,wq]，wd、wqHarmonic interference, L, respectively to the dq axisT＝Lg+Lc，RT＝rg+rc，rcAnd rgIs the equivalent resistance of the inverter and grid inductances. Designing the interference observer through a state space expression to obtain the interference observer:
Figure BDA0003153663670000083
wherein
Figure BDA0003153663670000084
For the interference estimation, u is the inverter control input and L is the design gain value, determinedThe pole position, z is an intermediate variable, defining the interference estimation error:
Figure BDA0003153663670000085
where d is the actual interference, the derivation is taken and substituted into the equation:
Figure BDA0003153663670000086
the estimated value of the interference can be approximated to the true value of the interference by making LB a Hurwitz matrix or negative in sign.
In the invention, the actual system model and the nominal model do not completely conform, so the state x taken from the nominal model is not the true state x, but considering that the nominal model and the true model are relatively close and the state x of the true model is difficult to restore from the original output, the state taken from the nominal model is used for estimating the interference d. Thus, the design of the disturbance observer is completed.
Step 5, as shown in fig. 1, designing a model predictive controller, and designing and performing online control on the predictive controller for the power grid model, wherein the specific implementation method is as follows:
writing a dq-axis current differential equation into a state space expression, specifically, neglecting interference influence, and establishing the state space expression of an inversion process as follows:
Figure BDA0003153663670000087
wherein:
Figure BDA0003153663670000091
state vector x ═ iq,id]Input vector U ═ Ucd,Ucq]Wherein U iscd＝ucd-ugd,Ucq＝ucq-ugq,ucdAnd ucqInput voltages u of dq axes, respectivelygdAnd ugqRespectively dq-axis grid voltage, LT＝Lg+Lc，RT＝rg+rc，rcAnd rgThe equivalent resistance of the inverter and the power grid inductor is designed by adopting the following mode based on the state space expression.
Discretizing a state equation by adopting a forward Euler method:
Figure BDA0003153663670000092
x(k+1)＝(I+TA)x(k)+TBu(k)
Figure BDA0003153663670000093
t is a discrete time interval, wherein:
Figure BDA0003153663670000094
recording the predicted system state of P cycles in the future as follows:
Xk＝[x(k+1|k)Tx(k+2|k)T…x(k+P|k)T]T
where P is the prediction time domain, and k +1| k in the parenthesis represents the system state at the time when k +1 is predicted at the current time k, and so on. In addition, when predicting the future state of the system, it is necessary to know the control amount U in the prediction time domainkM is the control time domain, M is less than or equal to P, and when M is equal to P, U is in the control time domainkComprises the following steps:
Uk＝[u(k|k)Tu(k+1|k)T…u(k+P-1|k)T]T
when M is<P, where M ≦ i ≦ P-1 at time k + i, u (k + i | k)TIs a control quantity at the time of a steady state of the system, where u (k + M | k)T＝u(k+M+1|k)T＝…＝u(k+P-1|k)T
At this time UkComprises the following steps:
Uk＝[u(k|k)Tu(k+1|k)T…u(k+M-1|k)Tu(k+M|k)T…u(k+P-1|k)T]T
is the decision variable of the optimization problem that is next required to be solved.
And then, sequentially predicting the system states of the future P prediction periods through a discretization equation:
Figure BDA0003153663670000101
integration into matrix form:
Xk＝Ψx(k)+ΘUk
wherein:
Figure BDA0003153663670000102
the next step is to list the optimized cost function, first defining the reference sequence in the prediction domain:
Rk＝[r(k+1)T r(k+2)T … r(k+P)T]T
defining an optimization cost function by using the accumulated error between the predicted state quantity and the reference value, and adding a constraint term to the control quantity:
J(Uk)＝(Xk-Rk)TQ(Xk-Rk)+Uk TWUk
q, W is a constraint matrix, in which case the optimization problem can be described as follows:
Figure BDA0003153663670000103
s.t.|u(k+j|k)|≤umax,j＝0,1,2,…P-1
will optimize function J (U)k) Merging the same kind of items after expansion:
Figure BDA0003153663670000104
in the formula ETQE is a constant term, has no effect on the minimization of the optimization problem, and can be rounded off:
order to
H＝2(ΘTQΘ+W)
fT＝2ETQΘ
The final optimized objective function can be obtained:
Figure BDA0003153663670000111
finally, the problem is converted into a convex quadratic programming problem, the quadratic programming problem is solved, and the obtained UkThe first element of the control period is extracted and used as the control quantity of the control period, circulation is carried out again, the steps are carried out again at the next moment, the control quantity of the current moment is obtained, online rolling optimization is carried out, and a real-time control result is obtained.
