CN116544964A - Impedance optimization method of wind power generation system - Google Patents

Impedance optimization method of wind power generation system Download PDF

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CN116544964A
CN116544964A CN202310503296.8A CN202310503296A CN116544964A CN 116544964 A CN116544964 A CN 116544964A CN 202310503296 A CN202310503296 A CN 202310503296A CN 116544964 A CN116544964 A CN 116544964A
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impedance
axis component
net
expression
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CN116544964B (en
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郭小强
章仕起
魏玉鹏
孔寒冰
王凡
刁乃哲
卢志刚
华长春
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Yanshan University
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    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
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    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
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    • H02P21/0003—Control strategies in general, e.g. linear type, e.g. P, PI, PID, using robust control
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    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
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Abstract

The invention discloses an impedance optimization method of a wind power generation system, which belongs to the field of power system stability, wherein a doubly-fed fan main circuit comprises the following components from left to right: the invention discloses an impedance optimization method for a doubly-fed fan system, which comprises a doubly-fed fan, a rotor side transformer T, a rotor side filter inductance Lr, a machine side converter MSC, a converter capacitor, a grid side converter GSC, a grid side filter inductance Lg, a grid side capacitor and a power grid, wherein the impedance optimization method is based on a control link of a virtual resistor of a doubly-fed fan rotor side control link, a control link of a doubly-fed grid side converter additional band-pass filter and an optimization debugging method of the doubly-fed grid side converter. The invention provides the impedance optimization scheme and the corresponding optimization and debugging method for the small wind working condition, which can pointedly solve the problem of subsynchronous oscillation under the small wind working condition, realize the impedance optimization of the doubly-fed fan, and have good technical effect and high practical value.

Description

Impedance optimization method of wind power generation system
Technical Field
The invention belongs to the field of power system stability, and particularly relates to an impedance optimization method of a wind power generation system.
Background
Under the goals of carbon peak and carbon neutralization, the large-scale development and utilization of new energy represented by wind energy and solar energy are quickened, the low-carbon transformation of energy power is facilitated, the power grid-connected installation 4757 ten thousand kW is newly increased by 2021, and the power grid-connected installation is increased by 16.6% in a same ratio. By the end of 2021, the wind power had accumulated installed capacity of 3.28 million kW, with an onshore wind turbine accumulated installed capacity of 3.02 million kW. High-power, high-voltage and long-distance conveying patterns are formed in the aspect of wind power. Wind power is sent out through a series compensation capacitor and is widely applied to practical engineering. However, the double-fed fan system has the problem of subsynchronous oscillation, and the subsynchronous oscillation of the system can be effectively restrained by carrying out impedance optimization on the double-fed fan. Therefore, the impedance optimization is carried out on the double-fed fan, and the suppression of the subsynchronous oscillation of the double-fed fan system is of great significance.
Li Penghan et al propose that the rotor side control link of the doubly-fed wind turbine utilizes the control strategy of the sliding mode variable structure to inhibit subsynchronous oscillation caused by the grid-connected subsynchronous control interaction of the doubly-fed wind turbine in the literature of feedback linearization sliding mode variable structure inhibition of subsynchronous control interaction of the doubly-fed wind turbine; su Tianyu et al in the literature of the phenomenon of grid-connected double-fed wind power plant subsynchronous/supersynchronous mixed oscillation and damping control scheme, aiming at subsynchronous/supersynchronous oscillation caused by series compensation grid connection of a double-fed wind power plant, a damper is added to control a rotor side of the double-fed wind power plant to inhibit the subsynchronous/supersynchronous oscillation; shan Bihan et al propose to use an additional damping control strategy in the rotor side control link to achieve subsynchronous resonance suppression in the literature "stator side analogue resistance based doubly fed wind farm subsynchronous oscillation suppression strategy study".
Under the working condition of small wind, namely the working condition of minimum active power (for example, the active power is the minimum power, 20% rated power, 50% rated power and the like), the impedance of the doubly-fed fan system is difficult to meet the technical requirements of the impedance characteristics of the new energy station. At present, a plurality of schemes are proposed for solving the problem of impedance optimization of the doubly-fed fans, but most of impedance optimization schemes based on rated power working conditions have poor optimization effect under small wind working conditions, are not suitable for impedance optimization of the doubly-fed fans under the small wind conditions, and are not designed for impedance optimization under the small wind working conditions; in addition, the existing scheme is not provided with a virtual resistor at the machine side, and a band-pass filter impedance optimization scheme is controlled and added at the network side.
Disclosure of Invention
The invention aims to provide an impedance optimization method of a wind power generation system, which can be used for carrying out impedance optimization on a doubly-fed fan under a small wind working condition and solving the problem of secondary super-synchronous oscillation under the small wind working condition.
In order to achieve the above purpose, the technical scheme adopted by the invention is as follows: an impedance optimization method of a wind power generation system, a main circuit of a doubly-fed wind power generation system comprises the following steps from left to right: double-fed fan, rotor side transformer T and rotor side filter inductance L r Side current transformer (MSC), current transformer capacitor, network side current transformer (GSC), network side filter inductance L g Network side capacitance and power grid.
Rotor side inductor current i r_abc The d-axis component i of the inductance current of the rotor side is obtained by collecting the inductance current from the rotor side line and transforming the coordinates dr And rotor side inductor current q-axis component i qr ；
Net side inductance current i g_abc The d-axis component i of the net-side inductance current is obtained after the coordinate transformation is acquired from the net-side line gd And net side inductor current q-axis component i gq ；
Network side capacitance voltage u g_abc The d-axis component u of the net-side capacitance voltage is obtained after the coordinate transformation is acquired from the net-side line gd And net side capacitor voltage q-axis component u gq ；
Rotor side phase angle theta r Frequency omega r Obtained via photoelectric encoder, net side phase angle theta g Frequency omega g Obtained via a Phase Locked Loop (PLL).
The modulation mode of MSC and GSC is space vector modulation (SVPWM), q-axis component control mode of MSC is torque outer ring-current inner ring double closed-loop control, d-axis component control mode is voltage outer ring-current inner ring double closed-loop control; the q-axis component control mode of the GSC is current closed-loop control, and the d-axis component control mode is voltage outer ring-current inner ring double closed-loop control.
Wherein the reference current i qr_ref From rotor-side reference torque T e_ref After adjustment, the regulator expression is: k omega g K is the active current coefficient, ω, calculated from the torque g Is the network side frequency; reference current i dr_ref From the q-axis component u of the net-side capacitor voltage gq After adjustment, the regulator expression is: 1/X m ，X m Excitation reactance at 50 Hz; reference current i d_ref By the capacitance voltage u of the current transformer dc Reference voltage u of converter capacitor dc_ref Obtained after passing through a PI regulator.
The DFIG rotor side introduces virtual impedance, and the d-axis component i of the rotor side inductance current acquired in the rotor side line dr And rotor side inductor current q-axis component i qr And as an input component, an additional signal is obtained through virtual impedance and added to an output link of the PI regulator, so that the function of impedance optimization is achieved. Wherein virtualThe impedance includes resistance, inductance or capacitance, and the transfer function Z(s) of the virtual impedance controller is expressed as:
wherein R represents resistance, L represents inductance, and C represents capacitance.
Meanwhile, a band-pass filter is added in a network side control link, and a network side capacitance voltage d-axis component u acquired in a network side line gd And net side capacitor voltage q-axis component u gq The input component is input into the PI regulator as negative feedback after passing through the band-pass filter, and plays roles in filtering harmonic waves and optimizing impedance. The bandpass filter transfer function expression is:
where m is the gain, k is the damping coefficient, 0.707, ω is the center angular frequency=2pi f, f is the center frequency.
The impedance optimization debugging method of the fan comprises the following steps:
step S1, debugging parameters of band-pass filtering gain m and center frequency f by utilizing a dragonfly algorithm;
step S2, judging whether the system can stably run, if so, executing step S3, and if not, returning to execute step S1;
step S3, judging whether the impedance phase of the system in the frequency range of 0-H1 meets the requirement, if so, executing step S4, and if not, returning to execute step S1;
s4, debugging virtual impedance parameters including virtual resistance, capacitance or inductance by utilizing a dragonfly algorithm;
step S5, judging whether the system can stably run, if so, executing step S6, and if not, returning to execute step S4;
and S6, judging whether the impedance phase of the system in all frequency bands meets the requirement, if so, ending the optimization debugging, and if not, returning to the step S4.