And 6, combining the interference observer with the prediction controller to realize anti-interference tracking control of the power grid current under the conditions of switching harmonic waves of the inverter and network side voltage fluctuation, obtaining control input of the inverter, further controlling the inverter, and finishing conversion of direct current voltage to alternating current voltage so that the inverter can deliver high-quality voltage and current to the power grid.
The simulation experiment of the power grid current composite prediction control method based on the harmonic interference observer is as follows:
DC voltage Vdc380V, filter capacitor C f10 muF, inverter side inductance LcAt 4mH, the network side inductance Lg2mH, the switching frequency of the grid-connected inverter is 10KHz, the public frequency of the grid voltage is 50Hz, and the equivalent resistance RTIs 2 omega. The disturbance observer L is designed as [ -100; 0-10]The PI controller parameter P is 2 and I is 2. The predictive controller parameters are set to: sampling time 1e-4, prediction step length p of 20, control step length m of 5, and constraint upper and lower limits of 25 and-25 respectively. The simulation duration is 1s, inA voltage jump is added at 0.3 second, with a jump amplitude of 30.
From fig. 3, it can be seen that Simulink simulation results in tracking the d-axis current waveform of the reference current in case of disturbance of the voltage fluctuation of the live grid. The reference current amplitude is 10, the tracking result on the d axis is shown in fig. 3, it can be seen that voltage amplitude fluctuation interference exists in 0.3 seconds, but under the control tracking of the composite controller, the current amplitude quickly continues to track the reference value, the interference is restrained and compensated in time, the reference current is well tracked, fluctuation exists in the steady state process, but the absolute value of the error is less than 0.05, the visible error is small, and therefore, the judgment can also be made that the current tracking has a very good tracking effect after entering the steady state. Fig. 4 is a simulation result diagram of the power grid under the condition of only using the original PI controller for control, and it can be seen from the diagram that a large fluctuation is generated when the voltage fluctuates for 0.3 second, and harmonic interference exists in the three-phase current in a steady state, so that the waveform of the three-phase current is distorted. Compared with the original PI controller, the current is tracked and controlled through the composite controller, the three-phase current waveform obtained in an actual power grid is shown in figure 5, as can be seen from the figure, the fluctuation exists in 0.3 second, the interference is quickly inhibited through the composite controller, the three-phase current waveform is adjusted back, the composite controller has good rapidity, and in a steady state, the three-phase current signal is consistent with the three-phase current signal required by the power grid, and the harmonic interference is well compensated. Compared with an original PI controller, the three-phase current controlled by the composite controller has very good steady-state performance.
Therefore, the composite observer aiming at the grid inversion process has the compensation and inhibition capability on harmonic interference and grid voltage fluctuation interference. Therefore, the method can improve the accuracy and robustness of current tracking control and improve the power consumption quality of power grid users.