The dragonfly algorithm in the optimization debugging method comprises the following steps:
step 1, setting related parameters, and randomly initializing a monomer position vector and a step length vector in an algorithm;
step 2, judging whether the current iteration times t is smaller than the maximum iteration times M, if yes, carrying out step 3; if not, outputting a parameter debugging result, and ending the debugging;
step 3, updating weight and field radius, calculating individual fitness, updating separation weight s, and adding Ji Quan weight a, cohesion weight c, food factor f and enemy factor e;
step 4, judging whether a field exists, namely whether a target solution exists in the field, if so, updating the step length vector and the position vector by using mathematical model expressions of the step length vector and the position vector, and then carrying out step 5; if not, directly carrying out the step 5;
the mathematical model expression of the step length vector is as follows:
ΔX t+1 ＝(sS i +aA i +cC i +fF i +eE i )+ωΔX t
wherein ω is an inertial weight; ΔX t Step length vector when the iteration times t are; s is S i For the ith individual isolation, the expression is:
x is the current individual position; xj is the j-th adjacent individual position; n is the number of adjacent individuals of the population;
A i aligned for the ith individual, the expression is:
V j the speed of the jth adjacent individual in the population;
C i is the firsti individual cohesive, expressed as:
F i for the i-th individual food source, the expression is:
F i ＝X + -X
X + is the current position of the food;
E i for the i-th individual enemy location, the expression is:
E i ＝X - -X
X - is the current location of the enemy;
the mathematical model expression of the position vector is:
X t+1 ＝X t +ΔX t+1
step 5, updating the step length vector by using the mathematical model expression of the step length vector in the step 4, and returning to the step 2 after updating the position vector by using Levy flight; the Levy flight update position vector expression is:
X t+1 ＝X t +Levy(d)×H t
wherein d is the dimension of the position vector;
wherein r is 1 、r 2 Is [0,1]2 random numbers in (a); beta is a constant; the calculation formula of sigma is:
wherein: Γ (x) = (x-1) +.! .
By adopting the technical scheme, the invention has the following technical effects:
the invention provides the impedance optimization scheme and the corresponding optimization and debugging method for the small wind working condition, which can pointedly solve the problem of subsynchronous oscillation under the small wind working condition, realize the impedance optimization of the doubly-fed fan, and have good technical effect and high practical value.
Drawings
FIG. 1 is a schematic diagram of a system circuit and control scheme of the present invention;
FIG. 2 is a rotor side converter current loop control diagram of the present invention;
FIG. 3 is a diagram of the current loop control of the grid-side current transformer of the present invention;
FIG. 4 is a flow chart of an optimization debugging method of the present invention;
FIG. 5 is a diagram of the full band impedance phase requirement of the present invention;
fig. 6 is a comparison of the impedance curves before and after optimization.
Detailed Description
The technical scheme of the invention is further described in detail below with reference to the accompanying drawings:
as shown in fig. 1, an impedance optimization method of a wind power generation system, a main circuit of a doubly-fed wind power generation system includes, from left to right: double-fed fan, rotor side transformer T and rotor side filter inductance L r Side current transformer (MSC), current transformer capacitor, network side current transformer (GSC), network side filter inductance L g Network side capacitance and power grid. In the figure, K: an active current coefficient calculated from the torque; x is X m : excitation reactance at 50 Hz; k (K) 1r : leakage reactance coefficient of the motor; l (L) s : self-inductance of the stator winding; l (L) m The stator and rotor windings are mutually inductive.
Rotor side inductor current i r_abc The d-axis component i of the inductance current of the rotor side is obtained by collecting the inductance current from the rotor side line and transforming the coordinates dr And rotor side inductor current q-axis component i qr ；
Net side inductance current i g_abc The d-axis component i of the net-side inductance current is obtained after the coordinate transformation is acquired from the net-side line gd And net side inductor current q-axis component i gq ；
Network side capacitance voltage u g_abc The d-axis component u of the net-side capacitance voltage is obtained after the coordinate transformation is acquired from the net-side line gd And net side capacitor voltage q-axis component u gq ；
Rotor side phase angle theta r Frequency omega r Obtained via photoelectric encoder, net side phase angle theta g Frequency omega g Obtained via a Phase Locked Loop (PLL).
The modulation mode of MSC and GSC is space vector modulation (SVPWM), q-axis component control mode of MSC is torque outer ring-current inner ring double closed-loop control, d-axis component control mode is voltage outer ring-current inner ring double closed-loop control; the q-axis component control mode of the GSC is current closed-loop control, and the d-axis component control mode is voltage outer ring-current inner ring double closed-loop control.
Wherein the reference current i qr_ref From rotor-side reference torque T e_ref After adjustment, the regulator expression is: k omega g K is the active current coefficient, ω, calculated from the torque g Is the network side frequency; reference current i dr_ref From the q-axis component u of the net-side capacitor voltage gq After adjustment, the regulator expression is: 1/X m ，X m Excitation reactance at 50 Hz; reference current i d_ref By the capacitance voltage u of the current transformer dc Reference voltage u of converter capacitor dc_ref Obtained after passing through a PI regulator.
The current loop control process of MSC and GSC is:
the MSC current loop control process comprises the following steps: as shown in fig. 2, the reference current i qr_ref /i dr_ref Q/d axis component i of inductor current on rotor side qr /i dr After difference, the output signal is adjusted by PI, and i qr /i dr The signals obtained by the virtual impedances are added to obtain a modulated wave. Wherein the phase angle of the modulated wave is theta g -θ r ，θ g For the net side phase angle, θ r The rotor side phase angle; the virtual impedance includes a resistance, an inductance, or a capacitance, and the transfer function Z(s) of the virtual impedance controller is expressed as:
wherein R represents resistance, L represents inductance, and C represents capacitance.
The GSC current loop control process comprises the following steps: as shown in FIG. 3, the reference current is 0/i d_ref Q/d axis component i of inductance current at network side gq /i gd After the difference is made, the filtered signal fed back is subtracted, and the output signal is obtained after PI regulation, and the q/d axis component u of the network side capacitor voltage is used gq /u gd Subtracting the output signal thereof to obtain a modulated wave. Wherein the phase angle of the modulated wave is theta g ，θ g Is the network side phase angle; the negative feedback signal is the d-axis component u of the net-side capacitance voltage collected from the net-side line gd And net side capacitor voltage q-axis component u gq The band-pass filter transfer function expression is as follows:
where m is the gain, k is the damping coefficient, 0.707, ω is the center angular frequency=2pi f, f is the center frequency.
As shown in fig. 4, the impedance optimization and debugging method of the fan of the present invention comprises:
step S1, debugging parameters of band-pass filtering gain m and center frequency f by utilizing a dragonfly algorithm;
step S2, judging whether the system can stably run, if so, executing step S3, and if not, returning to execute step S1;
step S3, judging whether the impedance phase of the system in the frequency range of 0-H1 meets the requirement, if yes, executing step S4, and if not, returning to execute step S1, wherein the value of H1 is 100, the value range of the full frequency range is 0-2000, and the full frequency range impedance phase requirement is shown in figure 5;
s4, debugging virtual impedance parameters including virtual resistance, capacitance or inductance by utilizing a dragonfly algorithm;
step S5, judging whether the system can stably run, if so, executing step S6, and if not, returning to execute step S4;
and S6, judging whether the impedance phase of the system in all frequency bands meets the requirement, if so, ending the optimization debugging, and if not, returning to the step S4.