Claims (3)

1. A power grid current composite prediction control method based on a harmonic interference observer is characterized by comprising the following steps:
firstly, applying kirchhoff's law to a phase-locked loop, a current controller, a voltage source inverter and an LCL filter which are involved in the grid inversion process and combining synchronous coordinate transformation to obtain a differential equation which is satisfied by dq-axis current; combining the dynamic characteristics of the switch harmonic interference with a dq-axis current differential equation to establish a state space model facing current tracking control;
secondly, designing a harmonic interference observer according to a state space model of current tracking control and dynamic characteristics of harmonic interference of a switch, and estimating and compensating the harmonic interference generated by the switching action of the inverter in real time;
thirdly, designing a model predictive controller according to a state space model of the current tracking control in the first step based on uncertain factors of voltage fluctuation, voltage mutation and voltage flicker existing in the power grid, and ensuring the robustness of the current tracking control of the power grid under the uncertain factors;
fourthly, compounding the harmonic interference observer in the second step with the model prediction controller in the third step to obtain a compound prediction control law containing a harmonic interference feedforward compensation term, and realizing simultaneous compensation and inhibition of unknown fluctuation of the inverter switch harmonic wave and the power grid voltage;
in the first step, the dq-axis current differential equation is:
Figure FDA0003596760840000011
Figure FDA0003596760840000012
wherein wdAnd wqRepresents the mapping of the harmonic disturbance w generated by the system on the dq axis, LT＝Lg+Lc，Lg、LcInductance of the grid side of the LCL filter and inductance of the inverter side, R, respectivelyT＝rg+rc，rg、rcThe resistance value of the grid end of the LCL filter and the resistance value of the inverter side, ucdAnd ucqInput voltages u of dq axes, respectivelygdAnd ugqGrid voltage, i, of dq axis respectivelygdAnd igqThe dq axis grid currents are respectively;
the state space model of the current tracking control is as follows:
Figure FDA0003596760840000013
y＝Cx
wherein:
Figure FDA0003596760840000021
state vector x ═ iq,id]Input vector U ═ Ucd,Ucq]Wherein U iscd＝ucd-ugd,Ucq＝ucq-ugq,ucdAnd ucqInput voltages u of dq axes, respectivelygdAnd ugqGrid voltage of dq axis, harmonic interference w0＝[wd,wq]，wd、wqHarmonic interference, L, respectively to the dq axisT＝Lg+Lc，RT＝rg+rc，rcAnd rgIs the equivalent resistance of the inverter and grid inductances.
2. The harmonic interference observer-based grid current composite predictive control method according to claim 1, characterized in that: in the second step, the disturbance observer is designed as follows:
Figure FDA0003596760840000022
wherein
Figure FDA0003596760840000023
For interference estimationAnd in the evaluation value, u is the control input of the grid-connected inverter system, A, B is a matrix A, B of a state space equation in the subsequent derivation process, x is a state vector, L is a design value, the pole position is determined, z is an intermediate variable, the value of L is designed, LB is a Hurwitz matrix or the sign is negative, so that the estimated value of the interference approaches the true value of the interference, namely when the LB matrix is negative or the Hurwitz matrix, the estimated interference value is more accurate.
3. The harmonic interference observer-based grid current composite predictive control method according to claim 1, characterized in that: in the third step, the model predictive controller designs and controls the predictive controller on line aiming at the power grid model, and the model predictive control algorithm is as follows:
Figure FDA0003596760840000024
changing the problem into a convex quadratic programming problem, solving the convex quadratic programming problem to obtain a UkThe first element of the control period is extracted and used as the control quantity of the control period, circulation is carried out again, the steps are carried out again at the next moment, the control quantity of the current moment is obtained, online rolling optimization is carried out, and a real-time control result is obtained, wherein UkFor predicting the control quantity in the time domain, H and fTIs a constraint term;
Uk＝[u(k|k)Tu(k+1|k)T…u(k+M-1|k)Tu(k+M|k)T…u(k+P-1|k)T]Tp is a prediction time domain, M is a control time domain, u (k +1| k) in parentheses represents a control quantity at the time of predicting k +1 at the time of k, and so on;
H＝2(ΘTQΘ+W)
fT＝2ETQΘ
wherein E ═ Ψ x (k) -RkX (k) is the system k time state, Rk＝[r(k+1)T r(k+2)T…r(k+P)T]TTo predict the reference sequence in the time domain, r (k +1) represents the reference value at time k +1, and so on,
Figure FDA0003596760840000031
Figure FDA0003596760840000032
for the discretized system state matrix, Q, W is the constraint matrix for solving the optimization problem.
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