The method for debugging parameters by using the dragonfly algorithm comprises the following steps of:
step 1, setting related parameters, and randomly initializing a monomer position vector and a step length vector in an algorithm;
step 2, judging whether the current iteration times t is smaller than the maximum iteration times M, if yes, carrying out step 3; if not, outputting a parameter debugging result, and ending the debugging;
step 3, updating weight and field radius, calculating individual fitness, updating separation weight s, and adding Ji Quan weight a, cohesion weight c, food factor f and enemy factor e;
step 4, judging whether a field exists, namely whether a target solution exists in the field, if so, updating the step length vector and the position vector by using mathematical model expressions of the step length vector and the position vector, and then carrying out step 5; if not, directly carrying out the step 5;
the mathematical model expression of the step length vector is as follows:
ΔX t+1 ＝(sS i +aA i +cC i +fF i +eE i )+ωΔX t
wherein ω is an inertial weight; ΔX t Step length vector when the iteration times t are; s is S i For the ith individual isolation, the expression is:
x is the current individual position; xj is the j-th adjacent individual position; n is the number of adjacent individuals of the population;
A i aligned for the ith individual, the expression is:
V j the speed of the jth adjacent individual in the population;
C i cohesive for the ith individual, the expression is:
F i for the i-th individual food source, the expression is:
F i ＝X + -X
X + is the current position of the food;
E i for the i-th individual enemy location, the expression is:
E i ＝X - -X
X - is the current location of the enemy;
the mathematical model expression of the position vector is:
X t+1 ＝X t +ΔX t+1
step 5, updating the step length vector by using the mathematical model expression of the step length vector in the step 4, and returning to the step 2 after updating the position vector by using Levy flight; the Levy flight update position vector expression is:
X t+1 ＝X t +Levy(d)×X t
wherein d is the dimension of the position vector;
wherein r is 1 、r 2 Is [0,1]2 random numbers in (a); beta is a constant; the calculation formula of sigma is:
wherein: Γ (x) = (x-1) +.! .
The comparison result is shown in fig. 6, the blue line in fig. 6 is the result before optimization, the purple line is the result after optimization, and the impedance phase requirement of 0-100Hz is set in the red dotted line, so that the impedance curve after optimization through the scheme is more in the red dotted line, and the impedance phase requirement is more satisfied.

Claims (7)

1. An impedance optimization method of a wind power generation system, a doubly-fed wind generator main circuit comprises from left to right: double-fed fan, rotor side transformer T, rotor side filter inductance Lr, machine side converter MSC, converter electric capacity, net side converter GSC, net side filter inductance Lg, net side electric capacity and electric wire netting, its characterized in that: the DFIG rotor side introduces virtual impedance, the d-axis component i of the rotor side current collected in the rotor side line dr And rotor-side current q-axis component i qr As an input component, an additional signal is obtained through virtual impedance and added to an output link of the PI regulator, so that the function of impedance optimization is achieved; meanwhile, a band-pass filter is added in a network side control link, and a network side voltage d-axis component u acquired in a network side line gd And net side voltage q-axis component u gq The input component is passed through a band-pass filter and then is input to a PI regulator as negative feedback.
2. A method of optimizing the impedance of a wind power generation system according to claim 1, wherein: rotor side inductor current i r_abc The d-axis component i of the inductance current of the rotor side is obtained by collecting the inductance current from the rotor side line and transforming the coordinates dr And rotor side inductor current q-axis component i qr The method comprises the steps of carrying out a first treatment on the surface of the Net side inductance current i g_abc The d-axis component i of the net-side inductance current is obtained after the coordinate transformation is acquired from the net-side line gd And net side inductor current q-axis component i gq The method comprises the steps of carrying out a first treatment on the surface of the Network side capacitance voltage u g_abc The d-axis component u of the net-side capacitance voltage is obtained after the coordinate transformation is acquired from the net-side line gd And net side capacitor voltage q-axis component u gq The method comprises the steps of carrying out a first treatment on the surface of the Rotor side phase angle theta r Frequency omega r Obtained via photoelectric encoder, net side phase angle theta g Frequency omega g Obtained via a phase locked loop.
3. A method of optimizing the impedance of a wind power generation system according to claim 1, wherein: the virtual impedance includes a resistance, an inductance, or a capacitance, and the transfer function Z(s) of the virtual impedance controller is expressed as:
wherein R represents resistance, L represents inductance and C represents capacitance;
the bandpass filter transfer function expression is:
where m is the gain, k is the damping coefficient, 0.707, ω is the center angular frequency=2pi f, f is the center frequency.
4. A method of optimizing the impedance of a wind power generation system according to claim 1, wherein: the modulation mode of MSC and GSC is space vector modulation, q-axis component control mode of MSC is torque outer ring-current inner ring double closed-loop control, d-axis component control mode is voltage outer ring-current inner ring double closed-loop control; the q-axis component control mode of the GSC is current closed-loop control, and the d-axis component control mode is voltage outer ring-current inner ring double closed-loop control.
5. A method of optimizing the impedance of a wind power generation system according to claim 1, wherein: reference current i qr_ref From rotor-side reference torque T e_ref After adjustment, the regulator expression is: k omega g K is the active current coefficient, ω, calculated from the torque g Is the network side frequency; reference current i dr_ref From the q-axis component u of the net-side capacitor voltage gq After adjustment, the regulator expression is: 1/X m ，X m Excitation reactance at 50 Hz; reference current i d_ref By the capacitance voltage u of the current transformer dc Reference voltage u of converter capacitor dc_ref Obtained by PI regulatorTo (d).
6. A method for optimizing the impedance of a wind power system according to any one of claims 1-5, characterized in that the optimization tuning method comprises the steps of:
step S1, debugging parameters of band-pass filtering gain m and center frequency f by utilizing a dragonfly algorithm;
step S2, judging whether the system can stably run, if so, executing step S3, and if not, returning to execute step S1;
step S3, judging whether the impedance phase of the system in the frequency range of 0-H1 meets the requirement, if so, executing step S4, and if not, returning to execute step S1;
s4, debugging virtual impedance parameters including virtual resistance, capacitance or inductance by utilizing a dragonfly algorithm;
step S5, judging whether the system can stably run, if so, executing step S6, and if not, returning to execute step S4;
and S6, judging whether the impedance phase of the system in all frequency bands meets the requirement, if so, ending the optimization debugging, and if not, returning to the step S4.
7. The method for optimizing the impedance of a wind power generation system according to claim 6, comprising the steps of: the steps of applying the dragonfly algorithm to debug parameters are as follows:
step 1, setting related parameters, and randomly initializing a monomer position vector and a step length vector in an algorithm;
step 2, judging whether the current iteration times t is smaller than the maximum iteration times M, if yes, performing a step S3; if not, outputting a parameter debugging result, and ending the debugging;
step 3, updating weight and field radius, calculating individual fitness, updating separation weight s, and adding Ji Quan weight a, cohesion weight c, food factor f and enemy factor e;
step 4, judging whether a field exists, namely whether a target solution exists in the field, if so, updating the step length vector and the position vector by using mathematical model expressions of the step length vector and the position vector, and then carrying out step 5; if not, directly carrying out the step 5;
the mathematical model expression of the step length vector is as follows:
ΔX t+1 ＝(sS i +aA i +cC i +fF i +eE i )+ωΔX t
wherein ω is an inertial weight; ΔX t Step length vector when the iteration times t are; s is S i For the ith individual isolation, the expression is:
x is the current individual position; xj is the j-th adjacent individual position; n is the number of adjacent individuals of the population;
A i aligned for the ith individual, the expression is:
V j the speed of the jth adjacent individual in the population;
C i cohesive for the ith individual, the expression is:
F i for the i-th individual food source, the expression is:
F i ＝X + -X
X + is the current position of the food;
E i for the i-th individual enemy location, the expression is:
E i ＝X - -X
X - is the current location of the enemy;
the mathematical model expression of the position vector is:
X t+1 ＝X t +ΔX t+1
step 5, updating the step length vector by using the mathematical model expression of the step length vector in the step 4, and returning to the step 2 after updating the position vector by using Levy flight; the Levy flight update position vector expression is:
X t+1 ＝X t +Levy(d)×X t
wherein d is the dimension of the position vector;
wherein r is 1 、r 2 Is [0,1]2 random numbers in (a); beta is a constant; the calculation formula of sigma is:
wherein: Γ (x) = (x-1) +.! .
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